berkshire older drivers insight study

Age,Mobility&Risk

Version2.2 Tanya Fosdick September 2012

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CONTENTS EXECUTIVE SUMMARY ............................................................................................................................ 3

INTRODUCTION ....................................................................................................................................... 5

RISK PROFILE ........................................................................................................................................... 6

CRASH PROFILES ................................................................................................................................. 6

WHAT? ............................................................................................................................................ 6

WHEN? .......................................................................................................................................... 10

WHERE?......................................................................................................................................... 11

HOW? ............................................................................................................................................ 12

OLDER CAR DRIVER PROFILES ........................................................................................................... 14

MOSAIC ANALYSIS ............................................................................................................................. 19

INDEX OF MULTIPLE DEPRIVATION (IMD) ........................................................................................ 21

ENGAGEMENT PLAN ......................................................................................................................... 27

Self Assessment ............................................................................................................................ 27

Manual for Older Drivers .............................................................................................................. 27

Flourish Course ............................................................................................................................. 27

Driving Assessments ..................................................................................................................... 27

Website & Apps ............................................................................................................................ 27

Messages ....................................................................................................................................... 28

EVALUATION ..................................................................................................................................... 29

CURRENT LOCAL SCHEMES ............................................................................................................... 30

SUMMARY OF OTHER EVIDENCE AND SUCCESSFUL SCHEMES ........................................................ 30

EXISTING SCHEMES ....................................................................................................................... 31

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EXECUTIVE SUMMARY Analysis of collisions involving people over the age of 60 years, either resident of or injured within

Berkshire, has been undertaken to determine the extent of the issue. The following is a summary of

this report’s findings:

21% of Berkshire’s fatalities between 2006 and 2010 were aged over 60 years.

60% of Berkshire’s over 60 year old casualties were drivers. These drivers are most likely to be

aged between 60 and 69 years old.

84% of over 60 year old casualties injured in Berkshire were involved in a collision with a driver

aged 60 years or over (suggesting that passenger and pedestrian casualty rates could be

positively affected by reductions in driver risk). Passengers of older drivers tend to be of similar

age to the driver and so are likely to be peers or partners. Children (perhaps grandchildren)

appear as passengers for some of the younger age group of 60 to 64 year olds.

Over 60 year old car drivers from Berkshire tend to crash on weekdays and during the day. This

is consistent with national findings where some older drivers self‐regulate to avoid difficult

situations. Most of their collisions occur in daylight and fine weather. 69% were involved in

collisions on 30mph or 40mph roads.

39% were not at a junction whereas 30% were at a T‐junction and 12% were at a roundabout.

47% of the drivers were going straight ahead; 11% were moving off or stopping; and 14% were

turning right. Two‐thirds of the drivers were involved in collisions with one other vehicle.

56% of Berkshire’s older car drivers were considered to be at fault in their collision. This is

consistent with national research that found that 85 to 89 year olds were four times more likely

to have caused the crash than to have been innocently involved. The most common contributory

factors assigned to Berkshire’s older drivers are: ‘failed to look properly’; ‘failed to judge other

person’s path or speed’; and ‘poor turn or manoeuvre’. ‘Illness or disability, mental or physical’

and ‘Uncorrected, defective eyesight’ are more likely to be attributed to older drivers than all

drivers.

The highest percentages of collision‐involved older drivers come from West Berkshire; Windsor

and Maidenhead; and Wokingham. These areas have also seen the largest percentage increases

in the older population since 1981 and also have the highest percentages of crash‐involved older

drivers from the 25% least deprived IMD deciles. 65% of older drivers involved in collisions in

Berkshire came from Berkshire.

Super output areas within Wokingham, Bracknell Forest and Windsor and Maidenhead have

been highlighted as areas of high risk based on average annual rates of collision involvement.

One area of Wokingham has an average annual rate of one‐in‐332 older people involved in injury

collisions as drivers.

Three Mosaic Groups were highlighted as over‐represented amongst Berkshire’s older drivers –

these are Groups C, D and L. Groups C and D share some characteristics – both types of people

are successful, comfortably off and enjoy the arts and classical music. They are well educated

and are likely to have grown up children. They also have high internet usage. This Group is over‐

represented in the younger age group but does not represent as many drivers in the collision

statistics. However, the analysis did identify that there were some less affluent older drivers that

need to be accounted for. Their communication preferences are face‐to‐face engagement, local

newspapers and post.

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Three personas have been created to allow us to visualise the target audience and shape the

intervention to fit their needs.

Other research has found that a combination of on‐road training and in‐class education, tailored

to specific needs, can be a positive intervention with older car drivers. It has also been

recommended that ceasing driving should be made as painless as possible and that an

information pack, providing details of alternative transport and forms of support, should be

provided. There have been a variety of schemes based on these lines that have been provided

across the country

The intervention culminating from the research is called Flourish and is about assessment and

self‐regulation being key to safer mobility in later life. The intervention is comprised of multiple

components, including self‐assessment; a manual of advice; an educational course; driving

assessments; and website and apps. All components are based on the research contained within

this Insight Study.

Process and outcome evaluations will be undertaken by measuring the number of self‐

assessments undertaken and how many subsequent Flourish courses and driving assessments

booked.

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INTRODUCTION It is a known fact that there is an ageing population – a combination of lower birth rates and

reductions in mortality have led to a situation where there is a greater proportion of older people in

the population than younger people. “Currently in the UK around one in six of the population is aged

65 or over, and it is predicted that by 2050 one in five will be.”i With increases in the older

population, measures should be put in place to ensure their independence, mobility and safety when

using the roads.

This report sets out analysis undertaken using MAST, an online analysis tool which combines

casualty and collision data from the Department for Transport with socio‐demographic insights

created by Experian through Mosaic Public Sector. The postcodes of drivers and casualties involved

in collisions are used to determine which Mosaic Groups and Types these individuals are likely to

belong to and this can be used by road safety professionals to understand who needs to be targeted

in road safety interventions. The report looks at older people involved in collisions in Berkshire and

also, more importantly, focuses on older people who live in Berkshire who have been involved in

injury collisions. The intention of this report is to provide the road safety practitioner in Berkshire

with a full understanding of the types of collision involving older people and to equip them with the

tools to target the issue.

The report works through the analysis by first determining the extent to which older people are

involved in collisions in Berkshire and in what context they are involved. The analysis shows that,

overwhelmingly, older people are most likely to be injured in Berkshire as car drivers. As such, the

remainder of the analysis focuses most intensively on car drivers who are aged over 60 years old,

who are from Berkshire and who were involved in an injury collision between 2006 and 2010.

Environmental factors, such as when, where and how the older car drivers were involved in collisions

are explored and provide information on the topics and issues that could be focused upon within an

intervention.

A large part of the analysis focuses on profiling the older car driver, with the aim of producing

‘personas’ that can be used to visualise the target audience. These personas are created using a

variety of socio‐demographic data, including looking at Indices of Multiple Deprivation, rurality and

Mosaic Groups. Profiling in this way allows the practitioner to understand how the older drivers will

respond to a road safety intervention and in what way it should be delivered.

All of this culminates in an ‘Engagement Plan’, where experts from Safer Roads have used all the

available information from the analysis, external research, and learning outcomes from other older

driver schemes, to create an intervention design.

The report also contains a plan for evaluating the intervention, both in terms of assessing the

processes involved in delivery and the overall effectiveness of the scheme. Principles and tools

developed and promoted by RoSPA are used for creating the evaluation design.ii

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RISK PROFILE This profile covers two distinct areas: information about the crash and information about the person

involved. Both are relevant to the analysis and are considered separately.

CRASH PROFILES

WHAT?

In order to determine who to focus on for the analysis into older road users in Berkshire, some

preparatory work was undertaken. Firstly, a needs analysis was undertaken to establish whether or

not older road users represented a road risk in Berkshire. National research has found that:

From the evidence available it is possible to deduce that older people are as safe behind the

wheel as the rest of the population. Contrary to popular belief the majority of older drivers

have good driving records. Up to age 80 most older drivers appear to perform as well as

middle‐aged motorists and after this age only a small minority of active older drivers, often

travelling less than approximately 2000 miles per year, are at an elevated risk per mile basis.

The fatality rate per driving licence increases with age because as people get older they

become increasingly frail, and so are more vulnerable to injury when involved in an accident.

Older drivers are in fact involved in fewer slight accidents than younger travelers, but a

disproportionate number of older travelers are killed in road accidents due to frailty. Drivers

also tend to reduce the distance they travel as they get older, which increases the casualty

rate per mile driven for the group. iii

This study seeks to uncover what the casualty and collision issues are in Berkshire in relation to older

residents; how these findings compare to the national picture and what interventions could be

adopted to reduce Berkshire’s older citizens’ collision involvement.

Looking at collision data from 2006 to 2010, there were 141 people over the age of 60 years old who

were killed on Berkshire’s roads. This represents 21% of Berkshire’s fatalities. In terms of serious and

slight casualties, over 60 year olds represented 12% and 9% of Berkshire’s casualties respectively. It

would suggest that over 60 year olds are not over‐represented amongst Berkshire’s casualties

generally but are more likely to be killed or seriously injured (KSI) than the average Berkshire

casualty – 15% of over 60 years injured in Berkshire are KSI casualties compared to 10% for all

casualties injured in Berkshire. To put this into context using population data, over 65 year olds

represented 13% of Berkshire’s population in 2010 but, on average, 17% of fatal casualties in

Berkshire. When indices are applied to the average annual rates of fatalities per head of population,

over 65 year olds have an index of 123. This is in comparison to the index of 121 applied to 16 to 64

year olds in Berkshire, which is a much larger age range (unfortunately there are restrictions in the

available population data available by age at local authority level). The over‐representation as fatal

and serious casualties could be due to the type of collision older people are involved in; their

vulnerability to injury and likelihood to suffer a collision due to frailty and existing conditions; or a

combination of the two. The analysis would suggest that interventions aimed at older road users

would be beneficial to reduce this severity ratio, especially when the ageing population is

considered.

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The next thing to consider is how these older road users became casualties. The chart above shows

the casualty class of those over 60 year olds injured in Berkshire between 2006 and 2010. It provides

several pieces of useful information. Firstly, it shows that older road users are most likely to be

involved in collisions as drivers. In fact, 60% of the over 60 year olds injured in Berkshire were

drivers.

Secondly, it shows distinct reductions in collision involvement as drivers age. There is a sharp

reduction in the number of driver casualties from the 60 to 64 age range to 65 to 69 age range and

then a further steady reduction from 65 to 69 years down to 80 to 84 years. The downward trend

continues to the 90+ age range where very few drivers are injured. There are less dramatic

reductions in passengers and pedestrians as the ages of casualties increases.

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Driver Passenger Pedestrian Berks All Ages

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The last area to consider is to determine how the crash involvement of over 60 year olds has

changed, if at all, in Berkshire over recent years. The previous chart shows the number of over 60

year old casualties, by casualty class, since 2004. It shows that the number of older driver casualties

increased in 2005, remained steady until 2008 and has decreased in 2010 to just below the 2004

figure. The number of older pedestrians injured in Berkshire each year has remained fairly static and

older passenger numbers have actually increased. It also shows the number of casualties of all ages

injured in Berkshire (as the line). This line shows a similar trend to the older drivers pattern: an

increase to 2006 in the number of casualties, followed by a plateau and then a reduction after 2007.

To determine if there is an emerging trend in older casualties, all classes of older casualty have been

compared over time with the total number of casualties of all ages in Berkshire and, to put it into

context, for the UK. The following chart shows casualty rates compared to the 2004 to 2006

baseline. It shows that for the whole of the UK and for Berkshire, the numbers of 60 plus casualties

are reducing at slower rates than for casualties of all ages (although for 2010, the gap in Berkshire

was less pronounced).

Looking at the relationships between casualty class and driver age, the analysis found that, on

average, 84% of over 60 year olds injured in Berkshire were involved in collisions where the related

drivers was over 60 years old. This means that either the over 60 year old driver was the casualty;

the over 60 year old passenger was in a vehicle where the driver was over 60 years old; or the over

60 year old pedestrian was struck by a driver who was aged over 60 years old. The analysis also

found that the percentage of over 60 year old passengers injured in an older driver’s vehicle

increased with the driver’s age – 36% of the passengers injured in 60 to 64 year old drivers’ vehicles

were aged over 60 years old compared to 91% for 85 to 89 year olds.

The relationships between age of passenger and age of older driver are shown in the chart below.

The analysis has been undertaken for the whole of the UK to increase the sample size; however, the

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2004 2005 2006 2007 2008 2009 2010

Casualty Rates by Age

UK All Ages UK 60+ Berks All Ages Berks 60+

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pattern is very similar in Berkshire. It shows how the ages of passengers increase with driver age,

implying that the passengers are partners and peers. For the younger older driver, there are younger

passengers and this could reflect time spent caring for grandchildren in the early stages of

retirement.

These findings are consistent with an Australian study, which found that:

older drivers have been shown not to pose a substantial threat to other road users. Once

involved in a crash, older drivers are likely to be the ones either killed or injured. The next

largest group consists of older drivers’ passengers, themselves likely to be elderly.iv

Lastly, the vehicle type of older drivers involved in collisions in Berkshire was examined. It found that

86% of the over 60 year olds were driving a car.

Based on the scoping analysis, it has been decided that the rest of the report will focus on over 60

year old car drivers as not only do they represent the largest casualty and driver group amongst

older road users in Berkshire but there are potential casualty reduction benefits to be gained for

older passengers and older pedestrians from reducing older driver crash involvement. Analysis of

Berkshire’s pedestrians aged over 60 years old found that 15% were struck by a driver aged over 60

years old. Looking at the times of day for when older drivers, passengers and pedestrians are all

injured shows that they all share the same time patterns as shown overleaf. This would suggest that

older people tend to be out and about at the same times of day thus bringing older drivers and older

pedestrians into conflict. There have sadly been cases across the country where older drivers have

run over older friends and relatives (often on driveways and in car parks) by accidently pressing the

accelerator instead of the brake and reversing instead of moving forward. It could be that restricted

mobility of the older pedestrians prevents them from moving out of the way when these errors

occur.v

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60‐64 65‐69 70‐74 75‐79 80‐84 85‐89 90+

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WHEN?

The remainder of the analysis focuses on older drivers known to be from Berkshire rather than those

who were involved in collisions in Berkshire but could live anywhere in the country.

Analysis of the collisions involving over 60 year old car drivers from Berkshire produces the following

chart. It clearly shows that Berkshire’s older drivers tend to be involved in collisions during the

daytime (between 6am and 8pm) and are more likely to be involved in a collision on weekdays than

weekends. In fact, Berkshire’s older drivers are 29% less likely to be involved in a collision on an

average weekend than an average weekday. This compares to all Berkshire’s car drivers where they

are only 17% less likely to be involved in a collision on an average weekend than an average

weekday. There are not significant differences between individual weekdays, although 23% of the

older drivers were involved in collisions on Tuesdays compared to 16% on Mondays. Some

assumptions about journey purpose and potential self‐regulation could be made here – it might be

the case that family days outs and visits which occur at weekends are when younger family members

are more likely to drive their older relatives. Older drivers may have less choice about driving on

weekdays because family support is unavailable and therefore in order to access shops, medical care

and social situations, they must drive themselves. It could be that they practice self‐regulation,

though, and opt to drive when they believe traffic is going to be lightest.

Older car drivers from Berkshire were involved in collisions throughout the year, with slight

increases in June and September and a slight decrease in February. Only 19% of Berkshire older

drivers were involved in collisions in darkness and only 6% were in crashes which occurred at night

or with no lit streetlights. For all Berkshire’s car drivers, 28% were involved in collisions in darkness,

with 8% with no lighting at all. 84% of Berkshire older drivers were involved in collisions in fine

weather (no wind or rain) compared to 82% for all Berkshire’s car drivers. These figures reflect

national analysis where:

around the age of 60 to 65 many older drivers adapt their lifestyle and change their driving

patterns, thus avoiding driving in situations where they are uncomfortable: they avoid

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driving in the rain so they have fewer accidents when it is wet and more in dry weather, they

avoid peak hour traffic periods but have more accidents between 10am and 4pm and they

drive less at night so have fewer accidents in the dark but more in daylight.vi

WHERE?

Analysis of the locations in which older car drivers from Berkshire were involved in collisions shows

that 69% of the drivers crashed on 30mph or 40mph roads. Fifty‐four percent of the older drivers

crashed on urban roads and they were most likely to be involved in a collision on A roads or

unclassified roads (46% and 33% respectively).

The following chart shows the details of the junctions at which Berkshire’s older car drivers were

involved in collisions. It shows that 39% of the older drivers were not a junction when they were

involved in a collision; a further 30% were at a T‐junction and 12% were at a roundabout.

The areas of Berkshire in which older casualties were involved in collisions between 2006 and 2010

were also looked at and were thematically mapped to show areas of concentration at the medium

super output area level (MSOA).

There were four MSOAs which had the highest number of over 60 year old casualties between 2006

and 2010 and these are shown in the darkest blue on the map. The areas were Reading 011

(covering the Civic Centre, King’s Meadow, Coley and HM Prison); Slough 014 (covering Colnbrook

with Poyle Parish); West Berkshire 001 (covering Farnbrough, East Isley, Compton and

Chaddleworth); and lastly Windsor and Maidenhead 002 (covering Cookham Rise, Waltham St

Lawrence, Shurlock Row and Warren Row).

No Junction 39%

T‐Junction 30%

Crossroads 8%

Mini Roundabout 2%

Roundabout 12%

Private Entrance 7%

Multiple Junction Types 1%Other 1%

Slip Roads 1%

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HOW?

Looking at the circumstances surrounding the collisions, analysis found that two‐thirds of the older

car drivers from Berkshire were involved in a crash with one other vehicle.

In terms of manoeuvres, 47% of the older drivers were going ahead in a straight line; 11% were

moving off or stopping; and a further 14% were turning right.

It is possible to analyse the contributory factors (CF) recorded by a police officer when completing

the collision records. Individual CFs can be attributed to individual vehicles, which allows a basic

analysis of the reasons for crashes. The following analysis only looks at collisions investigated at the

scene by an officer and even then, it needs to be remembered that these factors reflect the officer’s

opinion at the time of reporting and may not be the result of extensive investigation.

Analysis shows that 56% of Berkshire’s older car drivers were considered to be at fault in their

collisions. The next chart shows that contributory factors assigned to Berkshire drivers initially

decreases from a peak with young drivers down to a plateau at 35 years old. Blameworthiness then

increases with each age group from 70 years old onwards.

As contributory factors are subjective and are the reporting Police Officer’s opinion at the time of

the incident, there is the potential for prejudices within reporting which could potentially account

for the higher percentages of blame attributed to younger and older drivers. It could also be the case

that incidents involving younger and older drivers are more clear‐cut and therefore it is easier to

attribute CFs or that because of higher casualty severities, there is better investigation.

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A qualitative study of collisions involving over 60 year olds was undertaken to get a more in‐depth

understanding of the circumstances of older driver collisions. The study involved taking 2,000

collision reports from 3 Midlands Police Forces and working through the full sequential nature of

each collision and examining witness reports, without any time pressures or prejudices from the

scene. vii The study found very similar results to the CFs attributed to Berkshire’s car drivers and are

shown in the next chart. It found that 60‐64 year olds and 65‐69 year olds were

no more likely to have caused a crash than they were to have been innocently involved in

such a crash. However, by the second to last age‐band (85‐89 years), older drivers as a whole

appeared to be over four times as likely to have caused a crash than they were to have been

innocently involved.viii

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CFs atrributed to Drivers by Age

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Blameworthiness Ratios for Older Drivers

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The most common CFs attributed to older drivers were ‘Failed to look properly’ – 27%, ‘Failed to

judge other person’s path or speed’ – 12% and ‘Poor turn or manoeuvre’ – 7%.

These percentages do not differ significantly when compared to all Berkshire car drivers (21%, 12%

and 6% respectively) and therefore apart from ‘Failed to look properly’; older drivers are not

behaving particularly differently to drivers of all ages.

Two CFs which are commonly associated with older drivers are ‘Illness or disability, mental or

physical’ and ‘Uncorrected, defective eyesight’. The illness CF was assigned to 4% of older drivers

(compared to 1% of all ages of car drivers) and the eyesight CF was assigned to 1% of older drivers

(compared to 0% of all car drivers). It could be due to better reporting that these CFs are attributed

more to older drivers in that police officers are giving consideration to these factors for older drivers

and undertaking more investigation.

OLDER CAR DRIVER PROFILES

Moving away from the ‘when, where and how’ questions, we can now explore the ‘who’ question. It

is essential to understand more about the people involved in the collisions, including information

about their everyday lives, as well as demographics.

Unsurprisingly, the largest age band of older Berkshire drivers is the 60 to 64 year old group. This

group accounts for one‐third of all over 60 year old car drivers from Berkshire. The age range 60 to

74 years old accounts for 76% of all Berkshire’s over 60 year old car drivers. Two‐thirds of the over

60 year old car drivers from Berkshire are men and this increases to 72% for over 75 year olds. The

percentages of men involved in collisions are perhaps to be expected given the ratios of licence

holders: “More than 30 years ago, only one in three men and one in 20 women aged over 70 held a

driving licence; today, three in four men and one in three women are licensed to drive.”ix Looking at

the trips older car drivers make:

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“Men in their 60s drive for almost as many trips annually as men in their 40s and 50s;

men in their 70s make more trips as drivers than do men in their late teens and 20s

Older people rely heavily on their cars. Two thirds of trips made by men and one third by

women in their 60s are as car drivers. In their 70s, more than half of trips by men and a

fifth by women are as car drivers.

Women make far fewer trips as car drivers than men as fewer of them have a driving

licence, and men, tend to be the main car driver”x

Using the residency of Berkshire older car drivers can put the issue into context. It is a known fact

that there is an ageing population – a combination of lower birth rates and reductions in mortality

have led to a situation where there is a greater proportion of older people in the population than

younger people. “Currently in the UK around one in six of the population is aged 65 or over, and it is

predicted that by 2050 one in five will be.”xi It therefore makes sense to put collision involvement

into context by comparing it to population rates. The following chart shows a variety of socio‐

demographic measures for each local authority within Berkshire.

The chart tells us several things: firstly, it shows us the areas which have had the largest increases in

older people since 1981; namely Bracknell Forest, West Berkshire, Windsor and Maidenhead and

Wokingham. It shows that there has been little change in the percentage of older people who live in

Reading and Slough since 1981. Secondly, unsurprisingly, it shows that a higher percentage of older

drivers involved in collisions come from the areas with the largest increases in the older population.

However, in West Berkshire, Windsor and Maidenhead and Wokingham, the percentage of collision‐

involved older residents is higher than the percentage of the population they represent. Lastly, it

shows that the authorities with the highest percentages of older residents from the least 25%

deprived areas who were involved in collisions are the same authorities with the highest

percentages of older collision‐involved drivers.

The issue of residency is explored in the next two tables. The first looks at the local authority in

which the older drivers were involved in a collision and compares this to where the older drivers live.

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Reading Slough BracknellForest

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% Increase in Older Pop since 1981 % Least Deprived 25%

% Most Deprived 25% % Older Collision Involved Residents

2010 % Pop 65+

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There is quite a range of how local the drivers are to the local authority in which the collision occurs

– for Slough only 37% of the older drivers lived in Slough, compared to Wokingham where 60% were

local residents. The benefits of joint working across Berkshire are shown in the highlighted row –

sixty‐five percent of the older drivers who are involved in collisions across Berkshire come from

Berkshire. There are other areas listed where older drivers who crash in Berkshire come from and

there is perhaps scope for working in these areas or with their local authorities in order to help

reduce their residents’ risk on Berkshire’s roads.

Crash Location 2006‐2010

Driver Home Bracknell Reading Slough West

Berkshire RBWM Wokingham Berkshire

Local to authority 52% 45% 37% 49% 52% 60% ‐

Local to Berkshire 72% 69% 49% 57% 69% 74% 65%

London 1% 0% 11% 2% 4% 0% 3%

South West 3% 3% 3% 9% 2% 3% 3%

Hampshire 5% 4% 2% 7% 1% 4% 4%

Surrey 4% 1% 4% 1% 3% 1% 2%

Buckinghamshire 1% 0% 11% 1% 6% 2% 3%

Oxfordshire 1% 5% 0% 5% 1% 2% 2%

The second table looks at residency of older drivers compared to the location in which they were

involved in a collision and therefore explores what Berkshire’s residents are involved in outside of

the area. It shows that 72% of Berkshire’s residents are involved in collisions in Berkshire and that

between 52% and 62% were from the local authority in which they crashed. There are a few

authorities to which Berkshire’s residents travel to and are subsequently involved in collisions at but

the two tables are implying that more older drivers travel to Berkshire and are involved in collisions

than older drivers from Berkshire going elsewhere and crashing.

Residency 2006‐2010

Crash Location Bracknell Reading Slough West

Berkshire RBWM Wokingham Berkshire

In Local Authority 52% 62% 53% 60% 50% 55% ‐

Berkshire 67% 77% 68% 75% 67% 78% 72%

London 5% 0% 8% 1% 2% 2% 3%

South West 1% 6% 1% 6% 3% 3% 4%

Hampshire 6% 2% 0% 8% 1% 4% 4%

Surrey 14% 1% 3% 2% 11% 4% 6%

Buckinghamshire 0% 3% 15% 0% 10% 2% 5%

Oxfordshire 0% 8% 2% 4% 1% 4% 3%

Thinking of how far older car drivers from Berkshire travel, the following chart shows the average

distance from home at the time of the crash. It shows that older car drivers in England, the South

East and Berkshire all share similar average distances from home (between 17.3 and 17.6km). Many

of Berkshire’s older drivers have similar average distances from home, apart from Slough (where

average distances are less at 9.3km) and West Berkshire and Bracknell Forest (where older drivers

are slightly further away from home – 22.3km and 20.2km respectively). The chart also shows the

Page | 17

average distance from for all car drivers. It shows how the average distance from home varies across

the local authorities by age and that in Slough, Wokingham and Reading, older drivers tend to be

closer to home than all drivers. In West Berkshire and Bracknell Forest, older drivers tend to be

slightly further from home when involved in a collision. However, there should be some caution

applied when interpreting these distances as the small number of drivers involved in the sample

could affect the averages.

As with thematically mapping the locations of the older casualties injured in Berkshire, the home

areas of older drivers from Berkshire have also been mapped. To put the information fully into

context, annual rates have been calculated by taking the annual number of collision‐involved over 65

year old drivers and dividing it by the number of over 65 year olds living in each of the MSOAs. The

analysis is limited to over 65 year olds as this is the age group for which population numbers at

MSOA level are provided. This produces a risk rating for each area of Berkshire in the format of a

one‐in‐figure; the lower the rate, the higher the risk.

0 5 10 15 20 25

Bracknell Forest

Reading

Slough

West Berks

Windsor & Maidenhead

Wokingham

Berks

South East

England

Average Distance from Home (km)

All Drivers Older Drivers

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The areas with the highest risk are shown in the darkest green. The four areas with the lowest

annual rates, and thus the highest risks, are Wokingham 018 (covering Carter’s Hill, Arborfield and

Long Moor); Bracknell Forest 009 (covering Easthampstead Park area); Windsor and Maidenhead

001 (covering Pinkneys Green); and Wokingham 014 (covering Dowlesgreen and the south‐eastern

area of Wokingham).

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MOSAIC ANALYSIS

As well as demographic and spatial analysis of older car drivers, we can also undertake socio‐

demographic analysis using Mosaic. Mosaic is intended to provide an accurate and comprehensive

view of citizens and their needs by describing them in terms of demographics, lifestyle, culture and

behaviour. By matching postcodes we can segment the older driver community into one of 15

groups and analyse their relative representation in the statistics based on population figures.

Mosaic analysis by age band is less accurate than looking at all ages because it uses the entire

population of a postcode for the index value, rather than the population of the same age band

within a postcode. Nevertheless it gives a good idea of relative under‐ and over‐representation.

The first analysis looks at Mosaic Groups for all over 60 year old car drivers from Berkshire. The

group with the highest representation, shown on the dark shaded area, is Group D with 281 drivers

in five years. Other groups with high representations (over 100 drivers) are C, E and F. The index

values, which demonstrate over‐ or under‐representation based on population figures, tell a slightly

different story with Groups A, B, C, D, J and L being significantly over‐represented (index values over

120).

When carrying out Mosaic analysis you initially look for levels of high representation and high index

scores in individual groups and this is the case with Groups C and D. Groups E and F are highly

represented in the driver numbers but are less at risk compared to the total populations.

In the demographic analysis earlier, it appeared that there were two distinct age groups amongst

Berkshire’s older car drivers: those aged 60 to 74 years old (which account for 76% of crash‐involved

older drivers) and those aged 75 years and older. Further Mosaic analysis was carried out on these

two age bands.

0

50

100

150

200

250

0

50

100

150

200

250

300

A B C D E F G H I J K L M N O

Over 60 year old Car Drivers ‐Mosaic Profile

Value Index

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Unsurprisingly, the 60 to 74 year old Mosaic profile is very similar to that of all older drivers, because

this is the largest age band. There were 132 60 to 74 year old drivers from Group C (with an index of

158) and 204 from Group D (with an index of 155).

The over 75 year old Mosaic profile is shown in the chart below and reveals Group D is the most

over‐represented (with an index of 174) where there were 77 drivers.

0

50

100

150

200

250

0

50

100

150

200

250


60‐74 year old Car Drivers ‐Mosaic Profile

Value Index

0

20

40

60

80

100

120

140

160

180

200

0

10

20

30

40

50

60

70

80

90


Over 75 year old Car Drivers ‐Mosaic Profile

Value Index

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INDEX OF MULTIPLE DEPRIVATION (IMD)

As well as looking at the Mosaic socio‐demographic classifications, it also possible to look at relative

wealth using the UK IMD values for each postcode. IMD uses a range of economic, social and

housing data to create a single deprivation score for each small area of the country. The analysis

uses deciles, which creates ten groups of equal frequency, ranging from the 10% most deprived

areas to the 10% least deprived areas.

The results shows that older car drivers in Berkshire tend to come from the least deprived areas. This

is perhaps unsurprising given that 32% of Berkshire’s lower super output areas (LSOA) are classified

as being in the 10% least deprived decile. The previous chart shows the number of Berkshire

0%

3% 4%

7%

8%

8%

10%

10%15%

35%

IMD Decile Distribution ‐ Berkshire

Most Deprived 10%

Most Deprived 20%

Most Deprived 30%

Most Deprived 40%

Most Deprived 50%

Least Deprived 50%

Least Deprived 40%

Least Deprived 30%

Least Deprived 20%

Least Deprived 10%

0

20

40

60

80

100

120

140

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Numbers of Berks 65+ Drivers per IMD ‐Indexed by Pop

65 plus Drivers Index

Page | 22

collision involved drivers who live in each IMD vigintile, indexed against the number of 65 plus

residents of each vigintile. These indexes are the red bars and as with Mosaic, an index of 100 shows

an over‐representation. There are more indexes of over 100 in the least deprived vigintiles than in

the most deprived ones.

A useful tool created by the Office of National Statistics is the Atlas of the Indices of Deprivation

2010 for England which maps to LSOA level the various indices of deprivation. Areas such as West

Berkshire, Wokingham and Windsor and Maidenhead are mostly shown as light blue in the Index of

Multiple Deprivation maps (as being least deprived) but when the Barriers to Services indicator is

applied, these areas have LSOAs in the most deprived quintile. This indicator includes road distances

to a GP surgery, post office, primary school and general store or supermarket and suggests a reason

for the higher collision involvement of older drivers from these local authority areas; namely being

forced to drive longer distances to access services. Screen shots of Wokingham are shown below to

demonstrate the differences between overall IMD and the Barriers to Services indicator.

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PERSONAS

Following the analysis of risk, it is necessary to combine the elements of casualty and collision

profiling to create a person or personas which capture the key characteristics of those communities

or groups most at risk. Although a persona will not typify all, or perhaps even a majority of those

involved in collisions, it should represent a significant proportion of those who are most vulnerable.

The analysis of the socio‐demographic data as well as the collision information has allowed a picture

to be built up about the kinds of older car drivers from Berkshire who are involved in collisions. We

know that they mostly live in urban areas and are potentially self‐regulating their driving by avoiding

bad weather, darkness and higher speed limits. They may be experiencing deprivation in the form of

barriers to services. The data show that they are predominantly male. Older car drivers are often

carrying older passengers with them and therefore by targeting the drivers, there could potentially

be benefits to be gained in passenger casualty rates.

The Mosaic data has shown that there are three Groups which are over‐represented in the collision

statistics, with Group D, ‘Successful professionals living in suburban or semi‐rural homes’,

representing the largest number of drivers and a high index. It also covers both age groups of 60 to

74 years old and 75 years and older. Group C, ‘Wealthy people living in the most sought after

neighborhoods’ is over‐represented and has a high index.

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LeastDeprived MoreDeprivedGroupC Group D Group L

SuccessfulRewardingcareers

Substantialwealth

Influential

LuxuryItems

Professional

Well‐educated

Specialistadvice

Exclusivelypensioners(over‐represented–9.19%

ofGroup)

Suburban/semi‐rural Executive & managers

Small businesses Senior positions Significant equity

Married with children Comfortable

Good education Theatre/arts Car ownership

Exclusively pensioners (over‐represented – 10.13% of

Group)

Retired Bought a smaller property

Bungalow Pensions

Holidays, cruises Specialist shops

Pay off credit card in full Grandchildren Heritage sites

Exclusively pensioners (over‐represented – 12.09% of

Group) Single pensioner (over‐represented – 23.92% of

Group)

Receptiveto:Internet

Telephone

Post

Unreceptiveto:

Face‐to‐face

Localnewspapers

Receptive to: Telephone Internet Post

Magazines Unreceptive to: Face‐to‐face

Local newspapers National newspapers

Receptive to: Face‐to‐face

Local newspapers Post

Unreceptive to: Internet Telephone

Mobile telephone

60‐74yearsold 60‐74 years old

75+ years old 60‐74 years old

Groups C and D share some characteristics – both types of people are successful, comfortably off

and enjoy the arts and classical music. They are well educated and are likely to have grown up

children. Car ownership is high and they are likely to have multiple cars in the household. Group C’s

annual mileage is 6,813 compared to Group D’s 8,287.

In order to engage with these groups, it is necessary to identify what media they access. Group C has

the second highest internet usage of any group in the country (57% use it every day) and Group D

has the 3rd highest (50% every day). The types of internet sites Group D most commonly visit are

related to stocks and shares; house and garden; travel; property; and insurance. Group C also visits

sites associated with stocks and shares and property and in addition view news and media; food and

beverage; and educational sites. The other key communication channels for these two groups are

telephone and post. Both are unreceptive to face‐to‐face and local newspapers.

Page | 25

Both Groups have similar shopping patterns and both tend to shop at Sainsbury’s and Marks and

Spencer.

Group L, ‘Active elderly people living in pleasant retirement locations’, is also shown in the table.

This Group is over‐represented in the younger age group but does not represent as many drivers in

the collision statistics. However, the analysis did identify that there were some less affluent older

drivers that need to be accounted for. This group tends to be aged 60 to 74 years old and they are

less well educated or comfortably off than Groups C and D.

This Group is only likely to have one car and has an annual mileage of 5,527. They enjoy classical

music and reading books. This Group has the second lowest internet usage, with 24% using the

internet every day. Their communication preferences are face‐to‐face engagement, local

newspapers and post. They are unreceptive to the internet, telephone and mobile telephones and

so have opposite communication preferences to the other Groups.

In essence, there are 3 personas (shown in order of number of drivers they represent):

1. ‘David’ – is in his mid to late sixties and is a recently retired professional. He was successful

in his career and is wealthy. He has grown up children and the first change to his lifestyle

after retirement is spending more time caring for his grandchildren. He has multiple cars and

drives high mileage, perhaps due to habit but also to access services. He enjoys the arts and

classical music and tends to shop at Sainsbury’s and Marks and Spencer. An important

engagement tool for him is the internet and his website interests could allow the use of the

language of ‘investment and return’. There are initial post‐retirement changes to his lifestyle

and driving patterns and he will start to self‐regulate the times he drives as he gets older. He

is no more likely to have caused the collision in which he was involved than been an

innocent participant. As an educated individual, he may well be receptive to an intervention

that improves his driving awareness and his practical skills. However, as a successful person,

he will not be receptive to be lectured and as he is not more likely to have caused a crash

than people of other ages, he may question ‘what’s in it for him?’ Driver cessation is unlikely

to be a topic with him. (Between 2006 and 2010, there were 336 drivers from Berkshire

involved in collisions that fit this persona).

2. ‘Peter’ – is aged in his late seventies and is an older version of David. He specifically belongs

to Mosaic Group D. He has similar interests to David but spends less time caring for his

grandchildren as he gets older. The self‐regulation of his driving has continued but skills

errors are creeping in, possibly due to medical conditions. As his age increases, so does his

blameworthiness. He will still retain the characteristics of a successful professional and may

find the idea of ceasing driving difficult to cope with. It may be necessary to engage the

assistance of his spouse, children or doctor to persuade his to evaluate his driving skills.

(Between 2006 and 2010, there were 77 drivers from Berkshire involved in collisions that fit

this persona).

3. ‘John’ – is in his mid to late sixties and he has recently retired and bought a smaller property,

possibly a bungalow. He is likely to spend quite some time looking after his grandchildren.

He is less wealthy than David and drives fewer miles. It may be that he would be receptive to

information on alternative forms of transport (buses and cycling) for the financial benefits.

As David, he is not more likely to have been caused a collision than been innocently involved

Page | 26

and so would need to see the benefits of an intervention. He, too, will have changed his

driving patterns after retirement but may also be subject to ‘barriers to services’ deprivation

and be forced to drive. He is not receptive to the internet and instead prefers face‐to‐face

interaction: there could be a place for road safety officers to directly engage with him.

(Between 2006 and 2010, there were 42 drivers from Berkshire involved in collisions that fit

this persona).

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ENGAGEMENT PLAN

It is important that the intervention design is regarded as offering positive support for the older

driving community and that it chimes with the lifestyle choices of the more mature driving

population.

‘Flourish’ seeks to convey a positive unfurling of the future with imagery that will chime with an

audience who have invested time and energy into home and garden.

SELF ASSESSMENT

Research shows that Self‐Assessment in older drivers encourages the process of self‐regulationxii, a

key element of the engagement plan will therefore be the development of a self‐assessment tool for

older drivers. Drawing on the work of the Royal Automobile Association of Queensland and the AAA

Foundation for Traffic Safety, the questionnaire will be delivered online and provide instant

structured feedback on areas of risk prevention and mitigation.

MANUAL FOR OLDER DRIVERS

The flourish manual will provide a distillation of advice on the issues raised by the self‐assessment

tool and that are pertinent to the older driving population in general.

The manual will be available for distribution by local authorities with a digital version presented

online.

FLOURISH COURSE

Adopting a similar approach to the DriveStart model of unified branding for a portfolio of courses

and events working alongside projects that are already underway elsewhere, Flourish branding and

exhibition materials will be made available for local authority use.

A proposed curriculum will also be developed that draws on the insights from this study and

research into other courses available elsewhere.

DRIVING ASSESSMENTS

Adopting a model similar to the ‘Be a Better Driver’ scheme in Buckinghamshire would allow driving

assessments to be carried out by Advanced Driving Instructors who have received extra training to

support older drivers.

The cost for these courses would be borne by the individual, though there would need to be a

process of training and vetting appropriate ADIs to undertake the training.

WEBSITE & APPS

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The elements above would be underpinned by website information and possibly a smartphone

application which has been highlighted as a potential access point to informationxiii.

MESSAGES

KEY THEME

Assessment and self‐regulation is the key to safer mobility in later life

MEDIA MESSAGES

You have planned for and invested in your retirement – look after yourself to make sure it

counts

Older Drivers do a great job keeping themselves safe; we can help them even more by

training and assessment

Ill‐health & impairment increase risks; but these can be managed to keep you mobile and

active

FACTS

WHEN?

76% of all the drivers were involved in collisions between 8 am and 5pm

84% of the drivers were involved in collisions in daylight or with lighting present

WHERE?

61% were at junctions, crossroads or roundabouts

69% were on 30mph or 40mph roads

HOW?

56% of the older drivers were considered to be at fault

The most common reason was ‘Failed to look properly’

‘Poor turn or manoeuvre’ was another common contributory factor, as was ‘Failed

to judge other person’s path or speed’

MEASURES

Number of self‐assessment questionnaires completed

Number of Flourish Manuals distributed

Number of flourish courses attended

Numbers or driving assessments booked

Website traffic

Page | 29

Inputs Staff

Partners

Research

Time

Funding

Outputs # of engagement

events

# of mature drivers spoken to at events

# of Flourish manuals distributed

# of self‐assessments completed

# of courses booked

# of driving assessments booked

Short Term

Outcomes Mature drivers

spoken to at events and provided with information on safer mobility

Mature drivers encouraged to visit the Flourish website and gain more information

Mature drivers receive Flourish manual with information on safer mobility

Med

ium Term Outcomes Mature drivers undergo self‐assessment

Mature drivers attend Flourish course to discuss safer mobility

Long Term

Outcomes Mature drivers

reflect on their driving and make choices surrounding self‐regulation and skills assessing

Mature drivers undertake driving assessments

EVALUATION

An evaluation framework has been created which builds upon the analysis in this Study. Evaluation

work will see to measure outcomes that are reflective of changes in the knowledge, intentions,

attitudes and behavior of the target audience of older drivers.

The following logic model shows the aims and objectives of Flourish and how the intervention will be

measured. Uptake of self‐assessments, courses and driving assessment will be the main measures of

the evaluation. This will allow the Safer Roads team to undertake a process evaluation of the

intervention (to ensure that the correct mechanisms are in place to engage with the right people

and that the outputs lead to the desired outcomes). It will allow an outcome evaluation to be

undertaken by measuring the overall results of the intervention and to assess whether the aims and

objectives have been achieved.

AIM: To encourage assessment and self‐regulation amongst mature drivers to provide safer mobility in later life

OBJECTIVES: To encourage X number of mature drivers to undergo self‐assessment

For X number of mature drivers to attend a Flourish course

For X number of mature drivers to take a driving assessment

ASSUMPTIONS: That information and self‐assessment will lead to self‐regulation and decision to assess skills

EXTERNAL FACTORS:

Barriers to services could limit ability to self‐regulate driving Perceived restrictions on independence and freedom could limit willingness to engage Economic factors could limit ability to pay for courses/driving assessments

Page | 30

CURRENT LOCAL SCHEMES

In Berkshire, only West Berkshire Council has a current programme of engagement with older

drivers. The ‘O’ Drivers course has been promoted through a number of locations where the ‘retired

but mobile’ populous are likely to congregate; places such as garden centres. Whilst the information

has been well received and a number of bookings received attendance at the most recent course

was quite poor.

SUMMARY OF OTHER EVIDENCE AND SUCCESSFUL SCHEMES

Devon County Council’s Knowledge Transfer Partnership project with the University of Plymouth

conducted a literature review of older driving training interventions. The research found that

training interventions have focused on addressing the needs of older drivers, for example

identifying particular impairments, changing driver behaviour and knowledge and promoting

behavioural strategies to compensate for age decline. Increasing knowledge and behaviours

that will lead to safe driving is assumed to lead to a reduction in collisions. Research has

shown that the combination of on‐road training and in‐class education results in increased

awareness, driver knowledge and skills specific to driving. Older drivers have been shown to

be good candidates for in‐class education training due to their motivation to continue

driving, time to attend class and ability to acquire information in an interactive

environment.xiv

The research also found that training interventions need to be tailored to specific needs as it was

identified that women require information on driving skills and encouragement to continue driving.

Men, on the other hand, often find the idea of stopping driving harder to accept and need

information on health and age‐related limitations.xv

Driving is often seen as the most obvious choice for maintaining mobility as it gives individuals the

freedom to go where they please when they want and benefits those who can’t walk long distances

or carry shopping. Interventions should be aimed at making driving as safe as possible for as long as

possible.

The car’s status and role in modern day life can make it particularly difficult to give up

driving. This will be even harder for the younger old who are more likely to have driven all

their lives. In addition, as a result of urban planning, it is more common for them to drive to

the out of town supermarket than walk to the high street... However, although there are

many advantages to owning a car, there are also disadvantages, and many people choose

not to or simply cannot. Three quarters of single people over the age of 65 do not have a

car.xvi

As giving up driving has been linked to an increase in depression and lonelinessxvii and that mobility is

important to life satisfaction and quality of life, any intervention which might lead to the cessation of

driving should aim to make the process as easy and painless as possible.

PACTS recommends the development of a national information pack to inform and raise

awareness amongst older drivers, promote mobility, and encourage conversations and

reflections which may not have otherwise happened. Producing this content nationally

Page | 31

would ensure a research‐based approach and consistency across local authorities, and

would benefit from economies in scale….

Following on from awareness‐raising and information providing, the next stage would be

formal assessment and training. PACTS recommends the development of a national standard

course for older drivers, in line with best practice and academic research. xviii

Information which could be covered in the national information pack could be:

How to renew the driving licence and information on self‐declaration;

The potential difficulties older drivers may face and possible self‐regulation;

How vehicles can be made safer by adapting the vehicle or adding active safety devices;

Awareness of the cost of owning and driving a car;

Advice on vision and fitness to drive, particularly for those on medication or suffering from

dementia;

A self‐assessmentxix

In addition, local information could be added that includes:

Local information on transport provision/prices

Cycle map and information on bike storage facilities

A bus journey voucher – information on timetables and fares

Information on taxis with prices of example trips

EXISTING SCHEMES

The Driving Standards Agency (DSA) launched a scheme in 2002 entitled Arrive Alive Classic which

provides presentations for people aged over 50 years on topics such as complex road systems, rising

traffic volumes, effects of medication, eyesight and licensing requirements at 70 years old. The

presentation is free of charge and is conducted by an experienced, current, DSA driving examiner. It

last approximately an hour and includes a short DVD.

http://webarchive.nationalarchives.gov.uk/+/www.direct.gov.uk/en/Motoring/DriverSafety/DG_402

2428

In 2008, Norfolk County Council launched a scheme in partnership with the Department for

Transport for drivers who by age, ill health or mobility reasons would benefit from guidance and

advice via a scheme called GOLD – Guidance for the Older Driver.

The scheme coordinator visits the client in their own home and carries out an informal screening

process centred on driving and health/medical questions and eyesight screening. The client is

subsequently contacted to arrange a drive with a specialist appointed trainer, who will take the

client out in the client’s own vehicle and on roads they are familiar with. Further drivers are

arranged if necessary and advice on future mobility decisions provided if the client decides to cease

driving or they have been advised to refrain from driving, following the assessment. Discussions on

future mobility sometimes involve the client and family.

http://www.think.norfolk.gov.uk/Older‐Driver/Training‐and‐Campaigns

Page | 32

SAGE (Safer Driving with Age) is a program established by Gloucestershire County Council in 2000.

In a similar format to Norfolk’s scheme, a medication and health review is undertaken but involves

the client’s GP or practice nurse. The client must have had an eye examination in the last 12 months

and a ‘field test’ should be undertaken by their GP if the client has a medical condition which has

affected their field of view. A driving assessment is undertaken in the client’s own car, on roads they

are familiar with, with an experienced driving assessor. A written report is produced at the end of

the drive. The program is a three‐stage process and needs the buy‐in of the client’s GP or practice

nurse to complete the medical assessment. The current fee is £30 for a one hour assessment.

http://roadsafety‐gloucestershire.org.uk/wp‐content/uploads/2011/04/SAGE‐fact‐sheet.pdf

Dorset County Council provides the Dorset Driver course, which involves two elements: the first part

is a Driver Refresher Course us two hours long and is aimed at helping drivers update their

knowledge and skills through group discussions about observation, distractions, safety margins, dual

carriageways/motorways and roundabouts. The session costs £5. The optional Practical Refresher

Course lasts 90 minutes and involves the client driving their own car with an experienced driving

professional. The route usually includes town and country driving and costs £37.50.

http://www.boroughofpoole.com/transport‐and‐streets/public‐transport/drive‐55‐plus‐road‐safety‐

information/

Buckinghamshire run a similar scheme to SAGE called Be a Better Driver. It includes a driving

assessment for the cost of £35 and allows individuals to make referrals to the program, so

concerned family, friends and professionals can recommend an older driver attend.

http://www.buckscc.gov.uk/bcc/news/older_driver.page

Devon Road Casualty Reduction Partnership launched its Driving Safer for Longer (DSFL) program in

2007. An information pack and website provides information on mobility, fitness, medication,

driving tips and other travel options. The program also includes a two hour workshop and a practical

driving skills assessment. More information on the success of the scheme can be found on page 25

of Poppy Husband’s report ‘A literature review of older driving interventions: implications for the

delivery programmes by Devon County Council and Devon Road Casualty Reduction Partnership’.

http://www.devon.gov.uk/drivingsaferforlonger

Sussex Safer Roads Partnership has produced a brochure called Safer for Older Drivers which

provides extensive but clear information on eyesight, hearing, mobility and medication. It also

provides information on the law, provides suggestions for alternative modes of transport and how to

calculate the yearly cost of motoring. The brochure provides information on their Experienced Driver

Assessment, which involves the client undertaking a 45 minute driving assessment in their own car,

in a similar format to other schemes.

http://www.sussexsaferroads.gov.uk/safer‐for‐older‐drivers.html

Page | 33

i Baster, N., It’s my choice – Safer mobility for an ageing population, Parliamentary Advisory Council for Transport Safety, 2012, p.3 ii http://www.roadsafetyevaluation.com iii Box, Gandolfi and Mitchell, Maintaining safe mobility for the ageing population, RAC Foundation, April 2010, p. 15 iv Baster, N., , p.3 v Examples of older pedestrians (or disabled people) injured by older drivers are included below: http://www.thisishullandeastriding.co.uk/Beverley‐woman‐87‐dies‐hit‐elderly‐neighbour‐s‐car/story‐11955459‐detail/story.html http://www.telegraph.co.uk/news/uknews/crime/7951296/Elderly‐driver‐who‐killed‐disabled‐woman‐walks‐free‐from‐court.html http://www.stornowaygazette.co.uk/news/elderly‐driver‐being‐questioned‐after‐suspected‐hit‐and‐run‐1‐2140959 http://www.dailyrecord.co.uk/news/scottish‐news/2012/03/25/driver‐who‐ran‐over‐and‐killed‐fisherman‐hits‐pedestrian‐on‐skye‐s‐only‐zebra‐crossing‐86908‐23801187/ vi Hopkin, J., Older Drivers – Safe or unsafe?, IAM Motoring Trust, 2010, P.3 vii Clarke, D., Ward, P., Truman, W., and Bartle, C., Collisions Involving Older Drivers: An In‐depth Study, Department for Transport, September 2009, p. 11 viii ibid., p. 16 ix Hopkin, p. 4 x ibid., p. 5 xi Baster, N., p.3 xii Berry, ‘Can Older Drivers be Nudged?’ 2011, Pg 38 xiii ibid., p.39 xiv Husband, P., A literature review of older driving training interventions: implications for the delivery programmes by Devon County Council and Devon Road Casualty Reduction Partnership, 2010, p. 5 xv Baster, N., p.30 xvi ibid., p. 34 xvii ibid., p.35 xviii ibid., p.45 xix ibid., p.45

berkshire older drivers insight study

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