eprints.qut.edu.au the applicability of the precaution adoption process model in understanding older...

THE APPLICABILITY OF THE PRECAUTION

ADOPTION PROCESS MODEL IN

UNDERSTANDING OLDER ADULTS’ SELF-REGULATORY DRIVING BEHAVIOURS

Heidi Hassan

BDent, MPH, MEpi

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

Centre for Accident Research and Road Safety – Queensland

School of Psychology and Counselling

Faculty of Health

Queensland University of Technology

2017

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours i

Keywords

Ageing, driving, feedback, latent class analysis, older driver, PAPM, self-awareness,

self-regulation, stages of change.

ii The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

Abstract

The number of older Australian drivers is predicted to increase dramatically

in the next decade. Age-related declines in sensory, cognitive and motor abilities can

compromise older adults’ abilities to drive safely. There is a considerable variability

in the way older adults experience ageing and the associated physiological and

pathological declines. Older adults are relatively safe drivers, however, when

compared to young and middle-aged drivers they are more likely to sustain serious

injuries or die if involved in a crash. This over-representation in serious and life-

threatening crashes among older drivers is mainly attributed to their increased

fragility.

For years, mandatory age-based testing has been advocated (and sometimes

implemented) as a strategy to identify unsafe and unfit older drivers. Recently,

research has shown that there are no demonstrable safety benefits associated with

this strategy. Driving cessation is associated with many adverse consequences such

as social isolation and depression. In a society that relies heavily on private cars,

maintaining older adults’ safe mobility is a public health priority.

The transition from driving to non-driving is difficult and older adults should

be a part of the decision-making process. Some older drivers modify their driving

behaviours (e.g. reduction of overall driving and avoidance of challenging driving

situations) in response to perceived changes in their driving abilities. These

behavioural modifications are known as self-regulation of driving. Researchers have

promoted self-regulation as a positive approach that can balance the needs for

mobility and safety. There is however limited understanding pertaining as to why

some older drivers regulate their driving while others don’t. It is still unclear what

works best to promote self-regulation among older drivers. There is growing

evidence that older drivers go through different qualitative stages towards modifying

their driving behaviours. It therefore could be useful to examine the driving self-

regulation process within behaviour change framework. The lack of a theoretically-

informed model of driving self-regulation inhibits our ability to understand and

describe such complex process.

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours iii

This thesis addresses this gap by examining the applicability of a stage-based

theoretical model, the Precaution Adoption Process Model (PAPM), for

understanding why some older drivers adopt self-regulatory (precautionary)

behaviours intended to reduce their road crash risk. The PAPM describes how

individuals move through stages of change towards adoption of health protective

behaviour. The early stages of the PAPM are defined in terms of psychological

states and mindsets of individuals (Weinstein & Sandmand, 2002). The late stages

are mostly governed by factors that can facilitate or hinder the adoption of the

precaution. Individuals progress through seven stages from lack of awareness to

action: unawareness (stage 1); awareness that there is an issue but a lack of personal

engagement with it (stage 2); engagement (“this applies to me”) but indecision (stage

3) about the need to act; either a decision not to act (stage 4) or a decision to act

(stage 5); if the latter, acting by taking the precaution (stage 6) (e.g. self-regulating);

and maintaining the behaviour (stage 7). This thesis aims to develop a conceptual

framework based on the PAPM that profiles older adults into distinctive groups

according to their mindsets towards self-regulatory driving behaviours. By applying

a stage-based approach, the self-regulation process can be broken down into

qualitatively different categories that accommodate the heterogeneity of the older

driver population. This would allow interventions to be customised based on the

individual’s specific need.

The first stage of this research program was qualitative in nature and involved

a study that explored the preliminary fit of the driving regulation process within the

PAPM framework. Five focus groups with a total of 27 participants aged 70 years or

more were conducted. Thematic analysis resulted in the development of five main

themes: the meaning of driving, changes in driving pattern, feedback, the planning

process, and solutions. Driving was perceived as the key to maintaining participants’

mobility and independence. Participants were aware of the impact of ageing on

driving abilities, however, the majority were not aware of any personal changes. The

analysis also resulted in an initial model of driving self-regulation among older

drivers that was informed by the PAPM as the theoretical framework. It identified

several social, personal, and environmental factors that can either facilitate or hinder

older drivers’ transition between the proposed stages of change. The findings from

this study suggest that further examination of the PAPM is needed. The findings

iv The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

informed the development of a questionnaire that was used in the second stage of the

research. In this cross-sectional study, 222 Australian drivers aged 70 years and

more were categorised into five stages of the PAPM based on their intention to

regulate and/or restrict their driving. Participants also completed a self-administered

questionnaire measuring demographic, psychosocial, and environmental factors

related to self-regulation. The analysis of the data collected in study two was divided

in two phases. Phase one investigated the prevalence of the PAPM stages of change

within the sample. Further, the study investigated the psychosocial and

environmental factors associated with different stages of the PAPM and those that

predict the decision to adopt self-regulatory behaviour. Bivariate analyses were

performed to identify the differences between PAPM groups. In addition, logistic

regression was used to determine the predictive variables for adoption of self-

regulatory behaviours. Distribution of the sample across the stages was: unengaged,

n = 104 (46.8%); undecided, n = 24 (10.8%); resisting action, n = 23 (10.4%);

planning to act, n = 22 (9.9%); and acting, n = 49 (22.1%). The significant

predictors in the final model were self-rated driving confidence, family feedback,

self-rated quality of driving and driving relinquishment expectation. The study

indicates that there are significant differences among PAPM stages of change.

Further, several psychosocial variables significantly predicted the adoption of self-

regulatory behaviours among participants.

Phase two employed a bottom-up approach to profile older drivers based on

their mindset towards adopting self-regulatory driving behaviours using Latent Class

Analysis. Latent Class Analysis (LCA) is a person-centred approach used to identify

subgroups with distinctive patterns. The selection of LCA indicators was guided by

the PAPM and involved driving perception, importance of driving, and barriers

towards change. The identified classes were described in terms of socio-

demographic factors, alternative transport use, and self-reported avoidance

behaviour. The analysis identified three classes of self-regulatory behaviours of

older drivers which can be conceptualised to occur through different stages.

Individuals in class 1: willing to change, had the lowest levels of reported driving

confidence, driving comfort, and perceived driving abilities. They were least likely

to agree that giving up driving would restrict their mobility or independence. They

were also least likely to agree that giving up driving would be difficult in terms of

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours v

barriers. Individuals in class 2: the unengaged, had the highest levels of reported

driving ability. They were most likely to agree that driving cessation would restrict

their mobility and independence, and that lifestyle factors were barriers to changing

their driving. Individuals in class 3: the unwilling, had low perceived driving

abilities. They agreed that driving cessation would restrict their independence and

mobility and were most likely to agree that they would be letting other people down

if they stopped driving. This group overall were most likely to agree with statements

about barriers to giving up driving. Based on the findings, the initial model was

refined.

The last stage was experimental and aimed to assess the impact of providing

one-on-one feedback regarding driving performance on stage transition among a

sample of 26 older drivers. This study also investigated the impact of such feedback

on older drivers’ perception of the quality of their driving and their willingness to

modify their driving behaviour. A pre-experimental single group, pre-post design

was employed. No significant changes in participants’ self-rated quality of driving

were found before and after the feedback. However, following the feedback, the

number of participants willing to change their driving behaviour significantly

increased from 4 to 14.

This research program contributes to the theoretical understanding of older

drivers’ self-regulation through the application of the PAPM and the development of

a conceptual model that categorises older adults into different stages of behaviour

change while capturing a wide range of interpersonal, intrapersonal, and

environmental factors that influence self-regulatory driving behaviour. A theory-

based understanding of older drivers’ self-regulatory behaviours and how to

influence them can assist in the development of effective interventions. To the best

of the researcher’s knowledge, this is the first study to develop a comprehensive

model of older drivers’ regulatory behaviour using the stages of change approach.

The model is very flexible and can be customised in different contexts based on the

study population (e.g. women, rural drivers or professional older drivers), the self-

regulatory practice (e.g. tactical, strategic or life-goal) and the desired interventions

(e.g. in-vehicle technologies, educational interventions or health professional

interventions).

vi The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours vii

List of thesis publications and submitted manuscripts

Paper 1* Hassan, H., King, M., & Watt, K. (2015). The perspectives of older

drivers on the impact of feedback on their driving behaviours: a

qualitative study. Transportation Research Part F, 28, pp. 25-39. Q2

Paper 2* Hassan, H., King, M., & Watt, K. (2017). Examination of the

Precaution Adoption Process Model in understanding older drivers’

behaviour: an exploratory study. Transportation Research Part F,

46(A), pp. 111-123. Q2

Paper 3* Hassan, H. & King, M. (under preparation). Older adults’ self-

regulatory driving behaviour: A latent class analysis.

* These papers form chapters of this thesis by publication

Other publications related to the thesis Paper 1 Hassan, H., King, M., and Watt, K. (2015). Older adults’ driving

reduction: Is the gender gap narrowing? (Peer reviewed paper).

Proceedings of the 2015 Australasian Road Safety Conference, 14-16

October 2015, Gold Coast, Australia

Conference presentations relating to this thesis Conference 1 Hassan, H., King, M., & Watt, K. (2014). The applicability of the

Precaution Adoption Process Model for understanding self-regulatory

driving behaviour among older drivers (Poster). In 2014 Australasian

Road Safety Research, Policing and Education Conference, 12-14

November 2014, Grand Hyatt, Melbourne, VIC. Conference 2 Hassan, H., King, M., & Watt, K. (2015). Older adults and driving

reduction: Is the gender gap narrowing? In 2015 Australasian Road

Safety Conference, 14-16 October 2015, Gold Coast, Qld.

viii The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

Table of Contents

Keywords .................................................................................................................................. i

Abstract .................................................................................................................................... ii

List of thesis publications and submitted manuscripts ........................................................... vii

Other publications related to the thesis .................................................................................. vii

Conference presentations relating to this thesis ..................................................................... vii

List of Figures ......................................................................................................................... xi

List of Tables .......................................................................................................................... xii

List of Abbreviations ............................................................................................................. xiii

Statement of Original Authorship ......................................................................................... xiv

Acknowledgements ................................................................................................................ xv

Chapter 1: Introduction ...................................................................................... 1

1.1 Introductory comments .................................................................................................. 1

1.2 Background and rationale for the research Program ...................................................... 2

1.3 Research aims .............................................................................................................. 15

1.4 Significance of this study ............................................................................................. 17

1.5 Demarcation of scope of the research program ............................................................ 17

1.6 Thesis outline ............................................................................................................... 17

1.7 Chapter summary ......................................................................................................... 18

Chapter 2: Literature Review ........................................................................... 20

2.1 Introductory comments ................................................................................................ 20

2.2 Growing number of older drivers ................................................................................. 20

2.3 The importance of driving ............................................................................................ 21

2.4 Transportation alternatives ........................................................................................... 22

2.5 Factors enabling driving safety among older drivers ................................................... 23

2.6 Are older drivers a road safety problem compared to other drivers? ........................... 24

2.7 Patterns and characteristics of older drivers’ crashes ................................................... 26

2.8 Current older driver road safety Countermeasures ...................................................... 26

2.9 Chapter summary ......................................................................................................... 47

Chapter 3: Theoretical framework and current models of older adults’ driving behaviour ..................................................................................................... 49

3.1 Introductory comments ................................................................................................ 49

3.2 Descriptive models ....................................................................................................... 49

3.3 Explanatory models ...................................................................................................... 53

3.4 Other models ................................................................................................................ 59

3.5 Limitations with the existing models ........................................................................... 64

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours ix

3.6 The Precaution Adoption Process Model (PAPM) ....................................................... 67

3.7 Chapter summary and implications .............................................................................. 70

Chapter 4: Research Design .............................................................................. 73

4.1 Introductory comments ................................................................................................. 73

4.2 Research questions ....................................................................................................... 73

4.3 Research design and methodology ............................................................................... 75

4.4 Setting, population, and recruitment ............................................................................. 76

4.5 Methods ........................................................................................................................ 77

4.6 Data management and data analysis ............................................................................. 79

4.7 Organisation of papers .................................................................................................. 80

4.8 Ethics Approval ............................................................................................................ 81

Chapter 5: The perspectives of older drivers on the impact of feedback on their driving behaviours: a qualitative study (Study 1) ........................................ 83

5.1 Publication Status ......................................................................................................... 83

5.2 Statement of Contribution............................................................................................. 83

5.3 Abstract ......................................................................................................................... 85

5.4 Introduction .................................................................................................................. 86

5.5 Method .......................................................................................................................... 91

5.6 Analysis ........................................................................................................................ 93

5.7 Results .......................................................................................................................... 93

5.8 Discussion ................................................................................................................... 108

5.9 Limitations .................................................................................................................. 114

5.10 Conclusion .................................................................................................................. 114

Chapter 6: Examination of the Precaution Adoption Process Model in understanding older drivers’ behaviour: an explanatory study (Study 2, Phase 1) 116

6.1 Publication Status ....................................................................................................... 116

6.2 Statement of Contribution........................................................................................... 116

6.3 Abstract ....................................................................................................................... 118

6.4 Introduction ................................................................................................................ 119

6.5 Methods ...................................................................................................................... 122

6.6 Analysis ...................................................................................................................... 126

6.7 Results ........................................................................................................................ 126

6.8 Discussion ................................................................................................................... 133

6.9 Limitations .................................................................................................................. 138

6.10 Conclusion .................................................................................................................. 139

Chapter 7: Older adults’ self-regulatory driving behaviour: A latent class analysis (Study 2, Phase 2) .................................................................................... 140

x The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

7.1 Publication Status ....................................................................................................... 140

7.2 Statement of Contribution .......................................................................................... 140

7.3 Abstract ...................................................................................................................... 141

7.4 Introduction ................................................................................................................ 142

7.5 Method ....................................................................................................................... 145

7.6 Analysis ...................................................................................................................... 147

7.7 Results ........................................................................................................................ 149

7.8 Discussion .................................................................................................................. 152

7.9 Limitations ................................................................................................................. 155

Chapter 8: Feedback and older drivers (Study three) .................................. 157

8.1 Introductory comments .............................................................................................. 157

8.2 Methods ...................................................................................................................... 159

8.3 Analysis ...................................................................................................................... 161

8.4 Results ........................................................................................................................ 161

8.5 discussion ................................................................................................................... 165

8.6 Limitations ................................................................................................................. 167

Chapter 9: Discussion ...................................................................................... 167

9.1 Chapter overview ....................................................................................................... 167

9.2 Overall research findings ........................................................................................... 168

9.3 Contributions to research ........................................................................................... 184

9.4 Practical implications of the research program .......................................................... 186

9.5 Study strengths and limitations .................................................................................. 188

9.6 Future directions ........................................................................................................ 189

9.7 Concluding remarks ................................................................................................... 190

Bibliography ........................................................................................................... 192

Appendices .............................................................................................................. 209

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours xi

List of Figures

Figure 1.1 Annual fatalities: road user type within age groups. .................................. 5

Figure 1.2: Annual number of fatal crashes ................................................................. 6

Figure 1.3: Stages of the Precaution Adoption Process Model .................................. 12

Figure 1.4: Stages of the program of research ........................................................... 16

Figure 1.5: Overview of thesis chapters ..................................................................... 19

Figure 2.1: Multifactorial model of factors enabling safe driving among older drivers .......................................................................................................... 24

Figure 3.1: Driving reduction/cessation framework .................................................. 50

Figure 3.2: Conceptualization of the process of driving behaviour change within the TTM framework ......................................................................... 53

Figure 3.3: Model of the process of driving self-regulation with ageing ................... 55

Figure 3.4: Driving as an Everyday Competence Model for Older Adults .............. 56

Figure 3.5: The Multilevel Older Person’s Transportation and Road Safety Model ........................................................................................................... 58

Figure 3.6: Precede-Proceed model of motor vehicle crashes among older drivers .......................................................................................................... 60

Figure 3.7: Conceptual model of driving cessation process ...................................... 63

Figure 3.8: Challenges in examining older driver behaviour ..................................... 64

Figure 4.1: Flowchart of the research program ......................................................... 77

Figure 4.2: Organisation of the papers ....................................................................... 81

Figure 5.1: Stages of the Precaution Adoption Process Model- Source: (Weinstein & Sandmand, 2002). .................................................................. 89

Figure 5.2: Proposed theoretical model of stage-based driving change involving feedback and self-regulation ...................................................................... 110

Figure 6.1: Preliminary theoretical model of stage-based driving change involving feedback and self-regulation (Hassan et al., 2015) .................... 121

Figure 7.1: Refined model of self-regulatory driving behaviour ............................. 155

Figure 9.1: Refined model of self-regulatory driving behaviour ............................. 184

xii The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

List of Tables

Table 1.1: Adaptation of the PAPM to the older drivers’ regulatory behaviours ...... 14

Table 2.1: Driver Licensing Practice renewal for car drivers (excluding heavy vehicle and motorbikes) in Australia (2016) ................................................ 30

Table 4.1: Precaution Adoption Process Model: Stage Classification Algorithm as applied to self-regulatory driving behaviours among older adults (Adapted from (Weinstein & Sandmand, 2002)) ..................... 78

Table 5.1: Characteristics of Participants ................................................................... 92

Table 6.1: Precaution Adoption Process Model: Stage Classification Algorithm as applied to self-regulatory driving behaviours among older adults (Adapted from Weinstein & Sandmand, 2002) ......................................... 123

Table 6.2: Sample characteristics (n=222) ............................................................... 126

Table 6.3: Most avoided driving situations and reasons for avoidance ................... 128

Table 6.4: Descriptions of the psychometric properties of scales ............................ 129

Table 6.5: PAPM stages .......................................................................................... 129

Table 6.6. Characteristics significantly associated with PAPM stage ..................... 130

Table 6.7: Hierarchical regression analysis (n=199) ................................................ 132

Table 7.1: Sample characteristics (n=222) ............................................................... 147

Table 7.2. Model Fit Statistics ................................................................................. 149

Table 7.3: Item-response probabilities .................................................................... 150

Table 7.4. Significant differences between latent classes ........................................ 151

Table 7.5. Frequencies of LCA classes for PAPM stages obtained by staging algorithm .................................................................................................... 152

Table 8.1: Adaptation of the PAPM to older drivers’ regulatory behaviours .......... 158

Table 8.2: Sample characteristics (n=21) ................................................................. 162

Table 8.3. Fitness to drive ........................................................................................ 163

Table 8.4. Driving errors observed in the driving assessment ................................. 164

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours xiii

List of Abbreviations

ADAS Advanced Driver Assistance System

CDT Clock Drawing Test

DEC Driving as an Everyday Competence Model

KEYS Knowledge Enhances Your Safety

LCA Latent Class Analysis

MOTRS Multilevel Older Person’s Transportation and Road Safety Model

OECD The organisation for Economic Co-operation and Development

PAPM Precaution Adoption Process Model

PDA Perceived Driving Ability

PPM PRECEDE-PROCEED Model

RACQ Royal Automobile Club of Queensland

SPSS Statistical Package for the Social Sciences

TTM Transtheoretical Model

UFOV Useful Field of View

xiv The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

Statement of Original Authorship

I declare that this thesis is composed of my original work and that the work

contained in this thesis has not been previously submitted to meet requirements for

an award at this or any other higher education institution. To the best of my

knowledge and belief, the thesis contains no material previously published or written

by another person except where due reference is made. I have clearly stated the

contribution by others to jointly-authored works that I have included in my thesis.

Signature: QUT Verified Signature

Date: 17/01/2018

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours xv

Acknowledgements

When I first started this journey, I didn’t know what to expect. Five years later

and I am forever grateful for everyone who made this possible. This thesis couldn’t

have been completed without the unconditional support I have received from my

supervisors, Dr. Mark King, Dr. Kerrianne Watt, and Emeritus Professor. Mary

Sheehan. Mark, you have taught me that with persistence everything is possible. I

have learnt so much from you and you have always motivated me to go further than I

can! Through the times when I felt that this is not possible, you were there telling me

that I am on the right track. Kerrianne, you have always been there with your

feedback and you have always believed I can do this. Mary, thank you for every

wise and timely input you have provided.

Thank you to all the participants for their time and contribution. This would

have not been possible without them. Thank you to everyone at CARRS-Q for

making this journey easier.

To the three powerful women in my life, my mother, Rania and Marwa, you

have set a high example and you have taught me how to be the woman I am today.

Marwa, this is for you! To my husband, Tamer, you always believed in me! You

have been there by my side from the first day cheering and pushing me. To my boys,

Omar and Ryan, thank you for your patience, for all the times when I could not be

with you and for always welcoming me with smiles and hugs. To my big brother,

my “father” and my role model, Amr, thank you for being there for us when we

needed you the most. My brothers, Ahmed and Mohamed thank you for never losing

faith in me!

The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours 1

Chapter 1: Introduction

1.1 INTRODUCTORY COMMENTS

This chapter provides an overview of the research program comprising this

thesis-by-publication. Given the predicted ageing of the driving population in

Australia and the significant over-involvement of older drivers in fatal crashes,

enhancing the safety of older Australian drivers has become a priority. Mandatory

age-based testing has shown no road safety benefits. On the contrary, it can result in

the premature loss of driving and subsequent loss of mobility. Cessation of driving is

linked to many adverse effects such as depression and isolation. It is therefore

important to balance the mobility and safety needs of older adults.

Self-regulation of driving has been promoted as an alternative approach that can

assist older adults in maintaining their driving privilege. It is still unclear why some

older drivers choose to modify their driving behaviours and why others keep driving

when it is no longer safe to do so. Previous studies have identified many

interpersonal, intrapersonal, and environmental factors that impact driving self-

regulation. However, the relative importance and interaction between these factors

and how they affect the driving behaviours among older adults is still not clear. It is

therefore critical to develop a model of driving self-regulation that can guide the

development of interventions. There is growing evidence that older drivers go

through different stages towards modifying their driving behaviours. Therefore, It

would be useful to examine the driving self-regulation process within a behaviour

change framework. Previous studies examining older drivers’ behaviour within

stages of change framework have relied entirely on qualitative findings without

further validation (e.g. (Kowalski, Jeznach, & Tuokko, 2014)) or have been

simplistic and did not add much to our understanding of the driving regulation

process (e.g. (Kostyniuk , Shope, & Molnar, 2001)).

This program of research addressed this significant gap in the older drivers’

literature, the lack of a theoretically-informed model of driving self-regulation that

takes into account the stages of change. The current chapter starts by discussing the

road safety issues related to the older driver and outlines the research background

which inspired this research program (1.2). Section (1.3) presents the aim and

2 The applicability of the Precaution Adoption Process Model in understanding older adults’ self-regulatory driving behaviours

objectives of the research program. The significance of the study is presented in

section (1.4). Section (1.5) presents the scope of the research and the thesis outline is

presented in section (1.6).

1.2 BACKGROUND AND RATIONALE FOR THE RESEARCH PROGRAM

The older driver

There has been a growing interest in extending the safe mobility of older

adults, given the ageing of our population (Lang, Parkes, & Medina, 2013). Mobility

is critical for the quality of life and well-being of older adults. While mobility can be

achieved through different forms of public and private transportation, driving is the

easiest, most accessible and most common form of transport for people of all ages

(Oxley & Whelan, 2008). Drivers aged 65 years and above are the fastest growing

segment of the driving population in Australia and around 60% of those aged 75

years and above hold a driver license (Bureau of Infrastructure, Transport and

Regional Economics,2014).

The baby boomers (born 1946-64 in a post-war boom in births) rely heavily on their

private cars and driving is their preferred mode of transport (Buys, Snow, Van

Megen, & Miller, 2012). Baby boomers are significantly active, making more trips

than previous generations (Currie & Delbosc, 2010), relying more on their cars and

less on public transport (Alsnih & Hensher, 2003). Over the last decade, older

Australian drivers have increased their annual vehicle kilometres driven by an

estimated 18% (Bureau of Infrastructure, Tranpsort and Regional Economics, 2014).

Older adults view driving as key to their independence and mobility (Adler &

Rottunda, 2006; Musselwhite & Haddad, 2010a). Driving is described by some as a

symbol of identity (Eisenhandler, 1990), independence (Persson, 1993), and security

(Bauer, Kuskowski, Rottunda, & Adler, 2003). The decision to stop driving is one of

the most difficult decisions older adults have to make (Adler & Rottunda, 2006).

Restricting or stopping driving can be associated with feelings of regret and

loneliness (Johnson, 1999), increased risk of depression (Ragland, Satariano, &

MacLeod, 2005), isolation (Fonda, Wallace, & Herzog, 2001), decreased out-of-

home activities (Marottoli, Carlos, Glass, Williams, & et al., 2000), and increased

risk of entering long-term care facilities (Freeman, Gange, Munoz, & West, 2006).


Stopping driving has also been linked to increased risk of dying (Edwards, Perkins,

Ross, & Reynolds, 2009).

The cessation of driving and subsequent loss of mobility will even have greater

impact in subgroups of the older population such as rural drivers and women. Older

women drivers are over-represented in fatal crashes compared to older men due to

their increased fragility (Oxley, 2010). The future cohort of older women will rely

more on their private cars and may be more reluctant to give up driving compared to

current and past generations (Rosenbloom, 2009). Older women have a higher

disability rate than men of similar age (Alsnih & Hensher, 2003) and may require

more assistance to maintain their mobility needs. With the increasing number of

older women living alone (Siren, 2004), it is expected that cessation of driving

among this age group will have drastic consequences (Siren Hakamies-Blomqvist, &

Lindeman, 2004). As women are starting to resemble men in terms of education and

employment, their driving experience and their attitude towards driving may start to

resemble that of men (Rosenbloom, 2006). Driving will become an integral part of

their identity, and similar to men, it will be the key to their freedom and

independence (Rosenbloom & Herbel, 2009).

Driving is a complex task that requires dynamic interaction between various

cognitive, physical, and sensory functions (Anstey, Wood, Lord, & Walker, 2005).

Ageing is associated with declines in these abilities (Anstey et al, 2005) and

increased prevalence of poorer health and medical conditions that can compromise

driving performance (Marshall, 2008). If unable to compensate for these changes,

older drivers may put themselves and others at risk (Freund, Colgrove, Burke, &

McLeod, 2005; Marottoli & Richardson, 1998). There is great diversity in the way

older adults experience the physiological and pathological declines associated with

ageing and how this affects their driving abilities (Langford & Koppel, 2006). Age

alone is a poor predictor of fitness to drive (Donorfio, D'Ambrosio, Coughlin, &

Mohyde, 2008)). Therefore, chronological age should not be used as a criteria to

restrict people from driving (Yassuda & Wilson, 1997).

As a group, older drivers are relatively safe drivers (De Raedt & Ponjaert-

Kristoffersen, 2000a; Eberhard, 1996). However, when distance driven is taken into

account, older drivers are over-represented in crashes when compared to middle-aged

drivers (King, Soole, Watson, & Schramm, 2011). This could be attributed to the


low-mileage bias, that is, driving shorter distances is associated with greater crash

risk regardless of age (Janke, 1991). Increased crash risk seen in low-mileage drivers

is often the result of the location of driving (e.g. urban areas with increased incidence

of challenging traffic situations) (Langford et al., 2013). Recent findings from the

Candrive/Ozcandrive study has shown that low- mileage drivers did considerably

poorly on a variety of performance measures compared to other drivers (Langford et

al., 2013). However, the findings should be interpreted with caution given that the

study relied on self-reported measures of driving which fails to provide an accurate

reflection of the actual driving behaviours of older drivers. In fact, the unreliability

of the subjective exposure measures used in majority of previous studies affect the

credibility of the “low-mileage bias” (Staplin, Gish, & Joyce, 2008). In 2015, Coxon

and colleagues examined the association between age, function and driving exposure

using objective measures in a large sample of 380 drivers aged 75 years and above.

The study found that older people with poorer function drove fewer kilometres per

week and took shorter trips closer to home. However, the study was conducted for

one week only, which is a relatively short time to capture usual driving practices (

Coxon et al., 2015). Without objective measures of driving exposure, it is difficult to

determine if increased crash involvement among older drivers reflects low-mileage

drivers.

Older drivers are more likely to be injured or killed if being involved in a

crash compared to younger or middle-aged drivers (King et al., 2011). In fact, the

consistent reduction in the fatalities among younger drivers over the past decade has

not been observed among older drivers in Australia (Fig 1.1) (Bureau of

Infrastructure, Transport and Regional Economics, 2014). On average, 250

Australians aged 65 and above die and another 4000 are hospitalised due to road

crash injuries each year (Bureau of Infrastructure, Transport and Regional

Economics, 2014). Between 2008 and 2013 annual deaths from crashes involving an

older driver increased by an alarming 17 percent (Bureau of Infrastructure, Transport

and Regional Economics, 2014). This over-representation in serious and fatal

crashes is mainly attributed to older adults’ fragility (Meuleners, Harding, Lee, &

Legge, 2006) due to their reduced bone strength and fracture tolerance (Guest,

Boggess, Viljoen, Duke, & Culvern, 2014). In 2003, Li and colleagues examined the

association of frailty (measured as risk of dying in the event of a crash) and increased


fatal crash involvement among different age groups, with the quantity of exposure to

vehicle travel being controlled for. Their findings showed that fragility was a

substantial determinant of the increased risk per unit of travel among older drivers

(60 years or older) (Li, Braver, & Chen, 2003). Another study conducted in 2008

revealed that when compared to middle-aged drivers, those 85 years and older have

an eight times higher mortality risk per mile travelled but pose only 1.5 mortality risk

to others (Tefft, 2008).

Regardless of the reason for older drivers’ over-representation in fatal

crashes, reducing the personal and societal impact of older drivers’ crashes is a

public health priority.

Figure 1.1 Annual fatalities: road user type within age groups.

Source (Bureau of Infrastructure, Tranpsort and Regional Economics, 2014)


Figure 1.2: Annual number of fatal crashes

Source (Bureau of Infrastructure, Tranpsort and Regional Economics, 2014)

Initiatives to maintain older drivers’ safety

Since driving will continue to be the main source of mobility for older

people, it is important to ensure the safety of older drivers and other road users.

Identifying high-risk older drivers is problematic given that driving is a complex task

that relies on a wide range of abilities. Up until now, there is very limited evidence

to support the use of off-road screening batteries in assessing older adult’s fitness to

drive (Wood, Anstey, Kerr, Lacherez, & Lord, 2008). Much research is needed to

determine the ideal battery of tests to be used that can detect fitness to drive while

ensuring reliability and validity (King et al., 2011). Efforts to monitor older drivers

through age-based mandatory testing have failed to show any safety benefits (Lang et

al., 2013 ; Langford & Koppel, 2006). On the contrary, mandatory age-based testing

may cause older drivers to restrict their driving prematurely with the subsequent

early loss of mobility (Siren & Haustein, 2015; Whelan, Langford, Oxley, Koppel, &

Charlton, 2006).

The adverse consequences associated with driving cessation calls for

strategies that balance older adults’ safety and mobility needs. Further, since older

drivers pose greater risk to themselves than to others, they have the right to play an

active role in the decision-making process (Langford & Koppel, 2006). Considerable


attention has therefore been directed towards other strategies that can increase older

drivers’ safety without compromising their mobility.

Planning the decision to stop driving can help overcome some of the negative

aspects of driving cessation (Musselwhite, 2013). While uncommon, driving

cessation can occur unexpectedly as a result of sudden illness, involvement in an

accident, or failing a driving test (Dellinger, Sehgal, Sleet, & Barrett-Connor, 2001).

However, driving cessation is more of a gradual and voluntary process whereby the

driver will gradually increase self-imposed restrictions or reduce their driving until

ultimate cessation (Dellinger et al., 2001; Hakamies-Blomqvist & Wahlström, 1998).

These modifications in driving behaviour, prior to driving cessation, are known as

driving self-regulation. Driving cessation is sometimes viewed to be the end result

of the process of self-regulation among older drivers (Dellinger et al., 2001; Lyman,

McGwin Jr, & Sims, 2001).

Self-regulation of driving has been promoted as an alternative positive

approach to keep older adults driving safely for longer (Lang et al., 2013 ). Self-

regulation refers to efforts to modify thoughts, emotions, needs, and actions to reach

higher long-term goals (Ridder & Wit, 2006) . In the context of driving, it refers to

modifying one’s driving behaviours to reduce and/or eliminate crash risk. It is

defined as “the adjustments made by drivers in their driving behaviour that

adequately match changing cognitive, sensory and motor capacities” (Charlton et al.,

2006) which largely depends on the individual’s ability to monitor his/her driving

ability (Anstey et al., 2005). Common examples of self-regulation seen in older

drivers include reducing their overall amount of driving and avoidance of various

driving situations (e.g. avoiding driving at night or peak hours, travelling shorter

distances) (Anstey & Smith, 2003; Baldock, Mathias, McLean, & Berndt, 2006a;

Charlton et al., 2006).

Recently, Molnar and colleagues (2013) have expanded this definition to

include three levels of self-regulation. Strategic self-regulation involves the decisions

made by drivers prior to taking the trip and involves general planning such as

avoiding difficult driving situations or selecting certain driving routes. Tactical self-

regulation involves the decisions made by drivers while they are on the road, such as

gap and headway acceptance, speed choice, and overtaking. Life-goal level of self-

regulation involves the broader decisions made by older drivers in their lives such as


the choice or what kind of car to drive which can have an indirect but a long-term

impact on their driving future.

Self-regulation and actual crash risk

There are multiple risk factors associated with motor vehicle crashes among

older drivers which makes it difficult to determine if self-regulation is indeed

effective in reducing crashes among this age group (Horswill, Anstey, Hatherly,

Wood, & Pachana, 2011). The relationship between self-regulation and actual crash

risk is still poorly understood. Growing evidence suggests that self-regulation may

show promise in decreasing crash risk among older drivers (Keay et al., 2013).

Anstey et al. (2006) assessed 1446 older drivers aged 70 and above on several visual,

cognitive and functional measures and followed them for five years (1992-1997).

They found that the factors associated with driving cessation were similar to those

associated with increased crash risk in older adults. This could indicate that older

adults with impairments reduce their risk of crash by modifying their driving

behaviour (Anstey, Windsor, Luszcz, & Andrews, 2006). Keay et al., 2013 pointed

out that recent epidemiological results, based on the findings from the North

American Fatality Analysis Rating System, support the use of self-regulation to

increase older drivers’ safety (Keay et al., 2013). Individuals who drive in daylight

and individuals with a history of motor vehicle conviction were less likely to be

injured in a crash probably as these individuals recognise their limitations (Keay et

al., 2013).

Mandatory age-based testings have failed to result in crash reduction among

older drivers. This can be partly explained by the fragility bias discussed before.

Older drivers’ over-representation in fatal crashes is mainly attributed to their

fragility not to their driving abilities or skills (Langford & Koppel, 2006). Age-based

testings are restrictive policies that can result in unnecessary restrictions on older

adults’ mobility. The adverse consequences of driving cessation noted above calls

for strategies that can manage older adults’ safety and mobility needs. Self-

regulation shows promise as an approach that can help older drivers achieve that. It

allows older drivers to be involved in the decision-making process, which can

improve the outcome through better adaptation and planning. In addition, it

accommodates the diversity and heterogeneity of older drivers’ population in terms

of their abilities, resources, and needs. As mentioned before, it is not age perse, but


rather the associated pathological and psychological declines that compromise the

driving performance. Given that older adults vary considerably in the way they

experience these declines, there is a need for a more “adaptive” strategy that can

accommodate such diversity.

Successful self-regulation

The success of self-regulation, in terms of driving safety, is greatly influenced

by the ability of older drivers to have insight into their declining driving

performance, the accuracy of their insight, their willingness and ability to respond to

this insight, and the effectiveness of their responses (Anstey et al., 2005). Those who

are unaware of limitations in their driving abilities may engage in risky behaviours

that compromise their safety and the safety of others (Marottoli & Richardson,

1998). In addition, older drivers who are aware of declines in their abilities are more

likely to practice self-regulation than those who are less self-aware (Blanchard &

Myers, 2010; Holland & Rabbitt, 1992).

Unfortunately, the changes associated with ageing are usually subtle and older

people may not be aware of how these changes affect their driving abilities. In

addition, driving errors and violations will not necessarily result in crashes or

penalties and drivers may fail to develop an accurate estimation of their abilities

(Dogan, Steg, Delhomme, & Rothengatter, 2012). Should an incident take place, the

driver may not understand why it occurred and how to prevent it in the future (Dogan

et al., 2012). Even if one becomes aware of the need to change, motor vehicle

crashes are rare events, which may not create a sense of urgency, and other health

and life goals may be perceived as more important. Driving self-regulation may in

fact be viewed as a negative behaviour that can impair one’s mobility and

independence. Achieving driving self-regulation for individual older drivers is

therefore complicated and could require extensive deliberation about the pros and

cons and persuasion by influential people such as family members and medical

practitioners. To make matters worse, the strategies and behavioural changes needed

to achieve optimal driving self-regulation, in terms of reducing crashes, are not

clearly defined. It is difficult for older adults to determine which modifications in

their driving behaviours compensate for the loss of certain abilities and subsequently

translate into improved safety. Lack of adequate support and feedback can influence

older people’s ability to make an informed decision about the future of their driving.


This can result in some older people stopping driving prematurely while other

continues to drive where it is not safe to do so (Berry, 2011).

Gaps in the current literature

For the past forty years or so, a large body of studies have investigated the

process of self-regulation among older drivers. While it is often promoted as a

promising initiative to maintain older drivers’ safe mobility, there are some

significant gaps in the literature related to older drivers’ self-regulation (Molnar et

al., 2015). Driving avoidance and/or reduction is not always related to driving

abilities. Existing evidence indicate that some older adults reduce and/or restrict

their driving for reasons such as retirement, preference, or financial constraints

(Blanchard & Myers, 2010; Meng & Siren, 2012) which should not be regarded as

driving self-regulation.

As it is widely endorsed by road safety researchers as a positive strategy, it is

important to understand the factors that influence some older adults to modify their

driving behaviours. This in turn will assist in the development of interventions that

encourage older drivers to appropriately self-regulate their driving. Previous studies

have identified a large number of factors associated with self-regulation, still, how

these factors come together in the final decision remains unclear. As Molnar and

colleagues (2015) highlight “it is important to extend the current research by trying

to tease out the relationships between self-regulation and the factors for which there

is already considerable evidence” and there is a need “for a more comprehensive,

theoretically-informed, and uniform approach to investigating self-regulation by

older drivers”.

Few studies have attempted to find a theoretical framework to account for the

process of self-regulation in older adults. The challenge in developing a model of

driving self-regulation results from the heterogeneity of the older driver population in

terms of their abilities, needs, and resources. There is a need for a model of self-

regulation that can describe the complexity inherent in diversity of needs, abilities

and resources among older people. Previous studies have pointed out that older

drivers go through different stages of change towards modifying their driving and

ultimately stopping driving (Kostyniuk , Trombley, & Shope, 1998). The stages of

changes theories could be useful in describing and providing a general understanding

of change and planning interventions (Liddle, Carlson, & McKenna, 2004). This


suggests that older driver interventions might need to be tailored to the specific needs

of each individual (including the stage they are at) and would need to be customised

to move individuals through the stages of change towards adoption of safe driving

behaviour. They would ideally be developed by taking a strategic approach using

both a theory of the change process and existing evidence from previous attempts to

achieve change. However, there has been little development of stage-based theories

applied to driving self-regulation, and hence there is a lack of research on

theoretically-informed interventions that facilitate older drivers’ planning for future

self-regulation and even driving cessation. There is also a lack of consideration of the

role of feedback about behaviour in the stage process, such as responsiveness to

feedback, acceptable sources of feedback, and ability to modify behaviour in relation

to feedback.

Previous studies examining older drivers’ behaviour within stages of change

framework have either relied entirely on qualitative findings without further

validation (e.g. (Kowalski, Jeznach, & Tuokko, 2014)) or have been simplistic and

have therefore not added much to our understanding of the driving regulation process

(e.g. (Kostyniuk , Shope, & Molnar, 2001)). Kowalski and colleagues (2014)

examined older driver behaviour within the Transtheoretical (TTM) framework using

interviews/focus groups with current and former older drivers (Kowalski et al.,

2014). The TTM assumes that health behaviour change involves six stages: pre-

contemplation, contemplation, preparation, action, maintenance, and termination

(Prochaska & Velicer, 1997). A major limitation of the TTM is that it fails to

distinguish between people who are unaware of the risk and those who have decided

not to act. In the TTM as applied to older drivers, it is not clear whether individuals

in the pre-contemplation stage (the non-changers) are aware of their declining

abilities but refuse to modify their driving or are simply unaware. It is likely those

who are aware but refuse to change will not progress through stages of change

similarly to those who are unaware, and therefore that these groups will require

different types of interventions. Older drivers who resist change may not benefit

from traditional behavioural interventions and may be more reluctant to seek

feedback. Furthermore, the focus of the TTM is on changing an existing behaviour

(driving), whereas a focus on driver self-regulation involves an important but subtle


difference: it is about the adoption of a precaution which is expected to play a role in

later behaviour change.

The literature suggests that self-awareness and insight into driving ability

play a major role in successful driving regulation among older drivers (Anstey et al.,

2005). Therefore, older drivers need to perceive their declining driving abilities as a

threat to their overall safety before they are interested in self-regulation. This

situation is better suited to the application of the Precaution Adoption Process Model

(PAPM) to the self-regulatory behaviours of older drivers, which has been examined

by Kostyniuk et al. (2000). The PAPM (Figure 1.3) describes how individuals move

through stages of change towards adoption of health protective behaviour (Weinstein

& Sandmand, 2002). The early stages of the PAPM are defined in terms of

psychological states and mindset of individuals (Weinstein & Sandmand, 2002). The

later stages are mostly governed by factors that can facilitate or hinder the adoption

of the precaution. Individuals progress through seven stages from lack of awareness

to action: unawareness (stage 1); awareness that there is an issue but a lack of

personal engagement with it (stage 2); engagement (“this applies to me”) but

indecision (stage 3) about the need to act; either a decision not to act (stage 4) or a

decision to act (stage 5); if the latter, acting by taking the precaution (stage 6) (e.g.

self-regulating); and maintaining the behaviour (stage 7). A fuller account is given

in Chapter 3.

Figure 1.3: Stages of the Precaution Adoption Process Model From Health behaviour and health education (p. 127) by Glanz, K. et al., 2008,

Wiley, ProQuest Ebook Central


The PAPM does not offer explicit details about the barriers and facilitators at

each stage which allows for a more flexible framework that can be adapted to suit

each behaviour uniquely (Weinstein, Sandmand, & Blalock, 2008). Kostyniuk et al.

(2000) hypothesised that predicting problems in one’s driving ability is a key factor

in initiating the driving reduction and cessation process and investigated the impact

of older adults’ anticipation of driving problems on their driving reduction and

cessation by conducting a survey study among 1,053 older drivers and former drivers

over the age of 65. Their findings suggest that the awareness and anticipation of

limitations in driving ability may be the key factor for reducing and/or stopping

driving, which provides further support to the use of PAPM. Unfortunately, their

model failed to recognise the influence of other external and internal factors on the

process of self-regulation. Their model is therefore descriptive and does not provide

a clear idea of the factors that facilitate transition between stages and is not useful in

developing interventions.

Purpose of this study

The applicability of the PAPM to the examination of driving behaviours

among older adults deserves consideration. An attractive feature of this model is that

it deals with both the hazard and the precaution. It claims that for individuals to

consider adopting a precaution they must first perceive the hazard to be of sufficient

personal relevance. The age-related declines in people’s sensory, motor, or cognitive

functions are often subtle and gradual which can make it difficult for older people to

draw the link between these changes and the impact on their driving ability.

Therefore, the early stages of the PAPM emphasise the importance of increasing

people’s awareness about the impact of ageing on their driving ability. While it is

highly likely that older drivers are “generally aware” about the safety issues of older

drivers, they could lack “self-awareness” or insight into their own driving ability.

Once they become personally engaged with the hazard, people are more likely to be

more receptive towards adoption of the precaution and interventions should be

directed towards overcoming barriers of adopting self-regulation, promoting

alternative transport options, and improving the driving cessation outcomes. It also

differentiates between those who are unaware of the hazard and have never thought

about acting and those who have thought about acting and are still undecided (unlike

the TTM which groups them as the pre-contemplators). This differentiation is


important because those who have thought about acting are more likely to be more

knowledgeable, have different responses to information and are more resistant to

persuasion (Ditto & Lopez, 1992). By adapting the PAPM to address older adults’

self-regulatory driving behaviours, older drivers can be categorised into several

distinctive profiles as shown in Table 1.1. Interventions that promote successful self-

regulatory practice will vary according to the different stages of the PAPM.

Table 1.1: Adaptation of the PAPM to the older drivers’ regulatory behaviours

Stage Profile Characteristics

Stage 1 The

unaware

Generally unaware of the impact of age-related declines

on one’s driving abilities OR unaware of the self-

regulatory practices to reduce one’s risk of crash

Stage 2 The

unengaged

Generally aware of the problem but do not recognise the

changes in their own abilities and/or never thought about

the adoption of self-regulatory practices

Stage 3 The

undecided

Aware of changes in their own abilities but are either

unsure how it impacts their driving or how they should

modify their driving accordingly

Stage 4 The resister Thought about it but refused to either acknowledge the

need to modify their driving behaviours or unable to

modify their behaviours

Stage 5 The planner Thought about it and starting to monitor their driving and

plan to change their driving accordingly

Stage 6 The

regulator

Have started to reduce and/or avoid certain driving

situations in response to their declining abilities

Stage 7 The non-

driver

Have stopped driving altogether in response to their

declining abilities


1.3 RESEARCH AIMS

This research aims to contribute to the development of a theoretical

framework for a stage-based process leading to self-regulation of driving which

incorporates the role of feedback. This research program builds on the previous work

of Kostyniuk and colleagues (2000) by further examining the applicability of the

PAPM in understanding older adults’ self-regulatory driving behaviour. This aim is

addressed through the following specific objectives:

1. To explore the preliminary fit of older adults’ driving behaviour within the

PAPM framework using qualitative focus groups among current older drivers.

This is an assessment of the in-principle applicability of the PAPM.

2. To develop a conceptual model based on the PAPM that profiles older adults

into distinctive groups based on their mindsets towards self-regulatory driving

behaviours. An operationalisation of the PAPM for older drivers and their

adoption of self-regulation as a precaution.

3. To determine the prevalence of PAPM stages in a sample of older drivers and

identify the socio-demographic and psychosocial characteristics of stages

membership. An exploration of the application of the model stages in a sample

of older drivers.

4. To identify self-regulation profiles among older drivers based on their mindset

towards change using Latent Class Analysis (LCA) and determine the similarity

with the conceptual model. A test of whether the stages identified by the PAPM

reflect the underlying clustering of mindsets.

5. To examine the impact of providing one-on-one feedback regarding driving

performance on stage transition among a sample of older drivers and its impact

older drivers’ perception of the quality of their driving and their willingness to

modify their driving behaviour. A “real world” examination of the potential role

of feedback in contributing to progression through the stages of the PAPM.


These objectives are addressed through two stages comprised of three studies

with specific research questions (Figure 1.4; details presented in Chapter 4). The

first stage of the research employs an exploratory sequential mixed-method design.

Study 1, a qualitative study which examines the applicability of using the PAPM as a

framework for describing self-regulatory behaviours with a focus on the role of

feedback on the self-regulatory decision-making process. The findings from study 1

inform the development of a preliminary model of self-regulation. Study 2 is a

quantitative study that involves a survey (web-based and paper-based) of older

drivers. The analysis of study 2 is divided into two phases. Phase 1 aims to build on

the previous research by investigating whether a sample of older drivers can

accurately be assigned to the stages of the PAPM and to identify the psychosocial

and environmental factors associated with different stages of the PAPM. Phase 2

utilises a bottom-up approach to profile older drivers based on their mindset towards

adopting self-regulatory driving behaviours using Latent Class Analysis in an

attempt to empirically test the preliminary model. The preliminary model is then

refined and modified based on the findings from the LCA. Stage 2 is comprised of

study 3, an experimental study that assesses the impact of providing participants with

customised feedback on stage transitions and their intention to modify their driving

behaviours accordingly.

Figure 1.4: Stages of the program of research


1.4 SIGNIFICANCE OF THIS STUDY

The findings from this research program will:

• Contribute to the understanding of the older adults’ driving

experience, and the self-regulatory driving behaviour among older adults,

the decision-making process, and the facilitators and barriers to adopting

self-regulatory behaviours.

• Contribute to the understanding of older drivers’ perceptions and

experiences regarding receiving feedback about their driving abilities. Little

is known about the nature and content of feedback older drivers are

currently receiving about their driving and what type of feedback is

considered important to the older driver. Furthermore, it is still unclear

what would be the most effective way of delivering feedback to older

drivers to encourage them to modify their driving behaviour.

• Contribute to the literature on a theoretical level by developing a

framework of driving self-regulation based on the PAPM.

1.5 DEMARCATION OF SCOPE OF THE RESEARCH PROGRAM

The current research program focuses on the behavioural aspect of adopting

self-regulation and does not investigate the impact of improvements in road

infrastructure, vehicle standards/equipment, or in-vehicle technology on older adults’

safety. Even though Queensland (where respondents were sampled) has specific

licensing requirements for older drivers, this research does not address the

Queensland driver licensing system. Similarly, the research does not examine older

driver crashes or their contributing factors. Instead, it focuses on the psychological

and contextual influences on older driver self-regulation, an issue of common interest

across jurisdictions.

1.6 THESIS OUTLINE

The thesis outline is given in Figure 1.5. Chapter 1 provides an overview of

the research background, rationale, aims and objectives, and outlines the research

program. Chapter 2 reviews the literature on older driver safety and the current


interventions and strategies employed to address the problem. It identifies gaps in

current knowledge which inform the research questions underpinning the program of

research. Chapter 3 reviews the existing models of older adults’ driving behaviours

and the justification for choosing the PAPM as the underpinning theoretical

framework for this program of research. Chapter 4 provides an overview of the

research design of the thesis and briefly describes the methodology of the three

studies.

This is a thesis by publication, which contains two published journal articles

and a journal article currently under review. Chapter 5 presents the first published

study which describes Study 1 that involved focus groups with current older drivers

and how the findings resulted in the development of a conceptual model that partly

informed the direction of Study 2. Chapter 6 represents the second published article

which describes Phase 1 of Study 2 that involved a quantitative survey of current

older drivers for the investigation and the refinement of the conceptual model.

Chapter 7 represents the third article (on Phase 2 of Study 2) which is currently under

preparation and describes the findings from a Latent Class Analysis. Chapter 8

presents Study 3, an unpublished paper, which examines the usefulness of the model

by investigating the impact of customised feedback on moving people through

stages. Chapter 9 synthesises the results from the three studies and presents a

summary of the findings, discusses the limitations and strengths of this analysis and

provides recommendations for future research and clinical practice.

1.7 CHAPTER SUMMARY

This chapter presented the background to the current research and the specific

aims and research questions that this research program addresses. The expected

increase of the number of older drivers calls for urgent solutions that can maintain

their safe mobility. Previous studies indicate that self-regulation could be a

promising strategy to maintain older adults’ safe driving. However, little attention

has been directed towards developing a model that can enhance our understanding of

this complex process. This program of research adopts a unique approach by

examining the application of the PAPM in improving our understanding of the self-

regulatory driving behaviours among older adults. This improved knowledge can

assist in the developing of customised interventions that can help older drivers


accurately and successfully regulate their driving (i.e. without imposing unnecessary

restrictions or driving when it is no longer safe to do so).

Figure 1.5: Overview of thesis chapters

Chapter 1

Introduction and study background

Chapter 2

Literature review

Chapter 3

Theoretical approach

Chapter 4

Research design and methodology

Chapter 5

Paper 1 (published paper)

Chapter 6

Paper 2 (published paper)

Chapter 7

Paper 3 (under review)

Chapter 8

Draft research paper

Chapter 9

Synthesised discussion of research findings


Chapter 2: Literature Review


This chapter provides a review of the current literature on older drivers’ safety

and mobility issues with a focus on the existing countermeasures that attempt to

maintain older adults’ safe driving. The chapter starts by outlining the road safety

implications of the growing number of older drivers and the need to balance their

safety and mobility. The current approaches to older drivers licensing are discussed.

Next, the chapter provides an overview of the process of self-regulation and the

factors associated with self-regulatory behaviours among older drivers. The current

strategies and challenges of promoting successful self-regulation are also presented.

Finally, the chapter summarises the literature and concludes by identifying the

research gap from which the research questions are derived.

2.2 GROWING NUMBER OF OLDER DRIVERS

The ageing of the baby boomers along with the increased life expectancy of

successive generations will result in major changes in Australia’s demographic (

King et al., 2011). In 2007, 13% of the population were aged 65 years or more

(ABS, 2008). By the year 2030, it is expected that adults aged 65 years and more

will comprise 23% of the Australian’s population (Rakotonirainy, Steinhardt,

Delhomme, Darvell, & Schramm, 2012) and the proportion of adults aged 85 years

or more will rise from 1.6% of the population in 2007 to 7.3% by 2056 (ABS, 2008).

These significant changes in the population structure will provide new

challenges to road safety researchers (Alsnih & Hensher, 2003). First, the proportion

of drivers aged 65 years and above continues to be the fastest growing part of the

driving population (Ball et al., 2006; Wang & Carr, 2004). Second, a larger

percentage of older adults retain their driving license (Hakamies-Blomqvist &

Henriksson, 1999) and continue to drive much longer and for greater distances

compared to previous generations (Braitman & McCartt, 2008; Owsley, McGwin,

Phillips, McNeal, & Stalvey, 2004; Wang & Carr, 2004). Third, the mobility and

transportation needs for the baby boomers are distinctively different to those of

previous generations. Baby boomers are predicted to be significantly active, making


more trips than previous generations (Currie & Delbosc, 2010), relying more on their

cars and less on public transport (Alsnih & Hensher, 2003). This dependence on the

private automobile will result in unfavourable consequences when it is time to give

up the car keys and retire from driving (Buys, Snow, van Megen, & Miller, 2012).

2.3 THE IMPORTANCE OF DRIVING

Older people now have greater access to cars and their private automobiles are

their principal and favourable form of transport (Molnar & Eby, 2009). The majority

of older drivers view driving as key to their independence and mobility (Adler &

Rottunda, 2006; Musselwhite & Haddad, 2010a). Driving is described by some as a

symbol of identity (Eisenhandler, 1990), independence (Persson, 1993), and security

(Bauer, Kuskowski, et al., 2003), so the decision to stop driving is one of the most

difficult decisions older adults have to make (Adler & Rottunda, 2006).

Qualitative evidence has shown that older adults describe the idea of stopping

driving as traumatizing (Whelan et al., 2006). Driving is convenient and flexible

(Burkhardt, McGavock, & Nelson, 2002) and giving up driving can limit people’s

mobility and leave them feeling socially isolated (Coughlin, 2001; Eisenhandler,

1990). Further, driving is often described as an enjoyable activity by older people

(Burkhardt et al., 2002) and the negative aspects of driving are often attributed to

external factors such as behaviours of other drivers (Burkhardt et al., 2002; Yassuda

& Wilson, 1997) or financial cost associated with driving (Burkhardt et al., 2002).

Restricting or stopping driving can be associated with feelings of regret and

loneliness (Johnson, 1999), increased risk of depression ( Ragland et al., 2005),

isolation (Fonda et al., 2001), decreased out-of-home activities (Marottoli et al.,

2000), and increased risk of entering long-term care facilities (Freeman et al., 2006).

Stopping driving has also been linked to increased risk of dying. In a prospective

cohort study among 660 older adults aged 63 and above, non-drivers had an

increased mortality risk compared to drivers (Edwards et al., 2009). In a larger study

(n = 2,793), risk of dying was 1.68 times higher for non-drivers compared to drivers

(O'Connor, Edwards, Waters, Hudak, & Valdes, 2013), however, health problems

mediated this association (O'Connor et al., 2013).


2.4 TRANSPORTATION ALTERNATIVES

The availability of other transport options (Coughlin, 2001) and the cost of

public transport (Corpuz, 2007) have been identified as important factors in the

decision to give up driving among older adults. In fact, some older drivers may

continue to drive despite being aware of their declining ability to avoid the use of

alternative transports (Atkin, 2001). In a recent study conducted by Buys et al.

(2012), among a sample of 24 older adults in Queensland, the private automobile was

considered to be the most convenient mode of transport among participants

regardless of the availability of public transportation (Buys et al., 2012). As Buys et

al. (2012) points out, the convenience and ease offered by the car may act as an

important barrier to the use of alternative transport options among older drivers. In

addition, psychological barriers (e.g. feeling a burden, fear for safety) (Taylor &

Tripodes, 2001), geographical barriers (e.g. availability of alternative transport or

social support) (Musselwhite & Haddad, 2010b), and lack of knowledge (Peel,

Westmoreland, & Steinberg, 2002) can affect the usage of these alternatives.

Overall, older drivers often view public transportation to be costly, unreliable,

unsafe, and difficult to access (Allan & McGee, 2003; Gardezi et al., 2006). Older

adults often view taxis as an expensive form of transportation and report concern

over their personal safety (Oxley, Charlton, & Fildes, 2003). Qualitative evidence

suggests that former drivers prefer rides from others for their transportation and

mobility needs (Burkhardt et al., 2002) as it gives them a sense of closeness with

their family (Musselwhite & Shergold, 2013). However, they often express concerns

about the fear of becoming a burden (Bonnel, 1999). This is supported by the

research conducted by Bauer et al. (2003), where many of the women who

participated in the study used formal transit services regularly to maintain their

independence and freedom (Bauer, Rottunda, & Adler, 2003). Although transit

services did not provide them with the same freedom or flexibility they had when

driving, they valued the sense of “selectivity and decision-making involved in using

them” (Bauer, Rottunda, et al., 2003).

Shifting to a new transportation option requires active planning (Shergold,

Parkhurst, & Musselwhite, 2012) and people are not very keen on obtaining

information about alternative transport options (Nordfjærn, Şimşekoğlu, & Rundmo,

2014) especially if they do not consider they need such information (Shergold et al.,


2012). An interesting solution provided by Musselwhite & Shergold (2013)

emphasises the need to promote the use of alternative modes of transport throughout

life or at least from a much younger age. This gradual introduction of alternative

transport options might help eliminate the psychological barriers associated with

their use (Musselwhite & Shergold, 2013).

2.5 FACTORS ENABLING DRIVING SAFETY AMONG OLDER DRIVERS

Safe driving requires a dynamic interaction between different sensory,

cognitive and motor abilities. As people start to age, they may experience decline in

these abilities (Holland & Rabbitt, 1992). This is often caused by the increased

prevalence of health problems with ageing and the medications used to treat these

conditions but can also be seen with normal ageing (Anstey et al., 2005). If unable to

compensate for these changes, older drivers may put themselves and others at risk

(Freund et al., 2005). There is an extensive body of research that explains the link

between age-related declines among older drivers and higher risk of at-fault crash

involvement (Staplin, Lococo, Martell, & Stutts, 2012).

Anstey, Wood, Lord, and Walker (2005) presented a model of driving safety

in older adults (Figure 2-1) which consists of two main factors: driving capacity and

self-monitoring and beliefs about driving. Driving capacity is determined by

cognition, sensory, and physical function (Anstey et al., 2005). Self-monitoring

beliefs refers to the ability to evaluate one’s driving ability, and adapt driving

behaviours accordingly (Anstey et al., 2005). Therefore, older drivers’ insight into

their driving skill is crucial for accurate evaluation of their ability and accordingly

successful self-regulation behaviours. However, up until now, the relationship

between reduced fitness to drive and increased risk of crash is not fully understood.

The inconsistency in the measures used to assess the functional and cognitive

abilities among older drivers and the diversity in the driving outcome measures used

in previous studies makes it rather difficult to establish a clear and a consistent link

between a certain functional ability, driving performance and increased crash risk.


Driving Behaviour

Self-monitoring and beliefs about driving

capacity Capacity to drive safely

Cognition Vision Physical function

Figure 2.1: Multifactorial model of factors enabling safe driving among older drivers

From “Cognitive, sensory and physical factors enabling driving safety in older

adults” by Anstey et al, 2005, Clinical Psychology Review 25, p. 60.

2.6 ARE OLDER DRIVERS A ROAD SAFETY PROBLEM COMPARED TO OTHER DRIVERS?

In Queensland, drivers aged 60 years and above are over-represented in fatal

and life-threatening crashes and their involvement increases steadily with age

(Rakotonirainy et al., 2012). Furthermore, drivers aged 80 years and above are most

likely to be at fault for injury or death-related crashes (Rakotonirainy et al., 2012).

However, the association between age and crash risk is highly complex (Cheung &

McCartt, 2011) and there is an ongoing debate about the risks older drivers carry to

themselves and to other road users in terms of crash involvement. Still, age is often

used as the basis of strict licensing conditions and assessment and it is therefore

important to determine if older drivers have an elevated crash involvement. As a

group, older drivers are relatively safe drivers and account for far fewer crashes

compared to other drivers (De Raedt & Ponjaert-Kristoffersen, 2000a; Eberhard,

1996). However, when distance driven is taken into account, older drivers are over-

represented in crashes compared to middle-aged drivers (King et al., 2011). Older


drivers are also more likely to be injured or killed if being involved in a crash

compared to younger or middle-aged drivers (King et al., 2011). Researchers debate

that methodological biases are the reason for this overestimation of older drivers’

involvement in crashes; particularly the fragility and the low-mileage biases.

The fragility bias

Due to their frailty, older drivers are over-represented in serious and life-

threatening motor vehicle crashes (Meuleners et al., 2006) and this involvement

increases steadily with age (Bédard, Guyatt, Stones, & Hirdes, 2001). This can be

attributed to reduced bone strength and fracture tolerance (Guest et al., 2014). Since

crash data mostly relies on reported incidents (Hauer, 2006), the increased likelihood

of being seriously injured or dying in a crash among older drivers may result in

increased rates of incident (Hauer, 2006). In 2003, Li and colleagues examined the

association of frailty (measured as risk of dying in the event of a crash) and increased

fatal crash involvement among different age groups, with the quantity of exposure to

vehicle travel being controlled for. Their findings showed that fragility was a

substantial determinant of the increased risk per unit of travel among older drivers

(60 years or older) (Li et al., 2003). Another study conducted in 2008 revealed that

when compared to middle-aged drivers, those 85 years and older have an eight times

higher mortality risk per mile travelled but pose only 1.5 mortality risk to others

(Tefft, 2008).

The low-mileage bias

Driving shorter distances is associated with greater crash risk regardless of age

(Janke, 1991). Therefore, the increased crash rate among older drivers could be

exaggerated due to the lower mileage driver (Hakamies-Blomqvist, Raitanen, &

O’Neill, 2002). Increased crash risk seen in low mileage drivers is often the result of

the location of driving (e.g. urban areas with increased incidence of challenging

traffic situations) (Langford et al., 2013). Recent findings from the

Candrive/Ozcandrive study has confirmed the association between low mileage and

increased crash risk among older drivers where low mileage drivers did considerably

more poorly on a variety of performance measures (Langford et al., 2013). However,

this study relied on self-reported measures of driving which does not provide an

accurate reflection of the actual driving behaviours of older drivers. In 2015, Coxon

and colleagues examined the association between age, function and driving exposure


using objective measures in a large sample of 380 drivers aged 75 years and above.

They found that older people with poorer function drove fewer kilometres per week

and took shorter trips closer to home (Coxon et al., 2015) However, the study was

conducted for one week which may be relatively short to capture usual driving

practices.

2.7 PATTERNS AND CHARACTERISTICS OF OLDER DRIVERS’ CRASHES

Older drivers have distinctive crash patterns compared to other age groups.

They are often responsible for their crashes (King et al., 2011; Stutts, 1998) and the

most common causes of their crashes are failure to see other road users, sudden

illness, or lack of awareness to traffic signal (King et al., 2011). The large part of

their crashes involves collisions with another vehicle (Langford, Andrea, Fildes,

Williams, & Hull, 2005) and is more likely to occur at intersections (Boufous, Finch,

Hayen, & Williamson, 2008). A recent study analysing Queensland crash data over

9 years period has revealed that drivers aged 60 and above are over-represented in

fatal and serious crashes and failure to give way crashes (Rakotonirainy et al., 2012).

The impact to the vehicle’s side commonly seen in intersection crashes coupled with

older adults’ fragility have been attributed to the more serious injury or greater death

rates among older drivers in intersection crashes (Morris, Welsh, Frampton,

Charlton, & Fildes, 2003). Older drivers have a small share of speed-related or

alcohol-related crashes (OECD, 2001) and their crashes rarely occur at night

(Langford et al., 2005), on weekends, in peak hour traffic, or in adverse weather

(OECD, 2001).

Interestingly, recent studies indicate that older drivers’ crashes are decreasing.

Cheung & McCartt (2011) analysed crash rates in the United States and revealed that

older drivers’ fatal crash risk has declined through with the greatest decline observed

among those aged 70 years or above (Cheung & McCartt, 2011).

2.8 CURRENT OLDER DRIVER ROAD SAFETY COUNTERMEASURES

The significant over-involvement of older adults in fatal and life-threatening

crashes has prompted the development and implementation of a variety of

countermeasures to promote their safe mobility. These countermeasures aim to


maintain safer older drivers on our road systems and to manage the mobility needs of

older drivers; they include:

1) Identifying high-risk older drivers and referring them to licensing

authorities for additional assessment (Langford & Koppel, 2006). The main

aim should be to manage their limitations and improve their skills so that they

can maintain their driving for as long as they can safely (Langford & Koppel,

2006). However, if considered unsafe and unfit to drive, resources should be

directed to improve their cessation of driving experience.

2) Encouraging the older drivers to self-monitor their driving and

self-regulate accordingly and to seek feedback regarding their driving

abilities and performance regularly (Berry, 2011).

3) Encouraging older drivers to plan their driving cessation from

early age to minimise the negative consequences associated with driving

cessation (Musselwhite & Shergold, 2013).

2.8.1 Identifying high-risk older drivers

The major challenge faced by road safety researchers is the identification of

“high-risk” older drivers (Dobbs, Heller, & Schopflocher, 1998) who would benefit

from variety of interventions that intend to keep them driving safely and for longer

(Langford, Bohensky, Koppel, & Newstead, 2008). Throughout the literature, there

is inconsistency in the definition of “older driver” with no clear rationale that

explains the choice of a certain age limit above which one becomes an “older driver”

(Lang et al., 2013 ). Chronological age is a weak predictor of crash risk (Dickerson

et al., 2007) and it should not be used as a criteria to restrict people from driving

(Yassuda & Wilson, 1997). Using a single cut-point to define the older driver is

inadequate as it assumes that those over a certain age are a homogenous group and

crossing this age will shift the risk of crash from low to high (Newgard, 2008) and

ignores the fact that aging patterns vary widely among people (King et al., 2011).

Older drivers are often divided into two broad groups, those with medical

conditions that require reporting to a transportation authority and those who are

relatively healthy (Rudman, Friedland, Chipman, & Sciortino, 2006b). Certain

health conditions and medications are often associated with an increased risk of


crashes (Dobbs, 2008) and ageing is often accompanied with an increased incidence

of such conditions. Some researchers suggest that policies should be targeted

towards identifying medically-at-risk older drivers and to provide them with

individualized assessments (Dobbs, 2008). This strategy would mean that physicians

will play a greater role in the older drivers’ licensing policies. However, while

previous research has indicated that older adults trust and respect their physician’s

opinions regarding their driving (Coughlin, Mohyde, D'Ambrosio, & Gilbert, 2004),

there are various problems that could arise if the licensing system becomes overly

medically-regulated. Physicians often lack knowledge regarding the relationship

between medical conditions and driving (Dobbs, 2008), and they often express

concerns about compromising their patient’s trust (Betz, Jones, Petroff, & Schwartz,

2013). Another major concern is that a medically-regulated licensing system may

divert people away from disclosing and discussing changes in their driving abilities

with their physicians (Berry, 2011). They can also become more reliant on their

physicians to assess their driving abilities, and therefore do not monitor their driving

or regulate it in response to age-related declines that are not a part of medical illness

(Berry, 2011).

Driving is a complex task that requires dynamic interaction between various

cognitive, physical, and sensory functions (Anstey et al., 2005). Some medical

conditions may affect driving abilities and can assist healthcare professionals in

identifying older adults who may require further assessment (Marshall, 2008).

However, the diversity of ways a disease may affect two individuals, the severity of

the disease, the effect of treatment on crash risk, and the presence of multiple

medical conditions make it difficult to generalise the association between a medical

condition and fitness to drive (Marshall, 2008). Further, while medical conditions

have an effect on older drivers’ fitness to drive, the crash risk is only slightly-to-

moderately increased (Marshall, 2008) and driver retraining or other interventions

may have the potential to reduce crash risk (Marshall, 2008).

There is also a great discrepancy between the relatively healthy older adults

in terms of how they are experiencing non-pathological declines in their driving

abilities, the types of these declines, and how these declines could impact their

driving performance. In the absence of a medical condition that clearly affects

driving abilities, it may be difficult to identify older drivers who are suffering from


subtle and progressive age-related changes in their functional abilities and regulation

and/or restriction of driving is in many of these cases a voluntary act by the driver.

Still, policy makers view older drivers as a homogenous group and neglect the fact

that there is a considerable variation in driving performance and health measures

among older adults which is seen even at older ages (Langford & Koppel, 2006).

Overall, identifying high-risk group of older drivers is still problematic since

driving is a complex activity that relies on a wide range of sensory, motor, and

cognitive abilities. Up until now, there is very limited evidence to support the use of

off-road screening batteries in assessing older adult’s fitness to drive (Wood et al.,

2008) and there are contradicting evidence in regards to which abilities are crucial

for safe driving (Marshall, 2008). A recent systematic review has revealed that the

“use of a single tool measuring cognition, vision, perception or physical ability is not

sufficient to determine fitness to drive” (Dickerson, Meuel, Ridenour, & Cooper,

2014). Much research is needed to determine the ideal battery of tests to be used that

can detect fitness to drive while ensuring reliability and validity (King et al., 2011).

Attempts have been directed towards identifying older drivers through

measures of medical screening and on-road tests. The effectiveness of these

measures is discussed in the following section.

Age-Based Licensing Interventions

Age-based assessments have been proposed as a strategy that can help

identify older drivers at increased crash risk. There is a wide variation in the

assessment procedure and age requirements for licensing renewal in Australia as

shown in Table 2.1.

Still, despite its widespread use, age-based mandatory testing has not shown

any safety benefits in term of reduction of crash risks (Mitchell, 2010) and has not

been shown to be effective in identifying older drivers with increased crash risk due

to functional declines (Oxley & Whelan, 2008) .

Previous studies which compared the rate of crashes of older drivers between

areas with mandatory age-based testing and areas with no age-based renewal

requirements found no difference in the rate of crashes among older drivers

(Hakamies-Blomqvist & Peters, 2000). In 1986, Torpey conducted a study where he

compared older drivers’ fatality crash rates across different licensing jurisdictions in


Australia (with the exception of Victoria, all states had some form of mandatory age-

based assessment) (Torpey, 1986). Interestingly, the Victorian crash rate was lower

than crash rates for Queensland, Western Australia, and Tasmania and was closely

similar to those in South Australia and New South Wales (Torpey, 1986).

Table 2.1: Driver Licensing Practice renewal for car drivers (excluding heavy

vehicle and motorbikes) in Australia (2016)

State Age-requirement

for re-license

Medical Examination On-road Practical Test

ACT 75 Annual medical certificate from

the age of 75

When reported

New South

Wales

75 Annual medical certificate from

the age of 75

Biannual on-road test

from the age of 85

Not required for

conditional licences

Northern

Territory

- When reported When reported

Queensland 75 Annual medical certificate from

the age of 75

When reported

South

Australia

- When reported When reported

Tasmania 75 Annual medical assessment When reported

Victoria -

When reported When reported

Western

Australia

80 Annual medical examination

required from the age of 80 to

assess fitness to drive

Annual practical driving

assessment if

recommended by health

professional from the age

of 85


A similar study was conducted by Langford et al. in 2004 which determined

that mandatory assessment programs do not offer any noticeable safety benefits

(Langford, Fitzharris, Koppel, & Newstead, 2004).

Further, older drivers in states that employ some form of mandatory

assessment may choose to surrender their driving license while those in states with

no mandatory assessment may keep their license even after they stop their driving

(Langford, Fitzharris, Koppel, et al., 2004). To overcome the limitation associated

with previous study, Langford and colleagues compared the rates of fatal crash

among drivers aged 80 years and over in Melbourne which has no mandatory driving

assessment and Sydney where medical and on-road assessment is mandatory, using

population, number of licences held, total distance driven, and time spent driving as

exposure measures, while controlling for possible differences in driving activity

across the states (Langford, Fitzharris, Newstead, & Koppel, 2004). There was no

difference in crash risk based on population between Melbourne and Sydney. Per

licensed driver and per time spent driving, Sydney had statistically higher rates of

fatal crash involvement than older drivers in Melbourne (Langford, Fitzharris,

Newstead, et al., 2004).

In addition, a recent study by Ross et al. (2011) reported that drivers from

Victoria where no age-based testing is required are between 2 and 5 times more

likely to be driving than those from states with age-based testing (New South Wales

and South Australia) (Ross, Browning, Luszcz, Mitchell, & Anstey, 2011).

Interestingly, the percentage of older drivers suffering from cognitive impairments

(as measured by Mini Mental State Examination) and visual impairments (static

visual acuity) was similar between these three states (Ross et al., 2011).

In 2012, Tay examined the association between licensing requirements and

crash rates for older drivers in five Canadian provinces. There was a positive

association between the strictness of the licensing system and the mean crash rates.

The author concluded that since policies should be developed based on scientific

evidence, age-based testing is not recommended as they have no demonstrable safety

benefits (Tay, 2012). In New Zealand, older drivers aged 80 years and above were

subjected to a licence test through the period from 1999 to the end of 2006 which

involved an on road test of around 20 minutes that was suspended in 2006 (Keall &

Woodbury, 2014). Analysis of New Zealand Travel Survey data, licensing data, and


police-reported crash data failed to demonstrate any changes in the levels of road

injury involving drivers aged 80 and above (Keall & Woodbury, 2014). The study

provided further support to the ineffectiveness of on-road testing as an assessment

strategy for older drivers (Keall & Woodbury, 2014).

To conclude, attempts to address the older drivers’ safety problem through

mandatory testing offer no safety benefit (Lang et al., 2013 ). On the contrary, they

can compromise the mobility and safety of older adults and prompt premature

cessation of driving (Hakamies-Blomqvist & Wahlström, 1998). Premature

restriction of driving can cause older adults to use alternative riskier modes of

transportation such as walking or cycling (Langford et al., 2008; Oxley & Whelan,

2008). Older adults are at greater risk as vulnerable road users than when using a car

(Oxley & Whelan, 2008). Further, older drivers’ skills and performance can

sometimes be enhanced to satisfactory levels through a number of countermeasures

such as education, physical rehabilitation, self-regulation, and/or regulation by

licensing authorities ( Eby, Molnar, Shope, Vivoda, & Fordyce, 2003)

Langford and Koppel raise an interesting point about older drivers’ right to

choose to continue or stop driving (Langford & Koppel, 2006) as their over-

involvement in serious and fatal crashes is caused by their increased fragility and

they do not represent an increased risk to other road users (Langford & Koppel,

2006).

Licence Restrictions

In Australia, drivers with diagnosed medical conditions and disabilities that

impair their driving abilities could be subjected to licence restrictions. According to

Langford & Koppel (2011) licence restrictions attempt to:

● enhance fitness to drive – (e.g. wearing corrective lenses);

● create safer vehicles – (e.g. using automatic transmission); and

● avoid challenging driving situations- (e.g. night driving).

There are few studies that have attempted to examine the effectiveness of

restricted licenses on the crash risk of older drivers. A recent study using provincial

insurance claim data from all drivers aged 66 years or over for the years 1999-2006


in British Columbia compared crashes caused by drivers with restricted versus

unrestricted licenses (Nasvadi & Wister, 2009). Restricted licence holders were more

likely to be older, men, and with a history of at-fault crashes (Nasvadi & Wister,

2009). The results showed that drivers were involved in fewer crashes after

restrictions were placed on their licences (Nasvadi & Wister, 2009). Further,

compared to unrestricted drivers, restricted licence holders continued to drive crash

free for longer and their risk of causing a crash was 87% that of unrestricted drivers

after controlling for age and gender (Nasvadi & Wister, 2009).

Recently, Langford & Koppel examined the extent of use of restricted

licences and their safety benefits in the state of Victoria (Langford & Koppel, 2011).

Less than 10% of older drivers had a licence restriction (Langford & Koppel, 2011).

Majority of licence restrictions (95%) involved wearing corrective lenses when

driving followed by (2%) of driving a vehicle with automatic transmission (Langford

& Koppel, 2011). The findings indicate that restrictions associated with wearing

corrective lenses while driving, restricting travel to a specified distance from one’s

home and preventing night-time driving were associated with lower crash rates

(Langford & Koppel, 2011). License restrictions were associated with decreased

crash rates and the increased crash risk of restricted drivers relative to drivers with no

licence restrictions was small and within an acceptable level (Langford & Koppel,

2011). However, the small number of older drivers with licence restrictions makes it

difficult to reach a definite conclusion of the safety benefits (Langford & Koppel,

2011).

Older drivers view licence restriction policy favourably if it does not

negatively impact their mobility (King et al., 2011). Given that licence restrictions

can impose unnecessary limitations on older drivers’ mobility, further research is

needed before it can be widely employed as a strategy to manage older driver safety

and to determine those who are most likely to benefit from them (Langford &

Koppel, 2011).

2.8.2 Encouraging older drivers to self-monitor their driving and self-regulate accordingly

The process of self-regulation starts by recognising the decline in certain

driving abilities and the need to appropriately compensate for such decline. The

majority of older drivers’ studies view self-regulation strategies as either avoidance


behaviours or driving reduction. Recently, Molnar and colleagues have introduced a

new and a broader definition of self-regulation where they classify self-regulatory

behaviours into three levels; strategic, tactical and life-goal (Molnar et al., 2013).

Strategic self-regulation involves the decisions made by drivers prior to taking the

trip and involve general planning such as avoiding difficult driving situations or

selecting certain driving routes. Tactical self-regulation involves the decisions made

by drivers while they are on the road, such as gap and headway acceptance, speed

choice, and overtaking, avoiding potentially distracting secondary activities in the

vehicle while driving. Life-goal level of self-regulation involves the broader

decisions made by older drivers in their lives such as the choice or what kind of car

to drive, with safety often being an important consideration in the vehicle purchase

decision. Interventions to promote successful self-regulatory behaviours will vary

for each level. On the strategic level; interventions enhancing self-awareness of

limitations in driving abilities would be beneficial. On the tactical level, older

drivers would benefit from in-vehicle technologies that can assist them in making

safer decisions on roads. On the life-goal level, strategies should promote use of

alternative transport options, moving close to public transport, and planning retiring

from driving. Most of the previous studies investigating the process of self-

regulation have focused on strategic self-regulation. The following discussion will

focus on strategic self-regulation as there are very few studies that have examined the

tactical and life-goal self-regulatory behaviours among older drivers.

Factors associated with self-regulation

Socio-demographic factors

Age: Older age has been associated with mileage reduction (Marottoli et al.,

1993) and subsequent driving cessation (Freeman et al., 2006). However, some

studies failed to show a significant association between increasing age and self-

regulation (Blanchard & Myers, 2010). These mixed findings could be the result of

differences on how self-regulation is defined between studies or due to differences in

the sample (e.g. different age groups, prevalence of medical illnesses, and health

status).

Gender: Older women are more likely to self-regulate their driving than

older men (Anstey et al., 2006). When compared to males, older female drivers are

more likely to avoid driving at night, in bad weather, in rush hour and on highways


(Baldock et al., 2006a). They also make fewer trips, drive fewer days and fewer

miles/kilometres, and drive closer to home compared to older men (Rosenbloom &

Herbel, 2009). Men, on the other hand, make less radical changes to their driving

behaviours (Evans, 1991) and they are very reluctant to give up driving (Kostyniuk

et al., 1998). Further, compared to men, women are more likely to acknowledge

their declining abilities (McNamara, Chen, George, Walker, & Ratcliffe, 2013),

while men tend to associate their decision to giving up driving to external reasons

(e.g. medical conditions) rather than declining abilities (McNamara et al., 2013).

Older women are also more likely to stop driving before older men (Anstey et al.,

2006) and some could be even giving up driving prematurely (Siren & Meng, 2013).

A Finnish study indicated that women who surrendered their driving license at the

age of 70 (n=1476) had lesser overall health ratings than those women who

maintained their driving license (n=1494) (Siren, Hakamies-Blomqvist, & Lindeman,

2004). Interestingly, those health conditions affected that overall health and mobility

of former drivers but were not necessarily affecting their fitness to drive which

indicates that some women may be stopping driving too early when they are still fit

to drive (Siren et al., 2004).

But why do women give up driving earlier than men? This could be

attributed to how women view the role and the importance of driving. For women,

driving is an essential means to meet their daily practical needs (e.g. family

commitments, employment, social activities, etc.) while for men it is key to their

identity, independence and freedom (Musselwhite & Haddad, 2010b). In addition,

women often indicate that loss of confidence is the reason they stopped driving

(McNamara et al., 2013). Older women lack confidence in their driving as they often

have less driving experience when compared to men (Marottoli et al., 1993).

Another explanation is that their male partners often discourage them from driving

and criticise their driving performance (Siren & Hakamies-Blomqvist, 2005).

As women are starting to resemble men in terms of education and

employment, their driving experience and their attitude towards driving may start to

resemble that of men (Rosenbloom, 2006). Driving will become an integral part of

their identity, and like men, it will be the key to their freedom and independence. It

is therefore predicted that the future cohort of female drivers will be driving for

longer (Rosenbloom & Herbel, 2009).


Income and household composition: Qualitative evidence has shown that

financial comfort could impact older drivers’ decision to stop driving (Adler &

Rottunda, 2006). Some studies showed an association between lower annual

household income and self-regulation (Naumann, Dellinger, & Kresnow, 2011;

Ragland, 2004), higher income and driving cessation (Unsworth, Wells, Browning,

Thomas, & Kendig, 2007), and others have shown no association (West et al., 2003).

Charlton et al. (2006) reported that those who were not the major driver of the

household were more likely to report adoption of self-regulation. On the other hand,

Ragland et al. (2004) reported that household arrangements had no impact on self-

regulation. Braitman and McCartt (2008) reported that those who were single,

divorced or widowed were 53% more likely to self-regulate than those who were

married.

Experience of a crash

In a study conducted by Charlton et al. (2006), drivers with a history of self-

reported crash in the last two years were 1.5 times more likely to self-regulate their

driving compared to those who were not involved in a crash. Ball et al. (1998) also

reported more avoidance among older drivers with a history of at-fault crashes in the

prior five years as obtained from state records.

Health, medical conditions, and age-related decline

There is an association between a large number of health and physical

functioning measures and cessation of driving as evident in longitudinal studies

(Anstey & Smith, 2003). However, not all those suffering from serious health issues

regulate or stop their driving. A study by Stewart et al. (1993) revealed that an

alarming 68% of older drivers who suffered from a short-term vision loss continued

to drive (Stewart, Moore, Marks, May, & Hale, 1993). Similar findings were seen

among older women, where 38% of those with a self-reported condition or symptom

that may affect driving ability continued to drive (Siren et al., 2004). This could be

due to the fact that older drivers’ perceptions of their health conditions and how they

impact their driving are far more important factor than their objective health

condition (Anstey et al., 2005). In addition, individuals suffering from some types of

cognitive impairments may lack insight into their declining abilities and therefore

will not regulate accordingly (Ackerman et al., 2011). Recent findings have shown

that older drivers have high ratings of their driving ability regardless of their


cognitive ability assessed by the Clock Drawing Test (CDT) (Wong, Smith, &

Sullivan, 2012). Further those who failed the CDT were less likely to report driving

avoidance and were less interested in participating in driving programs (Wong et al.,

2012).

Knowledge and health literacy

A recent study among 322 Australian drivers aged 65 years and over

investigated the association between health literacy and self-regulation of driving

(Sargent-Cox, Windsor, Walker, & Anstey, 2011). Around 86% of participants

demonstrated good knowledge about health conditions and driving safety but around

50% lacked knowledge about the impact of certain medications on driving abilities

(Sargent-Cox et al., 2011). The findings also show that health knowledge is far less

significant for predicting driving behaviour than actual health experience (Sargent-

Cox et al., 2011).

Confidence

Numerous studies point to the significant association between self-reported

driving confidence/comfort and driving behaviour (Blanchard & Myers, 2010). Self-

regulation as a result of lack of confidence may be a cause for concern (Moták,

Gabaude, Bougeant, & Huet, 2014) rather than an indication of successful self-

regulation. Self-regulation of driving as a response to the discomfort older adults

experience in stressful driving conditions rather than intentional monitoring of their

driving ability (Meng & Siren, 2012) represents a failure of self-regulation rather

than a success. These drivers may attribute their feelings of discomfort to external

reasons (i.e. glare from other cars’ headlights on their glasses, changes in the road

systems) rather than possible declines in their own driving abilities. On the other

hand, drivers may impose unnecessary driving restrictions on their driving (Meng &

Siren, 2012), despite being able to safely drive in these situations if they adopted

other coping strategies such as pre-journey planning or vehicle modifications

(Gwyther & Holland, 2014).

Self-awareness

In the multifactorial model for enabling driving safety, factors of cognition,

sensory function and physical function predict an individual’s driving capacity;

however, accurate insight into one’s driving capacity is crucial for safe driving


behaviour (Anstey et al., 2005). In driving, not only it is important to recognise that

a specific ability has declined but also to understand the implication of that decline

on the driving performance (Charlton, Oxley, Fildes, & Les, 2001). Those who are

unaware of limitations in their driving abilities may engage in behaviours that

jeopardise their safety and the safety of others (Marottoli & Richardson, 1998). In

addition, older drivers who are aware of declines in their abilities are more likely to

practice self-regulation than those who are less self-aware (Blanchard & Myers,

2010; Holland & Rabbitt, 1992; Molnar & Eby, 2008). Whether older drivers are

aware of their functional abilities or not remains questionable. A study conducted

among older drivers (n=257) has shown that those with existing visual and/or

attentional impairments reported more avoidance than those free of impairments

(Ball et al., 1998). Further, a five-year longitudinal study showed that older drivers

at increased crash risk determined by Useful Field of View (UFOV) test reduced

their driving exposure and increased driving avoidance over time compared with

those at low risk of crash (Ross et al., 2009).

On the other hand, several studies have reported that older drivers overrate

their driving abilities and performance. For instance, Holland and Rabbitt (1992)

demonstrated that drivers in their 70s rated their sensory abilities to be similar to

those in their 50s. Freund et al. (2005) found that among drivers aged 65 years and

above who were referred to driving evaluation, 65% of the participants estimated

they will perform better and 31.9% estimated they will perform the same on the

driving test as others their own age. In addition, higher self-rating of skill was

significantly associated with increased risk of driving difficulty assessed by driving

simulation (Freund et al., 2005).

Further, some researchers point out that self-regulation of driving is actually

an automatic process performed by the driver to minimise the mental load associated

with the functional declines brought by ageing rather than to enhance their safety (De

Raedt & Ponjaert-Kristoffersen, 2000a) . Therefore, drivers may not be aware that

they are compensating for functional loss. Their self-regulation of driving may be

merely a response to the discomfort they experience in challenging driving

conditions rather than intentional monitoring of their driving ability (Meng & Siren,

2012).


Limitations of self-regulation literature

The discrepancies in the findings of previous studies on self-regulation can be

attributed to methodological problems (Molnar et al., 2015). To start with, the way

self-regulation is defined varies considerably between studies. The majority of these

studies have examined self-regulation in terms of avoidance of difficult situations,

e.g. driving at night, adverse conditions (Baldock et al., 2006a; Charlton et al., 2006).

Self-regulation of driving involves any decision drivers make to enhance their overall

driving safety by overcoming limitations in their driving. This involves a variety of

behaviours such as planning trips, reducing the overall amount of driving, restricting

driving, taking a passenger to assist with navigation and broader life decisions that

can impact their overall driving (e.g. relocating to a senior’s house, vehicle

adaptation) (Molnar et al., 2013). For example, recent findings suggest that the

reasons behind reducing driving are different from avoiding challenging situations

(Meng & Siren, 2012). Reducing the overall amount of driving is often attributed to

lifestyle factors and the reduced need for mobility (e.g. retirement, relocation) (Meng

& Siren, 2012). On the other hand, driving avoidance is often triggered by negative

feelings associated with driving situations (Meng & Siren, 2012). Latest findings

that younger drivers also avoid some driving situations (Naumann et al., 2011)

suggest that driving avoidance is not always the result of age-related declines in

driving abilities. In their study, Naumann et al. (2011) reported that around 25% of

drivers aged 18-24 avoided driving at night, 50% avoided driving in bad weather,

and almost 20% avoided driving on highways and high-speed roads. Reduced

driving has been linked to number of factors such as retirement (Burson, Larrick, &

Klayman, 2006) or changes in lifestyle (Blanchard & Myers, 2010). Up until now,

few studies have investigated the reasons for avoidance or reducing driving among

older drivers. Motivations to reduce driving and to avoid driving situations for

reason other than awareness of impaired abilities should not be regarded as self-

regulation. Future studies should examine the specific reasons older drivers choose

to modify their driving patterns before classifying it as self-regulation.

Second, most of these studies have relied on self-report measures. Recent

findings suggest that self-report measures of driving behaviours do not match

objective measures of real-world driving (e.g. older drivers can not accurately

estimate their driving distances (Huebner, Porter, & Marshall, 2006) and they tend to


drive more frequently in challenging situations than they actually report (Blanchard

& Myers, 2010).

Third, up until now, the majority of previous studies focused on the

association between self-regulation and specific impairments and medical conditions

among older adults (Rudman et al., 2006). Recently, attention has been diverted into

understanding the psychosocial factors that affect self-regulatory driving behaviours.

However, due to the differences in the way drivers’ perceptions are measured and

defined, it is difficult to compare the findings (Blanchard & Myers, 2010).

Fourth, majority of studies rely on convenience sample of older drivers which

can limit the generalisation of the findings. Previous studies vary considerably

regarding participants’ characteristics, their driving patterns, and their cultural and

social context (Molnar et al., 2015).

Finally, driving cessation is more of a gradual and voluntary process

whereby the driver will gradually increase self-imposed restrictions (Dellinger et al.,

2001). As suggested by previous research, the driving cessation process may occur

through stages and older adults’ response to feedback may vary depending on which

stage they are at. Without longitudinal studies that follow older drivers through the

process of self-regulation it will be difficult to conclude which and how certain

factors influence older drivers’ decision to change and/or stop their driving. The

majority of the studies examining the factors associated with self-regulation has been

cross-sectional (Ackerman, Edwards, Ross, Ball, & Lunsman, 2008).

Is self-regulation effective in eliminating crash risk?

The large number of factors and countermeasures that contribute to the crash

risk among older drivers and the methodological limitations outlined above make it

difficult to determine if self-regulation is effective in eliminating increases in crash

risk caused by age-related declines (Horswill et al., 2011). However, some evidence

suggests that the self-regulation may be a promising strategy in reducing crash risk

among older drivers. A study by Anstey et al. (2006) assessed 1446 older drivers

aged 70 and above at baseline on several visual, cognitive and functional measures

and followed them for a five years’ period (1992-1997). The authors found that the

variables associated with driving cessation to be similar to those associated with

increased crash risk in older adults, which suggests that older adults with cognitive or


visual impairments reduce their risk of crash by modifying their driving behaviour

(Anstey et al., 2006). Further, analysis of fatal crashes from the Fatality Analysis

Reporting System between 1997 and 2008, indicated that the licensing rate for

people 70 and older increased from 73 to 78 percent, but fatal passenger vehicle

crashes per licensed drivers in this age group fell 37 percent, in comparison to a 23

percent decrease for drivers ages 35 to 54 (Cheung & McCartt, 2011). The decline

was greatest (47%) among drivers 80 and older. While the reasons are not fully

understood, self-regulation may be playing a role (Braitman & Williams, 2011).

Keay et al., 2013 pointed out that recent epidemiological results, based on the

findings from the North American Fatality Analysis Rating System, support the use

of self-regulation to increase older drivers’ safety (Keay et al., 2013). Individuals

who drive in daylight and individuals with a history of motor vehicle conviction were

less likely to be injured in a crash probably as these individuals recognise their

limitations (Keay et al., 2013).

The impact of feedback on self-regulation among older drivers

To date, research that focuses on the impact of feedback on older drivers’

self-awareness and subsequent self-regulatory behaviours is limited. The changes

associated with ageing are usually subtle and older people may not be aware of how

these changes impact their driving abilities. In addition, driving errors and violations

will not necessarily result in crashes or penalties and drivers may fail to develop an

accurate estimation of their abilities (Dogan et al., 2012). If an incident takes place,

the driver may not understand why it occurred and how to prevent it in the future

(Dogan et al., 2012). Therefore, feedback can help drivers calibrate their perceptions

of their own performance with their actual performance (Donmez, Boyle, & Lee,

2007). Little is known about the factors that can influence the effectiveness of such

feedback, specifically in terms of timing and content.

Few studies suggest that feedback may lead older adults to make informed

decisions about their driving behaviour (Owsley, Stalvey, & Phillips, 2003). In a

study conducted by Holland and Rabbitt (1992), two thirds of participants (n=80)

reported making compensatory changes in their driving behaviours in response to

feedback about their sensory abilities. Eby et al. (2003) reported that 14% of older

adults, who completed a workbook that raised issues regarding health, cognition,

vision, and driving behaviour, discovered changes in their abilities, with 25%


reporting their intention to adjust their driving behaviour accordingly ( Eby et al.,

2003). In another study 129 older adults received feedback about their eligibility to

receive an insurance discount following the result of a UFOV test and those who

failed to qualify were more likely to increase driving avoidance over 3 months period

(Ackerman et al., 2011).

The following section will discuss existing interventions which are used to

provide older adults with feedback and promote driving self-regulation.

Self-screening tools

Self-screening tools can be used as first-tier assessment, pointing drivers to

the presence of adverse health problems and encouraging them to seek further

assessment and evaluation. They are available in both paper-based format and web-

based format. There are several advantages associated with the use of self-screening

tools. First they are relatively easy and cheap to dispense which makes them highly

accessible (Eby et al., 2003). They can also be completed in the driver’s house,

which is a friendly non-threatening environment (Eby et al., 2003). Further, previous

qualitative studies have indicated that such tools can promote early discussion of

driving future with family members and subsequently assist in the early identification

of driving-related problems which in turn may facilitate timely action to prolong safe

mobility (Eby et al., 2003). On the other hand, self-screening tools can only be

completed by cognitively intact individuals in order to understand the feedback and

act appropriately on it (Eby et al., 2003). In addition, individuals who choose to

complete self-screening are more likely to be more safety-oriented and older adults

with existing driving-related problems and limitations may be reluctant to use these

tools (Dunn, 2011). Self-screening tools are liable to self-enhancement bias which

can create a false sense of safety by providing inaccurate positive feedback on

driving abilities (Lang et al., 2013 ). Furthermore, the degree to which older drivers

can access information on age related changes and how these changes may affect

driving is still unknown (Siren & Haustein, 2015).

Family members and healthcare professionals

Older people are more likely to value the advice of those who have direct

knowledge about their driving abilities and those who are concerned about their best

interests (Coughlin et al., 2004). Generally, family members may be the first to


express their worries about an older adults’ ability to drive (Gillins, 1990). However,

the sensitivity of the topic may make it difficult to initiate such sensitive

conversation. Family members are often aware of the importance of driving in the

older person’s life and how it affects independence and wellbeing. In fact, some

family members may avoid being involved in this discussion altogether (Rudman et

al., 2006) to avoid creating problems (Connell, Harmon, Janevic, & Kostyniuk,

2013). This could also be complicated by existing difficulties or poor

communication (Connell et al., 2013). In a recent qualitative study, adult children

reported adopting a passive attitude towards their parents’ declining abilities such as

refusing to take rides with parents or discussing driving concerns with other family

members but not the parents (Connell et al., 2013). The loss of a driver’s license can

cause additional burden to families’ already busy lives (Johnson, 1999) and some

children would even tone down the risks associated with their parents’ declining

driving abilities to avoid being their carer (Connell et al., 2013). Therefore, family

members tend to ask the physicians to initiate the conversation (Persson, 1993).

In Queensland, drivers aged 75 years and above are required to hold a

current medical certificate that indicates their fitness to drive, regardless of whether

they have a medical condition or not. Therefore, physicians have the opportunity to

prevent and/or minimise the morbidity and mortality associated with traffic injury

among their patients and the general public (Molnar, Byszewski, Marshall, & Man-

Son-Hing, 2005). While many older drivers will give up driving based on their

physicians’ recommendations (Coughlin et al., 2004; D'Ambrosio, Coughlin,

Donorfio, Mohyde, & Meyer, 2008), there are number of barriers that can limit the

physician’s role in the decision-making process. To start with, physicians often

report that they lack the training and the confidence (Jang et al., 2007) necessary to

determine older adults’ fitness to drive. Further, none of the tools used in doctor’s

offices to assess the fitness-to-drive have been scientifically validated. Physicians

may also lack the knowledge regarding licensing policies and medical restrictions for

specific medical conditions (Bogner, Straton, Gallo, Rebok, & Keyl, 2004; Brooke &

Southward, 2006). Qualitative findings indicate that physicians may also be unaware

if their patients are still driving or not as some clinicians reported that they do not

routinely ask about driving (Bédard et al., 2001). In a recent study among 322

Australian drivers aged 65 years and more, an alarming 85.7% drivers indicated that


they did not receive any advice from their physician about the impact of their

medical condition on their driving abilities (Sargent-Cox et al., 2011).

Physicians often report feeling uncomfortable assuming an active role in

maintaining seniors’ mobility (Rudman et al., 2006b) as it may have a negative

impact on the physician-patient relationship (Jang et al., 2007). In fact, some older

drivers seek the input of another physician if the first one deem them unfit to drive

(Staplin & Freund, 2013).

Physicians can play an important role in the management of the older drivers’

safety issues if these gaps are addressed. In addition, normalising and discussing

fitness to drive from an early time can overcome the sensitivity associated with the

topic (Bédard et al., 2001).

In-vehicle technology

In- vehicle devices designed to prevent crashes are becoming technically

feasible and affordable (Walker, Stanton, & Young, 2001). These devices may have

the potential to improve road safety (Coughlin, 2005) and potentially maintain older

drivers’ mobility for longer (Rakotonirainy & Steinhardt, 2009). There has also been

a focus on the development of Advanced Driver Assistance Systems (ADAS), which

are electronic systems designed to help the driver manoeuvre through challenging

traffic circumstances (Lindgren, Chen, Jordan, & Zhang, 2008). Advanced Driver

Assistance Systems can improve driving safety by enhancing driver’s behaviour,

cognition, and perception. These systems can provide the driver with timely

feedback which can increase driver awareness about immediate environmental

changes (Zhao & Wu, 2012). However, little is known about the impact ADAS has

on older drivers’ insight into the impact of age-related declines on their driving

performance. It can be argued that ADAS can point out specific limitations in the

older adults’ driving. A blind spot detection and a lane change assist system, for

example, can improve older drivers’ awareness of existing motor and visual

limitations (difficulty in turning head and reduced peripheral vision) and assist them

in merging and lane changes. It can allow the driver to be aware of the difficulties

involved with the driving task, the actions (or the avoidance of actions), and whether

they have the necessary abilities to cope. But this form of feedback may not

communicate the information necessary to alter the driver’s behaviour (Donmez et

al., 2007). Combined feedback (i.e., immediate and retrospective), on the other


hand, may offer additional benefits. Retrospective feedback can refresh older

drivers’ memory and help them evaluate the driving errors and incidents which the

immediate feedback has highlighted during the drive (Donmez et al., 2007). A

recent review of the effect of a number of in-vehicle technologies has determined

that ADAS can in fact assist older drivers with their everyday performance, reduce

their possibility of being involved in a crash, and reduce the severity of the crash for

both drivers and occupants (Eby et al., 2015). Recent qualitative evidence suggests

that older drivers don’t seek ADAS for age-related reasons, however, they perceived

such technologies to be useful in terms of compensating for age-related changes,

enhancing their safety, and improving their overall driving performance (Gish,

Vrkljan, Grenier, & Van Miltenburg).

Educational interventions

A common shortfall among the majority of educational interventions

targeting older drivers is that they are not based on theoretical knowledge of

behavioural change (Tuokko, Rhodes, et al., 2014). In addition, the majority of

educational interventions have been designed to improve older drivers’ knowledge

which can only lead to crash reduction if it causes changes in behaviour (Stalvey &

Owsley, 2003). A promising program is The Knowledge Enhances Your Safety

(KEYS), which was developed for older drivers with visual impairments to enhance

their awareness about visual impairments and promote adoption of self-regulatory

behaviours. It can be delivered in a clinical setting in a one-on-one format in order to

facilitate the tailoring of the intervention to the requirements of each person (Stalvey

& Owsley, 2003). The intervention was based on the Social Cognitive Theory to

promote the adoption of self-regulatory behaviour and is based on four components

a) motivational conditions, (b) self-regulatory skills, (c) confidence in one’s ability to

perform the behaviour, and (d) prerequisite knowledge and skills (Stalvey & Owsley,

2003).

In a study conducted by Stalvey and Owsley (2003), 365 older drivers, aged

60 years and over with visual limitations were allocated to one of two groups. The

intervention group (i.e. those who received the educational intervention in addition to

a comprehensive eye examination) were significantly more likely to recognise their

visual limitations; report more difficulty with challenging driving situations; avoid

challenging situation and reduce their driving exposure compared to the control


group (i.e. those who received the eye examination) (Stalvey & Owsley, 2003). In

2004, Owsley et al. conducted a similar study among 403, 60 years and above older

drivers with visual impairments and followed participants every six months for two

years. Those who received the intervention reported more avoidance of challenging

driving situations and self-regulatory behaviours than the control group, however,

there were no differences in the crash outcome (Owsley et al., 2004). They explain

how the risk of being involved in a crash is determined by a large number of factors

(e.g. vehicle condition, environmental conditions, drivers’ abilities) and it might be

simplistic to assume that educational programs alone would affect crash rate (Owsley

et al., 2004). In addition, driving is a habitual skill which makes it difficult to change

driver attitudes and practices (Owsley et al., 2004). In addition, while educational

interventions can enhance older adults’ awareness of the limitations in their driving

ability they may not be enough to assist them in overcoming the barriers toward

changing their behaviour.

2.8.3 Encouraging older drivers to plan their driving cessation from an earlier age

Driving cessation is usually a gradual process where people start to reduce

and/or restrict their driving until complete cessation (Dellinger et al., 2001). Older

drivers may be unwilling to plan their driving retirement due to their awareness of

the potentially negative consequences of driving cessation (King et al., 2011).

However, planning retiring from driving can make the experience easier and less

traumatic (Gilhooly, Hamilton, O’Neill, & al., 2003) and can improve the outcomes

through better ongoing preparation and maintenance of control (Buys et al., 2012).

Having an early conversation about one’s driving future can allow for more time for

professional skill assessment, potential driver rehabilitation, and even family

adjustment to a new transportation support role (Coughlin, 2004). Musselwhite and

Shergold (2013) followed 21 older drivers in the United Kingdom over a period of

ten months through five waves of data collection (focus group, three interviews, and

a travel behaviour diary). Those who planned their cessation reported a relatively

higher quality of life after stopping driving as opposed to those who did not plan

their driving retirement (Musselwhite & Shergold, 2013). The planners went through

an experimental period; trying new transport options and new travel modes which

provided them with a sense of achievement and control (Musselwhite & Shergold,

2013). On the other hand, the non-planners found it very difficult to adjust without


their car and blamed external factors for the lack of transport options (Musselwhite &

Shergold, 2013).

Previous research indicates that the vast majority of older drivers do not plan

the transition to non-driving state, even those who suffer from medical conditions

that can impair their driving (Adler & Rottunda, 2006).

In a 2006 study among 656 older Victorian drivers aged 55 years and above,

83% of those aged 75 years and more had thought about stopping driving but only

17% of these had made plans for it (Charlton et al., 2006). In Australian Capital

Territory, a study by Oxley et al. (2010) among older women drivers (n=673) and

former drivers (n=53) aged 60 years and over showed that current drivers had not

made plans about giving up driving; however, those who experienced health

concerns (e.g. vision problems) were more likely to think about not driving in the

future compared to those with no problems. Around 58% of former drivers reported

that they stopped driving suddenly but the majority (66%) reported that it was not a

difficult decision (Oxley, Charlton, Scully, & Koppel, 2010). In another study

conducted by Bauer et al. (2003), women who made the decision to stop driving

without the interference of others were more likely to adjust to their new lifestyle. In

addition, when the decision to give up driving is gradual, women had more time to

plan ahead (e.g. relocation, gathering information about alternative transports) and

reported better adaptation compared to those who were forced to stop suddenly

(Bauer, Rottunda, et al., 2003).

2.9 CHAPTER SUMMARY

This chapter has presented the implications of the ageing population in

regards to road safety and mobility needs. Attempts to manage the older drivers’

problems can be broadly categorised into three groups: 1). Identifying high-risk older

drivers, 2). Encouraging older drivers to self-monitor and self-regulate their driving

behaviours, and 3). Encouraging older drivers to plan their driving retirement from

an earlier age. Self-regulation is a favourable approach that can help older drivers

maintain their active lifestyle without compromising their safety and the safety of

others. However, as outlined above, there is still a gap in our knowledge of how to

promote successful self-regulation and the need for a model that can help us clearly

explain and describe this process is much needed. As discussed before, the


heterogeneity among the older drivers’ population has not been addressed with the

existing interventions which are mostly designed as one-size-fits-all. The lack of a

theoretically-informed model of driving self-regulation inhibits our ability to

understand and describe such complex process. There is growing evidence that older

drivers go through different qualitative stages towards modifying their driving

behaviours. It therefore could be useful to examine the driving self-regulation

process within behaviour change framework. The following chapter discusses the

existing models of driving self-regulation and explains the potential use of PAPM in

understanding such complex process.


Chapter 3: Theoretical framework and current models of older adults’ driving behaviour


This section reviews the existing models of older adults’ driving behaviour

and summarises the key determinants identified by each model that influence older

adults’ driving behaviour. The limitations of each model will also be discussed.

Finally, this section concludes by justifying the selection of the PAPM as the

theoretical base for this program of research.

The theories and models included in this review are presented according to

their level of sophistication. The search identified six models which are specific to

the older drivers’ behaviour which varied greatly in terms of their theoretical

development and their level of sophistication, the models were grouped into:

1. Descriptive models which specify determinants of driving behaviours

without a clear indication of how these factors interact.

2. Explanatory models which describe and explain how the determinants of

self-regulatory behaviours interact to initiate change.

3.2 DESCRIPTIVE MODELS

Kostyniuk, Shope & Molnar (2000): The Precaution Adoption Process Model

Kostyniuk and colleagues (2000) were the first to highlight the need to

develop a comprehensive model of the driving reduction and cessation process using

behaviour change theories. They hypothesised that predicting problems in one’s

driving ability is a key factor in initiating the driving reduction and cessation process.

They examined the applicability of the Precaution Adoption Process Model (PAPM)

as the framework to look at how older drivers cope with the age-related declines and

their willingness to make changes in response to these declines (Kostyniuk et al.,

2001). The PAPM is a stage-based theoretical model which assumes that people

need to be aware of the risk associated with their behaviour before they are

susceptible to behavioural change (Weinstein & Sandmand, 2002). It characterises


seven stages along the path from lack of awareness to action (unaware, unengaged,

undecided, decided not to act, decided to act, planning, acting and maintaining).

They conducted a survey study among 1,053 older drivers and former drivers over

the age of 65 where they investigated the impact of older adults’ anticipation of

driving problems on their driving reduction and cessation. Their findings suggest

that the awareness and anticipation of limitations in driving ability may be the key

factor for reducing and/or stopping driving, which provides an initial support to the

use of PAPM.

Figure 3.1: Driving reduction/cessation framework

From “Driving reduction/cessation among older drivers: toward a behavioural

framework” by Kostyniuk, L., Shope, J. & Molnar, L., 2000, 9th International

Asscoiation for Travel Behaviour Conference, Gold Coast, Australia, . 17

Key determinant: anticipation of problems in older adults’ driving and awareness of

change in their driving abilities.

Limitations: the model doesn’t recognise the influence of other external and internal

factors on older adults’ decision to modify and/or reduce their driving. The model is

rather descriptive and does not provide a clear idea of the factors that facilitate

transition between stages and is not useful in developing interventions.


Anstey et al. (2005): Multifactorial model of factors enabling driving safety among older drivers

This model was developed based on a literature review of 13 empirical

studies examining the relationship between many cognitive, sensory, and physical

factors and either self-reported crashes, state crash records or on-road driving

measures by Anstey and colleagues in 2005. It consists of two main factors; driving

capacity and self-monitoring and beliefs about driving (Figure 2.1). Driving capacity

is determined by cognition, sensory, and physical function (Anstey et al., 2005).

Self-monitoring beliefs refers to the ability to evaluate one’s driving ability and adapt

driving behaviours accordingly (Anstey et al., 2005). This model suggests that older

drivers’ insight into their driving skill is crucial for accurate evaluation of their

ability and accordingly successful self-regulatory behaviours. In fact, perceptions

about one’s ability may be a stronger determinant to reduce and/or restrict driving

than actual ability (Anstey et al., 2005). The strength of this model is that it is based

on an exhaustive review of recent literature on the impact of ageing and health on

driving abilities among older adults. It also emphasises the impact of insight and

self-monitoring abilities on adoption of safe driving behaviour while incorporating

the objective determinants of driving capacity. However, this model fails to account

for the contextual factors relevant to older adults driving behaviours (e.g.

environmental, intrapersonal, and interpersonal).

Key determinants: driving capacity as a function of interaction of cognitive,

visual, and physical function and self-monitoring beliefs and insight into driving

capacity.

Limitations: while the model describes how these two determinants interact

to affect the driving behaviour, it is very simplistic and does not incorporate the

impact of other interpersonal, intrapersonal, and environmental factors on older

adults’ behaviour.

Kowalski, Jeznach, Tuokko: Transtheoretical Model (TTM) (2014)

In 2014, Kowalski and colleagues examined the older driver behaviour within

the TTM framework using interviews/focus groups with 32 drivers and 19 former

drivers (Kowalski et al., 2014). Their model describes how older drivers go through

different stages of the TTM towards changing or stopping their driving. Pre-


contemplation is viewed as the period where people drive without imposing any

changes to their driving. It is not clear if those in the pre-contemplation stage are

unaware of the need to change their driving behaviour or if they are aware but refuse

to change. In the contemplation stage people start to think about changing their

driving in the future. These two phases include the “non-changers”, those who did

not change their driving. In the preparation stage individuals are planning to change

their driving behaviour in the near future. The action stage involves the period where

drivers start to impose self-restriction on their driving and avoid challenging

situation. Maintenance stage involves the phase where the driving behaviour change

has been successfully attained and is being maintained. They also added a sixth

stage of termination where older adults stop driving altogether.

The model emphasises the role of self-awareness of limitations in driving

abilities on the driving behaviour among older adults. It is also the first model to

highlight that older drivers could be divided into “gradual restrictors”, imposing

certain restrictions on their driving as they move from pre-contemplation to action or

maintenance or “consistent restrictors”, those who have always imposed restrictions

on their driving which may reflect a specific personality type (e.g.,

conscientiousness), or other external factors (i.e., reduced need to drive due to

relocation) rather than an awareness of declining abilities.

Key determinants: awareness of the need to change, pros and cons of

driving and external factors.

Limitations: a limitation of the TTM is that it fails to distinguish between

people who are unaware of the risk and those who have decided not to act. As

shown in this model, it is not clear whether individuals in the pre-contemplation

stage (the non-changers) are aware of the declining abilities but refuse to modify

their driving or simply unaware. It is therefore logical to assume that the resisters

will not progress through stages of change similarly to those who are unaware and

that they will require different types of interventions. Older drivers who resist change

may not benefit from traditional behavioural interventions and may be more reluctant

to seek feedback.


Figure 3.2: Conceptualization of the process of driving behaviour change within the TTM framework

From “Stages of driving behaviour change within the Transtheoretical Model (TM)" by Kowalski, K., Jeznach, A. & Tuokko, H.A., 2014, Journal of Safety Research, 50,

p 19.

3.3 EXPLANATORY MODELS

Rudman’s model of self-regulation (2006)

This model was developed based on the result of qualitative findings from

focus groups with 29 pre-senior drivers, 24 senior drivers, and 26 retired senior

drivers. The model highlights the impact of interpersonal, intrapersonal and

environmental factors, on the ability of older adults to self-monitor and adjust their

driving. It also highlights the impact of older drivers’ level of comfort on their

driving behaviour.


Key determinants: this model (Figure 3.3) is the first comprehensive model

of self-regulatory driving behaviour among older drivers accounting for many

environmental, intrapersonal and interpersonal factors that affect older adults’

decision and ability to adopt safe driving behaviours. The influence and role of

feedback on older drivers’ decision-making process is highlighted in this model, an

area that is under researched in the older drivers’ literature.

Limitations: the model fails to account for the impact of driving capacity on

older adults’ driving behaviour. In addition, the model suggests that driving comfort

influenced by a number of interpersonal, intrapersonal, and environmental factors

acts as a key determinant of self-regulation (Rudman et al., 2006b). If older drivers

avoid certain driving situations because they feel uncomfortable then their self-

regulation of driving may be a response to the discomfort they experience in

challenging driving conditions rather than intentional monitoring of their driving

ability (Meng & Siren, 2012). This means that if participants’ discomfort was indeed

caused by factors unrelated to declines in their driving ability, it may have led to

unnecessary driving restrictions (Meng & Siren, 2012). Modifications in driving

behaviour for factors other than declines in the driving abilities (e.g. financial

reasons, lifestyle factors, affective factors) should not be regarded as self-regulation

as they do not necessarily result in improvement in safety. On the contrary, they

could cause the opposite effect.


Figure 3.3: Model of the process of driving self-regulation with ageing

From “Holding on and letting go: the perspectives of pre-seniors and seniors on driving self-regulation in later life” by Rudman, D., Friedland, J., Chipman, M. &

Sciortino, P., 2006a, Canadian Journal on aging, 25, p72.


Driving as an Everyday Competence model for older adults (DEC) (2010)

This model (Figure 3.4) was developed by Lindstrom et al. (2010) through a

review of the literature on driving models and on models of everyday competence to

explain older adults’ level of competency and level of performance for driving. The

DEC model incorporates elements from Willis’s model of everyday competence,

Michon’s hierarchical model of driving, and Anstey’s model. Driving competence

refers to what an individual is “capable of given the dynamic interaction within and

between the individual and the environment” and it is not directly measurable

(Lindstrom-Forneri, Tuokko, Garrett, & Molnar, 2010). The model suggests that the

level of driving competence is determined by the interaction between the individual

and the environment and is moderated by beliefs and awareness. Further, awareness,

beliefs, and self-monitoring can have an impact on the strategic level driving process

which would be expected to impact driving performance. The model includes

various sociocultural factors (e.g. availability of alternative transportation options)

and psychosocial factors (e.g. beliefs about driving). Further, it demonstrates how

driving competence (what one is capable of) leads to driving performance (what one

does).

Figure 3.4: Driving as an Everyday Competence Model for Older Adults

From “Driving as an everyday competence: a model of driving competence and behaviour” by Lindstrom-Forneri, W., Tuokko, H., Garrett, D. & Molnar, F., 2010,

Clinical Gerontologist, 33(4), p. 284


Key determinants: the DEC model proposes that the interaction within and

between the individual and environmental factors at the global and specific

contextual levels determine the individual’s level of driving competence. Driving

performance is what the older driver does on road and is measurable. Driving

performance is the subsequent action resulting from interactions of the global factors,

specific contextual factors, and moderators and involves decisions made at the

strategic, tactical, and operational levels.

Limitations: the DEC model contributes to our understanding of the dynamic

individual-environment interaction associated with driving competence and driving

performance among older drivers. While the DEC incorporates many factors, it

lacks specificity about how these factors interact together (Wong, Smith, Sullivan, &

Allan, 2014).

Multilevel Older Persons Transportation and Road Safety model (MOTRS) (Wong et al., 2014)

The model was developed by Wong et al. (2014) through a systematic review

of 29 empirical studies which examines self-regulation of driving among older

adults. The model consists of four levels: socio-demographic variables at both

individual level (e.g. age, gender, health condition) and environmental level (e.g.

urban density, driving specific policies), driving specific variables at both individual

level (e.g. insight, driving experience, availability of driving partners) and

environmental level (e.g. availability of alternative transport options, road

conditions), psychosocial variables (driving confidence, perceived behavioural

control, perceived barriers, normative influence), and self-regulatory driving

behaviours. The MOTRS model proposes that socio-demographic and driving

specific factors predict older adults’ adoption of driving-related self-regulation

through their psychosocial influences.

The MOTRS model (Figure 3-5) adopts a connectionist framework and

assumes that the adoption of self-regulation is determined by a combination of

excitatory and inhibitory activation received in parallel from various socio-

demographic and driving specific factors through their collective influence on their

psychosocial variables. The MOTRS model accounts for the process of learning

through the use of bidirectional causal pathways, particularly at the level between

self-regulatory behaviours the psychosocial factors. These bi-directional pathways


allow learning to occur whenever error responses (e.g. a near-miss) are noted and

sent back through the network, a process called back propagation. In addition to

explaining the changes of attitudes and beliefs using back propagation, the MOTRS

model also accounts for the incremental process of such changes. In a connectionist

network, the recency and frequency with which a pattern has been activated

influence the ease and speed of subsequent activation when elicited by similar cues.

When a stimulus is introduced, learning changes weight of related activation

pathways, making the current and similar pathways easier to reproduce in the future,

sometimes at the expense of other unrelated pathways.

Key determinants: this model is rather comprehensive, incorporating many

factors that could influence self-regulation and allowing for them to interact in many

ways.

Limitations: the model does not specify detailed theoretical relationships

between these variables. It also views driving self-regulation as a unidirectional

process and therefore does not clearly describe the decision-making process. In

addition, the model was developed based on a systematic review of quantitative

studies examining the driving self-regulation process. Excluding qualitative

evidence, may have to capture important factors that have not been explored

previously in quantitative studies.

Figure 3.5: The Multilevel Older Person’s Transportation and Road Safety Model

From “Toward the multilevel older person’s transportation and road safety model: a new perspective on the role of demographic, functional, and psychosocial factors” by

Wong, I.Y., Smith, S., Sullivan, K. & Allan, A., 2014, Journals of Gerontology: Psychological Sciences, 71(1), p. 82


3.4 OTHER MODELS

These models are concerned with the driving cessation process among older

drivers rather than self-regulatory driving behaviours but will be presented here

briefly.

Classen et al. (2007): Precede-Proceed model

Classen et al. (2007) argue that the answer to the older driver safety issue can

be achieved through the adoption of an ecological approach to health promotion. An

ecological approach recognises that all aspects of a person’s environment are

considered as potential intervention targets, as well as the person’s own cognitions,

skills, and behaviour (Crosby & Noar, 2011). Therefore, they propose the use of the

PRECEDE-PROCEED model (PPM) as a framework within which various

individual and community theories can be utilised so that the most effective

intervention strategies can be implemented. The PRECEDE-PROCEED model is not

intended to predict or explain the relationship between predictors of certain

behaviour but to provide a framework for applying theories for planning and

evaluating health behaviour change programs (Glanz, Rimer, & Viswanath, 2008)

The model (Figure 3.6) has two separate components, the PRECEDE and the

PROCEED. The PRECEDE phase (Predisposing, Reinforcing, and Enabling

Constructs in Educational Diagnosis and Evaluation) constitutes the diagnostic and

assessment component of the model and provides a framework for systematically

assessing the social epidemiological, educational and ecological, and administrative

and policy aspects of a topic under study. The PROCEED (Policy, Regulatory and

Organisational Constructs in Educational and Environmental Development) or

intervention phase, recognises the impact of improved environmental and

organizational resources and services in improving health. Overall, the model has

eight phases, with the PRECEDE component comprising four phases and the

PROCEED component comprising four phases.

Classen and colleagues utilised a mixed-method approach to examine the main

epidemiological factors within the social context of older drivers in the United States.

Their first study employed a cross-sectional design where they analysed the 2003

Fatality Analysis Rating System dataset. This was followed by a metasynthesis


based on inductive and deductive analyses, of six qualitative studies. By integrating

the quantitative and qualitative findings, they identified 11 multi-causal factors for

safe driving among older drivers (previous motor vehicle convictions, passengers,

registered vehicle owners, principal impact, hour of the day, relation to junction,

traffic control device, vehicle manoeuvre, gender, road surface condition, state

policies) (Classen et al., 2007). Their health promotion intervention plan has two

intermediate outcomes (3 months-1 years); increased insight on risk and protective

factors and application of protective strategies. It also has three long-term outcomes

(1-5 years); decreased risk of crash and injuries, driving safer for longer, and use of

alternative transport options which can be achieved through behaviour change, policy

change, and creating safer roads and safer vehicles.

Figure 3.6: Precede-Proceed model of motor vehicle crashes among older drivers

From “Population-based health promotion perspective for older driver safety: conceptual framework to intervention plan” by Classen, S. et al., 2007, Clinical

Interventions in Aging 2(4), p. 691


This model can serve as a framework to assist researchers in choosing

theories that support the development of older drivers’ interventions. A great

advantage of the PPM is that it utilises both quantitative and qualitative data to

identify priorities and to establish the multiple factors related to the problem (Crosby

& Noar, 2011). Further it assumes that efforts to effect health behaviour change

must be similarly multidimensional in nature (Tramm, McCarthy, & Yates, 2012).

In this model, the improvement in the older drivers’ safety can be achieved through

changes in the driver behaviour, physical environment, social environment and

policies. The findings from this study highlights the importance of the physical and

social environment on older drivers’ safety, however, little attention is directed

towards the intrapersonal (e.g. confidence, self-awareness, perceptions) and

interpersonal (e.g. feedback and social norms) predictors of driving behaviours.

Further, age-based licensing systems are viewed as enabling factors in this model

that can influence older drivers’ safety (Classen et al., 2007). However, current

evidence points out that age-based testing is not recommended as they have no

demonstrable safety benefits (Tay, 2012). In addition, the model is rather exhaustive

and broad and it may be extensive, expensive, and unrealistic to identify

theoretically-consistent interventions to achieve changes in all of these outcomes

(Tramm et al., 2012). The complexity of the model and the complex nature of the

proposed outcome (crash reduction) might also make it difficult to evaluate

effectiveness. In other words, if crash reduction is to occur, it will be difficult to

conclude if the improvement of physical environment or the adoption of self-

regulatory behaviours was the reason.

Stress-coping framework: Model of interpersonal health behaviour (2012)

Choi and colleagues (2012) examined the process of driving cessation within

the stress-coping framework. Stress-coping models of health propose that the

individual’s ability to cope with stressors can affect the outcome and consequences

of stressful events (Choi, Adams, & Mezuk, 2012). Individuals vary widely in their

abilities to adapt to major life challenges and in the available resources that can assist

them to cope with this change. Therefore, the authors argue that the application of

the stress paradigm to the topic of the driving cessation process can help understand

the psychosocial and physical well-being of older adults in relation to their

environment. This can assist in the development of interventions based on personal,


environmental and social resources to minimise the negative impact of driving

cessation.

Their model (Figure 3.7) was derived from reviewing the literature on older

drivers and their driving behaviours. In their model, the primary stressors mainly

refer to health and functional declines, which involves cognitive impairment, visual

impairment, and functional impairment. Secondary stressors, on the other hand,

could be internal such as subjective discomfort or anxiety about driving or external

such as pressures on older drivers to stop driving. Older adults who experience any

of these stresses can adopt either an emotion-focused coping (e.g. denial or

avoidance) or problem-focused coping strategy. Emotion-focused coping can be

effective (e.g. acceptance of the need to stop driving or denial of the importance of

driving) or ineffective if it causes older drivers to assume they can drive safely

despite suffering from cognitive and/or visual impairments. Problem-solving coping

strategies involve making informed decisions (e.g. self-regulation of driving, use of

alternative transport or attending a refresher course). Personal, environmental, and

social resources can act as buffers between stressors and health and well-being. The

driving cessation process takes place within spatial (e.g., residential environment,

living arrangements) and temporal (e.g. transportation policy) contexts. In addition,

the driving cessation process can be influenced by various socio-demographic factors

such as age, gender, or marital status.


Figure 3.7: Conceptual model of driving cessation process

From “Examining the aging process through the stress-coping framework: application to driving cessation in later life” by Choi, M., Adams, K.B. & Mezuk, B.,

2011, Aging and Mental Health, 16(1), p. 78

This model offers a comprehensive framework of the driving cessation process

among older drivers. It recognises the heterogeneity of the older drivers and that the

driving cessation process may vary among different socio-demographic groups.

Older drivers, who are mainly influenced by internal stressors may be more likely to

voluntarily give up their car keys. On the other hand, the decision to stop driving

may be more involuntary among those more affected by external stressors.

Therefore, interventions could be perceived and accepted differently by the two

groups. The secondary internal stressors in this model refer to experiencing

difficulty due to lack of confidence and fails to identify the role of insight and self-


awareness in adopting self-regulatory driving behaviours. Therefore, this model

does not allow the examination of the impact of targeted interventions that can

provide older drivers with feedback to enhance their awareness. It therefore fails to

acknowledge the important role of health professionals, in-vehicle technology, self-

assessment tools and other resources that can help promote safe driving among older

adults. In addition, self-regulatory driving is viewed in this model as a coping

strategy to deal with the stresses associated with declining health among older

drivers. However, self-regulation is a broad and a multifactorial process that is not

yet completely understood. This model is therefore useful in assisting to develop

interventions targeted towards promoting the well-being and quality of life of retired

drivers rather than examining the driving regulation/cessation process.

3.5 LIMITATIONS WITH THE EXISTING MODELS

Figure 3.8: Challenges in examining older driver behaviour

Examining older drivers’ decision-making process towards the adoption of

self-regulation within a behaviour change theory is difficult given the uniqueness of

the driving behaviour (Fig. 3.8). For baby boomers, driving is the most reliable and

convenient mode of transport. It is a big part of their identity and offers them

freedom of mobility and independence. The declines in driving abilities are usually

gradual or subtle and it is very hard for older drivers to draw the impact of such

declines on their abilities. Even when they start noticing some changes, older drivers

may be reluctant to discuss their driving as they fear it may result in losing their

64


driving privelges (Betz et al., 2016). In addition, driving is a habitual process

(Caragata, 2017) that is not viewed as a harmful or risky behaviour (Kostyniuk et al.,

2000). The harms associated with driving are often attributed to “risky driving

behaviours” such as driving under the influence, speeding, or distraction. It might

be difficult for older adults to recognise how the declines in certain abilities affect

their driving and increase their risk of being involved in a crash. Older adults often

have mixed feelings of denial and disbelief about the need to change their driving

behaviour (Betz et al., 2016). Their lack of control over the decision-making (Liddle

et al., 2008) can create a peroid of uncertanity full of unexpected information and

charged emotion. It is crucial that in this early phase older adults receive feedback

about their driving abilities that increase their self-awareness and create a state of

“personal engagment”. Feedback in this phase should help them to accurately

calibrate their perceived abilities with their actual abilities. Accurate perception of

one’s driving abilities can help older adults to adopt efficient regulatory behaviour to

minimise their risk (Horswill et al., 2013). Previous studies suggest that insight into

declining functional abilities may be the trigger for self-regulation among older

drivers (Anstey et al., 2005; Blanchard and Myers, 2010; Charlton et al., 2006;

Molnar and Eby, 2008). Few studies have demonstrated that those who are aware of

declines in their abilities may practice self-regulation (Holland and Rabbitt, 1992;

MacDonald et al., 2008).

Once engaged, older drivers start weighing the pros and cons of modifying

their driving behaviours. Prioritising driving self-regulation is very difficult. Unlike

the motivation associated with other behaviour changes (e.g. improved health, losing

weight, etc.), there are no tangible or immediate benefits to adopting self-regulation

(other than perceived reduced risk of crash and perceived increased comfort). In

addition, the decision to stop driving usually has implications on other people not the

driver alone (e.g. becoming a burden, loss of the prinicpal driver). Previous studies

suggest that older drivers’ experiences, needs, facilitators and barriers of change are

entirely different and can change with time. Therefore, interventions should provide

older drivers with customised feedback based on their individual circumstances and

should incorporate the environmental and social factors that impact older drivers’

ability to modify their driving. Previous studies indicate that customised feedback is

effective in improving safe driving habits of older drivers (Lavalliere et al., 2012).


The longevity of the process may cause older drivers to become discouraged and

relapse back to their old driving behaviours particularly in the lack of feedback.

There have been several attempts to develop a model that can explain the

driving modification and/or cessation process among older adults. The existing

models vary considerably in regards to their development, determinants, and utilities.

Collectively, they identify several environmental, interpersonal, and intrapersonal

determinants that influence older adults’ driving behaviours. However, the

interaction between these factors and how and when they can induce the change is

not always clear. A major drawback of the existing models is failing to acknowledge

the heterogeneity of the older driver population in regards to their driving abilities,

their attitudes toward driving, their perception of their driving abilities, and their

surrounding environment. They also fail to recognise that older drivers go through

different stages of change and their experiences, needs, facilitators, and barriers to

change are entirely different and can change with time. Therefore, the target

participants (e.g., baseline stage of participants) and the desired outcomes would

influence the content and the strategies used to implement the intervention (Tuokko,

Rhodes, et al., 2014).

The stages of changes theories could be useful in describing and providing a

general understanding of change and planning interventions (Liddle et al., 2004). A

model developed by taking a strategic approach using both a theory of the change

process and existing evidence from previous attempts to achieve change is much

needed to help designing interventions for older drivers that are customised, based on

the individual (the baseline stage) and the anticipated outcome (increased awareness,

enhance self-monitoring, adoption of self-regulation, or planning cessation), and

flexible to move individuals through the stages of change towards adoption of safe

driving behaviour (Tuokko, Jouk, et al., 2014). However, there has been little

development of stage-based theories applied to driving self-regulation, and a lack of

research on theoretically-informed interventions that facilitate older drivers’ planning

for future self-regulation and even driving. Previous studies examining older

drivers’ behaviour within stages of change framework have either relied entirely on

qualitative findings without further validation (e.g. Kowalski et al., 2014) or have

been simplistic and have therefore not added much to our understanding of the

driving regulation process (e.g. Kostyniuk et al., 2001). There is a need for a model


that does not limit its focus to changes in driving exposure (driving restriction and/or

avoidance) but emphasises how older drivers cope with declining abilities by

adopting precautionary behaviours. The PAPM is a preventative decision-making

framework constructed around the goal of preventing or minimising future harm

ideal when dealing with complex behaviours which fits well with driving self-

regulation.

3.6 THE PRECAUTION ADOPTION PROCESS MODEL (PAPM)

Stages of change theories suggest that behaviour change is a dynamic and a

temporal process (Prochaska & Velicer, 1997) where individuals progress through a

number of stages towards action (Weinstein & Sandmand, 2002). The progression of

stages is determined by certain variables. People in similar stages face common

barriers to change and those in different stages face different barriers to change

(Weinstein & Sandmand, 2002). The progression through stages does not necessarily

terminate in action and people can relapse and regress through stages (Weinstein &

Sandmand, 2002). All stage theories share the same main elements outlined by

Weinstein (1998): 1). A classification system to define the stages, 2). An ordering of

the stages, 3). Common barriers to change facing people in the same stage, and 4).

Different barriers to change facing people in different stages.

Structure of the PAPM

The Precaution Adoption Process Model describes how individuals move

through stages of changes towards adoption of health protective behaviour

(Weinstein & Sandmand, 2002). The early stages of the PAPM are defined in terms

of psychological states and mindset of individuals (Weinstein & Sandmand, 2002).

The late stages are mostly governed by factors that can facilitate or hinder the

adoption of the precaution. Individuals progress through seven stages from lack of

awareness to action: unawareness (stage 1); awareness that there is an issue but a

lack of personal engagement with it (stage 2); engagement (“this applies to me”) but

indecision (stage 3) about the need to act; either a decision not to act (stage 4) or a

decision to act (stage 5); if the latter, acting by taking the precaution (stage 6) (e.g.

self-regulating); and maintaining the behaviour (stage 7). The unique feature of the

PAPM is that it deals with both the hazard and the precaution arguing that


individuals must first perceive a hazard of sufficient personal relevance before they

are ready to hear messages about adopting a precaution.

The PAPM does not offer explicit details about the barriers and facilitators at

each stage which allows for a more flexible framework that could be adapted to suit

each behaviour uniquely (Weinstein et al., 2008). Weinstein and colleagues provide

some suggestions about possible factors that can determine progression between

stages. For instance, the early stages of the PAPM is concerned about enhancing

people’s awareness and achieving personal engagement. This can be achieved by

providing information about the health issue and the protective behaviour,

communication from reliable individuals, and personal experience with the hazard.

In the third stage, perceived significance of the hazard, beliefs about the likelihood of

the health hazard, and fear may influence one’s decision about adopting the

protective behaviour. To facilitate the decision-making process, it is crucial that

individuals are aware about their susceptibility to the hazard and the effectiveness of

the suggested precaution. In the final stages, it is important to address the barriers

towards adopting the behaviour. Individuals may regress to an earlier stage,

however, they can never go back to stage 2 as they have acquired a certain level of

awareness and engagement (Weinstein & Sandmand, 2002).

Application of the PAPM in the older driver settings

The PAPM appears to be an attractive model for studying older adults’ self-

regulatory driving behaviour for the following reasons:

1.) It emphasises that self-awareness of risk (e.g. compromised safety due to

driving limitations) is the first step to initiate change among individuals.

As outlined before, there is a considerable support that self-awareness is the

key towards modifying behaviour.

2.) It differentiates between those who are unaware about the hazard and never

thought about acting and those who have thought about acting and are still

undecided (unlike the TTM which groups them as the pre-contemplators).

This differentiation is important because those who have thought about

acting are more likely to be more knowledgeable, have different responses

to information and are more resistant to persuasion (Ditto & Lopez, 1992).

In the context of driving, information regarding declining driving abilities


which could subsequently require cessation of driving or modifying one’s

driving behaviour would often be viewed as undesirable information. If

someone has already formed an opinion about their driving abilities they

will have a greater tendency to adhere to their opinion; what is known as

“confirmation bias,” or “perseverance of beliefs” (Weinstein et al., 2008).

3.) The early stages of the PAPM deal with the attitudes and beliefs people

hold about the hazard and precaution while the later stages deal with

addressing barriers; whether internal or external, towards adoption of

change. This differentiation is important because while some people may

be aware and willing to change they may be unable to change their

behaviours.

4.) It offers a flexible framework with no clear information on what determines

transition between stages and therefore could be adapted to suit each

behaviour uniquely.

5.) It is concerned with the adoption of precaution or cessation of risky

behaviour which requires deliberate planning. Self-regulation of driving

refers to the driving behaviour modifications one adopts in attempt to

improve their safety. It is therefore a conscious process that requires active

planning. Modifications of driving behaviours for reasons other than

improving one safety (e.g. affective coping or lifestyle factors) is not

considered as self-regulation.

As discussed before, there has been limited application of the PAPM within

the older driver population. Kostyniuk and colleagues (2000) were the first to

highlight the potential use of the PAPM in understanding the older adults’ driving

behaviour. Their study was the initial step towards developing a behavioural

framework of driving reduction and cessation among older drivers where they

investigated the impact of drivers’ perception of their driving abilities on their

driving reduction and cessation. Their findings suggest that anticipation of problems

in driving ability may be the trigger for driving reduction which satisfies the initial

condition of the PAPM (Kostyniuk et al., 2000). The adaptation of the PAPM in their

study was not fully described, and was based mostly on older adults’ awareness of

their declining abilities but failed to recognise the influence of other external and

internal factors on the process of self-regulation.


Coxon and colleagues (2017) conducted a randomised controlled trial among

366 older drivers aged 75 years and above where intervention group participated in

an individualized, one-on-one safe-transportation program adapted from the

Knowledge Enhances Your Safety curriculum delivered in two sessions held

approximately 1 month apart. Further, the education messages were customised to

the behavioural change of each participant using the PAPM (Coxon et al., 2017).

Participants were followed for over 12 months where distance driven measured using

in-vehicle monitoring was examined. Secondary outcomes for driving exposure

included night driving, farthest radial distance driven from home, and self-reported

driving space. While intervention group participants showed greater readiness to

engage in self-regulatory driving practices, distance driven per week, use of

alternative transport and community engagement were similar between the two

groups (Coxon et al., 2016).

This could be attributed to the nature of the intervention provided.

Educational interventions can raise older drivers’ knowledge about existing issues

and problems but it may be difficult to translate into well-formulated instructions.

They often lack the practical component and training necessary to assist older drivers

in recognising the actual problems they face on the road. The intervention will vary

not only on the participant’s stage, but the desired outcome and their surrounding

environment. The content of the education intervention was tailored based on the

PAPM stage of the participants. However, an educational intervention may not be

the best type of strategy to promote the change for all of the participants or

participants may have not perceived it as useful. Second, the intervention did not

translate into reduced mileage or changes in driving exposures using objective

measures of driving. Driving reduction is not an indication of self-regulation, but

mostly reflect lifestyle choices. Participants may have engaged in different

regulatory behaviours that were not measured in this study (e.g. self-monitoring,

restriction and avoidance, and life goal changes).

3.7 CHAPTER SUMMARY AND IMPLICATIONS

This chapter summarises the existing models of older adults’ driving

behaviour. While the PAPM has been gaining recent attention in the older drivers’

literature, there is still considerable gaps in our understanding of how (if possible) it

can explain older drivers’ regulatory behaviour.


Chapter 4: Research Design


This chapter summaries the research design and methodology adopted to obtain

the aims and objectives outlined in Chapter 1. The chapter’s structure is as follow:

section 4.2 describes the specific research questions that will be examined in the

studies, section 4.3 discusses the mixed method research design implemented,

section 4.4 presents the recruitment strategies and participants’ characteristics;

section 4.5 describes the instruments used in the study; section 4.6 outlines the data

management and data analysis; section 4.7 presents the organisation of the papers

and, finally section 4.8 discusses the ethical considerations of the research

4.2 RESEARCH QUESTIONS

This program of research aims to examine the applicability of the Precaution

Adoption Process Model in understanding older adults’ self-regulatory driving

behaviour, specifically, to develop a comprehensive model that explains and

describes the process of driving self-regulation guided by the PAPM. A novel

approach using Latent Class Analysis (LCA) is employed to empirically validate or

reject the developed model. The research aim is addressed through four research

questions.

Research Question 1

Can older drivers be grouped into different stages of PAPM based on their

qualitative differences (e.g. attitudes, awareness, and perceptions) and patterns of

change?

The first research question is addressed in Study 1 presented in Chapter 5. The

PAPM has been explored previously in relation to driving behaviours among older

adults; however, this description has been very simplistic. This research question

provides the opportunity to obtain in-depth understanding of the process of driving

self-regulation among older adults by exploring their perceptions and experiences of

self-regulation. In addition, this research question constitutes the basis of this

program of research by exploring the preliminary fit of older adults’ driving

behaviour within the PAPM framework using qualitative focus groups among current


older drivers. The process of driving self-regulation starts by older drivers’

awareness of the need to change. This is followed by a decision-making process

where individuals weigh the pros and cons of modifying their driving. Once a

decision is reached, environmental and psychological barriers influence older adults’

ability to adopt such change. The findings from the study guided the development of

a preliminary model of older drivers’ self-regulatory behaviour. The choice of the

PAPM as the theoretical underpinning of this research has been discussed before.

The conceptual model served as a framework for the quantitative study. The

findings also informed the development of the questionnaire used in study 2.

Research Question 2

What is the prevalence of the stages of the PAPM in the study population and what

are the psychosocial and environmental factors associated with stages of the PAPM?

This research question is addressed in the second study presented in Chapter 6.

Participants were assigned into different stages of the PAPM based on a commonly

used stage algorithm. The aim of study 2 was to investigate the prevalence of PAPM

stages within a sample of older drivers. Further, the study aimed to identify the

psychosocial and environmental factors associated with different stages of the PAPM

and those that predict the decision to adopt self-regulatory behaviour which may be

worthy for further investigation.

Research Question 3

Would groups, identified utilising Latent Class Analysis (LCA), match those in the

conceptual model?

This research question investigated whether older adults’ self-regulatory driving

behaviour is truly a reflection of the stages of change described by the PAPM. To

achieve this, a bottom-up approach to profile older drivers based on their mindset

towards adopting self-regulatory driving behaviours using Latent Class analysis was

employed. Latent Class Analysis is a person-centred approach used to identify

subgroups with distinctive patterns. The selection of LCA indicators was guided by

the PAPM and involved driving perception, importance of driving, and barriers

towards change. The identified classes were described in terms of socio-

demographic factors, alternative transport use, and self-reported avoidance

behaviour. Findings from the LCA will assist in validating, refining, or rejecting the


conceptual model. There are three possible outcomes from conducting the LCA.

The sample may not contain different groups of driving behaviour, based on the

selected indicators. This outcome will therefore reject the hypothesis that PAPM can

describe older adults’ driving behaviour. The sample may contain subgroups of

older drivers that corresponds with the PAPM stages of change and therefore would

support the use of the PAPM. Finally, the sample may contain subgroups of older

drivers but does not correspond to the PAPM; which could indicate that there are

alternative ways to group older drivers.

Research Question 4

Can providing older adults with customised and evaluative feedback assist in

stage transition and modify their willingness to change their driving

behaviour?

This research question was addressed in study 3 where older drivers received

evaluative and customised feedback from a driving instructor. The literature

suggests that providing older drivers with feedback from someone they trust can help

enhance their awareness about limitations in their driving. The impact of such

feedback on participants’ insight and willingness to change was examined along with

participants’ opinions in regards to the usefulness of this feedback.

4.3 RESEARCH DESIGN AND METHODOLOGY

The research program used a mixed method approach comprised of two studies

that follows an exploratory sequential process. This was followed with a third

experimental study that assessed the impact of feedback on PAPM stage transition.

This design was chosen as the newness and complexity of the topic meant it is best to

explore the theory first qualitatively and to follow up with a quantitative study to

confirm the findings (Creswell & Plano, 2011). Further, mixing qualitative and

quantitative methods can help provide a more comprehensive understanding of the

research topic (Hesse-Biber, 2010) and can overcome the limitations of each

individual method, “producing richer and more rigorous understandings” of the

topic being studied (Creswell & Plano, 2011). Prior to conducting the first study, a

thorough review of the existing models of older drivers’ behaviour was conducted to

gain a better understanding of the various factors that affect the older adults’

regulatory behaviours. This later assisted in the developing of the conceptual model


along with the findings from study one. Study one involved qualitative focus groups

among older drivers to explore the applicability of the PAPM and to explore specific

aspects of their driving behaviour. The findings assisted in the development of the

questionnaire used for the quantitative survey. The second study was quantitative in

nature and further examined whether older drivers can be categorised within PAPM

stages and the sociodemographic and psychosocial factors associated with each

stage. The findings from study two are intended to provide further support for the

use of PAPM and to assist in refining the conceptual model. Study three was

experimental in nature and attempted to identify the impact of providing customised

feedback on the progression of stages of the PAPM. A flowchart of the research

program is presented in Figure 4.1.

4.4 SETTING, POPULATION, AND RECRUITMENT

The study was conducted in Queensland, Australia. The population of interest

for this research program were adults aged 70 or over who were still driving. A

convenience sampling technique was used to recruit potential participants. For the

focus group study and the quantitative survey, participants were required to be

English-speaking adults aged 70 years or over who hold a current valid driving

license. Various recruitment strategies were employed to ensure sample variability

including flyers posted in seniors’ clubs, geriatric clinics, and local shopping centres

and through social media. However, this strategy did not prove successful, so an

advertisement was placed in a Sunshine Coast seniors’ newspaper where people

interested in participating were encouraged to contact the research team. For the

experimental study, participants were drivers aged 70 or above who were either self-

referred or referred to the Royal Automobile Club of Queensland (RACQ) by their

doctor for an on-road driving assessment.


Figure 4.1: Flowchart of the research program

4.5 METHODS

Qualitative study

The qualitative data were collected through focus groups. A semi-structured

discussion guide was developed based on current literature on older drivers and the

research questions informed by the PAPM. Detailed description of the method is

provided in Chapter 5.

Literature Review of the

existing models of older

drivers’ behaviour

Qualitative Research

Focus group discussions

among current older drivers

Combine findings from the qualitative research and the literature review to:

-Develop a conceptual model of older drivers’ behaviour based on the PAPM

-Develop the questionnaire for the quantitative study

Quantitative Research

Online and paper-based survey

among current older drivers

Latent Class Analysis

-To identify subgroups of older drivers and determine whether they match those identified

by the PAPM

Refining the model

Experimental study

-To determine the impact of providing customised feedback on the progression of

stages of the PAPM.


Quantitative survey

Participants completed a questionnaire online or in a paper-based form with a

paid return envelope. Both questionnaires included an information sheet describing

the nature of the study and completing the questionnaire was considered evidence of

consent to participate. The questionnaire design was based on the qualitative study

findings and the literature review and collected information on socio-demographics

(age, gender, education, employment, etc.), self-rated health, crash history, driving

experience, current driving patterns, driving perceptions, feedback about driving and

transport options of older drivers. In addition, participants’ driving reduction and

avoidance behaviours were collected. Participants were classified into PAPM stages

based on their responses using an algorithm developed along similar lines to the one

used by Weinstein and Sandman (2002) (Table 4-1). Detailed description of the

questionnaire items is provided in Chapter 6.

Table 4.1: Precaution Adoption Process Model: Stage Classification Algorithm as

applied to self-regulatory driving behaviours among older adults (Adapted from

(Weinstein & Sandmand, 2002)) PAPM Stage Algorithm

Stage 2

Unengaged

Some other older drivers need to change their driving, but I believe that I

am a safe driver and have never thought about the need to change my

driving

Stage 3

Undecided

I am at the point where I am not sure if I should start thinking about ways

to avoid certain driving situation or reduce my driving

Stage 4

Resisting action Avoiding certain driving situations would be pointless to me

Stage 5

Planning to act I am planning to avoid certain driving situations and reducing my driving

Stage 6

Acting

I have just recently started to avoid challenging driving situations or drive

less

Experimental study

Prior to the assessment session, the driving instructor handed eligible

participants an information sheet describing the nature of the study. Participants

were then asked to complete a pre-test questionnaire that collect information on the

socio-demographics (age, gender, education, employment, etc.), self-rated health,


crash history, driving experience, current driving patterns, driving perceptions,

feedback about driving and transport options of older drivers. In addition,

participants’ driving reduction was measured by asking participants to rate the

overall amount of their driving compared to ten years ago on a 4-point scale from

“much less” to “more”. The driving assessment takes around 50 minutes to

complete. The driver instructor gives participants clear instructions as they start

driving in their familiar surroundings. If deemed safe, they start progressing to

busier and heavy traffic. The driving instructor assess participants based on a range

of driving skills. After the driving assessment, participants completed a post-test

questionnaire which collected information regarding the impact of receiving

feedback on changes in their perception and willingness to modify or change their

driving behaviour. Information regarding the usefulness of this type of feedback was

also collected.

4.6 DATA MANAGEMENT AND DATA ANALYSIS

For the qualitative focus group, thematic analysis was conducted following the

process outlined by Braun and Clarke (2013) to identify, analyse and report themes

within the data. Transcripts were read through carefully to gain familiarity with the

data content and to detect meaningful topics across the transcripts. Small sections of

the transcripts were initially coded, followed by an initial identification of themes

and collation of similar codes within themes (Braun & Clarke, 2013). The

supervisors independently conducted analyses of a sample of the transcripts.

The quantitative survey data were coded, entered and checked. Data coding for

each question, missing values and invalid answers were recorded in a code book.

Data were entered in the SPSS software version 20. Data checking was conducted by

checking for outliers, identifying genuine missing data, and assessing the distribution

of the data. Checks were performed by conducting descriptive statistics for

continuous and categorical variables. For continuous variables, the mean, standard

deviation, median, minimum, maximum, and skewness were calculated. For the

categorical variables, checks were performed by studying the proportion of cases in

each category. Normality of the continuous variables was examined by assessing

whether the mean values were within ± 10% of the median values and if the Z-score

obtained by dividing the skewness by its standard error was ≥-3 or ≤ 3, and

histogram was used as a measure of visual assessment. If data were normally


distributed, then bivariate analyses were conducted using parametric tests such as the

independent samples t-test and Pearson’s correlation. When data were not normally

distributed, non-parametric tests such as the Mann-Whitney U test were used. For

categorical variables, bivariate analyses were conducted by performing Pearson's chi-

squared test. For multivariable regression analyses, checks for multicollinearity were

performed by screening Pearson’s correlation matrices and/or computing variance

inflation factor. Multicollinearity was assumed to not be an issue if the variance

inflation factor for all variables were below 10. Latent class analysis is a person-

oriented statistical procedure that identifies unobservable subgroups within a

population based on certain pattern of observed responses (Hagenaars, McCutcheon,

& ebrary, 2002). For this study, LCA was exploratory and no assumption of specific

number of classes was made. The selection of the appropriate number of classes

depends on a number of fit indices. The procedure starts by running model with the

lower number of classes and gradually increasing number of classes while comparing

the fit indices (Geiser, 2013). Lower values of Bayesian Information Criteria (BIC),

the Akaike Information Criteria (AIC), and the sample size adjusted BIC indicate

better fit (Geiser, 2013). However, the BIC is regarded as a more reliable indicator

of model fit (Nylund, Asparouhov, & Muthén, 2007). Entropy is an index from zero

to one that is used to evaluate the precision of assigning latent class membership;

with a value of one indicating the individuals are perfectly classified into their latent

classes (Geiser, 2013). Further, the Vuong-Lo-Mendell-Rubin Likelihood Ratio Test

(VLMR LRT) is another indicator of model fit that provides a p value of the model

strength over a model with one fewer class (Geiser, 2013). Significant p values on

the VLMR LRT indicate that the current model is a significantly better fit for the

data than a model with one fewer class (Nylund et al., 2007). Given the nature of the

research, the theoretical implications guided decisions regarding the most appropriate

number of classes. Statistical analysis was conducted using SPSS and MPLUS 7.

4.7 ORGANISATION OF PAPERS

The papers are organised according to the four research questions of the

research program (Fig 4.2). Study one is presented in Chapter 5 as taken from Paper

1. Papers 2 and 3 relate to study two of the research program and are presented in

Chapter 6 and Chapter 7 respectively. Chapter 8 presents study three which is under

review.


Study 1 – Chapter 5 R.Q.1 Can older drivers be grouped into different stages of PAPM based on their qualitative differences (e.g. attitudes, awareness, and perceptions) and patterns of change? Published paper full title: The perspectives of older drivers on the impact of feedback on their driving behaviours: a qualitative study Sample: N=27 current Australian drivers aged 70 years and more Design and Method: Qualitative focus groups Analysis: Thematic analysis

Study 2- Chapter 6 First phase R.Q. 2 What is the prevalence of the stages of the PAPM in the study population and what are the psychosocial and environmental factors associated with stages of the PAPM? Published paper full title: Examination of the Precaution Adoption Process Model in understanding older drivers’ behaviour: an exploratory study Sample: N=222 Australian drivers aged 70 years and more Design and Method: Quantitative survey Analysis: Logistic regression

Study 2 – Chapter 7 Second phase R.Q.3 Would groups, identified utilising Latent Class Analysis (LCA), match those in the conceptual model and those of the staging algorithm? Submitted paper full title: Older adults’ self-regulatory driving behaviour: Results of a latent class analysis Sample: N=222 current Australian drivers aged 70 years and more Design and Method: Quantitative survey Analysis: Latent Class Analysis

Study 3 – Chapter 8

R.Q.4 Can providing older adults with customised and evaluative feedback modify their willingness to change their driving behaviour? Unpublished chapter Sample: N=21 drivers

Design and Method: pre-post-test design

Figure 4.2: Organisation of the papers

4.8 ETHICS APPROVAL

Ethical clearance to conduct the study was obtained from the Queensland

University of Technology Human Research and Ethics Committee (Approval number

1200000501). Consent for participation was obtained from eligible participants who

were instructed that their participation is entirely voluntary and withdrawal from the

study will not result in any penalty. If requested, all information provided by the

withdrawn participant would be completely destroyed. Participants were also

guaranteed that their confidentiality would be maintained and findings of the

research were reported anonymously. For the survey and final experimental study,


completion of the questionnaire was evidence of consent. The collected data were

treated with the confidentiality and were reported upon in an aggregate way to mask

the identity of the individual participants. In addition, the research materials were

stored locked, in the office of the researcher. The computer data were stored and

password protection, while backup copies were kept on a USB drive in locked filing

cabinets. As required by the Queensland University of Technology, the

questionnaires and coded information were, and will be, kept under strict security, at

all times, by the researcher, being stored for the required period of five years, and

then destroyed.


Chapter 5: The perspectives of older drivers on the impact of feedback on their driving behaviours: a qualitative study (Study 1)

5.1 PUBLICATION STATUS

This chapter comprises Paper 1 as taken from:

Hassan, H., King, M., & Watt, K. (2015). The perspectives of older drivers on the

impact of feedback on their driving behaviours: a qualitative study. Transportation

Research Part F, 28, pp. 25-39.

5.2 STATEMENT OF CONTRIBUTION

The candidate, as first author, accepts the overall responsibility for this

publication. The candidate was responsible for all aspects of the manuscript

preparation, including reviewing the literature, formulating the research question,

conducting and supervising data collection, analysing and interpreting the results and

writing and submitting the final manuscript. All co-authors meet the criteria for

authorship and take responsibility for their role in delivering the publication. All of

the co-authors of this paper are members of the candidate’s supervisory team and

their contribution to this paper was supervisory in nature. Written permission was

provided from each to include the publication as part of this thesis and its publication

on the QUT ePrints database.

The authors listed below have certified that:

1. they meet the criteria for authorship in that they have participated in the

conception, execution, or interpretation, of at least that part of the publication in their

field of expertise;

2. they take public responsibility for their part of the publication, except for the

responsible author who accepts overall responsibility of the publication;

3. there are no other authors of the publication according to these criteria;


4. potential conflicts of interest have been disclosed to granting bodies, the

editor or publisher of journals or other publications, and the head of the responsible

academic unit, and

5. they agree to the use of the publication in the student’s thesis and its

publication on the QUT’s ePrint site consistent with any limitations set by publisher

requirements.

Principal Supervisor Confirmation

I have sighted email or other correspondence from all Co-authors verifying their

authorship

Dr Mark King QUT Verified Signature 30 Aug 2017

------------------------- ----------------------------------- ------------

Name Signature Date


The perspectives of older drivers on the impact of feedback on their

driving behaviours: A qualitative study

Heidy Hassan a, Mark King b, Kerrianne Watt c

a The Centre for Accident Research and Road Safety – Queensland (CARRS-Q), GPO Box 2434, Brisbane, Queensland, Australia. Corresponding author. Tel: +61731387727. Email: [email protected] b The Centre for Accident Research and Road Safety – Queensland (CARRS-Q), GPO Box 2434, Brisbane, Queensland, Australia c School of Public Health, Tropical Medicine and Rehabilitation Sciences- James Cook University, Townsville, Queensland, Australia Highlights

• Focus group sessions were conducted with older drivers. • We explored older drivers’ perceptions and experiences of self-regulation,

using the Precaution Adoption Process Model as a framework. • We also investigated the possible impact of feedback on their decision-

making process. • Relevant issues that should be further investigated are discussed

5.3 ABSTRACT

Self-regulation is a coping strategy that allows older drivers to drive safely for

longer. Self-regulation depends largely on the ability of drivers to evaluate their own

driving. Therefore, the success of self-regulation, in terms of driving safety, is

influenced by the ability of older drivers to have insight into their declining driving

performance. In addition, previous studies suggest that providing feedback to older

adults regarding their driving skills may lead them to change their driving behaviour.

However, little is currently known about the impact of feedback on older drivers’

self-awareness and their subsequent driving regulatory behaviour. This study

explored the process of self-regulation and driving cessation among older drivers

using the PAPM as a framework. It also investigated older adults’ perceptions and

opinions about receiving feedback in regards to their driving abilities. Qualitative

focus groups with 27 participants aged 70 years or more were conducted. Thematic

analysis resulted in the development of five main themes; the meaning of driving,

changes in driving pattern, feedback, the planning process, and solutions. The

analysis also resulted in an initial model of driving self-regulation among older

drivers that is informed by the current research and the Precaution Adoption Process


Model as the theoretical framework. It identifies a number of social, personal, and

environmental factors that can either facilitate or hinder people’s transition between

stages of change. The findings from this study suggest that further elaboration of the

PAPM is needed to take into account the role of insight and feedback on the process

of self-regulation among older drivers.

Keywords Older drivers; Feedback; Self-regulation; Awareness; PAPM; Behaviour; Perception

5.4 INTRODUCTION

In Australia, it is estimated that the proportion of people aged 65 years and

more will increase from 13% in 2007 to approximately 25% in 2056 (ABS, 2008).

As the population ages, there will be an increased number of older licensed drivers

on our road system (King et al., 2011). Moreover, as the baby boomers age, they

will be driving more than previous generations (Wang & Carr, 2004). In

Queensland, drivers aged 60 years and above are over-represented in fatal and life-

threatening crashes and their involvement increases steadily with age (Rakotonirainy

et al., 2012). Furthermore, drivers aged 80 years and above are most likely to be at a

fault for injury or death-related crashes (Rakotonirainy et al., 2012). As a result, the

safety of older drivers has been receiving more attention from road safety researchers

in recent years.

Ageing is associated with non-pathological changes in the sensory, motor,

and cognitive functions that can impair people’s ability to safely operate a motor

vehicle (Molnar, Eby, St. Louis, & Neumeyer, 2007). Nevertheless, there is a

considerable variation in how individuals experience these declines (Eby, Trombley,

Molnar, & Shope, 1998) and the impact of such declines on actual crash risk is not

always fully known (Whelan et al., 2006). Further, older adults consider driving to

be key to their independence and mobility (Molnar et al., 2007). Restricting or

stopping driving can be associated with increased risk of depression (Ragland et al.,

2005), isolation (Fonda et al., 2001), and entering long-term care facilities (Freeman

et al., 2006).


Previous studies have indicated that some older adults adopt strategies to

reduce their crash risk while maintaining their driving, a process known as self-

regulation. Self-regulation has been defined as “the adjustments made by drivers in

their driving behaviour that adequately match changing cognitive, sensory and motor

capacities” (Charlton et al., 2006) which largely depends on the individual’s ability

to monitor his/her driving ability (Anstey et al., 2005). Common examples of self-

regulation seen in older drivers include reducing their overall amount of driving and

avoidance of various driving situations (e.g. avoiding driving at night or peak hours,

travelling shorter distances) (Anstey & Smith, 2003; Baldock et al., 2006a; Charlton

et al., 2006). Driving cessation is sometimes viewed to be the end result of the

process of self-regulation among older drivers (Dellinger et al., 2001; Lyman et al.,

2001). While uncommon, driving cessation can occur unexpectedly as a result of

sudden illness, involvement in an accident, or failing a driving test (Dellinger et al.,

2001). However, driving cessation is more of a gradual and voluntary process

whereby the driver will gradually increase self-imposed restrictions until ultimate

cessation (Dellinger et al., 2001; Hakamies-Blomqvist & Wahlström, 1998).

The question remains as to whether older drivers can accurately adjust their

driving in response to their age-related declines. The literature suggests that self-

awareness and insight into driving ability play a major role in successful driving

regulation among older drivers (Anstey et al., 2005). It is argued that individuals

who lack awareness of their abilities and limitations may engage in behaviours that

compromise their safety and the safety of those around them (Marottoli &

Richardson, 1998). In addition, older drivers who are aware of declines in their

abilities are more likely to practice self-regulation than those who are less self-aware

(Blanchard & Myers, 2010; Holland & Rabbitt, 1992). Lack of adequate support and

feedback can impact older people’s ability to make an informed decision about the

future of their driving. This can result in some older people stopping driving

prematurely while other continues to drive where it is not safe to do so (Berry, 2011).

Feedback may assist older drivers to appropriately monitor their driving and thus

results in proper adjustments in their driving behaviours.

Furthermore, the driving cessation process may occur through stages, and

interventions and feedback may be perceived differently at each stage (Kostyniuk et

al., 1998). This suggests that older driver interventions should be tailored to the


specific needs of each individual (including the stage they are at) and recognizes that

older adults should not be treated as a homogenous group. Such interventions would

therefore need to be customised to move individuals through the stages of change

towards adoption of safe driving behaviour. They would be developed by taking a

strategic approach using both a theory of the change process and existing evidence

from previous attempts to achieve change. However, there has been little

development of stage-based theories applied to driving self-regulation, and hence a

lack of research on theoretically-informed interventions that facilitate older drivers’

planning for future self-regulation and even driving cessation. There is also a lack of

consideration about the role of feedback about behaviour in the stage process, such

as responsiveness to feedback, acceptable sources of feedback, and ability to modify

behaviour in relation to feedback. This research aims to contribute to the

development of a theoretical framework for a stage-based process leading to self-

regulation of driving which incorporates the role of feedback, with the intention of

testing the theoretical approach in future research with older drivers.

The research approach builds on existing theory rather than starting from a

blank slate. The stage-based theoretical model used as the basis for the study is the

Precaution Adoption Process Model, or PAPM (Weinstein et al., 2008), which

provides a framework for understanding why older drivers adopt self-regulatory

(precautionary) behaviours intended to reduce their road crash risk. The PAPM

assumes that people need to be aware of the risk associated with their behaviour

before they are susceptible to behavioural change, and that awareness of the risk is

not necessarily enough to lead them to change their risk behaviour. It characterises

seven stages along the path from lack of awareness to action (Figure 5.1):

unawareness; awareness that there is an issue but a lack of personal engagement with

it; engagement (“this applies to me”) but indecision about the need to act; either a

decision not to act or a decision to act; if the latter, acting by taking the precaution

(e.g. self-regulating); and maintaining the behaviour. In each stage the types of

information and interventions needed to move people closer to action vary. The

greatest advantage of such a stage theory is that messages or other interventions can

be tailored for people at different stages. Interventions targeted at increased

awareness of risk and precaution effectiveness can move people between early stages


while later stages require interventions that address barriers to adoption of the

precaution.

Figure 5.1: Stages of the Precaution Adoption Process Model- Source: (Weinstein & Sandmand, 2002).

The PAPM has been used previously to study adoption of behaviours related

to osteoporosis prevention (Mauck et al., 2002), disaster preparedness (Glik,

Eisenman, Zhou, Tseng, & Asch, 2014), epilepsy (Elliott, Seals, & Jacobson, 2007),

colorectal cancer screening (Costanza et al., 2005), fruit intake (De Vet, De Nooijer,

Oenema, De Vries, & Brug, 2008), coping with premenstrual syndrome (Delara et

al., 2012), and home radon testing (Weinstein, Lyon, Sandmand, & Cuite, 1998).

In relation to driving, the PAPM has been explored by Kostyniuk et al., 2000

in which they argue that the use of the PAPM is a productive way to look at how

older drivers cope with age-related declines and their willingness to make changes in

response to these declines. Their description of the process of driving self-regulation

begins with driver acknowledgement of potential future problems with driving

ability, followed by awareness of their experience of increasing difficulties with

driving, and eventual avoidance of difficult driving situations (Kostyniuk et al.,

2001). Unfortunately, the adaptation of the PAPM in this study was not fully

described, and was based mostly on older adults’ awareness of their declining

abilities, i.e. it failed to recognize the influence of other external and internal factors

on the process of self-regulation. For example, external factors such as a lack of

alternative transport, and internal factors such as self-efficacy with respect to the

precautionary behaviour (“can I successfully regulate my driving?”) may interfere

with adoption of self-regulation in spite of awareness of the problem.


Nevertheless, the applicability of the PAPM to examine the driving

behaviours among older adults deserves further consideration. An attractive feature

of this model is that it deals with both the hazard and the precaution. It claims that

for individuals to consider adopting a precaution they must first perceive the hazard

to be of sufficient personal relevance. The age-related declines in people’s sensory,

motor, or cognitive functions are often subtle and gradual which can make it difficult

for older people to draw the link between these changes and the impact on their

driving ability. Interventions should encourage people to adequately regulate their

driving without imposing unnecessary restrictions or stopping driving prematurely.

Therefore, the early stages of the PAPM emphasize the importance of increasing

people’s awareness about the impact of ageing on their driving ability. While it is

highly likely that older adults are “generally aware” about the safety issues of older

drivers, they could lack “self-awareness” or insight into their own driving ability.

Once they become personally engaged with the hazard, people are more likely to be

more receptive towards adoption of the precaution.

Therefore, the main aim of this study was to further understand the process of

driving self-regulation among older adults by exploring their perceptions and

experiences of self-regulation, using the PAPM as a framework, and in particular to

investigate the possible impact of feedback on their driving on their decision-making

process. Further aims were: to determine the applicability of the PAPM to the self-

regulatory behaviour of older drivers and how it could be elaborated; to identify

barriers and facilitators to the progression of drivers between stages; and to identify

the current limitations and problems with the feedback older drivers are currently

receiving. The intention was not to support or reject the PAPM, but to use it as a

starting point for theory development.

A qualitative study design using focus groups was chosen to explore

participants’ perceptions of driving cessation and the impact of feedback on their

decision-making process. Qualitative research is appropriate given the theoretical

issues raised above. There has been limited application of stage-based approaches

such as the PAPM to older driver self-regulation and there is a consequent need to

pursue an exploratory approach, especially in regard to the role of feedback. Focus

groups are useful in exploring under-researched areas as they do not require any

prior empirical knowledge about the issue (Braun & Clarke, 2013). In addition,


focus groups can elicit a wide range of views, perspectives, or understanding of an

issue (Braun & Clarke, 2013).

5.5 METHOD

Recruitment

The research was conducted in the Brisbane and Sunshine Coast areas of the

state of Queensland, Australia. The estimated population of Queensland in 2012 is

4.5 million with 13.1 % of Queenslanders aged 65 years and over. In 2011, females

outnumbered males in the 75 years and above age groups (ABS, 2011). Females

were also more likely to be living alone with 33.8% of women aged 65 years and

over living alone compared with 18.4% of older men (ABS, 2011). Driving is the

preferred mode of transport in this area (Liddle, Turpin, Carlson, & McKenna, 2008)

and the licensing authority is Queensland Transport and Main Roads. Drivers aged

75 years and above are required to carry a valid medical certificate obtained from

their doctor. Participants were required to be English-speaking adults aged 70 years

or over. Initially recruitment was aimed at former drivers as well as current drivers

because of the importance of their perspective on the driving cessation process and

the feedback they received during this process. However, only one former driver

contacted the research team, probably due to the sensitive nature of the topic and/or

the difficulty in getting to the sessions, so only current drivers were used. Various

recruitment strategies were employed to ensure sample variability including flyers

posted in seniors’ clubs, geriatric clinics, and local shopping centres and through

social media. However, this strategy did not prove successful. The first author was

interviewed on local radio (on the Sunshine Coast) to promote the study and to solicit

older drivers, however only four participants responded. Finally, an advertisement

was placed in a Sunshine Coast senior’s newspaper where people interested in

participating were encouraged to contact the research team. This led to recruitment

of further 23 participants to give a total sample of 27, all of whom were current

drivers with 10 or more years of experience. Because only three participants resided

in Brisbane and the remaining participants were from the Sunshine Coast area, one

focus group session of four participants took place in Brisbane and the remaining

four sessions took place in Caloundra, a city on the Sunshine Coast.


Participants

Twenty-seven older drivers participated in the study. A summary of the

demographic characteristics of the participants is given in Table 5.1.

Table 5.1: Characteristics of Participants Characteristics Descriptive statistics (N=27)

Gender 17 (63%) Female

10 (37%) Male

Age Median=74 (range 74-90)

Education 2 (7.4%) Primary school

13 (48.1%) Secondary school

8 (29.6%) Certificate/Diploma

2 (7.4%) Bachelor degree

2 (7.4%) Postgraduate qualification

Type of Residence 18 (66.7%) Private home

9 (33.3%) Retirement home

Living situation 15 (55.6%) Living with spouse or partner

12 (44.4%) Living alone

Employment 18 (66.7%) Unemployed

7 (25.9%) Part-time work

1 (3.7%) Full-time work

Self-rated Health 9 (33.3%) Excellent

15 (55.6%) Very good

3 (11.1%) Fair

Procedure

A semi-structured discussion guide was developed based on current literature

on older drivers and the research questions informed by the PAPM. In particular, it

explored: (1) the importance of driving and the impact of driving cessation, (2)

changes of driving behaviour among older drivers, (3) awareness of changes in

driving abilities; (4) perceived indications of the need to give up driving, (5) their

future plans for stopping driving, and (6) impact of feedback on their planning and

decision making process. A total of five sessions were conducted from February


2014 to March 2014. Sessions were held in a private room where the moderator

explained the study goals and obtained signed consent from the participants. The

sessions lasted 60-90 minutes each and the number of participants varied between

two to eight. Sessions were audio-recorded and then transcribed verbatim for

subsequent coding and analysis. Participants completed a background questionnaire

to collect basic demographics and driving status. Each participant received a $40 gift

voucher at the end of the session for their time and travel. The study had full ethics

approval from the Research Ethics Unit at the Queensland University of Technology

(Approval number 1200000501).

5.6 ANALYSIS

Thematic analysis was conducted following the process outlined by Braun and

Clarke (2006) to identify, analyse and report themes within the data. Transcripts

were read through carefully to gain familiarity with the data content and to detect

meaningful topics across the transcripts. Small sections of the transcripts were

initially coded, following which the first author conducted an initial identification of

themes and collation of similar codes within themes (Braun & Clarke, 2006). The

other authors independently conducted analyses of a sample of the transcripts, as a

result of which the themes were refined. This process resulted in the development of

the five themes discussed below.

5.7 RESULTS

The analysis resulted in the development of five main themes. The themes were:

• The meaning of driving

• Changes in driving patterns

• Feedback

• The planning process

• Solutions

Under most of the main themes there were sub-themes. Each of the themes and sub-

themes is elaborated below, and quotes from the transcripts are used to provide

examples of the comments made.


Theme one, the meaning of driving

In order to capture what driving meant to the participants, they were asked

about the negative aspects or issues associated with driving at their age along with

the importance of driving. Participants discussed how driving enabled them to be

functional and independent, and how it provided them with a sense of enjoyment.

Driving was essential to maintain participants’ independence and social

inclusion: “Very important. I work part-time. I also play bowls a lot, and I go to

different clubs and things for that. You can't possibly lead a really independent life

relying on public transport. It's too difficult. It takes a whole day to do one thing, and

I don't have time to do that. It is very important to me, and I think for most older

people, it is part of their independence. Giving up driving is a really hard move, I've

discovered, with other people. They feel as if they've lost their independence. Even if

they're only driving to the local shops and back, they feel as though they've still got

their independence if they can drive. It's very important” (Female, 70)

Driving also enabled participants to stay connected with their family: “But we

have family that live good distance apart. And to get to see them in public transport,

well, there isn’t” (Female, unknown)

For those who lived in communities outside the main urban area, driving was

a necessity as alternative transport options were very limited: “The community that I

live in is very small community ……. if you can drive it’s fine, it’s 20-25 km to the

nearest supermarket shopping complex, the mall and all the rest of it. You need to

have a car to get in and out of the place. The elderly folk who don’t have a car have

to rely on neighbours, a once a week bus, of if they are sick at night they have to call

the ambulance……….. I’ve seen a couple of elderly folk absolutely go to pieces when

they got very sick and couldn’t drive anymore” (Female, 71)

Moreover, driving was something that they enjoyed doing: “I thoroughly

enjoy driving. I think it’s wonderful” (Female, 76)

Interestingly, the negative aspects of driving were mostly related to external

factors other than difficulties they encounter in their own driving. Other drivers’

behaviour and lack of courtesy was a major issue noted by the majority of the

participants: “Other drivers are appalling, especially young males. They tailgate

you, they've got to get past you. Bit of road rage there. There's all those things that


weren't there in my youth, when I was driving. I have to be aware of all those sorts of

things, as well” (Female, 70)

Safety was another issue mentioned by the participants. They did not view

the roads to be as safe as it used to be when they were younger: “When we learned to

drive, there weren't the drunks and addicts on the road. The roads were a lot safer

than they are now” (Female, 76)

Changes in the road systems and the lack of signage that meets the

participants’ needs was also raised by several participants: “There should be a street

sign on every corner so you know what road you’re on and what road you want to go

to and it would help a lot” (Female, 70)

Another issue was how they have become unfamiliar with the constant

changes in the road rules: “I find one of the negative things amongst our age group is

that a lot of older people aren't cognizant with the road rules that have changed. I've

actually got a copy of the latest road rules and went through it and there are a lot of

things that have changed. And a lot of new rules that I wasn't aware with” (Female,

72).

Theme two, changes in driving patterns

When asked about any changes in their driving behaviours as they aged, the

majority of participants noted that they are generally driving less for various reasons

such as retirement, relocation, changes in their family responsibilities, or a mere

preference, for example:

“I don't have to work anymore. I drove four hours to and from work, which I don't

do now” (Female, 76)

“I would drive a lot less nowadays only because I’m living in the metropolis of

Sippy Downs (a suburb of the Sunshine Coast, Queensland) - before I lived in the

country” (Female, 84)

“I drive a lot less though because all our grandchildren are all grown up, they've all

found their own ways. We don't need to meet them at school or take them to sports

events and things like that” (Male, 90)

“I'd rather stay at home, and play on my computer” (Male, 71)

However, a few female participants noted that they drive more now due to

death of their husbands: “I think I do drive more. My husband’s passed away, he


used to do the driving. So, you've got to do it yourself” (Female, 74). Others noted

driving more due to lifestyle changes: “I certainly drive more than when I was

working. Because we’ve got all this time on our hands!” (Female, 78)

Participants also noted that they plan their trips quite often now: “I find that I

tend to plan my journeys ahead a little bit more. If I'm going somewhere where I'm

not quite so familiar, I get the map out and I make sure that I've written down what

streets I'm [?], what roads I'm going” (Female, 72). However, they attributed this to

the constant changes in the road system: “I think that's because there's a lot more

roads and different angle, you know, they keep on changing roads and such, so we've

got to be more aware of it, haven't we? That's why we do it more now than we ever

used to, because it was only ever one road to take, wasn't there?” (Female, 70) and

for safety reasons as well: “You were safer to get out of your car and ask directions

as well. Now, I wouldn't dream of going up to somebody's door at night and saying,

I'm lost, can you help me. I would have, when I was young.” (Female, 76)

Night time driving was problematic for some of the participants:

“I find driving at night time. I don't drive at night-time if I can avoid it. If I'm down

to see my family, I always try and get home before dark. I can drive at night time, I

have to wear glasses at night time. I have intraocular lens in my eyes I wear, so I

don't need glasses so much, but at night time I really need them to get the clarity of

the lights” (Female, 75)

“I think I've changed my driving. Since I got these (points to his glasses), I don't drive

anywhere near as much in the night time…. Yeah, where it never used to worry me,

headlights or anything like that. Now, I'd rather not drive in the night time if I can

avoid it… That's right. No problems with the confidence, about handling the vehicle,

or avoiding an accident. It's just the sight” (Male, 84)

Another issue was neck turning and merging:

“The neck's a bit, looking over the shoulder. I use the mirrors an awful lot” (Female,

79)

“I did find even coming on the Sunshine Motorway from where we live, you had to

merge. Okay. I’m used to mirrors, but you still have to turn around and sometimes

there’s a bit of pain there and you can get a – What do they call it...Monocular

vision, that doesn’t give you the depth of perception so that was just one physical

angle that” (Male, 71)


Some participants find it difficult to read road signs as they drive: “I'm pretty

confident, but it's just if I know where I'm going. If you tell me to go such and such,

that lane, that street, do that, fine. But it's when I've got to read signs…. There

weren’t so many signs when we were younger.” (Female, 78)

Participants also noted that they don’t drive very long distances, they are

slower, and more cautious.

Theme three, feedback

We asked the participants if they have sought information about their driving

ability before. Doctor’s advice, a driving instructor, refresher courses, and the

internet were mentioned in several discussions:

“Oh, he knows (refers to his doctor). I've talked to him. He's just said, “If

that's the way you feel, don't drive. It's up to you.” (Male, 70)

“We did an advanced driving course many years ago, and then down here at

the university before it was at a university …anyway, it was very good, excellent! It

was run by two ex-policemen” (Female, Unknown)

“I went on the Internet about it, and downloaded a lot of information from

overseas. I don't know where they get the results for some of their studies from,

because it doesn't make any sense to me……. Some of the stuff you can download is

really hilarious. A lot of it's pretty right” (Male, 84)

“I felt I was getting a bit dicky driving so I rang the NRMA and asked them,

“Could I do a driving test?” And he said, “Well, we don't really do that.” He said,

“But I’ll get someone to come down and go with you.” So, they sort of came from

“?” and took me around where I usually shop and about two hours later, we got

back and I hadn’t hit anything. So anyway, he said – So I said, “How did I go?” He

said, “Well, only two things,” he said, “I could find.” He said, “You drive too fast

and you drive too close to the vehicle in front.” And do you know what? That has

helped my driving so much, just to be told that. You probably know you’re driving

too fast and you know you’re getting there, but just to be told by someone in

authority, it – And because up here, you get on the highway and it says travel three

chevrons behind, which is a wonderful indication because it hits you in your mind

and you just need a reminder about it” (Female, 71)


For the majority of participants, feedback about regulating or stopping

driving had to come from someone they trust and respect, and be evidence-based:

“It’s got to be from somebody that you trust and respect” (Male, 76)

“and people pay more attention to professional people rather than...it's tough

for you, you know… It carries more weight. They've got the evidence. They'll say,

well, you tick some of the boxes, but you don't tick some of the others” (Female, 71)

The majority of participants thought that they would listen to their physician:

“At this stage, I'm not going to discuss it with my medical people, but when

the time comes, I would certainly respect a professional giving me clues as which

way to go” (Male, 71)

Some even noted that it is the doctor’s responsibility to raise the issue and

they should be the first source of feedback:

“I think the main thing is you're seeing a doctor, the doctor knows what your

physical capacity is, if you know him well enough. He should be able to say...if

you're suffering from a particular disease or perhaps it is asthma, maybe a heart

attack. That's the time the doctor should at least say you're in an area where you

should not be driving, and should advise that” (Male, 70)

However, there were several grey areas and uncertainties identified about

receiving feedback from a physician, for example the fact that some physicians are

very busy was raised by one participant who had to get her medical certificate from

another doctor: “He's never said anything to me, my doctor. I go to the doctor late in

the afternoon, because I generally have to wait, and he's that busy that he just wants

to get rid of me, if you know what I mean” (Female, 79)

Another issue raised was the reliability of the criteria doctors use to assess

their patients for fitness to drive, especially related cognitive impairments and the

concept of differential ageing, for example:

“It's very hard for a doctor to say if somebody has a heart attack, they

shouldn't drive. There's a lot of people driving around that's got pacemakers, and

they've got no trouble driving, and yet, another person can be driving down the road,

never had a heart attack, never had anything wrong, and suffer a heart attack and

die at the wheel” (Female, 74)


“I know of several other people, one woman, who at 92 is still driving. She

had the beginnings of dementia. Physically, she was okay, eyesight fine. But she

should not have been driving, and she was. And it very much depends on what they

write on file” (Female, 70)

“It's a difficult thing. This is where it comes back to the medical profession, I

think (refers to another participant), he’s 86, he looks pretty fit for me, being able to

still drive at that age is phenomenal. Here I am, a little younger and I don't feel as

though I should be. It does come back to that, perhaps it's the medical profession

again. Have to say, this man's fit, or he's not.” (Male, 70)

The negative impact on the physician-patient relationship associated with

telling older adults not to drive was also noted by participants for example:

“But, as I say I know two other people whose doctors told them and it did not

happen very nicely. In fact, one gentleman went to another and got a tick on his…

And he continued to drive” (Female, 71)

Also, the fact that some doctors are very familiar with their patient, could

make it harder for them to notify authorities if they are unfit to drive:

“But your doctor signs...it's a certificate. And if you've been in the company

of elderly people like we have, it's only a matter of waltzing up to the doctor and say,

I need a certificate to get my license again, okay thank you very much, no problem at

all” (Male, 71)

“I think there needs to be some kind of interim body to make these sorts of

decisions, because doctors themselves are too familiar with patients. As we said

earlier, you might have been going to see that same doctor for many years. They're

reluctant to make those sorts of decisions” (Female, 70)

Interestingly, participants were not very open to receiving feedback from

their family members:

“I mean, there's been a lot of talk about children trying to persuade parents

that it's time to hang up the car keys, very difficult. I think it's probably the wrong

person telling them, you need one further away, a dispassionate person who's not

actually family to say this” (Female, 71)


And some noted that their children don’t understand their worries and

concerns:

“I tell my kids that I don't feel comfortable driving. Part of it is my age, and

they say, “Dad, you're mad. You're silly.” They can't see the fact that I feel

uncomfortable. I don't think that they've been in an accident where they've seen the

results of what can happen in a car” (Male, 70)

When asked about other sources of feedback that they think could raise

awareness of the older drivers, participants mentioned several options:

“So, should it be coming from TV announcements in a nice gentle kind of

way, should it be coming in the media, in the newspaper…” (Female, 70)

“The fact that you can get a brochure that says, how old are you? These are

the statistics of vehicle accidents that are occurring in this particular range, or this

medical area. There's a lot more people having heart attacks at the wheel…There’s

that, and I don't know, perhaps they've got to open up courses, so you can come and

say, “Look, how do you think you're driving? Are you one of those good 70-year-old

drivers? Come and we'll tell you why you are not” (Male, 70)

Theme four, the planning process

Majority of the participants did not plan or think about the possibility of

stopping driving in the future. There were five main areas explored under this

theme.

Reactions to giving up driving and expectations

Participants’ reactions to the possibility of giving up driving was very

emotional: “I hope by the time I can't drive, I'll be dead or I'll be making my plan to

go somewhere where I don't have to drive” (Female, 71). Stopping driving is a hard

decision: “It’s a big dilemma, because we're all aware of the fact that the day will

come, of course. But not yet. And you know, we have to drive” (Female, 71) and there

is a lot of uncertainty about what the future holds, not just in regard to their abilities

to drive but in the advances in technology as well: “I can't predict what I'm going to

be doing in 10 years' time, because partly…. the technology will change. Partly, I

don't know how I'm going to feel” (Female, 70)


Interestingly, some participants were more accepting of the idea and started

thinking about alternative options throughout the discussion: “I’d just go to other

places and I don't mind public transport…..It’s not as – You can’t get anywhere quite

as quick, but you can do it and I reckon if they – I got – Lost my license, I’d get one

of those mobility scooters and get around and use public transport and I don't think

I’d let it stop me getting out and about” (Female, 74)

Some participants drew their expectations from other older drivers’

experiences, which often meant driving less and to their local destinations: “Well, I

think you just be driving less, you know, like people do as they get older, they just

drive to church, to the big shopping centre, you know to the library, they don’t…

Like my daughter… you rely on the family to come and visit you” (Female, 72)

Others indicated that they are not planning to renew their licence in the near

future, which is mainly due to medical conditions or getting older:

“I probably won't renew my license next year…. I tear tendons and

shoulders. My neck is not getting any better. Occasionally, if I get up too quickly, I

get giddy. The doctor says it's up to you, but my recommendation is, when your

license is due next year, forget it. If you last that long” (Male, 84)

“I think in another three years or four I won’t be driving a lot, because I’m

getting too old.” (Male, 86)

Few participants indicated that they have thought about the possibility of

giving up driving one day, even though they are still fairly active and enjoy driving.

They have noted that they made some major changes in their lifestyle that would

facilitate their transition to a non-driving state one day:

“The place that I live in is not that far from where my daughter and her

family live and that was a consideration when I took the unit, and I can walk to the

shops and I can walk to church” (Female, 70)

“I've recently moved into a retirement village, and I've been very careful to

choose one where there's a very good bus service there. I'm quite prepared that when

the time comes where I feel I'm not good enough to drive, I will give it up, but it's

really important to me. It was one of the things that I looked at” (Female, 72)

Indications for giving up driving


Loss of confidence and nervousness was an important reason for giving up

driving as noted by some participants: “I’ll see at the moment, if I start to get nervy,

that, that is a big thing, if you’re getting nervous” (Female, 72)

Changes in their health condition and abilities was also perceived as an

important reason to give up driving: “I think it just depends very much on health”

(Female, 71)

For some, age did not seem to be an important factor per se, partly because

people age differently and start experiencing changes and declines in different way.

But also, because majority of the participants were in their 70s and the fact that

people are driving for longer now, meant that they believed they had 20 years or

more to still be actively driving:

“See, I’ve got friends who are 92 and they still drive. So, I’m thinking, well,

you know, I’ve got a way to go yet but that’s sort of – so it doesn’t sort of bother me”

(Female, 74)

“He’s said that to me a few times. And I say to him, “Why do you feel like

that?” and the only answer I get is “Because I’m, getting old,” but surely, that’s not

the criteria. And that’s why I’ve been trying to question him if he has any other

feelings that might be prompting that thought…. It doesn’t matter. The age doesn’t

come in to it. It’s just your mental attitude” (Female, Unknown)

Being involved in a crash was not considered by the participants as an enough

reason for stopping which could be due to the severity of the crash and the fact that

they did not view themselves to be at fault: “I had my first crash a few years ago, not

my fault, of course. <Laughs> But that’s about all…. And when I had this crash, I

thought that was a thing to say that I better give up driving. I lasted three days. It

was terrible” (Female, 84)

Loss of comfort was also another indication for giving up driving as noted by

one participant who had already reduced the amount of his driving in the past years:

“Perhaps that's one of the...I don't feel comfortable on the road. If someone else

would drive me, I'd do it, but that's why I walk, and that's why I cycle” (Male, 70)


Household composition was an important factor. Some participants indicated

that they will be relying on their spouses for driving in the near future. On the

contrary, female drivers who lost their husbands were doing more driving now as

opposed to the past:

“If I lose my license, I’ve lost my independence. I’ve got to get on a bus, but

I mean I’ve got (refers to his wife) anyway so she can drive and she’s a good driver”

(Male, 75)

“It’s very important to have a car for myself because I live by myself and

same thing goes” (Female, 76)

“I enjoy driving, I must admit it. I had a very sick husband for the last seven

years of his life so hence I was the designated driver” (Female, 71)

Advice and feedback from others was also seen as a reason for regulating or

giving up driving altogether:

“It wouldn't bother me if the doctor said to me, “Don't drive.” I would take

his advice” (Male, 70)

“We used to drive to Brisbane, but the reason we don't drive to Brisbane is

because we have a family problem there, as far as a family concern about not driving

long distances anymore” (Male, 86)

For others, it was more of a self-monitoring process, where people start to

notice changes in their driving as they age. Drawing from other people’s

experiences, they viewed that people were more accepting of giving up driving when

they made the decision:

“If you are a driver and I'm very grateful that I can and do, I think you

probably would be aware of what could or could not happen and hopefully take

steps” (Female, 71)

“I, I know of one lady who, voluntarily handed in her license said I don’t

think I can drive anymore, and she then accepted that quite well. But, as I say I know

two other people whose doctors told them and it did not happen very nicely. In fact,

one gentleman went to another and got a tick on his… And he continued to drive”

(Female, 71)

Abilities for safe driving and awareness of changes


Participants mentioned numerous sensory, physical and cognitive abilities

that they perceived critical for safe driving:

“Eyesight, for one” (Male, 76)

“And also, now your good physical health” (Female, 71)

“I think that your cognitive ability when your driving is one where also to

be… focused and be concentrating on the task at hand and try to take in as many

things as possible” (Female, 70)

“Be aware of your surroundings, for one thing” (Male, 90)

“Focus on your driving, when you're driving. Don't get distracted by other

things. You've got to concentrate. All these distractions, people don't concentrate

enough, and your reaction time gets longer as you get older.” (Female, 76)

The major changes in their abilities, were slower reaction time, being more

cautious, changes in their eyesight, and being more patient

“Yes. I find that I'm not as quick as I used to be, so in my youth, where I'd be

able to drive, a simple thing like that, look left and right. My mind would say

everything's clear, now I find I've got to look twice. I'm far more careful. I'm slower”

(Male, 70)

“I think one of the other issues could be sort of eyesight as well. I think now

there’s such a plethora of the road signs around that it’s probably quite easy to miss

one particularly because in my situation like a little bit in the distance, where before

you would have seen it but probably now you’re thinking “Is it or isn’t it.” (Male,

71)

However, the majority of participants did not report changes in their abilities

and even noted that their driving ability is much the same: “As far as our own

abilities are concerned, I don't think...there hasn't been a lot of change in the last 20

years, for me” (Female, 70)

One interesting point raised by several participants is that driving is a habitual

process that you should be able to maintain doing over time: “I think because in our

declining years, we're creatures of habit, if they've always been a good driver, why

would it change? Unless there are other forces at work like, you lose your hearing or


your eyesight isn't so good anymore, or your concentration. But it's difficult to break

the habit of years.” (Female, 71)

Barriers and facilitators for giving up driving

As noted above household composition was an important consideration in the

decision-making process. It appeared that having a spouse or family to rely on could

facilitate the transition to a non-driving state. On the contrary, having family relying

on their driving or living alone could mean that it is essential for older adults to drive

for longer.

Living arrangements and location was another important factor. It appeared

that participants who lived in retirement villages where everything is walking

distance found it easier to give up driving one day. Others who lived in communities

far from urban areas reported that giving up driving could mean isolation for them.

Participants’ opinions regarding the use of in-vehicle technology were highly

variable. Some viewed technology as a wonderful possibility that could help them

overcome some limitations they encounter in their driving, such as reverse parking,

merging, and driving in unfamiliar places:

“Automatic parking will be a dream” (Female, 76)

“I use cruise control a fair bit when I’m out on the highway. But you’ve only got to

touch the brake and then it goes off” (Male, 75)

“I think some of those are wonderful, my daughter’s got one that you know; she can

see what’s be-behind… See on the driveway behind her. Ahh, just wonderful, I

wouldn’t have to worry about my neck, now would I?” (Female, 72)

Others mentioned some issues associated with the use of in-vehicle

technology such as being user-friendly, affordability, and its impact on their

concentration and safety:

“I’m not interested in having them on my car. I can’t even work the microwave so

how am I able to work that?” (Female, 71)

“I’m never gonna be able to afford a car with all those things in it” (Female, 74)

“I wouldn't say the latest technology is a wrong thing, but when they get back to the

concentration of the drivers, concentrating on going wherever, the more modern

technologies now installed, the less the driver is concentrating. And it's

concentration that causes most of the accidents” (Male, 71)


“GPS. I think they're a menace. Because you've got to look at it or listen to it, and

you're taking your eyes off the road, and it only takes a second and you're at a crash”

(Male, 90)

Alternative transport option is an important factor as well. Issues concerning

availability, accessibility, convenience, and acceptance were raised. The majority of

participants held strong opinions against the public transportation system:

“Because I hate public transportation. Non-existent, at our end of the world”

(Female, 79)

They viewed it as time-consuming: “I find it useful having a car because you

pop into your car, you get A to B without going all around neighbourhoods that day.

That's probably a drive that's going to take you 20 minutes, it takes a bus an hour

and a half” (Female, 74), inconvenient: “If I had to give up driving, I'd be lost. I'd

have to ride on taxis, and I think the bus service is every hour at the least. So, it's

very important for me to keep on driving” (Male, 90), inaccessible: “I can walk

down to a bus stop, but I couldn't possibly walk up the hill climbing with my

shopping” (Female, 72), restricting: “So your evenings, you're confined. It's not so

bad in the day when there is public transport around, but at night, you can't go out

without your car. You can't go out to dinner” (Female, 76), difficult to plan: “I can’t

remember the last time I used public transport so that in itself is a little bit of a nervy

thing about finding out which bus goes where and timetables and everything”

(Female, 78), and unsafe: “and then you’re quite likely to get bashed on the bus.”

(Male, 71)

Other older adults’ experiences about giving up driving seemed to have left an

impact on some participants about how their life would look like without driving.

This may make it difficult for them to come to terms with the decision to give up

driving: “So it is extremely important that you drive, and I’ve seen a couple of

elderly folk absolutely go to pieces when they got very sick and couldn’t drive

anymore……. You have got to hand your license, they just, they just melt…it’s very

scary” (Female, 71)

Theme five, solutions

Participants expressed their opinions about possible sources of feedback

about older adults’ driving abilities.

On-road testing


Opinions varied regarding the introduction of age-based on-road testing.

Some were very accepting of the idea and saw it as “common sense” (Female, 74).

Others thought it should only be required if a medical condition is present: “It might

be even if you’re on medication or if you had the shakes or something like that, I take

great exception to that at 72” (Female, 72) and that it would need to be gradually

introduced from an early age: “I think it should be spread over all ages. The new

drivers, after they're off their P-plates, the last lot. The year after that, they should go

for another test” (Male, 84)

Medical examination

Overall, participants viewed the medical examination positively. However,

they thought it should incorporate a physical component as well and need to be more

strictly enforced:

“I really do agree with that examination, because I’ve had my eyes fixed

annually, you know, and they noticed any deterioration, and you've got to trust your

doctor” (Male, 76)

“I thought it would be good idea though that you could go and have a

physical test sometime” (Male, 71)

“But then it's a matter of being enforced, isn't it? This chap, it wasn't

obvious. But he was elderly, and the fact that he had a medical condition and was

still driving, it was dangerous” (Male, 70)

Driving courses and driving schools

Participants who attended driving courses viewed them positively and noted

that they helped raise their awareness about limitations in their driving:

“One thing that – We were at a lecture the other day with the national seniors

group and the person was talking physio care for elderly people and one of the

things he did mention was ability to turn your neck around, and he was saying

particularly in the bottom area and I did find even coming on the Sunshine

Motorway from where we live, you had to merge. Okay. I’m used to mirrors, but

you still have to turn around and sometimes there’s a bit of pain there and you can

get a – What do they call it?......Monocular vision, that doesn’t give you the depth of

perception so that was just one physical angle that” (Male, 71)


“And you could go on a refresher course and improve your...I think that is an

RACQ course for drivers. They pick up your faults and advise you how to adapt your

driving” (Female, 76)

“I think it would be a very good idea, and I'd be quite prepared if someone

came with me for half an hour, or an hour. Whether they be a driving instructor or

somebody else and just pick up any bad habits that I might have, or give me

feedback. I think that would be a great thing to do. My sister has just done it. She

almost had a very bad high speed accident because she misjudged the speed of the

car coming towards her, so she got someone from a driving school to take her for a

lesson and it was quite helpful” (Female, 72)

“That one I had with the NRMA, that only cost me about $75 and they’re

absolutely worth every penny. What he – the information and the feedback he gave

me and the feeling I had when I was doing it” (Female, 71)

5.8 DISCUSSION

This study used the PAPM as a framework for understanding older drivers’

transition from a state of unawareness about declines in their driving abilities to

adopting self-regulatory driving behaviours. Overall, participants were conscious of

the fact that driving abilities change with age, despite not being personally engaged

or aware of the effect ageing might have had on their own abilities. It also seemed

that some older drivers engage in what appears to be self-regulatory driving

behaviour, such as driving less, but for reasons other than compensating for age-

related declines. As suggested by previous studies (Ball et al., 1998; Blanchard &

Myers, 2010) , it appeared that changes in their lifestyle (such as retirement,

household composition, relocation) played a major role in the changes in their

driving patterns. Similar to previous research on older drivers, the most challenging

driving situations identified by the participants were night time driving (Ball et al.,

1998; Charlton, Oxley, Fildes, Oxley, & Newstead, 2003) and neck turning (Staplin,

Gish, Decina, Lococo, & McKnight, 1998a). Building upon previous research and

the findings of the current study, we have developed an initial model of driving self-

regulation among older drivers (Figure 5.2). It can be seen that Stage 1 of the PAPM

(unawareness that driving may change with age) has been omitted and that the

additional construct of insight has been inserted, while actual capacity to drive safely


(with its cognitive, physical and vision aspects) has been separated from the stages.

It is important to note that this model shares a lot of similarity with Rudman et al.’s

(2006) model of driving comfort. However, our model is consistent with the PAPM

in that it identifies awareness and insight into declining ability as the first step

towards self-monitoring and self-regulatory driving behaviours. Rudman et al.’s

model suggests that driving comfort influenced by a number of interpersonal,

intrapersonal, and environmental factors acts as a key determinant of self-regulation

(Rudman, Friedland, Chipman, & Sciortino, 2006). If older drivers avoid certain

driving situations because they feel uncomfortable and without being aware of

possible declines in their abilities, then their self-regulatory behaviour could be seen

as an automatic process to minimise the mental load associated with the functional

declines brought by ageing rather than enhance their safety (De Raedt & Ponjaert-

Kristoffersen, 2000b). Their self-regulation of driving may be a response to the

discomfort they experience in challenging driving conditions rather than intentional

monitoring of their driving ability (Meng & Siren, 2012). It is interesting that even

though some participants in our study noted that they encountered certain difficulties

and felt discomfort in some driving situations (such as night time driving or driving

in unfamiliar places) they attributed this discomfort to external reasons (i.e. glare

from other cars’ headlights on their glasses, changes in the road systems) and did not

increase their awareness about possible declines in their driving abilities. If

participants’ discomfort was indeed caused by factors unrelated to declines in their

driving ability, it may have led to unnecessary driving restrictions (Meng & Siren,

2012). To be effective, self-regulation should result in decreased exposure to

challenging situations and conditions. Therefore, drivers need to be conscious and

aware of deficits in their driving abilities and how they can compromise their safety.

Furthermore, self-imposed restrictions on driving due to lack of confidence can be

worrying (Moták et al., 2014) as highlighted by a recent study which found that

drivers who are not confident or moderately confident of being a safe driver are up to

1.94 times more likely to be involved in a crash than drivers who are very confident

of being safe drivers (Oxley et al., 2010).


Figure 5.2: Proposed theoretical model of stage-based driving change involving feedback and self-

regulation

For people to move from stage 2 to stage 3, they need to perceive the hazard

or precaution to be of personal relevance to them which requires people to have

insight into the impact of age-related declines on their driving ability. As suggested

by (Weinstein et al., 2008) persuading people to think about an issue can be

accomplished by personally experiencing the hazard (i.e. being involved in a crash)

and/or communications from significant others (i.e. feedback from family, friends, or

health professionals). Previous research has shown that an individual’s perceived

susceptibility of being involved in a crash can be an important factor in stopping

driving (Lafont, Laumon, Helmer, Dartigues, & Fabrigoule, 2008). However, some

studies have indicated that history of crashes was not a major influence in the older

adult’s decision to stop driving (Dellinger et al., 2001; Persson, 1993) which is

consistent with our findings. Still, further research is needed to determine whether

the severity of the crash, the recency of the crash, and the perception of being at fault

might have an impact on the individual decision to modify or stop driving. Providing

feedback regarding age-related declines and their impact on older adults’ driving

performance can lead to appropriate adjustments in their driving behaviours

(Ackerman et al., 2011). In a study conducted by Holland and Rabbitt (1992), two

thirds of participants reported making compensatory changes in their driving


behaviours in response to feedback about their sensory abilities. Eby et al. (2003)

reported that 14% of older adults, who completed a workbook which raised issues

regarding health, cognition, vision, and driving behaviour, discovered overlooked

changes in their abilities, with 25% reporting their intention to adjust their driving

behaviour accordingly. Older drivers can receive feedback from various sources.

The content, timing, and effectiveness of such feedback, however, may vary. It

appeared that participants are open to receiving feedback from their doctor which is

consistent with previous studies (Coughlin et al., 2004). However, physicians have

reported that there are barriers toward discussing the issue of driving cessation with

their patients such as unawareness about reporting requirements, negative reactions

from their patients (Betz et al., 2013), and lack of confidence and skill (Marshall,

Demmings, Woolnough, Salim, & Man-Son-Hing, 2012).

Furthermore, health literacy related to driving safety can increase older

adult’s awareness of the effects of age-related declines on their driving ability ( Eby

et al., 2003; Owsley et al., 2003) and might have an influence on the self-regulation

of driving behaviours in older adults (Sargent-Cox et al., 2011).

There are number of factors identified by Weinstein et al. (2008) that can

determine people’s transition from stage 3 to stage 5 which we have included in our

model. While we have not explored all of these factors in our study, we explored

participants’ beliefs and expectations of their driving future. It appeared that some

participants drew their expectations from other older people’s experiences which for

them meant driving less and in local areas. In addition, participants were aware of the

importance of driving in maintaining their independence and quality of life as they

have seen with other older people who stopped driving. It seemed that participants

were looking forward to continue driving for longer as more and more people are

driving in their 90s now. We also explored the pros and cons of driving among

participants. The results also suggest that driving is vital to participants’ identity and

well-being and not just a mean of getting around. Consistent with previous studies,

participants viewed driving to be the key to their independence and the principal

form of their transportation (Rakotonirainy & Steinhardt, 2009). It enabled them to

stay connected in their community (Eisenhandler, 1990) and provided them with

feelings of enjoyment (Coughlin, 2001). There were few negative aspects associated

with driving among participants which were mainly related to external factors such


as other drivers’ behaviours and constant changes in road systems. Interestingly, it

appeared that loss of confidence or comfort is an important determinant in the

decision-making process among some participants. Decreased confidence among

older adults has been identified as an important factor to giving up driving

(Ackerman et al., 2011; Meng & Siren, 2012; Ross, Dodson, Edwards, Ackerman, &

Ball, 2012). Two studies that asked older adults to rate their confidence level in

several driving conditions found that confidence was significantly related to self-

reported avoidance of difficult driving situations (Baldock et al., 2006a; Marottoli &

Richardson, 1998). Parker et al. (2001) also found that drivers with higher ratings of

nervousness reported more driving problems, lower mileage and less frequent driving

(Parker, MacDonald, Sutcliffe, & Rabbitt, 2001)

Having decided to modify or stop their driving, older adults need to start

dealing with barriers associated with giving up their driving. In our study, we have

identified some barriers and facilitators that can impact older adults’ decision to

modify or stop driving. The issues and problems with alternative transport raised in

this study were consistent with previous literature. The availability of other transport

options (Coughlin, 2001) and the cost of public transport (Corpuz, 2007) have been

identified as an important factor in the decision to give up driving among older

adults. Older drivers often view public transportation to be inaccessible, expensive,

inconvenient, unsafe, and unreliable which may affect their decisions regarding their

driving behaviours (Allan & McGee, 2003; Gardezi et al., 2006). Older adults often

view taxis as an expensive form of transportation and report concern over their

personal safety (Oxley et al., 2003). On the other hand, buses and trains are viewed

to be inconvenient and inaccessible due to a number of factors such as difficulty

getting on and out of the bus, having to walk to and from stops, and lack of

experience with public transport options (Oxley et al., 2003). An interesting solution

provided by Musselwhite & Shergold (2013) emphasizes the need to promote the use

of alternative modes of transport throughout life or at least from a much younger age.

This gradual introduction of alternative transport options might help eliminate the

psychological barriers associated with their use (Musselwhite & Shergold, 2013). It

appeared also that household composition is an important factor in the decision-

making process. Having family relying on their driving or living alone, could make

it difficult for some older adults to give up driving. There are inconsistent findings


among the literature in regards to living arrangements and self-regulation. While

some studies have reported that those who were not the principal driver of the

household were more likely to adopt self-regulation (Charlton et al., 2006; Donorfio,

D'Ambrosio, Coughlin, & Mohyde, 2009) other studies have reported that living

conditions have no impact on adoption of self-regulation (Ragland, Satariano, &

MacLeod, 2004) and those who are living alone are more likely to self-regulate than

those who are living with a spouse (Braitman & McCartt, 2008). The finding also

indicates that technology could play an important in prolonging older drivers’ safe

mobility by compensating for limitations in their driving ability. For example, a

blind spot detection and a lane change assist system can compensate for existing

motor and visual limitations (difficulty in turning head and reduced peripheral

vision) and assist them in merging and lane changes. While most participants

viewed such in-vehicle systems positively, there were number of barriers identified

in this study to the adoption of technology among older drivers (e.g. complexity,

safety and reliance issues, and affordability). Emerging studies suggest that in-

vehicle technology can assist older drivers by augmenting their driving ability

(Coughlin, 2005; Guo, Brennan, Edwards, & Blythe, 2012). It thus carries the

promise of allowing older adults to drive for longer without compromising their

safety (Rakotonirainy & Steinhardt, 2009). However, these technologies should be

centred around older adults’ needs and opinions (Musselwhite & Haddad, 2008).

Another important issue raised in this study is the way older adults cope with

driving cessation. Some older adults are able to cope well with the challenges of

later life than others (Hamarat, Thompson, Steele, Matheny, & Simons, 2002), an

aspect essential to successful ageing (Fiksenbaum, Greenglass, & Eaton, 2006).

Planning to stop driving could be difficult, partly because of what driving means to a

person’s identity and well-being, but also because of the uncertainty surrounding the

issue in terms of when, why, and how one would or should give up driving. Planning

can make it easier for people to come to terms with giving up driving as it gives them

a sense of control over the decision making process (Musselwhite & Shergold,

2013). Coping with driving cessation has mainly been viewed as reactive though it

can also involve a proactive approach. The available interventions mainly assist

older adults in reacting effectively to cessation of driving. However, it may be

equally important to assist older adults in coping proactively with giving up driving.


A recent study conducted by Musselwhite & Shergold (2013) which followed 21

individuals over a period of 10 months through the process of driving cessation

revealed that people who plan their driving cessation ahead are more likely to have a

better quality of life after stopping driving. Further research is needed to explore the

possibility of designing an intervention that can help older adults take steps toward

this planning process, similar to those programs that assist with major life transitions

(e.g. retirement). Furthermore, we need to raise people’s awareness that self-

regulatory behaviours are not solely linked to health deterioration. Older people can

suffer from subtle and deceptive changes in their abilities (decreased reaction time,

joint stiffness) that can affect their driving behaviour.

5.9 LIMITATIONS

The study participants were volunteers, of good health, and leading an active

lifestyle. The findings may have differed for participants with poorer health and a

less active lifestyle. Furthermore, the majority of participants resided in the

Sunshine Coast area which is different from urban locations such as Brisbane

particularly in terms of a relative lack of public transportation options and a high

proportion of retirees in the population. The qualitative nature of the study meant

that participants’ responses could be subject to social desirability, although as the

quotes demonstrate the comments were wide-ranging and participants reported

behaviours that were not necessarily desirable. In addition, due to the nature of the

study, the results are not generalizable to all older drivers and do not permit

statistical inference. Our aim was to gain in-depth data about older drivers’

perceptions and opinions about the changes in their driving behaviours over time and

it was not the aim of this study to collect data that are generalizable. Nevertheless,

the exploratory nature of this study allowed us to gain significant insight into the

issue being studied and can therefore help define specific research questions that

should be tested with quantitative data from questionnaire surveys.

5.10 CONCLUSION

This study explored the process of self-regulation and driving cessation

among older drivers using the PAPM as a framework. It also investigated older

adults’ perceptions and opinions about receiving feedback in regards to their driving

abilities. The findings from this study suggest that further elaboration of the PAPM


is needed to take into account the role of insight and feedback on the process of self-

regulation among older drivers. Since the driving cessation process occurs over

time, it would be beneficial to conduct a study that follows a larger sample through

the decision-making process.

Acknowledgment

The Australian Postgraduate Award Scheme provided funds for the PhD

research program of the first author. We also gratefully thank Amy Williamson from

the Centre for Accident Research and Road Safety-Queensland for assisting in

conducting the focus group sessions.


Chapter 6: Examination of the Precaution Adoption Process Model in understanding older drivers’ behaviour: an explanatory study (Study 2, Phase 1)


This chapter comprises Paper 2 as taken from:

Hassan, H., King, M., & Watt, K. (2017). Examination of the Precaution Adoption

Process Model in understanding older drivers’ behaviour: an explanatory study.

Transportation Research Part F, 46(A):111-123.












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------------------------- ----------------------------------- ------------

Name Signature Date

Examination of the Precaution Adoption Process Model in understanding older

drivers’ behaviour: an explanatory study


Heidy Hassan a, Mark King b, Kerrianne Watt c

a The Centre for Accident Research and Road Safety – Queensland (CARRS-Q), GPO Box 2434, Brisbane, Queensland, Australia. Corresponding author. Tel: +61731387727. Email: [email protected] b The Centre for Accident Research and Road Safety – Queensland (CARRS-Q), GPO Box 2434, Brisbane, Queensland, Australia c School of Public Health, Tropical Medicine and Rehabilitation Sciences- James Cook University, Townsville, Queensland, Australia

6.3 ABSTRACT

Self-regulation of driving has been proposed as an effective strategy to keep

older adults driving safely for longer. Little is known of what influence older adults’

decision to adopt self-regulatory driving behaviours. Hassan and colleagues (2015)

developed an initial model of self-regulation using the Precaution Adoption Process

Model (PAPM) as a theoretical framework. The present study aims to build on the

previous research by investigating whether a sample of older drivers can accurately

be assigned to the PAPM stages of change. Further, the study aims to identify the

psychosocial and environmental factors associated with different stages of the PAPM

and those that predict the decision to adopt self-regulatory behaviour. Logistic

regression analysis indicated that self-rated driving confidence, family feedback,

self-rated quality of driving and driving relinquishment expectation were significant

predictors of PAPM stages. Findings from this research have practical and theoretical

applications for improving our understanding of the self-regulatory behaviours of

older drivers.

Keywords

Awareness; Behaviour; Older drivers; Perception; PAPM; Self-regulation


6.4 INTRODUCTION

There has been a growing interest in understanding the risk factors for motor

vehicle crashes among older adults, given the ageing population and the predicted

increase in the number of older drivers (King, Soole, Watson, & Schramm, 2011).

Driving provides people with a sense of independence and freedom which improves

their quality of life (Liddle et al., 2014). Stopping driving has been associated with a

large number of negative outcomes such as decreased out-of-home activities,

increased dependency, and increased depression (Fonda et al., 2001; Marottoli et al.,

2000).

However, ageing is often accompanied by declines in the sensory, cognitive

and motor abilities considered necessary for safe driving (Anstey et al., 2005). If

unable to compensate for these changes, older drivers may put themselves and others

at risk (Freund et al., 2005; Marottoli & Richardson, 1998). In addition, due to their

increased fragility, older drivers are overrepresented in serious and fatal crashes (Li

et al., 2003).

Previous studies have shown that some older adults modify their driving (e.g.

driving reduction and/or driving restriction) in response to declines in their abilities,

a process known as self-regulation (Hassan, King, & Watt, 2015). While often

viewed as an effective strategy to maintain older adults’ safe mobility, the process of

self-regulation is still not completely understood, particularly in terms of the factors

that influence older drivers’ decision to restrict and/or reduce their driving. The

majority of previous research has focused on examining the association between self-

regulation and specific impairments and medical conditions among older adults

(Rudman et al., 2006). However, recent findings that younger drivers also avoid

some driving situations (Naumann et al., 2011) suggest that driving avoidance can be

the result of factors other than declining abilities. In fact, up until now, it is still

unclear whether older drivers adopt self-regulatory behaviour to compensate for their

age-related declines or whether it is simply a lifestyle choice (Siren & Kjær, 2011).

In addition, the success of self-regulation in terms of maintaining older drivers’ safe

mobility depends largely on their awareness of limitations in their driving abilities,

rather than their actual abilities (Anstey et al., 2005). Therefore, a strong emphasis

has been placed on identifying the impact of self-awareness on self-regulation among

older drivers, and recently growing attention has been directed towards


understanding the psychosocial factors that affect the self-regulatory driving

behaviours. However, the inconsistencies in the way drivers’ perceptions are

measured and defined, make it difficult to compare the findings (Blanchard & Myers,

2010).

Given the large number of factors influencing older drivers’ behaviour, it is

essential that research in this area is well grounded, both theoretically and

practically. Theories and models of driver behaviour can help us describe, explain,

predict and change behaviours through the development of appropriate intervention

programs (Crosby & Noar, 2011). The driving cessation process can be

conceptualised as occurring in stages (Kostyniuk et al., 1998). Interventions for

older drivers should therefore be customised, based on the individual (the baseline

stage and the personal, social, and environmental circumstances) and the anticipated

outcome (increased awareness, enhanced self-monitoring, adoption of self-

regulation, or planning cessation), and be sufficiently flexible to move individuals

through the stages of change towards adoption of safe driving behaviour (Tuokko,

Jouk, et al., 2014). However, there has been little development of stage-based

theories applied to driving self-regulation, and hence a lack of research on

theoretically-informed interventions that facilitate older drivers’ planning for future

self-regulation and even driving (Hassan et al., 2015).

Hassan et al. (2015) examined the applicability of the stage-based Precaution

Adoption Process Model (PAPM) in understanding older adults’ self-regulatory

driving behaviour. Building upon the relevant literature and on findings from a

series of qualitative focus groups among 27 Australian older drivers, the authors

developed a preliminary model of driving self-regulation among older drivers

(Figure 6.1). It can be seen that Stage 1 of the PAPM (unaware about the issue) has

been omitted as previous studies clearly demonstrate that older drivers are generally

aware about the impact of medical or functional impairments on driving abilities

(Sargent-Cox et al., 2011), however, they sometimes lack insight into their own

driving ability and are therefore not receptive towards adoption of self-regulation.

The model identifies self-awareness and insight into declining ability as the

first step towards self-monitoring and self-regulatory driving behaviours. It

incorporates both personal and environmental factors that have been found to impact


older adults’ driving behaviours and delineates suggested strategies to help people

move through stages.

Figure 6.1: Preliminary theoretical model of stage-based driving change involving feedback and self-regulation (Hassan et al., 2015)

The present study aims to build on the previous research by investigating

whether a sample of older drivers can accurately be assigned to the stages of the

PAPM. Further, the study aims to identify the psychosocial and environmental

factors associated with different stages of the PAPM and those that predict the

decision to adopt self-regulatory behaviour which may be worthy for further

investigation. However, predictors of stage transitions can only be identified through

prospective longitudinal research (Weinstein & Sandmand, 2002).

Specifically, this study will answer the following questions:


1. To what extent are the PAPM stages observed in our study

population?

2. What are the psychosocial and environmental factors

associated with stages of the PAPM?

3. What are the differences between those who have adopted

self-regulatory driving behaviours and those who did not think about

regulating their driving or resisted changing?

6.5 METHODS

Participants and recruitment

A total of 247 Australian drivers took part in this cross-sectional study. This

study took place in the Brisbane and Sunshine Coast areas of the state of Queensland,

Australia. In 2015, the estimated resident population of Queensland was 4.8 million

and the proportion of those aged 65 years and over in Queensland has increased by

4% from June 2014 to June 2015 (ABS, 2015). In 2011, females outnumbered males

in the 75 years and above age groups (ABS, 2011) with around 33.8% of women

aged 65 years and over living alone compared to 18.4% of older men (Australian

Bureau of Statistics, 2011). The licensing authority is Queensland Transport and

Main Roads and drivers aged 75 years and over are required to carry a valid medical

certificate obtained from their doctor. Participants were recruited through various

recruitment strategies to ensure sample variability such as flyers posted and

distributed in seniors’ clubs, geriatric clinics, and local shopping centres,

advertisements in local newspapers and through social media. A web-based version

of the questionnaire was also developed to gain access to a wider range of older

drivers. Eligible participants were current drivers aged 70 years and older. The

study was conducted between May 2014 and October 2014. Participants completed

the questionnaire online or in a paper-based form with a paid return envelope to the

principal researcher. Both questionnaires included an information sheet describing


consent to participate. All participants received the chance to enter a draw to win

one of ten $50 shopping vouchers. All procedures were approved by the Human

Research Ethics Committee of Queensland University of Technology.


Materials

A questionnaire was designed to collect information on the socio-

demographics (age, gender, education, employment, etc.), self-rated health, crash

history, driving experience, current driving patterns, driving perceptions, feedback

about driving and transport options of older drivers. In addition, participants’ driving

reduction was measured by asking participants to rate the overall amount of their

driving compared to ten years ago, on a 4-point scale from “much less” to “more”.

Participants’ self-restriction and avoidance behaviour was measured by asking

participants to rate the extent to which they would avoid driving under 18 various

challenging driving conditions (e.g. driving at night-time, driving alone, driving on

high traffic roads, etc.) on a five point Likert type scale from “not at all” (0) to

“avoid completely” (4). These situations have been reported consistently in previous

studies (Sullivan, Smith, Horswill, & Lurie-Beck, 2011) and were considered to be

relevant to our study population (i.e. we did not include driving in snow even though

it has been reported before because there is no snow in Queensland). A driving

restriction score was calculated based on the average score of responses to the 18

items with higher scores indicating increased avoidance.

Outcome variable

Participants were classified into stages of the PAPM based on their responses

using an algorithm that was developed along similar lines to the one used by

Weinstein and Sandman (2002). We omitted stage 1 (general unawareness that

driving may change with age) because people are generally aware of the problems

associated with ageing and driving through the media. We also omitted stage 7

(maintenance) as we interpreted it as driving cessation and we did not include former

drivers in our sample. We asked participants to indicate which of the statements

presented in Table 6.1 better describe them. Based on their answers, participants

could then be categorised into stages of the PAPM (stage 2 to stage 6).

Table 6.1: Precaution Adoption Process Model: Stage Classification Algorithm as

applied to self-regulatory driving behaviours among older adults (Adapted from

Weinstein & Sandmand, 2002) PAPM stage Algorithm

Stage 2

Unengaged

Some other older drivers need to change their driving, but I believe that I

am a safe driver and have never thought about the need to change my


driving

Stage 3

Undecided

I am at the point where I am not sure if I should start thinking about ways

to avoid certain driving situation or reduce my driving

Stage 4

Resisting action Avoiding certain driving situations would be pointless to me

Stage 5

Planning to act I am planning to avoid certain driving situations and reducing my driving

Stage 6

Self-regulating

I have just recently started to avoid challenging driving situations or drive

less

Independent variables

Socio-demographics, self-rated health and driving experience

The questionnaire collected data about participants’ demographics.

Participants’ self-rated health was assessed by a single question asking respondents

to rate their health as “very poor”, “poor”, “fair”, “very good”, and “excellent”.

Driving experience was measured using two questions, the length of possession of an

open driving license and annual kilometres driven.

Feedback

Participants were also asked whether they received feedback about their

driving from their doctor, family, or friends.

Alternative transport, living conditions and life-goal changes

Data about participants’ use of alternative transport options and barriers

towards use were measured. Participants’ life goal decisions (e.g. moving to a senior

home, moving closer to public transport, or moving closer to common destinations),

in-vehicle technology use, living conditions and whether they were the principal

driver were also assessed.

Psychosocial variables

Participants’ driving confidence was measured by a single question

“compared to ten years ago, do you still feel confident that you can safely drive to

places you need to go” with answers ranging from “much less”, “a little less”, “the

same”, and “more”. For the purpose of analysis, participants were grouped into two

categories, reduced confidence (much less, a little less), or not reduced (the same,

more).


Participants’ overall self-rated quality of driving was measured by a single

question “How would you rate the quality of your driving” with answers ranging

from “excellent”, “good”, “average”, “fair”, and “poor”.

Perception of crash risk was measured using three different questions: “how

likely is it for you to have a car crash compared to other people your age”, “how

likely is it for you to have a car crash compared to yourself ten years ago”, and “how

likely is it for you to be injured if you are involved in a car crash” with answers

ranging from “extremely likely”, “somewhat likely”, and “not at all likely”.

Regulatory self-efficacy was measured by asking participants to rate how

easy it would be for them to avoid driving in the 18 challenging driving situations,

similar to the items used for assessing self-regulation of driving by avoidance, on a

three-point scale ranging from very hard (0) to not hard at all (2). An index was

calculated based on the average score of the responses to the 18 items.

The perceived driving ability scale (PDA) is a previously validated 15-item

scale (MacDonald, Myers, & Blanchard, 2008) used to measure participants’ current

perceived driving abilities (e.g., to see road signs at a distance, to see vehicles

coming up alongside, to make an over the shoulder check) along a 4-point scale

(‘‘poor’’, ‘‘fair’’, ‘‘good’’, ‘‘very good”). A mean scale score was computed with

higher scores indicating more positive perceptions.

A driving stress scale similar to the one used by Hakamies-Blomqvist

(1994a), was used to measure participants’ experienced stress in a number of driving

situations on a 4 point scale ranging from 0 (heavy stress) to 3 (no stress) and a total

“Driving Stress” score was calculated (Hakamies-Blomqvist, 1994a)

A driving relinquishment scale was developed to assess participants’ views

about the importance of driving and barriers toward giving up driving and was

measured by asking participants to indicate their agreement with eight statements

about the importance of driving and barriers to giving up driving (e.g. giving up

driving will simplify my life, giving up driving is not possible because of my

lifestyle). A mean scale score was computed with higher scores indicating a more

positive attitude towards giving up driving.


6.6 ANALYSIS

Before conducting the analysis, data screening was performed to check for

missing data. Six cases were missing responses on the dependent variable and

therefore were excluded from the analysis. One case was missing responses on the

dependent variable and therefore was excluded from the analysis. One case was

missing a response on gender and was excluded. Another 16 cases were missing

responses on important psychosocial predictors and were excluded. A total of 222

cases were included in the final analyses. Missing values on psychosocial scales

were replaced with the series mean to compute the average score. Several variables

were collapsed into two or three alternatives in order to obtain meaningful categories

with respect to the purposes of the study. Descriptive statistics and bivariate analysis

were conducted for all five PAPM stages. However, for the purpose of the binomial

regression analysis and due to the small number of participants in some of the PAPM

stages, we decided to combine participants into two stages. The Pre-decision stage

(stage 2 and stage 3) includes participants who are still actively driving without any

changes to their driving. Participants in this stage may have never thought about the

need to change their driving (stage 2) or may start to wonder about the need to

modify their driving but have not made a decision yet (stage 3). The Decision stage

(stage 5 and stage 6) includes participants who are planning to or have started to

reduce and/or restrict their driving. Participants in stage 4 (resisting action) are

omitted from the regression analysis as they may be over-confident and resistant to

conventional interventions. Data were analysed in SPSS version 20.0 (IBM

Corporation, Armonk, NY).

6.7 RESULTS

Table 6.2: Sample characteristics (n=222) Mean age in years (SD) 75.5 (5.1) Gender Male Female

135 (60.8%) 87 (39.2%)

Principal driver Yes No

154 (69.4%) 68 (30.6%)

Education Primary school Secondary school Certificate Bachelor degree Postgraduate degree

13 (5.9%) 90 (40.5%) 55 (24.8%) 39 (17.6%) 25 (11.3%)

Dwelling A private home A retirement home or seniors’ complex

172 (77.5%) 50 (22.5%)

Living condition


Alone With spouse or partner Other

74 (33.3%) 136 (61.3%) 12 (5.4%)

Employment Yes No

66 (29.7%) 156 (70.3%)

Driving environment City Suburb Rural

28 (12.6%) 160 (72.1%) 15 (6.8%)

Trip length Less than 15 minutes 15-30 minutes More than 30 minutes

22 (9.9%) 125 (56.3%) 75 (33.8%)

Driving experience, years open driving license (mean and standard deviation) 55.4 (6.3%) Annual km driven Less than 5,000 km/year 5,000-10,000 km/year More than 10,000 km/year

52 (23.4%) 89 (40.1%) 81 (36.5%)

Driving reduction Much less A little less The same More

88 (39.6%) 70 (31.5%) 52 (23.4%) 12 (5.4%)

Self-rated health Excellent Very good Fair Poor

39 (17.6%) 132 (59.5%) 48 (21.6%) 3 (1.4%)

Self-rated quality of driving Excellent Good Average

53 (23.9%) 136 (61.3%) 33 (14.9%)

Perception of crash compared to ten years ago Somewhat likely Not likely

52 (23.4%) 170 (76.6%)

Perception of crash risk compared to others same age Extremely likely Somewhat likely Not likely

2 (0.9%) 37 (16.7%) 183 (82.4%)

Perception of risk of injury if involved in a crash Extremely likely Somewhat likely Not likely

12 (5.4%) 141 (63.5%) 69 (31.1%)

Driving confidence Much less A little less The same More

1 (0.5%) 51 (23%) 167 (75.2%) 3 (1.4%)

Sample characteristics

The sample ranged in age from 70 to 94 years (M= 75.5, SD ± 5.1), and

included 87 females (39.2 %) and 135 males (60.8%) (Table 6.2). By comparison,

official data shows that 46% of drivers aged 70 and above are female (Department of

Transport and Main Roads, 2015), which indicates that this sample has a lower

proportion of females. As noted in the Results section, gender was not a significant

factor in the regression analyses. Around 23% of participants rated their health to be

fair, 59.5% to be very good, and 17.6% to be excellent. The majority of participants

(71%) indicated that they have reduced their overall driving compared to ten years

ago. Responses to the questions on the most frequently avoided driving situations


are presented in Table 6.3. Driving at night in the rain was the most commonly

avoided situation (41%) followed by peak hour driving (35.6%), driving at night

(31.1%), and long distance driving (29.7%). The most stressful situation was

fatigued driving (65.8%) followed by driving on slippery roads (58.1%), driving in

unfamiliar areas (46.4%), and night-time driving (44.6%).

Table 6.3: Most avoided driving situations and reasons for avoidance Driving situation Avoidance (n, %) Reasons for avoidance

At night in the rain 91 (41%)

No need (n=31) Not comfortable (n=26)

Not confident (n=19) Other (n=5)

Peak hour

79 (35.6%)


Not confident (n=7) Other (n=4)

At night

69 (31.1%)


Not confident (n=14)Long distance driving

66 (29.7%)

No need (n=30)

Not comfortable (n=12) Not confident (n=6)

Other (n=3)Glare

49 (22.1%)

No need (n=11)

Not comfortable (n=16) Not confident (n=5)

Other (n=4)

Feedback

Participants preferred to receive feedback about their driving from their

doctor (30.6%), their partner (30.2%), their family members (14%), or from a person

of authority (12.2%). Around 82% of the participants indicated that a medical or a

vision problem could be a reason to stop or modify their driving with 75.5% of

participants indicating that they would stop driving if advised by their doctor. Only

five (2.3%) participants indicated that they had been involved in a crash in the past

year and only four (1.8%) had received suggestions to stop or modify their driving.

Around 44.6% of participants reported being involved in a conversation about their

driving with their doctor recently, followed by 43.2% with their family members, and

21.2% with a friend.

Alternative transport, living conditions and life-goal changes

Around 64% of participants in our study indicated that they rarely or never

use public transport. Most of these participants reported that they did not use public

transport because they did not need to (73.4%), while specific barriers were


inconvenience (40.6%), and having the nearest bus stop located too far from home

(25.9%). Around 92% of participants indicated that they rarely or never use taxis.

Again, most reported that this was because they did not need to (80.4%), while cost

was also identified as a specific barrier (43.6%). Finally, 50% of participants

indicated that they rarely or never rely on their family for transport. Around 25.2%

of participants have moved to a new place closer to their common destinations,

22.1% of participants have moved to a place with better transportation options, and

14.9% of participants have moved to a seniors’ home. Around 61.3% of participants

were living with a spouse/partner and 69.4% were the principal drivers in their

households.

Psychosocial variables

Psychometric properties of all scales used in this study are shown in Table

6.4, together with means and standard deviations.

Table 6.4: Descriptions of the psychometric properties of scales

Scale Number of

items Mean SD Scale actual range

Scale sample range

Cronbach’s alpha

Driving avoidance scale 18 0.7 0.6 0-4 (4 greatest avoidance) 0-2.8 0.91Self-regulatory scale 18 1.5 0.6 0-2 (2 higher self-efficacy) 0-2 0.96

PDA scale 15 2.3 0.5 0-3 (3 higher ratings) 0-3 0.93Driving stress scale 16 1.96 0.6 0-3 (3 less stress) 0-3 0.94

Driving relinquishment scale 8 1.3 0.5 0-3 (3 indicates more positive attitude) 0-2.6 0.8

PAPM stages

Participants’ PAPM stages for regulating driving are presented in Table 6.5.

Almost half of participants (46.8%) belonged to stage 2, 10.8% were categorised into

stage 3, 10.4% were in stage 4, 9.9% were in stage 5, and 22.1% of participants were

in stage 6.

Table 6.5: PAPM stages PAPM stage N (%)

Stage 2 (Unengaged) Stage 3 (Undecided)

Stage 4 (Resisting action) Stage 5 (Planning to act) Stage 6 (Self-regulating)

104 (46.8%) 24 (10.8%) 23 (10.4%) 22 (9.9%)

49 (22.1%)


Characteristics associated with PAPM stages

Several characteristics varied as a function of PAPM stages (Table 6.6;

associations which were not significant are not shown).

Table 6.6. Characteristics significantly associated with PAPM stage Variable Stage 2 Stage 3 Stage 4 Stage 5 Stage 6Annual km driven Less than 5,000 km/year 5,000-10,000 km/year More than 10,000 km/year

20 (19.2%) 46 (44.2%) 38 (36.5%)

6 (25%) 6 (25%)

12 (50%)

1 (4.3%) 9 (39.1%) 13 (56.5%)

9 (40.9%) 6 (27.3%) 7 (31.8%)

16 (32.7%) 22 (44.9%) 11 (22.4%)

Driving reduction Reduced Not reduced

64 (61.5%) 40 (38.5%)

18 (75%) 6 (25%)

14 (60.9%) 9 (39.1%)

18 (81.8%) 4 (18.2%)

44 (89.8%) 5 (10.2%)

Driving confidence Reduced Not reduced

10 (9.6%)

94 (90.4%)

8 (33.3%)

16 (66.7%)

2 (8.7%)

21 (91.3%)

7 (31.8%)

15 (68.2%)

25 (51%) 24 (49%)


39 (37.5%) 59 (56.7%)

6 (5.8%)

3 (12.5%)

13 (54.2%) 8 (33.3%)

7 (30.4%) 12 (52.2%) 4 (17.4%)

1 (4.5%)

18 (81.8%) 3 (13.6%)

3 (6.1%)

34 (69.4%) 12 (24.5%)

Perception of crash compared to self, ten years ago Not likely Somewhat likely

89 (85.6%) 15 (14.4%)

14 (58.3%) 10 (41.7%)

16 (69.6%) 7 (30.4%)

15 (68.2%) 7 (31.8%)

36 (73.5%) 13 (26.5%)

Public transport use Frequently or sometimes Never or rarely

29 (27.9%) 75 (72.1%)

8 (33.3%)

16 (66.7%)

8 (34.8%) 15 (65.2%)

14 (63.3%) 8 (36.4%)

20 (40.8%) 29 (59.2%)

Family discussion Yes No

32 (30.8%) 72 (69.2%)

11 (45.8%) 13 (54.2%)

8 (34.8%) 15 (65.2%)

14 (63.6%) 8 (36.4%)

31 (63.3%) 18 (36.7%)

Mean (±SD) Mean (±SD) Mean (±SD) Mean (±SD) Mean (±SD) Age 74.88(4.57) 74.33 (3.35) 74.04 (5.56) 77.68 (6.08) 77.20 (5.64)Driving experience 55.13 (5.88) 52 (6.79) 54.13 (4.65) 56.95 (6.28) 57.58 (6.74)Driving Avoidance Scale 0.49 (0.54) 0.59 (0.50) 0.39 (0.53) 1.04 (0.46) 1.07 (0.60)PDA scale 2.45 (0.45) 2.02(0.61) 2.41 (0.48) 1.98(0.43) 2.04 (0.44)Driving stress scale 2.11 (0.54) 1.78 (0.67) 2.21 (0.64) 1.77 (0.51) 1.69 (0.51)Driving relinquishment scale 1.17 (0.59) 1.33 (0.54) 1.08 (0.51) 1.54 (0.33) 1.41 (0.47)

Annual kilometres driven differed significantly between PAPM groups (χ2(8)

= 18.539, p = 0.018). Around 40.9% of participants in stage 5 (Planning to act) and

32.7% of participants in stage 6 (Self-regulating) reported driving less than 5,000

km/year compared to 4.3% of those in stage 4 (Resisting action) and 19.2% of those

in stage 2 (Unengaged). Reduction of driving compared to ten years ago differed

significantly between PAPM groups (χ2(4) = 15.564, p = 0.004). Around 81.8% of

participants in stage 5 (Planning to act) and 89.9% of participants in stage 6 (Self-

regulating) reported driving less compared to 60.9% of those in stage 4 (Resisting

action) and 61.5% of those in stage 2 (Unengaged). Self-rated confidence differed

significantly between PAPM groups (χ2(4) = 36.820, p <0.001). Around 31.8% of

participants in stage 5 (Planning to act), 33.3% of those in stage 3 (Undecided) and

51% of participants in stage 6 (Self-regulating) reported less confidence compared to

8.7% of those in stage 4 (Resisting action) and 9.6% of those in stage 2 (Unengaged).


Perception of the likelihood of being involved in a crash compared to ten years ago

differed significantly between PAPM groups (χ2(4) = 10.908, p = 0.028).

Interestingly, around 41.7% of participants in stage 3 (Undecided) reported greater

likelihood of being involved in a crash compared to 31.8% of participants in stage 5

(Planning to act), 30.4% of those in stage 4 (Resisting action), 26.5% of participants

in stage 6 (Self-regulating) and 14.4% of those in stage 2 (Unengaged). Public

transport use differed significantly between PAPM groups (χ2(4) = 10.887, p

=0.028). The majority of participants (63.6%) in stage 5 (Planning to act) reported

using public transport frequently/sometimes compared to 40.8% of those in stage 6

(Self-regulating), 34.8% of those in stage 4 (Resisting action), 33.3% of those in

stage 3 (Undecided) and 27.9% of those in stage 2 (Unengaged). Being involved in a

family discussion differed significantly between PAPM groups (χ2(4) = 19.061, p

<0.001). Around 63.6% of participants in stage 5 (Planning to act) and 63.3% of

participants in stage 6 (Self-regulating) reported having a family discussion

regarding their driving compared to 45.8% of those in stage 3 (Undecided), 34.8% of

those in stage 4 (Resisting action), and 30.8% of those in stage 2 (Unengaged).

Driving avoidance differed by PAPM stage (F(4,217)=13.69, p<0.001). Post

hoc tests revealed that the driving avoidance scale scores were higher for those in

stage 6 (Self-regulating) than in stage 4 (Resisting action) (0.682, 95% CI (0303 to

1.06), p <0.001), stage 3 (Undecided) (0.474, 95% CI (0.100 to 0.847), p=0.005), and

stage 2 (Unengaged) (0.581, 95% CI (0.322 to 0.841), p<0.001). Driving

relinquishment scale scores also varied by PAPM stage (F(4,217)= 3.86; p=0.005)

and the mean scale scores were statistically significantly lower for those in stage 2

(Unengaged) than those in stage 5 (Planning to act) (0.37, 95% CI (0.024 to 0.714), p

=0.030), and participants in stage 4 (Resisting action) scored significantly lower than

those in stage 5 (Planning to act) (0.46, 95% CI (0.02 to 0.89), p=0.035). Driving

Stress scores differed by PAPM stage (F(4,217) =7.02; p<0.001). Mean driving

stress scale score were higher for those in stage 6 (Self-regulating) compared to stage

2 (Unengaged) (0.411, 95% CI (0.145 to 0.676, p <0.001), and stage 4 (Resisting

action) (0.512, 95% CI (0.125 to 0.900), p <0.05). Mean PDA scores varied with

PAPM stage (F(4,217) =10.78; p<0.001) and were higher for those in stage 2

(Unengaged) compared to stage 3 (Undecided) (0.422, 95% CI (0.0127 to 0.718), p

<0.001), stage 5 (Planning to act) (0.474, 95% CI (0.169 to 0.781), p <0.001), and


stage 6 (Self-regulating) (0.407, 95% CI (0.181 to 0.633), p<0.001). In addition,

PDA scores were higher for those in stage 4 (Resisting action) compared to stage 3

(Undecided) (0.38, 95% CI (0.0062 to 0.767), p =0.004), stage 5 (Planning to act)

(0.43, 95% CI (0.0498 to 0.8276), p =0.018), and stage 6 (Self-regulating) (0.37,

95% CI (0.0413 to 0.7006), p=0.019).

Predictors of PAPM stages

Binary logistic regression modelling was used to determine the characteristics

of those who plan and adopt changes in their driving in comparison to those who

have decided not to change. Intercorrelations between predictor variables showed no

excessive multicollinearity. A hierarchical regression model was developed, where

we controlled for the effect of socio-demographics, driving experience, and self-rated

health as these variables have been commonly used within the older driver literature

as predictors of self-regulatory behaviours. Our analysis therefore focused on the

effect of modifiable psychosocial and environmental factors. Relevant independent

variables were included in the analysis with a p-value cut-off point of 0.25. Stepwise

logistic regression was conducted and variables were retained in the model at p<0.05.

Binomial regression analysis was conducted to compare the characteristics only of

those in the “Pre-decision” versus “Decision” phases. Table 6.7 presents the result of

the hierarchical logistic regression.

At step 1 of the regression analysis, socio-demographic, self-rated health, and

driving experience variables significantly predicted group membership (F (7,199)

=20.066, p<0.001) and accounted for 13.2% of the variance in decision to change

driving.

Table 6.7: Hierarchical regression analysis (n=199) Step Variable B Wald Exp(B) R2 R2 change F 1

Age Gender (reference Female) Annual Km/driven (reference >10,000 km/yr.) 5,001-10,000 km/yr. Less than 5000 km/yr. Self-rated health (reference Excellent) Very good

0.066 -0.139 0.268 0.734 0.534

2.680 0.160 0.510 3.026 1.235

1.069 0.870 1.307 2.083 1.706

0.132* 20.066*


Average Licensed year

0.972 0.034

3.354 1.006

2.643 1.035

2 Age Gender (reference Female) Annual Km/driven (reference >10,000 km/yr.) 5,001-10,000 km/yr. Less than 5000 km/yr. Self-rated health (reference Excellent) Very good Average Licensed year Self-rated quality of driving (reference excellent) Good Average Family discussion Yes Driving relinquishment scale Confidence Reduced

0.032 -1.22 0.419 0.797 0.076 0.310 0.076 1.879 2.141 1.151 1.020 1.065

0.438 0.090 0.954 2.384 0.017 0.238 3.575 9.445* 8.248* 8.623* 7.959* 6.841*

1.032 0.885 1.521 2.218 1.078 1.363 1.079 6.548* 8.505* 3.165* 2.772* 2.902*

0.412 0.28 71.014*

N=199, *p<0.05,

After controlling for the effect of socio-demographic factors and driving

experience, the psychosocial and environmental factors in the model accounted for

an extra 28% of the variability. In the final model, age, gender, self-rated health, and

driving experience were not significant predictors of group membership. The

significant predictors in the final model were self-rated driving confidence (β =

1.065, p <0.01), family feedback (β = 1.152, p <0.01), overall self-rated quality of

driving (β = 1.879 and 2.141, p <0.01) and driving relinquishment scale (β = 1.020, p

<0.01).

6.8 DISCUSSION

The purpose of this study was to further examine the applicability of the

Precaution Adoption Process Model in understanding self-regulatory driving

behaviours among older adults. A major concern regarding the older driver literature


is the scarcity of theoretically-based research. To the authors’ knowledge, few

studies have attempted to develop a model of self-regulatory driving behaviours

among older adults based on the stages of change theory.

The findings from this study indicate that older drivers can be categorised into

stages of the PAPM (Table 5) with the majority of participants (46.8%) in stage 2

(Unengaged). This may indicate that older drivers, while aware of the impact of

ageing on driving abilities, are not personally engaged. Only 22.1% of participants

belonged to stage 6 (Self-regulating) of the PAPM, despite over two thirds of

participants indicating they have reduced their driving compared to ten years ago.

Driving reduction could be a reflection of individual’s lifestyle preference and not

related to the declining abilities associated with ageing. This is partly supported by

the emerging evidence that, similar to older drivers, younger drivers also avoid some

driving situations (Blanchard & Myers, 2010; Naumann et al., 2011)

Of interest in this study are the characteristics associated with stages of PAPM.

It is postulated that awareness of risk and precaution effectiveness can influence

people’s movement between early stages of the PAPM (Weinstein & Sandmand,

2002). In our sample, participants in stage 2 (Unengaged) and stage 4 (Resisting

action) scored significantly higher on the PDA scale, which indicates higher self-

ratings of driving ability, compared to those in the other stages. The role of insight

and self-awareness in driving self-regulation has been identified by several authors

(Anstey et al., 2005). Whether older drivers are aware of their functional abilities or

not remains questionable. According to Ball et al. (1998) older drivers are aware of

their declining driving abilities and regulate their driving accordingly (Ball et al.,

1998). On the other hand, a number of studies have reported that older drivers tend to

overrate their driving abilities and performance. For instance, Holland and Rabbitt

(1992) revealed that drivers in their 70s rated their sensory abilities to be similar to

those in their 50s (Holland & Rabbitt, 1992). Freund et al. (2005) demonstrated a

significant association between higher self-rating of skills and increased risk of

driving difficulty (Freund et al., 2005).

The importance of driving is another significant factor that can impact older

drivers’ decision to regulate and/or stop driving. The majority of older drivers view

driving to be key to their independence and mobility (Adler & Rottunda, 2006;

Musselwhite & Haddad, 2010a). Described by some as a symbol of identity

(Eisenhandler, 1990), independence (Persson, 1993), and security (Bauer,


Kuskowski, et al., 2003), it is no wonder that the decision to stop driving is one of

the most difficult decisions that older adults have to make (Adler & Rottunda, 2006).

In our study, participants viewed driving to be extremely important. There was a

statistically significant association between PAPM stages and driving relinquishment

scale. Participants in stage 5 (Planning to act) reported significantly higher scores on

the driving relinquishment scale (which indicates more positive attitude towards

giving up driving) compared to those in stage 2 (Unengaged) and stage 4 (Resisting

action).

Previous studies point to the important role of confidence as a mediator

between declining abilities and self-regulation (Parker et al., 2001; Rudman et al.,

2006), with a large number of studies reporting significant association between self-

reported driving confidence/comfort and driving behaviour (Baldock et al., 2006a;

Marottoli & Richardson, 1998; Parker et al., 2001). Older drivers avoid situations

where they lack confidence (e.g. driving at night or at night in the rain) (Baldock et

al., 2006; Charlton et al., 2006). In our sample, confidence was significantly

associated with PAPM groups and higher scores (which indicate greater confidence)

were seen among those in stage 4 (Resisting action) and stage 2 (Unengaged).

However as pointed out by Motak et al. (2014) self-regulation as a result of lack of

confidence may be cause for concern (Moták et al., 2014) rather than an indication of

successful self-regulation. Therefore, the success of self-regulation in terms of

enhancing safety depends largely whether it is based on awareness and resulting

compensation, or lack of confidence. Self-regulation of driving as a response to the

discomfort older adults experience in stressful driving conditions rather than

intentional monitoring of their driving ability (Meng & Siren, 2012) may therefore

represent a failure of self-regulation rather than a success. These drivers may

attribute their feelings of discomfort to external reasons (i.e. glare from other cars’

headlights on their glasses, changes in the road systems) rather than possible declines

in their own driving abilities (Hassan et al., 2015). However, this effect of

discomfort can also have the opposite effect, with drivers indulging in unnecessary

driving restrictions (Meng & Siren, 2012). Drivers who impose unnecessary

restrictions on their driving due to lack of confidence may be able to safely drive in

these situations if they adopted other coping strategies such as pre-journey planning

or vehicle modifications (Gwyther & Holland, 2014).


Providing feedback regarding driving-related abilities may assist older adults in

making better and informed decisions regarding their driving (Holland & Rabbitt,

1992; Owsley et al., 2003). In our study, 44.6% of participants had discussed their

driving with their doctors, 43.2% with their family, and 21.2% with their friends.

Being involved in a family discussion about driving in the past year differed

significantly between PAPM stages. Qualitative research indicates that older drivers

prefer to receive feedback from someone who has direct knowledge and

understanding with their driving (Coughlin et al., 2004). Generally, family members

may be the first to express their concerns over an older adult’s driving ability

(Gillins, 1990). Feedback can also be given by healthcare professionals and many

older drivers will give up driving if advised to do so by their physician (Coughlin et

al., 2004; D'Ambrosio et al., 2008).

The later stages of the PAPM deal with barriers towards adoption of the

precaution. In our study, participants in stage 5 (Planning to act) were significantly

more likely to report more use of public transport. These findings are consistent with

previous research which indicates that the availability of other transport options

(Coughlin, 2001) and the cost of public transport (Corpuz, 2007) are important

factors in the decision to give up driving among older adults. Unfortunately, older

drivers often view public transportation to be inaccessible, expensive, inconvenient,

unsafe, and unreliable (Allan & McGee, 2003; Gardezi et al., 2006) and often view

taxis as an expensive form of transportation and report concerns over their personal

safety (Oxley et al., 2003). A number of psychological barriers (e.g. feeling they are

a burden, fear for safety) (Taylor & Tripodes, 2001) and geographical barriers (e.g.

availability of alternative transport or social support) (Musselwhite & Haddad,

2010b) can also affect the usage of these alternatives. Shifting to a new

transportation option requires active planning (Shergold et al., 2012) and people are

less keen to obtain information about alternative transport options (Nordfjærn et al.,

2014) especially if they do not consider they need such information (Shergold et al.,

2012).

Planning retiring from driving can make the experience less traumatic and

improve the outcomes through gradual preparation and feeling of control (Buys et

al., 2012; Liddle, Gustafsson, Bartlett, & McKenna, 2012). In line with previous

research conducted by Molnar et al. (2013), we investigated participants’ life goal


decisions and whether they impact their driving behaviour and decision making

process. Around 25.2% of participants indicated that they had moved to a new place

closer to their common destinations, 22.1% had moved to a place with better public

transport options, and 14.9% had moved to a seniors’ home. While not significantly

different among PAPM groups, moving to a seniors’ home was significantly

associated with driving reduction with 87.9% of those living in seniors’ homes

indicating that they have reduced their driving compared to 68.3% of those who are

still living at home. Unfortunately, previous research indicates that the vast majority

of older drivers do not plan the transition to a non-driving state, even those who

suffer from medical conditions that can impair their driving (Adler & Rottunda,

2006; Peel et al., 2002). Older drivers may be reluctant to engage in planning due to

their awareness of the potentially negative outcomes of driving cessation ( King et

al., 2011).

A hierarchical regression analysis was conducted after controlling for the effect

of age, gender, self-rated health, and driving experience to examine the impact of the

psychosocial and environmental factors on PAPM stages. Given the small sample

size, participants were grouped into two groups based on their decision to self-

regulate their driving. Those in stages 2 and 3 were collapsed into one group, the

Pre-decision group, while those in stages 5 and 6 were collapsed into the Decision

group. The significant predictors in the final model were self-rated driving

confidence, family feedback, overall self-rated quality of driving and driving

relinquishment scale. The cross-sectional nature of the study makes it impossible to

determine if these variables predict transitions between stages of PAPM. However,

the previous older drivers’ literature point out the role each of these variables plays

in the decision-making process among older drivers. It is therefore crucial to

investigate the role of these factors as predictors for PAPM stages transition by

conducting longitudinal studies that follow older drivers through stages of change.

It is also important to note that stage theories have been criticised for

oversimplifying complex human behaviour and imposing artificial stages (Littell &

Girvin, 2002). While uncommon, driving cessation can occur unexpectedly as a

result of sudden illness, involvement in a crash, or failing a driving test (Dellinger et

al., 2001). Driving cessation is usually more of a gradual and voluntary process

(Dellinger et al., 2001; Hakamies-Blomqvist & Wahlström, 1998) and there is


evidence that the driving cessation process may occur through stages (Hassan et al.,

2015; Kostyniuk et al., 1998; Kowalski et al., 2014). This suggests that older driver

interventions should be tailored to the specific needs of each individual (including

the stage they are at) and recognises that older adults should not be treated as a

homogenous group (Hassan et al., 2015). Further, the determinants of driving-

regulation are a mixture of environmental, psychological, and social factors.

Theorizing self-regulatory driving behaviour is therefore important to enhance our

understanding of this process. Stages of change theories can assist in providing a

generalized description and a means of planning interventions (Liddle et al., 2004).

The PAPM has been used previously to study adoption of behaviours related to

osteoporosis prevention (Mauck et al., 2002), disaster preparedness (Glik et al.,

2014), epilepsy (Elliott et al., 2007), colorectal cancer screening (Costanza et al.,

2005), fruit intake (de Vet et al., 2008), coping with premenstrual syndrome (Delara

et al., 2012), and home radon testing (Weinstein et al., 1998). In relation to driving,

the PAPM has been explored by Kostyniuk et al. (2000), however the adaptation of

the PAPM in their study was not fully described, and was based mostly on older

adults’ awareness of their declining abilities, i.e. it failed to recognize the influence

of other external and internal factors on the process of self-regulation (Kostyniuk et

al., 2000).

To the authors’ knowledge, this study is the first to attempt to examine the

association between psychosocial and environmental variables and PAPM stages of

change among older drivers. This study provides further support for the proposition

that self-regulatory driving behaviour among older drivers can be examined using the

PAPM. Further experimental research is planned to investigate the impact of

evaluative feedback on participants’ self-awareness of their driving ability and

subsequent stage transition. However, there is a need for a prospective study where

older drivers are followed through the stages of change as they occur, to better

determine which variables predict the adoption of self-regulatory driving behaviours

among older adults.

6.9 LIMITATIONS

The recruitment strategy may have attracted active and healthier drivers who

are more interested in driving and more safety-oriented. This may have resulted in

fewer participants in stage 4 (Resisting action). The findings are based on a small


sample of Brisbane and Sunshine Coast drivers and the extent to which the results

can be generalised to other Australian states is unclear. Cognitive functioning was

not assessed in this study. This is an important factor in the ability to self-regulate

driving. Very few participants reported that they were involved in a crash recently

which made it difficult to explore this variable. Self-report measures were used to

assess driving pattern and health status, and may be subject to recall bias. This study

also employed a cross-sectional design and without longitudinal studies that follow

older drivers through the process of self-regulation it will be difficult to conclude

which and how certain factors influence older drivers’ decision to change and/or stop

their driving. This study used a staging algorithm adopted from previous studies,

however, with limited validity and reliability. This may have resulted in participants

being misclassified into the wrong stages. Future studies should attempt to overcome

this limitation by employing reliable and valid tools for classification.

6.10 CONCLUSION

A theory-based understanding of the process of self-regulation among older

drivers will support the development of effective interventions to promote safe

driving or improve outcomes of driving cessation. By applying a stage-based

approach, the self-regulation process can be broken down into qualitatively different

categories that accommodate the heterogeneity of the older driver population. This

would allow interventions to be customised based on the individual’s specific need.

Successful self-regulation relies on accurate insight into one’s driving ability and the

PAPM identifies awareness and personal engagement as the initial step towards

behaviour change. Further, the PAPM differentiates between those who are not

engaged by the issue and those who are resistant to change. Older drivers who are

reluctant to modify their driving may benefit from interventions targeted towards

creating safer vehicles and safer road networks. Our study indicates that there are

significant differences among PAPM stages of change. Further, a number of

psychosocial variables significantly predicted the adoption of self-regulatory

behaviours among participants.

Acknowledgment


research program of the first author.


Chapter 7: Older adults’ self-regulatory driving behaviour: A latent class analysis (Study 2, Phase 2)


This chapter comprises Paper 3 as taken from: Hassan, H. & King, M. (Under

preparation). Older adults’ self-regulatory driving behaviour: A latent class analysis.














authorship


------------------------- ----------------------------------- ------------

Name Signature Date


Older adults’ self-regulatory driving behaviour: A latent class analysis

7.3 ABSTRACT

Self-regulation of driving has been proposed as an effective strategy to keep

older adults driving safely for longer. Little is known of what influence older adults’

decision to adopt self-regulatory driving behaviours. Previous studies have shown

that older drivers go through different stages towards adopting self-regulation.

Interventions that address factors relevant to each stage can therefore be more

effective than “one-size-fits-all” strategies. Hassan and colleagues (2015)

developed an initial model of self-regulation using the Precaution Adoption Process

Model (PAPM) as a theoretical framework. The present study aims to build on the

previous research by investigating whether there are distinct profiles of older adults

based on their mindsets towards adopting self-regulatory driving behaviour which

match those in the PAPM model. We used latent class analysis to identify driving

self-regulatory profiles of 222 older adults based on their driving perceptions,

importance of driving, and perceived barriers towards giving up driving. Latent class

analysis identified three classes of older drivers. Class 1 (n=104) consisted of those

who had the lowest levels of reported driving confidence, driving comfort, and

perceived driving abilities. They were least likely to agree that giving up driving

would restrict their mobility or independence. Class 2 (n=66) consisted of those who

had the highest levels of reported perceived driving ability. They were most likely to

agree that driving cessation would restrict their mobility and independence, and that

lifestyle factors were barriers to changing their driving. Class 3 (n= 52) consisted of

those who had low perceived driving abilities and were most likely to agree that they

would be letting other people down if they stop driving. The latent class analysis

categories differed in terms of the kinds of intervention that appear likely to address

them. It is recommended that interventions be customised to meet the need of each

class.

Keywords

Mobility, Precaution Adoption Process Model, Safety


7.4 INTRODUCTION

The proportion of older drivers in Australia is predicted to increase due to a

combination of population ageing and increased licensure of successive age cohort

(King & Scott-Parker, 2016). This in turn will present some major challenges in

terms of maintaining their safety and mobility. Driving is essential to older people’s

independence and well-being and driving cessation has been linked to many negative

outcomes (Liddle, Carlson, & McKenna, 2004). As people age, they start

experiencing declines in the sensory, motor, and cognitive abilities necessary for safe

driving (Anstey, Wood, Lord, & Walker, 2005). As a group, older adults are

relatively safe drivers, however due to their increased fragility, they are over-

represented in serious and fatal crashes (Li, Braver, & Chen, 2003). Considerable

attention has been directed towards strategies that can ensure road users’ safety

without compromising older adults’ mobility. Self-regulation of driving has been

promoted as an alternative positive approach to keep older adults driving safely for

longer (Lang, Parkes, & Medina, 2013 ).

Previous studies have identified several factors associated with self-regulation, still,

how these factors come together in the final decision remains unclear. As Molnar

and colleagues (2015) highlight “it is important to extend the current research by

trying to tease out the relationships between self-regulation and the factors for which

there is already considerable evidence” and there is a need “for a more

comprehensive, theoretically-informed, and uniform approach to investigating self-

regulation by older drivers”. Few studies have attempted to find a theoretical

framework to account for the process of self-regulation in older adults. The

challenge in developing a model of driving self-regulation results from the

heterogeneity of the older driver population in terms of their abilities, needs, and

resources. Previous studies have pointed out that older drivers go through different

stages of change towards modifying their driving and ultimately stopping driving

(Kostyniuk et al., 1998; Liddle et al, 2004). The stages of changes theories could be

useful in describing and providing a general understanding of change and planning

interventions (Liddle et al., 2004). This suggests that older driver interventions

might need to be tailored to the specific needs of each individual (including the stage

they are at) and would need to be customised to move individuals through the stages

of change towards adoption of safe driving behaviour. They would ideally be


developed by taking a strategic approach using both a theory of the change process

and existing evidence from previous attempts to achieve change. However, there has

been little development of stage-based theories applied to driving self-regulation, and

hence there is a lack of research on theoretically-informed interventions that facilitate

older drivers’ planning for future self-regulation and even driving cessation.

The literature suggests that self-awareness and insight into driving ability play a

major role in successful driving regulation among older drivers (Anstey et al., 2005).

Therefore, older drivers need to perceive their declining driving abilities as a threat

to their overall safety before they are interested in self-regulation. This situation is

suited to the application of the Precaution Adoption Process Model (PAPM) to the

self-regulatory behaviours of older drivers, which has been examined by Kostyniuk

et al. (2000). The PAPM describes how individuals move through stages of change

towards adoption of health protective behaviour (Weinstein & Sandmand, 2002).

The early stages of the PAPM are defined in terms of psychological states and

mindset of individuals (Weinstein & Sandmand, 2002). The later stages are mostly

governed by factors that can facilitate or hinder the adoption of the precaution.

Individuals progress through seven stages from lack of awareness to action:

unawareness (stage 1); awareness that there is an issue but a lack of personal

engagement with it (stage 2); engagement (“this applies to me”) but indecision (stage

3) about the need to act; either a decision not to act (stage 4) or a decision to act

(stage 5); if the latter, acting by taking the precaution (stage 6) (e.g. self-regulating);

and maintaining the behaviour (stage 7). Hassan et al. (2015) examined the

applicability of the PAPM in understanding older adults’ self-regulatory driving

behaviours (Hassan, King, & Watt, 2015). Subsequently, they applied these stages to

a survey sample of older drivers, demonstrating the utility of the approach. However,

the question remains whether older adults’ self-regulatory driving behaviour is a

reflection of the stages of change described by the PAPM. This study, therefore,

builds on the research reported in Hassan et al. (2017) by utilising a bottom-up

approach to profile older drivers based on their mindset towards adopting self-

regulatory driving behaviours using Latent Class Analysis. Latent Class Analysis

(LCA) is a person-centred approach commonly used to identify subgroups with

distinctive patterns. Unlike cluster analysis which identifies groups based on some


measure of similarity, LCA classifies objects according to their probabilities of the

values of all observed variables (Elliott, Jacobsohn, Winston, & Ginsburg, 2012).

Graver and colleagues (2008) states that “latent class regression analysis allows the

researcher to build, identify, and test a regression model that is relevant for each

latent, unobservable segment of the population. Specifically, latent class regression

analysis forms segments of subjects (employees, customers, suppliers) that possess

similar beta coefficients from multiple regression analysis. The technique is relevant

for both academic researchers and practitioners, and can be valuable to theoretical

development”. LCA has been used previously in the transport literature (De Oña,

López, Mujalli, & Calvo, 2013; Elliott et al., 2012) and with older drivers (Choi,

DiNitto, & Marti, 2015). A recent study in 2017 described three latent classes of

driving self-regulation among 729 older drivers based on their self-reported driving

frequency and avoidance behaviour (Bergen, West, Luo, Bird, et al., 2017).

The PAPM explain how people reach decisions to act and how they translate

that decision into actions. The early stages (from stage 1 to stage 5) describe the

decision-making process, while the late stages (stages 6 and 7) describe the acting

process. All the stages prior to action are defined in terms of mental states rather

than in terms of factors external to the person. Our study attempted to investigate

whether there are distinct profiles of older drivers based on their mindsets towards

self-regulating their driving behaviours rather than their actions which correspond to

the early stages of the PAPM (stages 1-5).

We hypothesised that there are three possible outcomes to the LCA

1. Our sample is homogenous and does not contain different groups of

driving behaviour.

2. Our sample is heterogeneous and contains subgroups of older drivers that

correspond with the PAPM stages of change.

3. Our sample is heterogeneous and contains subgroups of older drivers

that do not correspond to the PAPM stages of change.


7.5 METHOD

Participants and procedure

The detailed method for collection of the survey data on which this study is

based has been published previously (in press). Briefly, we recruited a total of 247

Australian drivers through various recruitment strategies to ensure sample variability.

Eligible participants were current drivers aged 70 years and older who resided in the

Brisbane and Sunshine Coast areas of Queensland, Australia. The study was

conducted between May 2014 and October 2014. Participants completed the

questionnaire online or in a paper-based form with a paid return envelope to the

principal researcher. Both questionnaires included an information sheet describing


consent to participate. All participants received the chance to enter a draw to win

one of ten $50 shopping vouchers. All procedures were approved by the Human

Research Ethics Committee of Queensland University of Technology.

Material

The questionnaire collected information on the socio-demographics (age,

gender, education, employment, etc.), self-rated health, crash history, driving

experience, current driving patterns, driving perceptions, driving feedback

experiences and transport options of older drivers.

Indicators of willingness to regulate and/or stop driving latent class membership

The selection of the latent class analysis indicators was guided by the PAPM

and the literature on older drivers’ safety. The PAPM offers a flexible framework

and the factors influencing stage transitions are not clearly defined. The early stages

of the PAPM reflect individuals’ mindsets towards adopting the change and are

affected by individuals’ perceptions and perceived barriers towards adopting the

change. Perceptions about one’s ability is a strong determinant to reduce and/or

restrict driving (Anstey et al., 2005). Numerous studies point to the significant

association between self-reported driving confidence/comfort and driving behaviour

(Blanchard & Myers, 2010). The importance of driving is another significant factor

that can impact older drivers’ decision to regulate and/or stop driving (Adler &

Rottunda, 2006; Musselwhite & Haddad, 2010a). In addition, perceived barriers


(e.g. maintenance of independence and lifestyle) can affect adoption of self-

regulation (Gwyther and Holland, 2012).

Assuming that these predictors comprise the most relevant factors for

explaining behaviour change, it should be possible to characterise individuals in

different mindsets. For instance, those in the early stages of the PAPM will have

lower perception of risk and greater perceived barriers to change.

Driving perception

Driving confidence was measured by a single question “compared to ten

years ago, do you still feel confident that you can safely drive to places you need to

go” with answers ranging through “much less”, “a little less”, “the same”, and

“more”. For analysis, participants were grouped into two categories, reduced

confidence (much less, a little less), or not reduced (the same, more). In addition,

participants’ self-reported driving stress was measured using a scale developed by

Hakamies-Blomqvist (1994a) that measures participants’ experienced stress in a

number of driving situations on a 4-point scale ranging from 0 (heavy stress) to 3 (no

stress) and a total “Driving Stress” score was calculated (Hakamies-Blomqvist,

1994a).

Perception of crash risk was measured using three different questions: “how

likely is it for you to have a car crash compared to other people your age”, “how

likely is it for you to have a car crash compared to yourself ten years ago”, and “how

likely is it for you to be injured if you are involved in a car crash” with answers

ranging from “extremely likely”, “somewhat likely”, and “not at all likely”.

The perceived driving ability scale (PDA), a previously validated 15-item

scale (MacDonald, Myers, & Blanchard, 2008), was used to measure participants’

current perceived driving abilities (e.g., to see road signs at a distance, to see vehicles

coming up alongside, to make an over the shoulder check) along a 4-point scale

(‘‘poor’’, ‘‘fair’’, ‘‘good’’, ‘‘very good”). A mean scale score was computed with

higher scores indicating more positive perceptions.

Importance of driving

Participants’ views about the importance of driving were measured by asking

participants to indicate their agreement with two statements (“giving up driving will

restrict my mobility” and “giving up driving will restrict my independence”) along a


5-point scale (“Strongly disagree”, “disagree”, “neither disagree or agree”, “agree”,

“Strongly agree”)

Barriers towards giving up driving

Participants’ views about the barriers toward giving up driving were measured

by asking participants to indicate their agreement with five statements (“giving up

driving will let other people down”, “changing my driving is not possible because of

my lifestyle”, “changing my driving is not possible because others rely on me”,

“changing my driving is not possible because public transportation is not available

for me”, and “changing my driving is not possible because I can’t rely on others”)

along a 5-point scale (“Strongly disagree”, “disagree”, “neither disagree or agree”,

“agree”, “Strongly agree”)

7.6 ANALYSIS


missing data. A total of 222 cases were included in the final analysis. Missing

values on psychosocial scales were replaced with the series mean to compute the

average score. Several variables were collapsed into two or three alternatives to

obtain meaningful categories with respect to the purposes of the study. Scales were

dichotomised on the median for ease of interpretation of the latent classes. We

performed LCA using MPlus Version 7.1. The number of latent classes was

determined based on the findings from several statistical fit indices: the Akaike

information criterion (AIC), the Bayesian information criterion (BIC), the sample-

size-adjusted BIC (SSABIC), the Vuong-Lo-Mendell-Rubin adjusted likelihood ratio

test (LMR), and the entropy values. Lower values on the AIC, BIC, and SSABIC

indicate better fitting models, with the BIC being the most reliable of these fit indices

(Nylund, Asparouhov, & Muthén, 2007) . Higher entropy values indicate clearer

classification (Ramaswamy, Desarbo, Reibstein, & Robinson, 1993).

Table 7.1: Sample characteristics (n=222) Mean age in years (SD) 75.5 (5.1) Gender Male Female

135 (60.8%) 87 (39.2%)

Principal driver


Yes No

154 (69.4%) 68 (30.6%)


13 (5.9%) 90 (40.5%) 55 (24.8%) 39 (17.6%) 25 (11.3%)

Dwelling A private home A retirement home or seniors’ complex

172 (77.5%) 50 (22.5%)

Living condition Alone With spouse or partner Other

74 (33.3%) 136 (61.3%) 12 (5.4%)

Employment Yes No

66 (29.7%) 156 (70.3%)

Driving environment City Suburb Rural

28 (12.6%) 160 (72.1%) 15 (6.8%)

Trip length Less than 15 minutes 15-30 minutes More than 30 minutes

22 (9.9%) 125 (56.3%) 75 (33.8%)

Driving experience, years open driving license (mean and standard deviation)

55.4 (6.3%)

Annual km driven Less than 5,000 km/year 5,000-10,000 km/year More than 10,000 km/year

52 (23.4%) 89 (40.1%) 81 (36.5%)

Driving reduction Much less A little less The same More

88 (39.6%) 70 (31.5%) 52 (23.4%) 12 (5.4%)

Self-rated health Excellent Very good Fair Poor

39 (17.6%) 132 (59.5%) 48 (21.6%) 3 (1.4%)


53 (23.9%) 136 (61.3%) 33 (14.9%)


52 (23.4%) 170 (76.6%)

Driving confidence Much less A little less The same More

1 (0.5%) 51 (23%) 167 (75.2%) 3 (1.4%)


7.7 RESULTS

Sample Characteristics

The sample ranged in age from 70 to 94 years (M= 75.5, SD ± 5.1), and

included 87 females (39.2 %) and 135 males (60.8%) (Table 7.1). Around 23% of

participants rated their health to be fair, 59.5% to be very good, and 17.6% to be

excellent.

Determination of number of classes

Latent class solutions containing 2 through 5 classes were fitted to the data.

Based on the LMR test value, the three-class solution was the best fitting model

(Table 7.2). Specifically, the LMRT value did not indicate that the four-class

solution was a better fit than the three-class solution, despite having lower values on

other fit indices. In addition, the addition of the fourth class did not add

substantively to the meaning of the latent classes and was formed of only a small

number of cases. Model fit should always be judged based on substantive meaning

(i.e., the classes should be distinct and meaningful) (Nylund et al., 2007).

Table 7.2. Model Fit Statistics

Number of classes 2 3 4 5 AIC 2718.747 2681.277 2648.596 2636.819BIC 2797.009 2800.371 2808.522 2837.577BIC adjusted 2724.120 2689.453 2659.575 2650.601Entropy 0.805 0.814 0.804 0.846 Vuong-Lo-Mendell-Rubin Likelihood ratio test

-1461.798 (p<0.0001)

-1336.374 (p<0.02)

-1305.639 (p=0.2774)

0.2947

Class indicators and interpretation of classes

The average latent class assignment probabilities for individuals assigned to

each class is presented in Table 7.3. Overall, values close to 1 indicate a high

precision or reliability of the classification; with values of 0.8 or larger indicating a

good class solution (Celeux & Soromenho, 1996). We obtained high class

assignment probabilities for the three classes (0.96, 0.89, 0.89). As shown in Table

7.3, participants in class 1 and class 3 were more likely to report lower ratings of

their driving abilities and higher ratings of driving stress compared to those in class

2. Participants in class 2 and class 3 were more likely to report greater barriers to

stopping driving compared to those in class 1. For those in class 3, letting others


down and having people relying on their driving appeared to be a greater barrier

compared to the other two classes.

Table 7.3: Item-response probabilities

Class homogeneity Class separation

Variable Class 1 N=104

Class 2 N=66

Class 3 N=52

Class 1 vs. 2

Class 1 vs. 3

Class 2 vs. 3

Stress (high) 0.7 0.1 0.6 0.04 0.64 15.8 PDA (poor) 0.7 0.05 0.7 0.02 0.9 45.39

Letting others down

0.3 0.8 1 9.65 1 1

Lifestyle is a barrier

0.2 0.8 0.8 21.98 21.13 0.96

Others rely on me

0.03 0.6 0.9 51.17 325.9 6.38

(Class homogeneity individuals within a given class are similar to each other with respect to item responses (above 0.7 or below 0.3) and class separation individuals across two classes are dissimilar with respect to item responses. (>5 or <0.2))

Class 1 N= 104

Class 2 N=66

Class 3 N=52

Confidence Reduced Not reduced

0.354 0.646

0.053 0.947

0.218 0.782

Perception compared to others Somewhat likely Not likely

0.205 0.795

0.000 1.000

0.332 0.668

Giving up driving will restrict my mobility Agree Disagree

0.737 0.263

0.922 0.078

0.935 0.065

Giving up driving will restrict my independence Agree Disagree

0.772 0.228

0.982 0.018

0.944 0.056

Giving up driving will let other people down Agree Disagree

0.312 0.688

0.814 0.186

1.000 0.000

Changing my driving is not possible because of my lifestyle Agree Disagree

0.216 0.784

0.858 0.142

0.853 0.147

Changing my driving is not possible because others rely on me Agree Disagree

0.032 0.968

0.627 0.373

0.915 0.085

Changing my driving is not possible because public transportation is not available Agree Disagree

0.217 0.783

0.376 0.624

0.608 0.392


Changing my driving is not possible as I can’t rely on others Agree Disagree

0.297 0.703

0.571 0.429

0.816 0.184

Stress High stress Low stress

0.738 0.262

0.104 0.896

0.646 0.354

PDA Low perception High perception

0.751 0.249

0.057 0.943

0.733 0.267

The LCA identified 3 classes; 104 of the participants were classified into

class 1, 66 were classified into class 2, and 52 were classified into class 3. Table 7.4

presents the characteristics of the classes where significant differences were found;

they related primarily to travel and driving patterns, and feelings regarding fitness to

drive. It can be seen there are distinct differences which are discussed further below.

Almost all participants of class 3 were principal drivers opposed to two third of

participants in class 1 and class 2. Participants in class 2 reported greater use of in-

vehicle technology and limited use of public transport compared to those in the other

two classes. They were also more likely to driver for greater distances and longer

durations. Participants in class 1 were more likely to report feeling unfit to drive

compared to the other two classes.

Table 7.4. Significant differences between latent classes

Class 1 Class 2 Class 3 Age (Mean, SD) 76.2 (5.2) 74 (3.5) 76.1 (6.3)Annual Km Less than 5,000 km/year 5,001 to 10,000 km/year More than 10,001 km/year

33 (31.7%) 41 (39.4%) 30 (28.8%)

7 (10.6%) 29 (43.9%) 30 (45.5%)

12 (23.1%) 19 (36.5%) 21 (40.4%)

Trip Length Less than 15 minutes 15-30 minutes More than 30 minutes

11 (10.6%) 58 (55.8%) 35 (33.7%)

1 (1.5%) 41 (62.1%) 24 (36.4%)

10 (19.2%) 26 (50%) 16 (30.8%)

In-vehicle technology use Yes No

47 (45.2%) 57 (54.8%)

48 (72.7%) 18 (27.3%)

29 (55.8%) 23 (44.2%)

Public Transport use Sometimes Never/Rarely

50 (48.1%) 54 (51.9%)

13 (19.7%) 53 (80.3%)

16 (30.8%) 36 (69.2%)


66 (63.5%) 38 (36.5%)

41 (62.1%) 25 (37.9%)

47 (90.4%) 5 (9.6%)

Motivation to change driving Feeling unfit to drive

76 (73.1%)

37 (56.1%)

28 (53.8%)

Avoid driving at night in the rain Avoid completely Very often

21 (20.2%) 14 (13.5%)

1 (1.5%) 3 (4.5%)

6 (11.5%) 9 (17.3%)


Reasonably often Not often Not at all

20 (19.2%) 26 (25%) 23 (22.1%)

6 (9.1%) 21 (31.8%) 35 (53%)

11 (21.2%) 13 (25%) 13 (25%)

Table 7.5. Frequencies of LCA classes for PAPM stages obtained by staging algorithm

Stages obtained by PAPM algorithm Latent Class 1 Latent Class 2 Latent Class 3

Stage 2 (unengaged) 33 43 28

Stage 3 (Undecided) 12 6 6

Stage 4 (Decided not to act) 8 11 4

Stage 5 (Decided to act) 19 0 3

Stage 6 (Acting) 32 6 11

Total 104 66 52

Table 7.5 demonstrates the frequencies of LCA classes for PAPM stages obtained by

the staging algorithm adopted from Weinstein et al. (2008) (χ2(8) = 37.596, p <

0.0001). The latent classes consisted mainly of participants in stage 2 the

unengaged, with the majority seen in class 2. Almost half of the participants in stage

5 and 6 of the PAPM belonged to class 1.

7.8 DISCUSSION

This study aimed to identify distinct self-regulatory driving profiles of older

drivers based on their mindset towards change. Using LCA, we identified three

unique classes. Individuals in class 1, which we have labelled as “willing to

change”, had high levels of stress and poor perception of their driving abilities.

Driving was still important in terms of their mobility and independence; however,

they identified fewer barriers in regard to changing their driving. This class

resembles stage 5 (decided to act / the planner) in the PAPM where individuals

acknowledge the limitations in their driving and the need to modify their driving

behaviour accordingly. While driving is still important, participants are more open

towards change and are relying more on the public transport system. Participants in

this class reported greater use of alternative transport which could indicate that they

are looking and testing alternative options to driving. Individuals in this class would

benefit best from support in overcoming barriers toward modifying their driving (e.g.

social support, alternative transport options, enhances self-efficacy).


Individuals in class 3, labelled “the unwilling” also had high levels of stress and

poor perception of their driving abilities. However, they differ from participants in

class 1 in that they perceive greater barriers in regard to giving up driving

particularly in letting others down and having others relying on them. This

resembles stage 4 of the PAPM where drivers have been made aware of limitations

in their driving abilities however, they are unwilling or unable to change.

It is notable that 90% of participants in this class were principal drivers, compared to

almost 60% in the other two classes. It is possible that the drivers in this class are

expressing an inability to self-regulate because of external factors, such as the

expectations of others, an unvarying mobility need and a lack of alternatives. This

implies that they perceive self-regulation as impossible given these (supposedly)

external factors. In practice, these factors may not be as impossible to change as

these drivers believe. For example, they may not be aware of some alternative

options, and the people who rely on them to drive may understand the issues faced

by these drivers and can find their own alternatives. It is also possible that

individuals in this class, despite being aware of limitations in their driving, cannot

see the impact of such decline on their safety. Motor vehicle crashes are rare events

so that possibility of increased crash risk may not create a sense of urgency, and

other health and life goals may be perceived as more important. On the contrary,

driving self-regulation may be viewed as a negative behaviour that can impair one’s

mobility and independence. Prioritising driving self-regulation is therefore a

complicated task that could require extensive deliberation and persuasion. To make

matters worse, the strategies and behavioural changes needed to achieve optimal

driving self-regulation, in terms of reducing crashes, are not clearly defined. It is

difficult for older adults to determine which modifications in their driving behaviours

can translate into improved safety. Individuals in this class may not respond well to

feedback and could benefit from passive interventions (e.g. in-vehicle technology,

improvements in road infrastructure).

Individuals in class 2 were labelled as “the unaware”, and had positive perceptions

about their driving abilities. This group also had the highest probability of

identifying lifestyle factors as a barrier to changing their driving. This class is

similar to stage 2 of the PAPM (unengaged) which is comprised of older adults who

are either not experiencing declines in their abilities that necessitate changes in their


driving behaviour or who are unaware of such declines. It represents a stage prior to

the decision-making process, where individuals have not thought about the need to

change. Interestingly, participants in this class reported greater use of in-vehicle

technology compared to the other two classes. It could be possible that the use of

such technology enables the driver to compensate for some limitations and to

maintain safe driving, an area that deserves more attention. Individuals in this class

would benefit from interventions that enhance their awareness of limitations in their

driving abilities (e.g. customised feedback, on-road assessments).

It is notable that the LCA did not identify all the stages that comprise the

PAPM. To some extent this is an artefact of the study design; for example, the

recruitment material and participant information sheets suggest that age-related

declines in driving exist, so it is unlikely that a participant could claim to be

“unaware” of the issue and therefore in stage 1 of the PAPM. It has been noted in

other research on stages of change approaches that some stages are passed through

very rapidly (Lenio, 2006), which means that the probability of selecting participants

while they are in this stage is low; the non-identification of a class similar to stage 3

the undecided may be an example of this. Nevertheless, examining the self-

regulatory driving behaviour within a health behaviour framework is challenging.

Health behaviour theories deal with behaviours considered “harmful” to the

individual (e.g. smoking, lack of physical activities). As noted by Kostyniuk et al.

(2000) driving in itself is not a harmful behaviour, it is only when certain abilities are

compromised that the risk of crash might increase. The PAPM is a preventative

decision-making framework constructed around the goal of preventing or minimising

future harm, ideal when dealing with complex behaviours, which fits perfectly with

driving self-regulation.

The findings suggest that the driving self-regulation of older adults can be

conceptualised within the PAPM. However, some modifications to the PAPM

framework are needed given the unique nature of driving. The refined model

consists of self-regulatory profiles of older drivers identified from the LCA which

represents certain stages of the PAPM.

Another important finding is that the latent classes and the stages obtained by

the staging algorithm adopted from Weinstein et al. (2008) do not correspond well.


The use of such staging algorithm without further validation can increase the risk of

misclassification.

Figure 7.1: Refined model of self-regulatory driving behaviour

7.9 LIMITATIONS

The recruitment strategy may have attracted active and healthier drivers who

are more interested in driving and more safety-oriented. The findings are based on a

small sample of Brisbane and Sunshine Coast drivers and the extent to which the

results can be generalised to other Australian states is unclear. Self-report measures

were used to assess driving pattern and health status, and may be subject to recall

bias. This study also employed a cross-sectional design and without longitudinal

studies that follow older drivers through the process of self-regulation it will be

difficult to conclude which and how certain factors influence older drivers’ decision

to change and/or stop their driving.

Conclusion

This study provides further support that older drivers are heterogeneous

group and interventions should be customised to meet individuals’ needs. The

findings also indicate that older adults’ self-regulatory driving behaviour could be

classified within the PAPM framework, although there are differences in latent

classes associated with awareness of decline and perceived ability or opportunity to


address it. Therefore, it is implied that interventions should be designed to cater for

each distinct class. However, future studies incorporating larger samples are needed

to validate this finding and to identify the social factors and explanatory mechanisms

that are linked with membership in each profile In addition, future research should

be directed toward prospectively examining self-regulatory profiles of older drivers.

Acknowledgment


research program of the first author.


Chapter 8: Feedback and older drivers (Study three)


As discussed in the previous chapters, older drivers hold different attitudes and

beliefs towards driving. Older drivers go through different stages of behavioural

change towards modifying their driving. Distinctive profiles of older drivers can

represent different stages of the PAPM and would correspond to different

interventions (Table 8.1). As Weinstein et al (2008) state “the PAPM is a conceptual

framework or a skeleton that needs to be fleshed out for each behaviour with

information about how stage transitions occur”. Older adults driving behaviour has

not been examined before within the PAPM framework. Therefore, the interventions

proposed in Table 8.1 are guided by the recommendations provided by Weinstein et

al (2008), previous literature on older drivers, and the results of the qualitative study.

Feedback can play a major role in promoting stage transition. The transition

between stage 2 (unengaged) to stage 3 (engaged but undecided) can be facilitated by

feedback that comes from trusted individual (e.g. health professionals or family

members). This feedback would allow older drivers to start wondering about their

own abilities and whether it has changed as they aged. It could be the starting point

for them to seek more customised feedback that can help them evaluate their own

skills and bridge the gap between their perceived and actual driving abilities. It will

therefore enhance older adults’ awareness about their driving limitations and could

initiate the decision-making process (the later stages of the model).

Kruger and Dunning (1999) states that inaccurate self-evaluation of one’s skills

and abilities can be caused by four feedback-related reasons; lack of feedback,

attributing failure to other causes than lack of skill, not understanding why failure

occurred, and not receiving self-corrective information (Dogan, Steg, Delhomme &

Rothengatter, 2012). As driving is a habitual process, older drivers hardly receive

any evaluative feedback about their driving and therefore fail to accurately evaluate

their driving skills and abilities. Few participants in study one indicated that they

sought feedback from professional driving instructors which they viewed positively.

Driving instructors can objectively assess older adults’ actual driving performance.


They can provide them with driving-specific feedback on how to improve their skills.

As noted by Di Stefano and Lovell (2006) “Driving instructors have a major role in

assisting older drivers to maintain their driving skills and retain their licences in

both ‘refresher’ and ‘rehabilitation’ contexts”. This pilot study aimed to assess the

acceptability of providing one-on-one feedback regarding driving performance to a

sample of older drivers. The study also investigated the impact of such feedback on

older drivers’ perception of the quality of their driving and their willingness to

modify their driving behaviour.

Table 8.1: Adaptation of the PAPM to older drivers’ regulatory behaviours Stage Profile Characteristics Interventions

Stage 1 The unaware Generally unaware of the impact of

age-related declines on one’s

driving abilities OR unaware of the

self-regulatory practices to reduce

one’s risk of crash

Unaware Uninformed

(general)

This stage is not relevant to

the older drivers because

older drivers are generally

aware that driving changes

as they age. However,

individuals may benefit from

media campaigns that help

eliminate the negative

stereotyping of the older

drivers, encourage them to

seek feedback and promote

self-regulation.

Stage 2 The unengaged Generally aware of the problem but

do not recognise the changes in their

own abilities and/or never thought

about the adoption of self-regulatory

practices

Unaware uninformed

(personal)

Individuals in this stage will

correspond well to

interventions that provide a

personal message relevant to

their situation. Feedback

should be personalised and

delivered from trusted

person.

Stage 3 The undecided Aware of changes in their own

abilities but are either unsure of how

it impacts their driving or how they

should modify their driving

accordingly

Undecided

Individuals in this stage are

often reluctant to change and

weighing the pros and cons.

Interventions should

persuade drivers-at-risk of

modifying their driving

behaviours and inform them

about the benefit of adopting

self-regulation

Stage 4 The resister Thought about it but refused to

either acknowledge the need to

modify their driving behaviours or


very difficult to change

because they have informed


unable to modify their behaviours

Unwilling or discouraged decisions about the topic.

They may benefit well from

passive interventions (e.g.

improvement in road

environments, ADAS).

Continuous persuasion and

encouragement is needed.

Stage 5 The planner Thought about it and starting to

monitor their driving and plan to

change their driving accordingly

Willing or encouraged


planning to change but they

may lack the needed

resources or the detailed

direction of how to adopt the

change. Interventions should

remove the surrounding

barriers and provide them

with detailed instructions on

how to adopt the change.

Stage 6 The regulator Have started to reduce and/or avoid

certain driving situations in

response to their declining abilities

Reinforcement

Stage 7 The non-driver Have stopped driving altogether in

response to their declining abilities

Reinforcement

8.2 METHODS

Participants and recruitment

A total of 26 Australian drivers were recruited through the Royal Automobile

Club of Queensland (RACQ) which is a motoring club and mutual organisation,

providing roadside assistance, insurance, travel, finance and other services to its

Queensland members. They are involved in running a number of older driver

programs in Queensland that aims to improve the safety of senior drivers. They run

a 50-minute, one-on-one Driver Assessment program which covers; driving skills

and behaviours, application of road rules in traffic conditions and hazards that drivers

may come across in their everyday driving. As will be explained below, a much

higher number of participants had been anticipated, based on advice from RACQ

about the rates of referral in previous years. Eligible participants were current

drivers, English speaking, aged 65 years and older. All procedures were approved by

the Human Research Ethics Committee of Queensland University of Technology.


Procedure

Most of the participants were referred to RACQ by their physician to assess their

fitness to drive. The remaining participants took part in the RACQ one-on-one

Driver Assessment Program to get their driving skills evaluated. The study was

conducted between March 2015 and November 2015. The driver instructor met the

participants at their home either in the morning or the afternoons. Participants

received an information sheet describing the nature of the study (Appendix H). The

drive was conducted in an RACQ vehicle which is dual-controlled, 4-cylinder

automatic car. The drive occurred in a light-to-moderate traffic density in fine

weather conditions and took approximately 50 minutes to complete. The drive

included variety of locations such as roundabouts, lane-changing and merging,

narrow suburban roadways, intersections, Stop and Give way situations, and self-

navigation exercises. Participants completed a pre-test questionnaire prior to their

on-road assessment (Appendix I). After the drive, participants received customised

feedback in regard to their driving and were asked to complete the post-test

questionnaire (Appendix J). The feedback was customised one-on-one which

involved:

• Driving skills and behaviours

• Application of road rules in traffic conditions

• Hazards that drivers may come across in their everyday driving.

The feedback provided the driver with a clear idea about their driving performance,

their driving errors, and how to continue to drive safely (Appendix K).

Materials

A questionnaire was designed to collect information on the socio-

demographics, self-rated health, crash history, driving experience, current driving

patterns, driving perceptions, feedback about driving and transport options of older

drivers. In addition, participants’ driving reduction was measured by asking

participants to rate the overall amount of their driving compared to ten years ago, on

a 4-point scale from “much less” to “more”. Participants’ self-restriction and

avoidance behaviour was measured by asking participants to rate the extent to which

they would avoid driving under 18 various challenging driving conditions (e.g.

driving at night-time, driving alone, driving on high traffic roads, etc.) on a 5-point

Likert type scale from “not at all” (0) to “avoid completely” (4). A driving


restriction score was calculated based on the average score of responses to the 18

items with higher scores indicating increased avoidance.

Outcome variables:

Participants’ self-rated quality of driving was assessed by asking participant

“how would you rate your quality of driving?” with possible answers ranging from

poor, fair, average, good, excellent prior to and after the drive.

Participants’ willingness to change was assessed by asking “now that you have

received the driver instructor’s feedback which statement better describe you?” with

possible answers ranging from I will not change my driving, as I believe I am a safe

driver and my driving abilities has not changed, I intend to start monitoring my

driving abilities and changing my driving accordingly, I intend to start avoiding some

challenging driving situations, I intend to consider giving up driving altogether. This

was compared to their PAPM stage.

8.3 ANALYSIS


missing data. A total of 21 cases were included in the final analyses. Missing values

on psychosocial scales were replaced with the series mean to compute the average

score. Several variables were collapsed into two or three alternatives to obtain

meaningful categories with respect to the purposes of the study. Participants’

characteristics were described with median and range for continuous variables or

frequencies and percentages for categorical variables. Exploratory non-parametric

tests were chosen given the small sample size and the violations of the assumption of

normality (Wilcoxon signed-rank test and McNemar’s test). The alpha level for

significance was adjusted to a value p < 0.025. Data were analysed in SPSS version

20.0 (IBM Corporation, Armonk, NY).

8.4 RESULTS

Sample characteristics

The sample ranged in age from 71 to 88 years (Median= 80.5, Range= 17), and

included 6 females (28.6 %) and 15 males (71.4%) (Table 8.2). Nine participants

rated their health to be fair, nine to be very good, and three to be excellent. Most

participants (57.1%) rated their driving to be good. The majority of participants

(57.1%) indicated that they have reduced their overall driving compared to ten years


ago. Participants preferred to receive feedback about their driving from their doctor

(71.4%), their family members (9.5%), or from a person of authority (19%). All the

participants indicated that a medical problem could be a reason to stop or modify

their driving with 71.4% of participants indicating that they would stop driving if

advised by their doctor. Six participants received recommendations to stop driving,

two of them ignored the advice, two requested their driving to be formally assessed,

one restricted driving, and one has stopped driving. Around 66% of participants in

our study indicated that they rarely or never use public transport. Around 90% of

participants indicated that they rarely or never use taxis. Finally, 52% of participants

indicated that they rarely or never rely on their family for transport. Psychometric

properties of all scales used in this study are shown in Table 4, together with means

and standard deviations.

PAPM stages

Around 33% of participants belonged to stage 2, 14.3% were categorised into

stage 3, 33.3% were in stage 4, 14.3% were in stage 5, and 4.8% of participants were

in stage 6. For the analyses, participants were combined into two groups; those who

did not change their driving behaviour comprising stages 2, 3 and 4 (81%); and those

who changed their driving behaviour or intend to do so comprising stages 5 and 6

(19%).

Table 8.2: Sample characteristics (n=21)

Age (Median and range) 80.5 (17) Gender Male Female

15 (71.4%) 6 (28.6%)


17 (81%) 4 (19%)


3 (14.3%) 12 (57.1%) 4 (19%) 1 (4.8%) 1 (4.8%)

Living condition Alone With spouse or partner Other

6 (28.6%) 13 (61.9%) 2 (9.5%)

Employment Yes No

3 (14.3%) 18 (85.7%)

Driving reduction Reduced Not reduced

12 (57.1%) 9 (42.9%)


Self-rated health Excellent Very good Fair

3 (14.3%) 9 (42.9%) 9 (42.9%)


6 (28.6%) 15 (71.4%)

Perception of crash risk compared to others same age Extremely likely Somewhat likely Not likely

1 (4.8%) 5 (23.8%) 14 (66.7%)

Self-rated quality of driving

No significant changes were found before and after the feedback.

Willingness to change

Prior to the drive, only 4 (19%) participants indicated that they were planning

to or have already modified their driving behaviours. After the drive, the number of

participants willing to change their driving behaviour increased to 14 (66.7%). An

exact McNemar's test determined that the difference was statistically significant, p =

.006.

Participants’ reviews of the feedback

All participants viewed the feedback to be useful in helping older adults

improve their driving abilities. Around 67% of participants indicated that they would

recommend this form of feedback to their friends. Of the 13 participants who

indicated they were not aware of any limitations in their driving; 6 indicated that the

feedback has made them more aware of certain limitations (e.g. hesitation and

judgement issues). However, 18 participants indicated that they will not seek help

(e.g. driving refresher course or doctor’s consultation).

Fitness to drive and driving errors

Only two participants were considered not fit to drive with recommendation for

further assessment (Table 8.3).

Table 8.3. Fitness to drive

Fit to Drive 17 Fit to Drive, recommendations to restrict the client to local and familiar areas

1


Fit to drive but with recommendations to enhance skills and confidence

1

Not fit to drive 2

The first participant displayed on several occasions his complete lack of

mirror and shoulder check for vehicles potentially hidden in his blindspot. He also

had problems with road positioning prior to turning as he turned from the centre of a

wide single lane road to the right with minimal indication. The driving instructor

commented that “although the client drives with confidence and is not

inappropriately overcautious, he does not display forward planning and I was not

satisfied with their ability to predict and avoid conflicts”. The second participant

displayed on several occasion his complete lack of mirror and shoulder check (e.g.

changing lane while another vehicle is beside him, wandering into an adjacent lane

and turning across an intersection too slowly). His vehicle operation skills were not

always appropriate, such as slowing down to almost a complete stop when turning

into side streets. The participant’s concentration seemed to waver at some times and

he caused an unsafe situation to eventuate and as a result the driving instructor was

required to verbally and physically intervene during the assessment. The driving

instructor commented that “Even though the client appeared to drive with a high

degree of self-confidence, I did not feel entirely safe as a passenger and was not

totally satisfied with their ability to predict and avoid all traffic conflicts. My main

concern is the driver’s lack of awareness at times of his surrounding and what he

perceives to be a safe speed in some situations. On the day, the only reason the

client was not involved in an incident was due to my intervention and the evasive

action of other drivers. I am not convinced that he will act upon the advice given”.

Driving errors were classified into legal or safety errors (Table 8.4). There

was a total of eight errors and nineteen errors that fell under the legal and safety

categories respectively.

Table 8.4. Driving errors observed in the driving assessment

Legal errors Indication at Roundabout-Incorrect Technique Inconsistent indication at roundabouts Line and lane markings were crossed on multilane roads/roundabouts Crossing lane line markings at intersections Failure to give way to other vehicles/pedestrians at intersections Failure to indicate when turning and when merging Speeding

1 6 2 1 1 2 3


Failure to stop at Stop sign 2 Safety errors Generally insufficient use of rear-view mirrors Insufficient/Absence blind spot observation when merging or changing lanes Not cancelling indicators at times Not keeping up with traffic at times Insufficient safe space when stopped in traffic Inadequate lateral scanning Failure to observe traffic signs, lane/road markings Insufficient safe space when driving Inappropriate speed Occasional issues with holding a safe lane position Generally poor forward observation In car conversation caused a loss of concentration at times Reversing errors Very late indication and incorrect road position for a turn Late braking Seating position too reclined Gap selection when merging Lane changing process too slow Slow to proceed when turning at intersections

9 8 1 1 5 8 7 7 7 2 3 4 4 1 1 1 1 1 1

8.5 DISCUSSION

Before discussing the findings from the study, it is important to note that

recruitment of participants proved to be very difficult and the small sample size

makes it difficult to reach significant findings. The driving instructors indicated that

the number of referrals made by health professionals (on which the planning for this

study was based) had significantly decreased compared to previous years. Many

eligible participants refused to take part in the study. The sensitivity of the topic and

the anxiety associated with the whole assessment procedure may have contributed to

this. The recruitment difficulty highlights important issues that deserve further

exploration in future studies. First, it is important to examine the perceptions of both

physicians and older drivers on the physician referral system and how this impacts on

the patient-doctor relationship. Second, it is important to “normalise” the topic of

driving assessment and cessation among the older population. The introduction of

this topic from early stages may make it easier to discuss it later (Betz, Jones,

Petroff, & Schwartz, 2013). Third, the stereotyping of the older drivers as timid and

dangerous may add to the sensitivity of the topic and refusal to participate. Lastly, it

is important that the driving assessment programs are more readily available,

appropriately tailored, and promoted.

Nevertheless, the findings from this study add to our understanding of the

acceptability of providing feedback to older drivers and its impact on their self-rated


quality of driving and willingness to change. Overall, majority of participants were

in stage 2 or stage 4 of the PAPM. These findings are consistent with previous

research (Freund et al., 2005) which demonstrated that older drivers assign high

ratings to their driving skill even when being referred for assessment. This could

indicate that discussion with physicians about possible problems in their driving and

being referred for further evaluation did not increase their self-awareness.

Participants may have truly viewed their driving abilities to be unchanged and did

not feel the need to change. It could also reflect a state of conscious denial

complicated by the importance of driving on their independence and mobility

(Freund et al., 2005). This is interesting because around 71% of participants

indicated that they would stop driving if advised by their doctor. It could be possible

that the discussion with their physicians lacked the depth needed to persuade them

about the need to monitor and/or modify their driving. The feedback received from

their doctor could have been non-evaluative and incomprehensive which failed to

increase their awareness. Another possibility is that participants may have been

referred by doctors who are not their regular physicians. Therefore, they may have

lacked the trust in the advice given.

Another interesting finding is the limited use of public transportation and

taxis among our sample. This could be because the majority of participants were the

principal drivers in the household and others may have relied on their driving.

Few participants were considered unfit to drive as they displayed on several

occasions their lack of safe driving skills. Consistent with previous studies, the

majority of driving errors were related to visual scanning and signalling and

indication (Koppel et al., 2016). Emerging studies indicate that older drivers’ skills

can improve with evaluative feedback and driving training programs (Romoser,

2012). In regards to feedback, all participants viewed the feedback to be useful in

helping older adults improve their driving abilities and the majority indicated that

they would recommend this form of feedback to their friends. Of the 13 participants

who indicated they were not aware of any limitations in their driving; 6 indicated that

the feedback has made them more aware of certain limitations (e.g. hesitation and

judgement issues). However, 18 participants indicated that they will not seek help

(e.g. driving refresher course or doctor’s consultation). The feedback had no impact

on participants’ ratings of their driving ability. Still, the majority of the participants


indicated that they are now planning to modify their driving behaviours. It could be

possible that the short-time frame did not give the participants enough time to reflect

on the content of the feedback.

8.6 LIMITATIONS

The study used a very small sample, the findings can’t be generalised to wider

population. The study did not include a control group and feedback was provided by

different instructors and may not be standardised. Participants were referred by their

doctors, social desirability bias and conscious denial may have affected their

answers. Participants’ cognitive abilities were not assessed.

Chapter 9: Discussion

9.1 CHAPTER OVERVIEW

Self-regulation of driving is a promising approach that can assist older adults to

maintain their driving privilege. Still, there is a lack of a comprehensive theoretical

model that positions the process of self-regulation within a framework of behaviour

change. By enhancing our understanding of the process of driving self-regulation,

we can develop effective interventions that can assist in addressing the mobility

needs of the older driver population. The overarching aim of this research program

was to examine the process of self-regulation among older drivers using the PAPM

as a framework in an attempt to develop a comprehensive theoretical model of

driving self-regulation. By doing so, interventions can be adapted to the individual’s

needs and the desired outcome. The previous chapters have documented the research

program which addressed the following objectives:


Objective 1: Explore the preliminary fit of older adults’ driving behaviour

within the PAPM framework using qualitative focus groups among current

older drivers.

Objective 2: Develop a conceptual model based on the PAPM that profiles

older adults into distinctive groups based on their mindset towards adopting

self-regulatory driving behaviours.

Objective 3: Determine the prevalence of PAPM stages in a sample of older

drivers and identify the sociodemographic and psychosocial characteristics of

stages membership.

Objective 4: Identify self-regulatory driving profiles among older drivers

based on their mindset towards change using Latent Class Analysis (LCA)

and determine whether they are similar to those in the conceptual model.

Objective 5: Examine the impact of providing one-on-one feedback

regarding driving performance on stage transition among a sample of older

drivers and its impact older drivers’ perception of the quality of their driving

and their willingness to modify their driving behaviour.

This chapter presents a synthesis of the main findings of the research and

discusses the strength and limitations of the research. The chapter is organised

according to the research questions and concludes with recommendations for future

research.

9.2 OVERALL RESEARCH FINDINGS

Research Question 1

Study One: Can older drivers be grouped into different stages of PAPM based

on their qualitative differences (e.g. attitudes, awareness, and perceptions) and

patterns of change?

Consistent with previous findings (Adler & Rottunda, 2006; Musselwhite &

Haddad, 2010a), participants viewed driving to be key to their independence and

mobility. Most participants, despite being aware of the impact of ageing on driving


abilities, indicated that their abilities have not changed. Participants indicated that

they have reduced their driving over the years. However, by delving into the

motivations behind such behaviours, it appeared that reasons other than declining

abilities played the biggest role in the decision-making (e.g. retirement and

preference). This is consistent with previous studies (Ball et al., 1998; Blanchard &

Myers, 2010) which have shown that lifestyle factors play a major role in the

changes of older adults’ driving patterns. Without delving deep into the motivations

behind such behaviour, it is impossible to conclude that these behaviours are self-

regulatory in nature. As highlighted by Molnar et al. (2015), this is a major

limitation in most of the previous studies. Another form of strategic self-regulation

that was highly adopted by participants was journey planning which participants

attributed to the constant changes in the roads and for safety reasons. In regards to

driving avoidance, night-time driving and merging were problematic for some

participants which is consistent with previous studies (Ball et al., 1998; Charlton,

Oxley, Fildes, oxley, & Newstead, 2003 & Staplin, Gish, Decina, Lococo, &

McKnight, 1998a).

There is a paucity of research investigating the impact of feedback on older

drivers’ self-awareness and subsequent self-regulatory behaviours. Participants were

asked if they have sought information about their driving ability. Doctor’s advice, a

driving instructor, refresher courses, and the internet were mentioned in several

discussions. For most participants, feedback about regulating or stopping driving had

to come from someone they trust and respect.

This study was also unique in terms of investigating the impact of life-goal

decisions on older adults’ driving patterns. It appeared that participants who lived in

retirement villages where everything is walking distance found it easier to be

prepared to give up driving one day. Others who lived in communities far from

urban areas reported that giving up driving could mean isolation for them.

Participants’ opinions regarding the use of in-vehicle technology were highly

variable. Some viewed technology as a wonderful possibility that could help them

overcome some limitations they encounter in their driving, such as reverse parking,

merging, and driving in unfamiliar places. Alternative transport option is an

important factor as well. In fact, some older drivers may continue to drive despite

being aware of their declining ability to avoid the use of alternative transports (Atkin,


2001). Issues concerning availability, accessibility, convenience, and acceptance

were raised which is consistent with previous findings (Allan & McGee, 2003;

Gardezi et al., 2006).

The findings from the first study resonate with existing literature on older

driver. However, it was unique because it conceptualised older adults’ driving

behaviour within the stages of the PAPM. It is important to note that the intention

was not to support or reject the PAPM, but to use it as a starting point for the

development of the model.

The first stage of the PAPM was omitted because older adults are generally

aware of the age-related declines in driving abilities. The unengaged which matches

stage 2 of the PAPM is comprised of participants who were aware that ageing can

have impact on people’s driving ability and that older drivers adapt to these changes

by restricting and reducing the amount of their driving. However, participants in this

stage were confident about their driving and did not feel the need to change their

driving or seek feedback regarding their driving ability. Some of the drivers in this

stage indicated that they have not changed the amount of driving “I think I'm still

driving around about as much as we used to, because we're still young enough to get

out and about and we firmly believe that you do what when you can.” Those who

have changed the amount of their driving have attributed the changes to merely

preference or lifestyle changes “I drive less than I did, but that's partly because

driving was part of my career, my work career, and I'm only working part-time now.

I don't have to go out on the road.”

Interestingly, participants in this stage pointed out that age per se is not an

indication to start monitoring or restricting one’s driving “He’s said that to me a few

times. And I say to him, “Why do you feel like that?” and the only answer I get is

“Because I’m, getting old,” but surely, that’s not the criteria. And that’s why I’ve

been trying to question him if he has any other feelings that might be prompting that

thought. It doesn’t matter. The age doesn’t come in to it. It’s just your mental

attitude”. People are driving for longer now and people in their 70s view themselves

capable of driving for the next 20 years or so “It’s never an easy thing when

somebody has to stop driving, I’m not looking forward to it, I’m 70. I just talked to a

friend of mine the other day; her mother stopped driving at 91. I said 91; she goes


“oh! But Gloria she is a perfectionist she could not drive unless she knew she was

doing it right”.

It also appears that participants in this stage were unable to draw the link

between the impact of the decline of certain ability on their driving performance and

some of them were highly overconfident “My ability is much the same as it always

has been, because when I retired from the workplace, I didn't stop driving. I kept

going, and I've kept going, and I do still drive a lot. Maybe I've slowed down a little,

last time I ever had a speeding ticket in my life. But, I do now tend to be much more

aware of my surroundings. But my ability to drive I think hasn't changed all that

greatly”. However, later in the conversation the same participant admitted to

changes in his vision which had an impact on their driving “I can speak on that for

myself. At Christmas time...I have an eye problem, which has never been a real

problem. But, I went for a check-up two week before Christmas and the specialist

said, do you require glasses to drive, and I said no. I used to have them for reading,

close-up reading. He said, “I have to be honest, if you were here today for a driver's

test, I would have to fail you.” I've gotten used to seeing things the way they are, or

the way they are now, not how they used to be. I went to the eye optometrist and got

a pair of glasses for driving, and yes, it did make a heck of a difference, to see more

clearly when I'm driving”. Participants in this stage did not appear to think about the

future of their driving or plan their retiring from driving “We are travelling now as

much as we can while we can. Because, ahead in the future, who knows. Who knows

about tomorrow, who knows in 10 years' time? But I am very confident in saying that

when I realise, I will give up driving”. They also did not feel the need to seek

feedback about their driving abilities “At this stage, I'm not going to discuss it with

my medical people, but when the time comes, I would certainly respect a professional

giving me clues as which way to go”. Participants in this stage viewed giving up

driving as an emotional and an overwhelming step “Giving up driving is a really

hard move, I've discovered, with other people. They feel as if they've lost their

independence. Even if they're only driving to the local shops and back, they feel as

though they've still got their independence if they can drive. It's very important”.

Driving allowed them to stay connected and was essential for their wellbeing “Very

important. I work part-time. I also play bowls a lot, and I go to different clubs and

things for that. You can't possibly lead a really independent life relying on public


transport. It's too difficult. It takes a whole day to do one thing, and I don't have time

to do that. It is very important to me, and I think for most older people, it is part of

their independence”. They also held strong opinions against public transport options

“You can't possibly lead a really independent life relying on public transport. It's too

difficult. It takes a whole day to do one thing, and I don't have time to do that.”

The undecided stage matches stage 3 of the PAPM. In this stage, participants

have started to notice changes in their driving ability and are starting to think about

the future of their driving “I think in another three years or four I won’t be driving a

lot, because I’m getting too old”. Driving is still key to their independence; however,

they are starting to consider alternative options such as relying on their partners to

drive them “If I lose my license, I’ve lost my independence. I’ve got to get on a bus,

but I mean I’ve got Maureen anyway so she can drive and she’s a good driver”, or

on public transport “I don't mind public transport. I lived – I’ve – Up when I was in

the country, we had one bus a day and that was a school bus which was pretty hectic,

but if you went out of the school bus, you didn’t get to town. But up here where I

live, there’re lots of buses and there’s trains”. Crash involvement appears to be a

reason to seek advice or consider their driving ability. A female participant who had

been involved in a crash that affected her confidence attempted to seek professional

feedback about her driving ability “I felt I was getting a bit dicky driving so I rang

the NRMA and asked them, “Could I do a driving test?” And he said, “Well, we

don't really do that.” He said, “But I’ll get someone to come down and go with

you.” So, they sort of came from Goldman and took me around where I usually shop

and about two hours later, we got back and I hadn’t hit anything. So anyway, he

said – So I said, “How did I go?” He said, “Well, only two things,” he said, “I

could find.” He said, “You drive too fast and you drive too close to the vehicle in

front.” And do you know what? That has helped my driving so much, just to be told

that. You probably know you’re driving too fast and you know you’re getting there,

but just to be told by someone in authority, it – And because up here, you get on the

highway and it says travel three Chevrons behind, which is a wonderful indication

because it hits you in your mind and you just need a reminder about it” and this

feedback helped her to continue driving and regain her confidence for the time being

“That one I had with the NRMA, that only cost me about $75 and they’re absolutely


worth every penny. What he – the information and the feedback he gave me and the

feeling I had when I was doing it”.

In the resistant stage, which matches stage 4 of the PAPM, participants have

experienced a situation in which their driving ability has been questioned but it did

not seem as a strong indication for them to change or stop their driving. A female

participant was involved in a crash few years ago that made her questioned whether

she should continue to drive or not “I had my first crash a few years ago, not my

fault, of course. <Laughs> But that’s about all. When I had this crash, I thought

that was a thing to say that I better give up driving. I lasted three days. It was

terrible”. However, few years later she still has not noticed any changes in her

abilities “I think my ability is still the same, but one thing, I think I do notice now,

that I’m a little bit more cautious”. Driving for her is fairly important “I’m more or

less echoing those, yes, independence and lack of public transport. I have family

fairly close by, but I’m the one who goes to see them”. Another participant, who had

recently had her medical certificate issued by the doctor, believes that the doctor had

made a mistake “That was the doctor I went to have it all filled out, and she filled it

out that I always have to wear spectacles, as they call them. Fine. She ticked some

box in it which meant that I had a medical condition. I just had to see her, because I

wanted this form filled out, and I didn't see my usual doctor in the clinic. They kicked

up a fuss down at the registration part, made me fill out acres of forms. I said what's

all this about? They said, medical, medical. I said, I've got to wear glasses, which

are all I consider it. They all looked at me…. Yes. My doctor said she shouldn't have

ticked that. That means if you've got epilepsy or some medical condition that will

interfere with your driving. That now is stuck on my license”. For her, public

transportation is not an option and giving up her driving would have a devastating

impact on her mobility “Because I hate public transportation. Non-existent, at our

end of the world”.

Participants in the planner stage recognise the need to monitor one’s ability

and regulate their driving accordingly “I feel it needs to be self-limiting but feel that,

for me, anyway, there comes to a stage where I will be putting other people on the

road at risk. No matter how much I wanted to keep driving, I wouldn't do it. So, that's

my criteria”. They have made life goal changes to facilitate giving up driving in the

future “I've recently moved into a retirement village, and I've been very careful to


choose one where there's a very good bus service there. I'm quite prepared that when

the time comes where I feel I'm not good enough to drive, I will give it up, but it's

really important to me. It was one of the things that I looked at” and are more

knowledgeable and acceptable of alternative transport options “The village where I

live, they run a bus to all the shopping centres twice a week, and on the way home,

they'll actually deliver you to your door if you've got shopping. So, that's a wonderful

solution for people. You've got to plan for that”. They are aware that they need to

keep informed about that constant changes around them “I find one of the negative

things amongst our age group is that a lot of older people aren't cognizant with the

road rules that have changed. I've actually got a copy of the latest road rules and

went through it and there are a lot of things that have changed and a lot of new rules

that I wasn't aware with, and I think that the older drivers don't have the experience.

There are road rules that we don't necessarily know. Whereas the younger ones do

and they take their right of way”.

“I think it would be a very good idea, and I'd be quite prepared if someone

came with me for half an hour, or an hour. Whether they are a driving instructor or

somebody else and just pick up any bad habits that I might have, or give me

feedback. I think that would be a great thing to do. My sister has just done it. She

almost had a very bad high-speed accident because she misjudged the speed of the

car coming towards her, so she got someone from a driving school to take her for a

lesson and it was quite helpful”

The last stage which matches stage 6 of the PAPM, the regulator is comprised

of participants who have started to restrict their driving or avoid certain challenges

situations in response to changes in their driving abilities “I think I've changed my

driving. Since I got these (point to his glasses), I don't drive anywhere near as much

in the night-time…. Yeah, where it never used to worry me, headlights or anything

like that. Now, I'd rather not drive in the night-time if I can avoid it… That's right.

No problems with the confidence, about handling the vehicle, or avoiding an

accident. It's just the sight”. They are aware of the changes in their abilities and have

sought feedback from a health professional “I probably won't renew my license next

year. My sight is growing together, it's not calcifying. It's the opposite. My bone

density is over the top of the scale. As a result, I tear tendons and shoulders. My neck

is not getting any better. Occasionally, if I get up too quickly, I get giddy. The doctor


says it's up to you, but my recommendation is, when your license is due next year,

forget it if you last that long”. They have made plans that would make giving up

driving easier in the future “It's the best move we made. We'd shifted from the Coast

down to the Glass House. We were out there for eight years. Half-acre block was

getting a bit too much for me to manage. My wife was still working, she ran the

Lifeline shops. I was talking to the dog all day and weeding” “We're not going out as

much as what we did. We live in a retirement village, and we're the type of people

that are happy with each other's company. We can sit down and listen to some music,

or watch a DVD, or watch the television, and talk about various things that don't

need to go out. When we were younger, we seemed to always be visiting friends. Our

friends now are within a 50-metre radius, you just walk across the way”. Still, they

are aware that in the future technology can assist to overcome some of the limitations

they are experiencing and promote their mobility for longer “Things have changed,

because technology, you can drive a car now, and it can park itself. Before long,

they're also, as I mentioned earlier, they've got technology where they're thinking

about getting a car from here to there. You jump in your car and say, “I want to go

to...” and it'll happen. Under those circumstances, I would be using those sort of

facilities, and if need be, purchase a car that would be able to do that. There might

be others that would not be able to afford the technology, part of the cost now. They

can't afford an up-to-date car now. I think down in the future, I can see that it will be

happening”.

The findings also informed the development of a conceptual model of self-

regulation, based on the PAPM that provided a description of the factors that can

promote the transition between each stage. By addressing these factors, it appears

possible to design interventions that are specific for individuals’ needs. The model

was based on the stages of the PAPM and provided suggestion of some factors that

can facilitate the transition between the stages towards adoption of change. The

model is described in Chapter 5. It emphasises the role of self-awareness and insight

into one’s driving abilities in moving people from being unengaged (stage 2) to the

pre-decision stage (stage 3). This can be achieved by providing individuals with

customised feedback from trusted sources. Interventions at this stage should aim to

enhance older adults’ awareness and increase their knowledge about the impact of


ageing on driving (e.g. educational interventions, feedback from health professionals,

or self-assessment tools).

Once engaged, the decision-making process start by examining one’s risk of being

involved in a crash compared to their younger self or compared to others in the same

age. This is the main factor that impact people’s transition to stage 4 or stage 5 of

the PAPM. Individuals who don’t perceive themselves at risk of crash will move to

stage 4 and they may benefit from passive interventions (e.g. in-vehicle technologies,

improvements in road designs, and vehicle modifications) and persuasion. On the

other hand, if older adults perceive themselves to be at risk of crash they will

progress to the stage 5, self-monitoring. In this stage, individuals start to actively

monitor their driving and to determine if they are encountering difficulties or

problems while driving. Individuals also start to seek additional feedback from

various sources (e.g. family, friends, health professionals, or driving instructor).

Based on the content of the feedback and the suggested modifications to one’s

driving, individuals start to weigh the pros and cons of such change. The presence of

environmental barriers such as lack of alternative transport options or being the

principal driver in the household can greatly hinder the progression to stage 6.

Interventions at this stage should aim at addressing barriers towards changing or

modifying behaviours. The final stage represents the stage where drivers are

continuously modifying and regulating their driving in response to declines in their

abilities until they stop driving altogether. It is important that interventions in this

stage reinforce the messages provided in stage 5.

Research Question 2

Study 2, Phase 1: What is the prevalence of the stages of the PAPM in the

study population? What are the psychosocial and environmental factors associated

with stages of the PAPM?

This study aimed to further examine the applicability of the PAPM in

understanding self-regulatory driving behaviours among older adults. Participants

were classified into different stages of PAPM using a stage algorithm adapted from

Weinstein et al. (2002). The majority of participants were in the unengaged stage

(46.8%) followed by stage 6 (22.1%), stage 3 (10.8%), stage 4 (10.4%), and stage 5

(9.9%). The first stage of the PAPM was omitted because older drivers are generally

aware of the impact of ageing on the driving abilities. The last stage of the PAPM


was also omitted because it was postulated as driving cessation and the study did not

include former drivers. These findings indicate that a significant proportion of

Australian older drivers don’t regulate their driving. Despite around 70% of

participants indicating that they have reduced their driving compared to ten years

ago, only 22% indicated that they are regulating their driving. This is consistent with

the first qualitative study which suggests that older drivers may appear to engage in

self-regulatory driving behaviours such as reducing their overall amount of driving or

avoiding certain challenging situations. However, this reduction or avoidance

behaviour could be the result of lifestyle changes and mere preferences rather than an

actual decline in one’s driving ability.

This study investigated the psychosocial characteristics associated with PAPM

stages. The early stages of the PAPM deal with individual’s mindset, perceptions,

and awareness. There was a significant association between psychosocial factors and

PAPM stages membership. In particular, perceived driving abilities, driving

confidence, and attitudes towards giving up driving were significantly associated

with PAPM stages. The findings indicated that participants in stages 2 and 4 of the

PAPM assign higher self-ratings to their driving abilities, have more negative

attitude towards giving up driving, and have higher driving confidence compared to

those in stages 5 and 6. Successful self-regulation depends largely on individual’s

awareness of limitations in driving abilities rather than the actual abilities (Anstey et

al., 2005). This suggests that individuals in the early stages of the PAPM could

benefit from interventions targeted toward enhancing their self-awareness about their

driving abilities. The late stages of the PAPM deal with barriers towards adoption of

the precaution. Participants in stage 5 (Planning to act) were significantly more

likely to report more use of public transport. These findings are consistent with

previous research which indicates that the availability of other transport options

(Coughlin, 2001) and the costs of public transport (Corpuz, 2007) are important

factors in the decision to give up driving among older adults. Planning retiring from

driving can make the experience less traumatic and improve the outcomes through

gradual preparation and feeling of control (Buys et al., 2012; Liddle, Gustafsson,

Bartlett, & McKenna, 2012). In line with previous research conducted by Molnar et

al. (2013), this study investigated participants’ life goal decisions and whether they

impact their driving behaviour and decision-making process. Around 25.2% of


participants indicated that they had moved to a new place closer to their common

destinations, 22.1% had moved to a place with better public transport options, and

14.9% had moved to a seniors’ home. While not significantly different among

PAPM groups, moving to a seniors’ home was significantly associated with driving

reduction with 87.9% of those living in seniors’ homes indicating that they have

reduced their driving compared to 68.3% of those who are still living at home.

Unfortunately, previous research indicates that the vast majority of older drivers do

not plan the transition to a non-driving state, even those who suffer from medical

conditions that can impair their driving (Adler & Rottunda, 2006; Peel et al., 2002).

Older drivers may be reluctant to engage in planning due to their awareness of the

potentially negative outcomes of driving cessation (King et al., 2011). Of interest in

this study was the impact of feedback on stage membership. Providing feedback

regarding driving-related abilities may assist older adults in making better and

informed decisions regarding their driving (Holland & Rabbitt, 1992; Owsley et al.,

2003). 44.6% of participants had discussed their driving with their doctors, 43.2%

with their family, and 21.2% with their friends. Being involved in a family

discussion about driving in the past year differed significantly between PAPM

stages. Qualitative research indicates that older drivers prefer to receive feedback

from someone who has direct knowledge and understanding with their driving

(Coughlin et al., 2004). Generally, family members may be the first to express their

concerns over an older adult’s driving ability (Gillins, 1990). A hierarchical

regression analysis was conducted after controlling for the effect of age, gender, self-

rated health, and driving experience to examine the impact of the psychosocial and

environmental factors on PAPM stages. Given the small sample size, participants

were grouped into two groups based on their decision to self-regulate their driving.

Those in stages 2 and 3 were collapsed into one group, the Pre-decision group, while

those in stages 5 and 6 were collapsed into the Decision group. The significant

predictors in the final model were self-rated driving confidence, family feedback,

overall self-rated quality of driving and driving relinquishment scale.

This study provided further support for the proposition that self-regulatory

driving behaviour among older drivers can be examined using the PAPM. Ideally,

the next step would be to conduct a prospective study where older drivers are

followed through the stages of change as they occur, to better determine which


variables predict the adoption of self-regulatory driving behaviours among older

adults. However, this was not feasible both in regards to time and financial

constraints. To overcome these limitations and test the applicability of the model,

the second phase of study 2 adopted a novel approach. Latent Class Analysis was

employed to determine if distinct self-regulatory driving profiles of older drivers

based on their mindset towards change can be identified from the sample. These

emerging profiles (if any) would then be compared to the stages of the PAPM. The

selection of the indicators was guided by the findings from the first phase of study 2

and the significant characteristics associated with the PAPM stages.

Research Question 3

Study 2, Phase 2: Would groups, identified utilising Latent Class Analysis (LCA),

match those in the conceptual PAPM and those assigned by the stage algorithm?

The LCA identified three unique classes that may be targeted using

intervention programs. Individuals in class 1, which have been labelled as “willing

to change”, had the poorest perception about their driving abilities. Driving was still

important in terms of their mobility and independence, however, they identified

fewer barriers in regards to changing their driving. This class resembles stage 5

(decided to act / the planner) in the PAPM where individuals acknowledge the

limitations in their driving and the need to modify their driving behaviour

accordingly. While driving is still important, participants are more open towards

change and are relying more on the public transport system. Individuals in this class

would benefit best from support in overcoming barriers toward modifying their

driving (e.g. social supports, alternative transport options, enhance self-efficacy).

Individuals in class 2 were labelled as “the unaware”, and had positive perceptions

about their driving abilities. This group also had the highest probability of

identifying lifestyle factors as a barrier to changing their driving. This class is

similar to stage 2 of the PAPM (unengaged) which is comprised of older adults who

are either not experiencing declines in their abilities that necessitate changes in their

driving behaviour or who are unaware of such declines. It represents a stage prior to

the decision-making process, where individuals have not thought about the need to

change. Participants in this class reported greater use of in-vehicle technology

compared to the other two classes. It could be possible that the use of such

technology enables the driver to compensate for some limitations and to maintain


safe driving, an area that deserves more attention. Individuals in this class would

benefit from interventions that enhance their awareness of limitations in their driving

abilities (e.g. customised feedback, on-road assessments).

Individuals in class 3, labelled “the resisters” as for stage 4 of the PAPM (although

they differ in some respects), are those who have identified weakness in their driving

but are unable or unwilling to change their driving. It appears that having others

relying on their driving and unavailability of other transportation options prevents

them from changing their driving. It is possible that the drivers in this class are

expressing an inability to self-regulate because of external factors, such as the

expectations of others, an unvarying mobility need and a lack of alternatives. This

implies that they perceive self-regulation as impossible given these (supposedly)

external factors. In practice these factors may not be as impossible to change as these

drivers believe. For example, they may not be aware of some alternative options,

and the people who rely on them to drive may understand the issues faced by these

drivers and can find their own alternatives. It is also possible that individuals in this

class, despite being aware of limitations in their driving, cannot see the impact of

such decline on their safety. Motor vehicle crashes are rare events so that possibility

of increased crash risk may not create a sense of urgency, and other health and life

goals may be perceived as more important. On the contrary, driving self-regulation

may be viewed as a negative behaviour that can impair one’s mobility and

independence. Prioritising driving self-regulation is therefore a complicated task that

could require extensive deliberation and persuasion. To make matters worse, the

strategies and behavioural changes needed to achieve optimal driving self-regulation,

in terms of reducing crashes, are not clearly defined. It is difficult for older adults to

determine which modifications in their driving behaviours can translate into

improved safety. Individuals in this class may not respond well to feedback and

could benefit from passive interventions (e.g. in-vehicle technology, improvements

in road infrastructure).

Research Question 4

Study 3: Can providing older adults with customised and evaluative feedback assist

in stage transition and modify their willingness to change their driving behaviour?


To answer this question, a study was conducted where participants were

provided with customised one-on-one feedback in regards to their driving skills and

driving abilities. The feedback was provided by a driving instructor; which was

identified in focus group as a trustworthy and useful form of feedback.

Unfortunately, even though the recruitment lasted for around 9 months, only 22

participants were included in the final study. Therefore, the results should be

interpreted with caution and can’t be generalised to the population. All participants

viewed the feedback to be useful in helping older adults improve their driving

abilities. Around 67% of participants indicated that they would recommend this

form of feedback to their friends. Of the 13 participants who indicated they were not

aware of any limitations in their driving; 6 indicated that the feedback has made them

more aware of certain limitations (e.g. hesitation and judgement issues). However,

18 participants indicated that they will not seek help (e.g. driving refresher course or

doctor’s consultation). No significant changes were found before and after the

feedback in participants’ self-rated quality of driving. Prior to the drive, only 4

(19%) participants indicated that they are planning to or modified their driving

behaviours. After the drive, the number of those who were willing to change their

driving behaviour has significantly increased to 14 (66.7%).

Refining the initial model

Examining the self-regulatory driving behaviour within a health behaviour

framework is challenging. To start with, health behaviour theories deal with

behaviours considered “harmful” to the individual (e.g. smoking, lack of physical

activities). As noted by Kostyniuk et al. (2000) driving is not a harmful behaviour, it

is only when certain abilities are compromised that the risk of crash might increase.

Further, crashes are rare events and modifying one’s driving behaviour can be

limiting and inconvenient. Therefore, older adults may not perceive self-regulation

as a priority and could even perceive it as a negative behaviour. It is also important

to note that unlike other behaviours, there are no tangible or immediate benefits to

adopting self-regulation (other than perceived reduced risk of crash and perceived

increased comfort). The longevity of the process may cause older drivers to become

discouraged and relapse back to their old driving behaviours. Second, modifying

one’s driving can have implications on other people such as family members. Older

drivers may be reluctant to modify their driving behaviours because of having family


members who rely on their driving or because they want to avoid being a burden on

other family members. In other risky behaviours investigated previously within

behaviour change theories, minimising or stopping the behaviours can have no or

positive impact on other people.

The PAPM is a preventative decision-making framework constructed around

the goal of preventing or minimising future harm, ideal when dealing with complex

behaviours, which fits perfectly with driving self-regulation. First, it starts with

one’s awareness of risk and the need to adopt the precautionary behaviour. As

discussed in previous chapters, self-awareness is key to adopting self-regulation. In

fact, modification in driving behaviours for reasons others than increased insight into

limitations of driving abilities should not be regarded as self-regulation. Second, it

differentiates between those who are unaware and those who are resistant to change.

This is particularly useful because having different interventions for each stage is

rather useful. Third, the stages account for the qualitative differences in behaviours

and motivators among older drivers.

Overall, this research program suggests that the driving self-regulation of

older adults can be conceptualised within the PAPM. However, some modifications

to the PAPM framework are needed given the unique nature of driving. The refined

model consists of self-regulatory profiles of older drivers identified from the LCA

which represents certain stages of the PAPM.

As discussed before, stage 1 of the PAPM in the preliminary model was

omitted because it is most likely that older drivers are generally aware of the impact

of ageing on driving abilities. In addition, actual capacity to drive safely adapted

from Anstey et al. (2005) (with its cognitive, physical and vision aspects) has been

included but separated from the stages. The first stage in the model represents the

“unaware driver” which is comprised of individuals who lack personal engagement

about the impact of ageing on their driving abilities. This lack of insight is due to

lack of feedback or experience with the hazard (e.g. being involved in a crash). This

study found no significant association between crash involvement and PAPM stages.

However, only few participants were involved in a crash which made it difficult to

test for any significant association. Future studies should investigate the impact of

being involved in a crash and crash characteristic (e.g. severity, recency, outcome,

and being at fault) on self-awareness. This is a stage prior to the decision-making


process where older drivers have not thought about the future of their driving. As

suggested from the qualitative findings, older adults’ attitudes and perceptions

towards driving self-regulation are the result of the information within their family

and community. At this stage, individuals benefit most from interventions that can

increase their self-awareness and encourage them to think about precautionary

behaviours (i.e. driving self-regulation) to overcome any driving limitations.

Feedback at this stage should be provided from a trustworthy person, be evidence-

based, and allow the driver to accurately assess their driving ability. As previous

studies suggest, family members and healthcare professionals often initiate such

discussion with the older driver.

Once engaged, the decision-making process starts and individuals start to estimate

their risk of crashing and their risk of being injured. In addition, individuals weigh

the pros and cons of modifying their driving behaviour. This stage, the undecided, is

critical because individuals start to acquire and manage new information, assess their

surrounding environments and resources, and evaluate the immediate and long-term

outcome of their decision. It is very important at this stage to provide individuals

with objective and evaluative feedback of their driving abilities. Equally important is

recommendations on how to overcome barriers associated with adopting self-

regulation (e.g. lack of transport options, relying on family members). Some older

drivers perceive their risk of crash to be minimal and view self-regulation to be

unnecessary or inconvenient. The “resister” is very difficult to change since he/she

has already formed an opinion about the precaution. Individuals in this stage will

benefit from reinforcing the message and persuasion. They could also benefit from

passive interventions (e.g. in-vehicle technology or improvements in road structure).

The “planner” on the other hand represents those who have decided to modify their

driving behaviour. In this stage individuals start to monitor their behaviour and

assess their need to change. This can be difficult within the driving context for

several reasons. First, it may be difficult for older drivers to draw the link between

the decline in certain driving ability and impairment in their performance. Second, it

may be difficult to determine which modifications are needed to overcome such

limitation and improve their safety. Third, there is a possibility that some drivers

may become more anxious and their discomfort may cause unnecessary restrictions.

It is therefore crucial at this stage that participants receive accurate, objective,


evaluative, and exhaustive feedback. It is also important to reinforce the

recommendations on overcoming barriers toward adopting self-regulation.

The final stage is the regulator driver. In this stage, individuals are constantly

monitoring and regulating their driving according to their driving abilities. In line

with Molnar et al. (2013), self-regulation should be divided into strategic, tactical

and life-goal. These terms have described previously in chapter two. To encourage

life-goal changes, individuals can benefit from interventions aimed at planning

driving retirement, use of alternative transport options, and modifying their living

arrangements. To encourage strategic self-regulation, individuals could benefit from

education interventions, similar to KEYS that encourage older drivers to reduce

and/or restrict their driving according to their driving abilities. Finally, tactical self-

regulation could be achieved through driving retraining programs on-road or in the

simulator to enhance the driver skills and performance.

Figure 9.1: Refined model of self-regulatory driving behaviour

9.3 CONTRIBUTIONS TO RESEARCH

This research program contributes to the theoretical understanding of older

drivers’ self-regulation through the application of the PAPM and the development of

a conceptual model that categorises older adults into different stages of behaviour

change while capturing a wide range of interpersonal, intrapersonal, and

environmental factors that influence self-regulatory driving behaviour among the


older drivers. A theory-based understanding of older drivers’ self-regulatory

behaviours and how to influence them can assist in the development of effective

interventions. To my knowledge, this is the first study to develop a comprehensive

model of older drivers’ regulatory behaviour using the stages of change theories.

The model includes a large number of interpersonal, intrapersonal, and

environmental factors associated with driving self-regulation and identified

previously in the literature. Still, the model is very flexible and can be customised in

different contexts based on the study population (e.g. women, rural drivers or

professional older drivers), the self-regulatory practice (e.g. tactical, strategic or life-

goal) and the desired interventions (e.g. In-vehicle technologies, educational

interventions or health professional interventions). The model can also be applied to

a large number of “precautionary behaviours” adopted by the older population. The

findings from the LCA have provided empirical support to the use of the model

through the identification of classes of older drivers that match to a degree those in

the conceptual model.

This program of research adds to our understanding of the impact of feedback

on older adults’ self-regulatory driving behaviour. The findings from the qualitative

study indicate that some older adults seek feedback in regards to their driving

abilities. The problems often encountered are the lack of trusted and evidence-based

source of such feedback. The study identified numerous sources that can provide

older adults with different form of feedback about ageing and driving. It is important

to emphasise that the content and source of feedback will vary greatly based on

individual’s stage in the conceptual model. For instance, participants identified the

lack of readily-available printed materials that contains facts and statistics about the

older driver. These materials can be made readily available in physicians’ offices or

seniors club with the aim of enhancing older adults’ knowledge about the problems

encountered with ageing on their driving abilities.

Finally, this program of research investigated the impact of life-goal decisions

on older adults’ self-regulatory driving behaviour, an area that deserves further

exploration. The qualitative findings indicated that those who were living in seniors’

villages or in areas with better public transport options had thought about the future

of their driving. The quantitative findings indicated that 25.2% of participants had

moved to a new place closer to their common destinations, 22.1% had moved to a


place with better public transport options, and 14.9% had moved to a seniors’ home.

While not significantly different among PAPM groups, moving to a seniors’ home

was significantly associated with driving reduction with 87.9% of those living in

seniors’ homes indicating that they have reduced their driving compared to 68.3% of

those who are still living at home.

9.4 PRACTICAL IMPLICATIONS OF THE RESEARCH PROGRAM

Findings from this research program have implications for the management of

the older drivers’ safety issues. The conceptual model can act as a framework for

further investigating the older adults’ driving behaviours. It can also assist in

designing interventions that encourage older drivers to self-monitor and

appropriately self-regulate their driving while taking into accounts the needs and

expectations of the older driver and assist them in making informed decisions about

the future of their driving. Previous studies have shown that involving older drivers

in the decision making provides them with sense of control which can ease the

transition to the non-driving state in the future. The practical implications of this

study correspond to the stages proposed by the conceptual model. Interventions will

vary in their source, content, and timing based on each stage. Interventions would

only work if they are customised based on individual’s baseline and the anticipated

outcome. Older drivers are generally aware of the impact of ageing on one’s driving

ability. Still, older drivers are overall safe drivers, despite being portrayed in the

media as a heightened crash risk. This stereotyping, could be adding to the

sensitivity of the topic and the difficulty of initiating discussion with older drivers.

The media need to stop stereotyping the older driver as timid and dangerous.

Accurate information about older drivers’ crash statistics and impact of ageing on

driving abilities should be made readily available and accessible to the public. For

stage 2, the unengaged, it is important to increase self-awareness of the impact of

age-related declines on older adults’ driving. Previous literature suggest that older

drivers are generally aware of the impact of ageing on driving. However, due to the

complexity of the driving behaviour and the subtle nature of the declines associated

with ageing, older drivers may find it difficult to draw the link between the two. It is

therefore important to design interventions that can enhance older drivers’ self-

awareness. As noted in study 1 and study 2, the majority of participants did not feel

the need to modify their driving, which could reflect lack of insight. Findings from


qualitative focus groups indicated that participants are open to receiving feedback

about their driving, provided that it comes from a person they trust. Older drivers

would benefit from one-to-one discussions with their healthcare professionals who

can accurately assess if they have a medical or non-pathological condition that

impact their driving. Future studies should address the barriers associated with

providing feedback to older drivers in healthcare setting (e.g. compromising patient-

doctor relationship, lack of training to medical professionals, and sensitivity of the

topic). In addition, interventions should also incorporate the family and carers of

older drivers who can play a role in enhancing their awareness but may lack the

understanding and knowledge of how to do that. For stage 3, individuals would

benefit from interventions that accurately reflect their risk of crash and encourage

seeking feedback accordingly. Assessment of driving in a friendly environment can

provide older drivers with objective measure of their driving skill and performance.

This study suggests that driving instructors could play an important role. Future

work should develop a battery of test that can assess older drivers’ skills with high

reliability and sensitivity. Some individuals however may choose to make their

own assessment and refuse the feedback. Older drivers who were made of aware of

limitations in their driving but refuse to change will progress to stage 4. Individuals

in this stage are the most difficult to tackle because they have made their opinions

and will not be respond well to conventional interventions. They can benefit best

from passive interventions. Others who believe they are at risk of crash will move to

stage 5 where they will start to actively observe their driving and seek further

feedback. In this stage, individuals can benefit from more detailed information of

how to adopt the change and how to overcome the barriers towards such change.

This research identified a large number of barriers towards change that should be

addressed in designing older drivers’ interventions. Lack of alternative transports is

a common barrier which could even be a greater issue for rural older drivers. In

addition, interventions that can assist older drivers plan their driving retirement may

be beneficial. To improve mobility and road safety for older drivers, interventions

must consider modifiable (i.e., different than age or gender) facilitators and barriers

to the use of adaptive strategies, as well as the needs of older drivers. These

interventions must be personalised, proactive and planned on a continuum to

promote safe and responsible driving according to the abilities of older drivers, but

also considering their personal and environmental factors, as well as their social


participation. In fact, many personal factors such as openness, perceptions,

knowledge and abilities must be considered, but also environmental factors such as

support, cost and the proximity of resources

9.5 STUDY STRENGTHS AND LIMITATIONS

The strengths and limitations of this research program have been presented

in previous chapters. Overall, it has a number of strengths. This study was unique in

its attempt to utilise a bottom-up approach; through Latent Class Analysis, in

identifying self-regulatory driving behaviour profiles among older adults based on

their mindset towards changing their driving behaviour. In addition, the study used a

robust theoretical model, PAPM. The present study utilised an exploratory

sequential mixed method design which resulted in enhancing our understanding of

the self-regulatory process among older drivers. Another methodological strength is

the inclusion of large number of interpersonal, intrapersonal, and environmental

factors associated with the process of self-regulation.

The study had several limitations. Overall, recruitment has proven difficult

for the three studies despite utilising various recruitment strategies. This can be due

to transportation difficulties, health problems common at this age group, sensitivity

of the topic, lack of interest, or not understanding the potential benefits of the

research. For the qualitative study, it was extremely difficult to recruit former

drivers and the study failed to capture the experiences of driving-regulation and

driving cessation among this group. For the quantitative study and the pre-post

study, the sample was relatively small in number which limited the power for some

of the group analyses and may have increased the risk of Type II error. This in turn

may affect the generalisability of the results to the broader population.

Second, the sampling method may have introduced some biases. The study

relied on convenience sample and therefore may have attracted participants who are

more safety-oriented; more motivated to continue driving, and have higher awareness

of their driving abilities. In addition, the findings are based on a small sample of

Brisbane and Sunshine Coast drivers and the extent to which the results can be

generalised to other Australian states is unclear.

Third, the study relied on self-report and participants were required to think

back retrospectively and report on their reasons and patterns of driving restriction.


This self-report may have been biased or subject to forgetting. The self-rating

questionnaires used did not measure response bias and therefore it is uncertain if

participants answered the questions in a forthright manner. In addition, participants

may have scored themselves higher than average introducing social desirability bias.

In this study, standard scales were used to measure the psychosocial variables.

While their use is common, it is possible that they do not capture the variables

related to the older drivers.

Fourth, this study did not assess the cognitive skills of the participants and

findings may be different for cognitively impaired drivers.

In addition, the staging algorithm used in this study was similar to the one

recommended by Weinstein et al. (2008). There is limited research that examines

the validity and reliability of such staging algorithm despite being used before in the

transport literature (Coxon et al., 2015). This may have resulted in participants being

misclassified into the wrong stages. Future studies should attempt to overcome this

limitation by employing reliable and valid tools for classification.

The study was cross-sectional in nature and therefore causality cannot be

established.

9.6 FUTURE DIRECTIONS

This exploratory research program provided reasonable support for the use of

PAPM as a framework in investigating driving regulation and/or cessation among

older adults. Future research should attempt to employ a larger prospective design

that initially stage older drivers in the PAPM and follow them through their driving

regulation and cessation process. This will assist in the identification of the factors

and the critical events that help stage progression. The process of self-regulation is

highly complex and it is important to expand the way we define and measure self-

regulation to include any behaviours that the driver embark upon to enhance their

safety. Majority of previous studies have focused on driving restriction and

avoidance of challenging situation. There is also paucity of research regarding

tactical self-regulation among older drivers.


While there is an increased shift towards using objective measures of driving

abilities; more attention is still needed in developing reliable and valid measures of

older drivers’ perception. As discussed before, older adults’ perception of their

driving ability rather than their actual driving is what motivate them to change. A

major drawback of previous studies is that there is inconsistency in the way older

drivers’ perceptions are measured and defined. Further, the majority of these

measures have no information about their reliability and validity.

While this research program attempted to examine the impact of feedback on

older drivers’ intention to change; the small sample size made it difficult to reach a

significant result. Future research should attempt to examine the impact of

customised feedback on moving older drivers through stages of change using a large

sample size and control groups.

In future research, it is useful to conceptualise self-regulation using stages of

change theories. This will accommodate for the heterogeneity of the older drivers’

population in terms of their mindset towards change (e.g. perceptions and self-

efficacy) and barriers towards adopting the change (e.g. presence of alternative

transport options and household composition). By knowing the stage of change

where the individual is at, interventions could be customised to move them towards

the desired outcome. The barriers identified in the qualitative study serve as

appropriate targets for future interventions. On the other hand, older drivers’

willingness to seek feedback and to rely on in-vehicle technology could be seen as

avenues to promote safe mobility. Future research should also be directed towards

the use of in-vehicle technology and their role in maintaining older drivers’ mobility

by overcoming limitations in their driving abilities.

9.7 CONCLUDING REMARKS

This program of research has enhanced our understanding of the process of

self-regulation among older drivers. First, this research program presented a

comprehensive theoretically-based model of older adults’ driving self-regulation.

The model was based on the PAPM which identifies various stages of change that

start by unawareness to modifying one driving. The model included a large number

of interpersonal, intrapersonal and environmental factors that influence stage

transition. It can assist in designing, implementing, and evaluating interventions that


can assist older adults regulate their driving successfully. Second, a novel approach

using LCA has identified three class of self-regulatory driving behaviours similar to

those identified by the model providing further empirical support to the model.


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Chapter 10: 209

Appendices

Appendix A

Recruitment Flyer for Focus Groups


Appendix B

Newspaper advertisement for Focus Groups

We are inviting individuals aged 70 years or more who are either former drivers or current drivers to participate in a study on driving. This project is being conducted by researchers at Queensland University of Technology (QUT) to explore your beliefs and attitudes regarding receiving feedback about driving. Your participation will involve completing a background questionnaire and attending a 90-minute focus group session. All participants will receive $40 Coles and Myer gift voucher. Please email [email protected] or phone 0416 779 400 for further information. Thank you for your interest and feel free to tell your friends about the study. Participation is confidential and all responses and information will be stored securely and remain confidential. This project has been approved by QUT's Human Research Ethics Committee (Ref No. 1200000501).

Chapter 10: 211

Appendix C

Focus Group Protocol and Discussion Guide Preparation: 1. Confirm room booking. 2. Call to confirm location, date, and time with participants. 3. Check materials; tape recorder, batteries, pens, name tags, participant information sheet and consent forms, background questionnaires, incentives and refreshments. On the day: 1. Welcome participants, invite them to help themselves with the refreshments. Make sure you check if they want to go to the bathroom and they know where the bathroom is. Once everyone is seated provide them with name tags. 2. Introduce yourself and hand each person the participant information sheet, the consent form, and the background questionnaire to fill in. 3. Once collect them, ask them if they have any questions. 4. Introduce the Ground Rules: - Introduce yourself and your role again and the reason for this discussion. -Please try and speak one at a time, so that we will not miss important information. - There are no right or wrong answers, all comments are important. - It is okay for people to disagree or express different opinions. Turn on tape recorder Ice-breaker: okay everyone, let’s start today by introducing ourselves, tell us how long you have been driving. Would you say driving is important for you? If so, can you tell us why? Rationale: Importance of driving Perceived advantages of driving Reasons for driving (e.g. other relying on driving)

Probes: Independence, convenience, enjoyment, sense of control, identity, social inclusion, other relying on your driving.

Would you say that now at your age, there are negative aspects associated with driving? Rationale: Perceived disadvantages of driving (Intrapersonal factor) Levels of comfort Level of confidence

Probes: Expense and cost, fear and anxiety, discomfort, behaviour of other drivers and pressure from others to stop driving.

Do you think there are differences now versus say ten or twenty years ago in your driving ability? If so can you tell us how?


Rationale: Perceived changes in driving ability Self-efficacy Confidence

Probes: physical changes (vision, hearing, reflexes, head and neck mobility, fatigue) Psychological changes (confidence, enjoyment, and ability to be in stressful situation while feeling safe) What abilities do they think are important for safe driving?

Have you changed your driving over the last ten years or so? If yes, can you tell us how? Rationale: change process Probes: Drive less, adopt certain strategies, and avoid certain driving

situations What made you aware that you need to adopt strategies to continue driving? Rationale: Interpersonal influence Insight Knowledge and health literacy Self-efficacy Feedback Probes: family, friends, health professional, refreshing course, self-

assessment tool In ten or twenty years from now, do you think your driving will be changed, would you say you will be doing things differently? Rationale: Beliefs about likelihood and personal susceptibility to impaired driving Self-enhancement bias Level of confidence Probes: avoid certain driving situation; drive less, use alternative transportation options more or stop driving altogether Have you ever thought about the possibility of stopping driving someday? How will you know it is about time to stop? What will influence your decision to stop driving? Have you ever sought information about the effect of ageing on your driving ability? If yes, then why? Have you ever discussed with someone your driving concerns or worries, say your doctor or your family? Would you say it is helpful if you receive feedback about your driving ability? If so can you suggest how and from whom? In your opinion, what would you be looking forward in your discussion with your physician?

Chapter 10: 213

Is there anything else that comes to your mind?

Appendix D

Consent Form for Focus Groups

Chapter 10: 215

Appendix E

Background Questionnaire- Focus Group Study

QUESTIONNAIRE

Feedback and Older Driver Study

This questionnaire booklet contains questions about you and your driving practices. All information received will be treated confidentially. Please respond carefully to all questions and remember there are no right

or wrong answers.

Centre for Accident Research and Road Safety – Queensland (CARRS-Q) Queensland University of Technology

130 Victoria Park Road, Kelvin Grove, Queensland 4059 Australia Email [email protected] Web www.carrsq.qut.edu.au

CRICOS No. 00213J

Thank you for your assistance


Background questionnaire

1. Are you (please tick) □ Male

□ Female

2. Your age (Years) ________________

3. What is your postcode? ________________

4. What is your highest education level?

□Primary School

□Secondary

□Certificate/Diploma

□Bachelor degree

□Postgraduate

5. Is English your native language?

□Yes

□No

6. Do you live in?

□A private home

□A retirement home or seniors’ complex

□Other, please specify________________

7. Do you live:

□Alone

□With spouse or partner

□With family members

□With friend(s)

□With paid caregiver

□Other, please specify ________________

8. Do you work (paid or voluntary) at the moment?

□Yes, full-time

□Yes, part-time

□No

9. Are you still driving? □Yes

□No

Chapter 10: 217

10. Do you hold a current open driver’s licence?

□Yes

□No

□Other, please specify________________

11. For approximately how many years you have had your open driver’s licence?

12. What is your annual number of kilometres driven?

□Less than 5000 km/yr.

□5,000-10,000 km/yr.

□10,001-20,000 km/yr.

□20,001-30,000 km/yr.

□More than 30,000 km/yr.

13. Overall would you say your health is?

□Excellent

□Very good

□Fair

□Poor

□Very poor

14. Are you currently taking any prescribed medications?

□No

□Yes, please specify and how many ________________ ________________ ________________

End of questionnaire Thank you very much for your participation in this study


Appendix F

Participant Information Sheet-Survey

Chapter 10: 219

Appendix G

Study Two Questionnaire

SURVEY Feedback and Older Driver Study

This survey booklet contains questions about you and your driving practices. All information received will be treated confidentially. Please respond carefully to all questions and remember there are no right or wrong answers.

Thank you for your assistance Centre for Accident Research and Road Safety – Queensland (CARRS-Q) Queensland University of Technology (QUT) 130 Victoria Park Road Kelvin Grove Queensland 4059 Australia Email [email protected] Web www.carrsq.qut.edu.au CRICOS No. 00213J


Gender Male Female

Your age (Years) _____________________

What is your postcode? _____________________

What is your highest education level?

Primary School

Secondary

Certificate/Diploma

Bachelor degree

Postgraduate

Is English your native language?

Yes

No

Do you live in?

A private home

A retirement home or seniors’ complex

Other, please specify_______________________________________

Do you live:

Alone

With spouse or partner

With family members

With friend(s)

With paid caregiver

Other, please specify _______________________________________

Do you work (paid or voluntary) at the moment?

Yes, full-time

Yes, part-time

No

Overall would you say your health is?

Excellent

Very good

Fair

Poor

Very poor

Are you still driving?

Chapter 10: 221

Yes

No

Are you the main driver in your household?

Yes

No

Shared equally

For approximately how many years you have had your open driver’s licence?

______________________________________

What is your annual number of kilometres driven?

Less than 5000 km/yr.

5,000-10,000 km/yr.

10,001-20,000 km/yr.

20,001-30,000 km/yr.

More than 30,000 km/yr.

Have you taken any driving courses?

No

Yes

Do you remember who offered the course? _______________________________________

In the past ten years or so, have you ever taken (please tick all that applies):

Vision test

Rules test

Road test

In an average week, how many days per week do you normally drive? _________________________________

Where do you generally drive

City

Rural

Suburb

How long are most of your driving trips (each way)?

Less than 15 minutes

15-30 minutes

30-60 minutes

Over 60 minutes

Which way do you prefer to get around?

Drive yourself

Have someone drive you


Use public transportation or taxi

Other, please explain ________________________________

If you had to go somewhere and did not want to drive yourself, what would you do?

Ask a friend or relative to drive you

Call a taxi or take a bus or other public transport

Drive yourself regardless of how you feel

Cancel or postpone your plans and stay home

Other, please specify ________________________________

Please think for a moment about all the places you drive in a typical week. You can tick more than one.

Shop

Church (or other place of worship)

Work

Relative’s house

Friend’s house

Out to eat

Appointments (hair, doctor)

Other, please specify_______________________________________

How would you rate the quality of your driving? Would you say it was?

Excellent

Good

Average

Fair

Poor

In the past year, have you had any crashes when you were the driver?

(Please include minor scrapes and bumps)?

No

Yes

If yes, please specify the number of all the crashes and whether or not you were at fault. _________________________________

Compared to ten years ago, would you say that you drive

Much less

A little less

The same

More

Compared to ten years ago, do you still feel confident that you can safely drive to places you need to go

Much less

Chapter 10: 223

A little less

The same

More

How likely is it for you to have a car crash, compared to other people your age?

Not likely

Somewhat likely

Extremely likely

How likely is it for you to have a car crash, compared to yourself ten years ago?

Not likely

Somewhat likely

Extremely likely

How likely is it for you to be injured if you are involved in a crash?

Not likely

Somewhat likely

Extremely likely

How often do you use public transport?

Always

Frequently

Sometimes

Rarely

Never

If you use public transport rarely, can you tell us why (you can tick more than once)

Don’t need to

Don’t know enough about it

Inconvenient

Time-consuming

Don’t feel safe

Cost too much

Unreliable

Bus stop far from home

Other _______________________________________

How often do you use taxis?

Always

Frequently

Sometimes

Rarely

Never


If you use taxis rarely, can you tell us why (you can tick more than once) Don’t need to

Don’t know enough about it

Inconvenient

Time-consuming

Don’t feel safe

Cost too much

Unreliable

Other _______________________________________

How often do you take rides from family or friends? Always

Frequently

Sometimes

Rarely

Never

In general, how comfortable are you asking family or friends for rides? Very comfortable

Somewhat comfortable

Somewhat uncomfortable

Very uncomfortable

How important is it for you to continue to drive? Extremely important

Very important

Moderately important

Somewhat important

Not that important

Have you moved to a new place closer to your common destinations (shops, family, church, etc.)?

Yes

No

If you ticked no, is this something that you would consider in future? Yes

No

Did not think about it

Have you moved to a senior community that provides transportation? Yes

No


Chapter 10: 225

No


Have you moved to a new place with better options for public transportation? Yes

No


No


Do you use in-vehicle technology to make your driving easier? (e.g. navigation system, cruise control, blind spot detection)

Yes

No


No


In the past year, have you talked about your driving with any of the following? You can tick more than one.

Your doctor

Family members

Friends

Other, please specify ___________________________________

Has anyone suggested over the past year that you limit or stop your driving? No

Yes

If you ticked yes, please indicate all that apply Family member

Friend

Your doctor

An eye care professional

Other, please specify ____________________________________

What did you do in response to their suggestion? Ignored it

Made own assessment of ability and decided no action was required

Restricted my driving, please specify _______________________________________

Other, please specify

_______________________________________

Whose suggestion regarding change in driving status would you most likely


listen to? Partner

Other family members

Doctor

Friend

Person of authority (e.g. police)

Which of the following could make you consider changing your current driving? (Please tick all that apply)

Medical condition

Vision problem

Feeling unfit to drive

Feeling nervous when driving

Feeling uncomfortable when driving

If I have a crash

If advised by my family

If advised by my doctor

If my license is revoked

Other _______________________________________

Which of the following statements better describe you?

I am at the point where I am not sure if I should start thinking about ways to avoid certain driving situation or reduce my driving

Avoiding certain driving situations would be pointless to me

Some other older drivers need to change their driving, but I believe that I am a safe driver and have never thought about the need to change my driving

I am planning to avoid certain driving situations and reducing my driving

I have just recently started to avoid challenging driving situations or drive less

To what extent do you avoid driving under the following conditions?

Not

at a

ll

Not

oft

en

Reas

onab

ly o

ften

Very

oft

en

Avoi

d co

mpl

etel

y

At night in the rain 1 2 3 4 5 In the rain 1 2 3 4 5 When alone 1 2 3 4 5 With distracting passengers 1 2 3 4 5 Parallel parking 1 2 3 4 5

Chapter 10: 227

Not

at a

ll

Not

oft

en

Reas

onab

ly o

ften

Very

oft

en

Avoi

d co

mpl

etel

y

Familiar roads 1 2 3 4 5 Unfamiliar roads 1 2 3 4 5 Freeways 1 2 3 4 5 High traffic roads 1 2 3 4 5 Peak hour 1 2 3 4 5 At the start/end of school time 1 2 3 4 5 At night 1 2 3 4 5 When there is roadworks 1 2 3 4 5 Long distance driving 1 2 3 4 5 Lane changes 1 2 3 4 5 Right turns 1 2 3 4 5 When sun in my eyes 1 2 3 4 5 Roundabouts 1 2 3 4 5


If you ticked any of the situations above, why do you avoid driving at this situation(s)?

Not

con

fiden

t

Not

com

fort

able

No

need

Oth

er p

leas

e sp

ecify

At night in the rain □ □ □ _________________

In the rain □ □ □ _________________

When alone □ □ □ _________________

With distracting passengers □ □ □ _________________

Parallel parking □ □ □ _________________

Familiar roads □ □ □ _________________

Unfamiliar roads □ □ □ _________________

Freeways □ □ □ _________________

High traffic roads □ □ □ _________________

Peak hour □ □ □ _________________

At the start/end of school time □ □ □ _________________

At night □ □ □ _________________

When there is roadworks □ □ □ _________________

Long distance driving □ □ □ _________________

Lane changes □ □ □ _________________

Right turns □ □ □ _________________

When sun in my eyes □ □ □ _________________

Roundabouts □ □ □ _________________

Chapter 10: 229

If you want to, how easy will it be for you to avoid driving at the following conditions?

Very

har

d

Som

ewha

t har

d

Not

har

d at

all

At night in the rain 1 2 3 In the rain 1 2 3 When alone 1 2 3 With distracting passengers 1 2 3 Parallel parking 1 2 3 Familiar roads 1 2 3 Unfamiliar roads 1 2 3 Freeways 1 2 3 High traffic roads 1 2 3 Peak hour 1 2 3 At the start/end of school time 1 2 3 At night 1 2 3 When there is roadworks 1 2 3 Long distance driving 1 2 3 Lane changes 1 2 3 Right turns 1 2 3 When sun in my eyes 1 2 3 Roundabouts 1 2 3


Please rate your current ability in the following conditions (assume daytime driving unless specified otherwise).

Ver

y go

od

Goo

d

Fai

r

Poo

r

To see road signs at a distance 1 2 3 4

To see road signs at a distance (night) 1 2 3 4

To see your speedometer and control 1 2 3 4

To see pavement lines (at night) 1 2 3 4

Avoid hitting curbs or medians 1 2 3 4

See vehicle coming up beside you 1 2 3 4

See object on the road (at night) with glare from light or wet roads

1 2 3 4

Quickly spot pedestrian stepping out from between parked cars 1 2 3 4

Move your foot quickly from the gas to the brake pedal 1 2 3 4

Make an over the shoulder check 1 2 3 4

Quickly find a street or exit in an unfamiliar area or heavy traffic 1 2 3 4

Get in and out of your car 1 2 3 4

Reverse or back up 1 2 3 4

Make quick driving decisions 1 2 3 4

Drive safely (avoid crashes) 1 2 3 4

Please indicate your agreement or disagreement with the following statements.

Chapter 10: 231

Stro

ngly

agr

ee

Agre

e

Disa

gree

Stro

ngly

dis

agre

e

Most of my friends do not drive 1 2 3 4

People who are important to me think I should change my driving behaviours

1 2 3 4

People who are important to me approve of my driving behaviour 1 2 3 4

Giving up driving will save me money 1 2 3 4

Giving up driving will simplify my life 1 2 3 4

Giving up driving will restrict my mobility 1 2 3 4

Giving up driving will restrict my independence 1 2 3 4

Giving up driving will relieve me of unwanted responsibilities 1 2 3 4

Giving up driving will mean letting down people who rely on me 1 2 3 4

Changing my driving is not possible because of my lifestyle 1 2 3 4

Changing my driving is not possible because other people rely on me 1 2 3 4

Changing my driving is not possible because public transportation is not available to me

1 2 3 4

Changing my driving is not possible because I don’t want to use public transportation

1 2 3 4

Changing my driving is not possible because I can’t rely on others to drive me

1 2 3 4


Please rate the experienced stress connected to the following traffic conditions. (Please assume your general everyday driving.)

Heav

y st

ress

Mod

erat

e st

ress

Neg

ligib

le st

ress

No

stre

ss

Driving on slippery road 1 2 3 4

Driving when tired 1 2 3 4 Night driving 1 2 3 4 Coping with competitiveness of other drivers 1 2 3 4

Driving in rush hours 1 2 3 4

Driving in unfamiliar surroundings 1 2 3 4

Driving long distance 1 2 3 4

Coping with carefulness of others 1 2 3 4

Overtaking 1 2 3 4

Parking or reversing 1 2 3 4

Driving in crossings 1 2 3 4 Adjusting to traffic flow 1 2 3 4 Switching lanes 1 2 3 4 Observing traffic signs 1 2 3 4

Driving on highways 1 2 3 4

Merging from side roads 1 2 3 4

Thank you for completing the survey.

Chapter 10: 233

Appendix H

Study 3 Participant Information Sheet


Appendix I

Questionnaire (1)

Feedback and Older Driver Study This survey booklet contains questions about you and your driving practices. All information received will be treated confidentially. Please respond carefully to all questions and remember there are no right or wrong answers. Please tick only one answer unless otherwise specified.

Thank you for your assistance Centre for Accident Research and Road Safety – Queensland (CARRS-Q) Queensland University of Technology (QUT) 130 Victoria Park Road Kelvin Grove Queensland 4059 Australia Email [email protected] Web www.carrsq.qut.edu.au CRICOS No. 00213J

Chapter 10: 235

Office Only IDENTIFICATION NUMBER ___________________ Please answer the following questions (tick only one answer unless otherwise specified) Gender Male Female Your age (Years) _____________________

What is your highest education level? Primary School Secondary Certificate/Diploma Bachelor degree Postgraduate

Is English your native language? Yes No

Do you live: Alone With spouse or partner With family members With friend(s) With paid caregiver Other, please specify

_______________________________________ Do you work (paid or voluntary) at the moment?

Yes, full-time Yes, part-time No

Overall would you say your health is? Excellent Very good Fair Poor Very poor


Are you the main driver in your household? Yes No Shared equally

For approximately how many years you have had your open driver’s licence? _______________________________________

How would you rate the quality of your driving? Would you say it was? Excellent Good Average Fair Poor

Compared to ten years ago, would you say that you drive Much less A little less The same More

How likely is it for you to have a car crash, compared to other people your age? Not likely Somewhat likely Extremely likely

How likely is it for you to have a car crash, compared to yourself ten years ago? Not likely Somewhat likely Extremely likely

How often do you use public transport? Always Frequently Sometimes Rarely Never

How often do you use taxis? Always Frequently Sometimes Rarely

Chapter 10: 237

Never How often do you take rides from family or friends?

Always Frequently Sometimes Rarely Never

How important is it for you to continue to drive? Extremely important Very important Moderately important Somewhat important Not that important

In the past year, have you talked about your driving with any of the following? You can tick more than one.

Your doctor Family members Friends Other, please specify

_______________________________________ Has anyone suggested over the past year that you limit or stop your driving?

No Yes

If you ticked yes, please indicate all that apply Family member Friend Your doctor An eye care professional Other, please specify

_______________________________________ What did you do in response to their suggestion?

Ignored it Made own assessment of ability and decided no action was required Restricted my driving, please specify

_______________________________________

Other, please specify ______________________________________


_ Whose suggestion regarding change in driving status would you most likely listen to? Please tick only one option

Partner Other family members Doctor Friend Person of authority (e.g. police)

Which of the following could make you consider changing your current driving? (Please tick all that apply)

Medical condition Vision problem Feeling unfit to drive Feeling nervous when driving Feeling uncomfortable when driving If I have a crash If advised by my family If advised by my doctor If my license is revoked Other

_______________________________________ Which of the following statements better describe you?

I am at the point where I am not sure if I should start thinking about ways to avoid certain driving situation or reduce my driving

Avoiding certain driving situations would be pointless to me Some other older drivers need to change their driving, but I believe that I am a safe

driver and have never thought about the need to change my driving I am planning to avoid certain driving situations and reducing my driving I have just recently started to avoid challenging driving situations or drive less

Chapter 10: 239

To what extent do you avoid driving under the following conditions?

Nev

er

Rare

ly

Som

etim

es

Oft

en

Alw

ays

At night in the rain 1 2 3 4 5 In the rain 1 2 3 4 5 When alone 1 2 3 4 5 Parallel parking 1 2 3 4 5 Freeways 1 2 3 4 5 High traffic roads 1 2 3 4 5Peak hour 1 2 3 4 5 At night 1 2 3 4 5 Right turns 1 2 3 4 5 How confident are you in your ability to drive under the following conditions?

Not

at a

ll

Not

ver

y co

nfid

ent

Reas

onab

ly

conf

iden

t

Very

con

fiden

t

Com

plet

ely

Conf

iden

t At night in the rain 1 2 3 4 5 In the rain 1 2 3 4 5 When alone 1 2 3 4 5 Parallel parking 1 2 3 4 5 Freeways 1 2 3 4 5 High traffic roads 1 2 3 4 5Peak hour 1 2 3 4 5 At night 1 2 3 4 5 Right turns 1 2 3 4 5


How hard would it be for you?

Very

har

d

Som

ewha

t har

d

Not

har

d at

all

To avoid driving in the rain 1 2 3 To avoid driving alone 1 2 3 To avoid reverse parallel parking 1 2 3 To avoid right turns 1 2 3 To avoid driving on freeways 1 2 3 To avoid high traffic roads 1 2 3 To avoid driving in peak hour 1 2 3 To avoid driving at night 1 2 3 To avoid driving at night in the rain 1 2 3

Please rate your current ability in the following conditions (assume daytime driving unless specified otherwise).

V

ery

good

Goo

d

Fai

r

Poo

r

To see road signs at a distance 1 2 3 4

To see road signs at a distance (night) 1 2 3 4

To see your speedometer and control 1 2 3 4

To see pavement lines (at night) 1 2 3 4

Avoid hitting curbs or medians 1 2 3 4

See vehicle coming up beside you 1 2 3 4

See object on the road (at night) with glare from light or wet roads

1 2 3 4

Quickly spot pedestrian stepping out from between parked cars 1 2 3 4

Move your foot quickly from the gas to the brake pedal 1 2 3 4

Make an over the shoulder check 1 2 3 4

Quickly find a street or exit in an unfamiliar area or heavy traffic 1 2 3 4

Get in and out of your car 1 2 3 4

Reverse or back up 1 2 3 4

Chapter 10: 241

Ver

y go

od

Goo

d

Fai

r

Poo

r

Make quick driving decisions 1 2 3 4

Drive safely (avoid crashes) 1 2 3 4

Please indicate your agreement or disagreement with the following statements.

Stro

ngly

dis

agre

e

Disa

gree

Nei

ther

ag

ree

or

disa

gree

Agre

e

Driving a vehicle is pleasurable 1 2 3 4

I am experiencing increasing apprehension about driving 1 2 3 4

I am becoming more concerned about the unsafe behaviours of older drivers

1 2 3 4

Being able to drive is important to me 1 2 3 4

Driving is necessary to my life to give me the flexibility I desire 1 2 3 4

Driving is central to my independence 1 2 3 4

Some people think I should stop driving 1 2 3 4

People close to me disapprove of my driving 1 2 3 4

My friends drive their vehicle regularly 1 2 3 4

The physical demands of driving a vehicle (e.g. turning my head to shoulder check) are becoming a challenge

1 2 3 4

The financial cost of driving and maintaining a vehicle is an increasing concern of mine

1 2 3 4

Parking is becoming more difficult to me 1 2 3 4

I plan to continue driving in the foreseeable future 1 2 3 4

I intend to keep driving when I want to in the near future 1 2 3 4

Giving up driving will simplify my life 1 2 3 4


Giving up driving will restrict my mobility 1 2 3 4 5

Giving up driving will restrict my independence 1 2 3 4 5

Giving up driving will relieve me of unwanted responsibilities 1 2 3 4 5

Giving up driving will mean letting down people who rely on me 1 2 3 4 5

Changing my driving is not possible because of my lifestyle 1 2 3 4 5

Changing my driving is not possible because other people rely on me 1 2 3 4 5

Changing my driving is not possible because public transportation is not available to me

1 2 3 4 5

Changing my driving is not possible because I don’t want to use public transportation

1 2 3 4 5

Changing my driving is not possible because I can’t rely on others to drive me

1 2 3 4 5


Chapter 10: 243

Appendix J

Questionnaire (2)

Feedback and Older Driver Study

Thank you for your assistance

Centre for Accident Research and Road Safety – Queensland (CARRS-Q) Queensland University of Technology (QUT)

130 Victoria Park Road Kelvin Grove Queensland 4059 Australia

Email [email protected] Web www.carrsq.qut.edu.au

CRICOS No. 00213J


Office Only IDENTIFICATION NUMBER ___________________ Before the drive, were you aware of some of the limitations in your driving (if any) that has been pointed out by the driving instructor?

No Yes, please explain

__________________________________________________________________________________ After the drive, are you more aware of changes in your abilities that could be affecting your driving?


__________________________________________________________________________________ Before the drive, did you think that you need to modify or adjust your driving behaviours?


__________________________________________________________________________________ After the drive, do you think that you need to modify or adjust your driving behaviours?


__________________________________________________________________________________ Before the drive, did you have any concerns in regards to your driving?


__________________________________________________________________________________ Did the feedback you received answered some of these concerns?


__________________________________________________________________________________

Chapter 10: 245

After the drive, how would you rate the quality of your driving? Would you say it was? Excellent Good Average Fair Poor

Would you say that now you will consider seeking more help in regards to your driving (e.g. a driving refresher course, doctor’s consultation)

No Yes Don’t know yet

Now that you have received the driver instructor’s feedback, which statement better describe you?

I will not change my driving, as I believe I am a safe driver and my driving abilities has

not changed. I intend to start monitoring my driving abilities and changing my driving accordingly I intend to start avoiding some challenging driving situations I intend to consider giving up driving altogether

If you want to how hard will it be to reduce or give up driving? Very hard Somewhat hard Not hard at all

If you think giving up driving is not possible, would you say it is because I don’t want to rely on public transportation It will limit my mobility and independence I don’t have family members to rely on to drive me Other family members rely on me Other

________________________________________________________________________


In the near future, will you consider? Moving to a senior home or a retirement village,

Yes No

Moving to a place with a better transportation options, Yes No

Depending on other family members and relative to drive you, Yes No

Do you think that this form of feedback could be useful for helping older adults improve their driving abilities?

No Yes

Would you recommend this to any of your friends? No Yes

How can this form of feedback be improved in your opinion? ______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ Overall how would you rate the usefulness of this feedback?

Very useful Somewhat useful A little useful Not at all useful


Chapter 10: 247

Appendix K

Feedback provided by driving instructor

eprints.qut.edu.au the applicability of the precaution adoption process model in understanding older...

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