gujarat technological university ahmedabad [february … · employee wellness: a study of banking...

Employee Wellness: A study of Banking Sector in Gujarat

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

In

Management

by

Thakar Manali Bankimbhai [Enrollment No. 139997292010]

under supervision of

Dr. Sampada Kapse

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD [February – 2019]

Employee Wellness: A study of Banking Sector in Gujarat

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

In

Management

by

Thakar Manali Bankimbhai [Enrollment No. 139997292010]

under supervision of

Dr. Sampada Kapse


AHMEDABAD

[February – 2019]

DECLARATION

I declare that the thesis entitled Employee Wellness: A study of Banking Sector in Gujarat

submitted by me for the degree of Doctor of Philosophy is the record of research work carried

out by me during the period from January, 2014 to October, 2018 under the supervision of

Dr. Sampada Kapse and this has not formed the basis for the award of any degree, diploma,

associateship, fellowship, titles in this or any other University or other institution of higher

learning.

I further declare that the material obtained from other sources has been duly acknowledged in

the thesis. I shall be solely responsible for any plagiarism or other irregularities, if noticed in

the thesis.

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Name of Research Scholar: Thakar Manali Bankimbhai

Place : Ahmedabad

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Tolani Motwane Institute of Management Studies

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(PH001)

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i

ABSTRACT

Since last few years, banks have been going through enormous changes in terms of

organization and structure. Technological innovations and new structure of the operation

have made an impact on the working conditions and daily lives of employees. Continuous

changes in employment and working conditions are significantly reshaping working lives. It

has a relevant impact not only on companies‘ organization but also on employee‘s health.

Thus, it is imperative that wellness of bank employees is assessed. Thus, the purpose of the

research investigation was to develop the Employee Wellness Scale and examine its

psychometric features in a sample of bank employees. A correlational research design was

employed for this investigation.

Specifically, the researcher examined: (a) the factor structure of the Employee Wellness

Scale with a sample of Bank employees; (b) the internal consistency reliability of the

Employee Wellness Scale; (c) the relationship between the Employee‘s total Wellness Score

and their reported demographics; (d) the relationships between the Employee‘s factor wise

total score and their reported demographics; and (e) the prevalence of health issues among

bank employees in Gujarat.

A review of the literature is provided, discussing theoretical and empirical support for all the

items on Employee Wellness Scale. The data was collected by face-to-face administration.

The sample size for the investigation was 496. Data analysis resulted in a seven-factor

Employee Wellness Model that accounted for 55% of the total variance. The findings of the

research suggest, that early onset of noncommunicable diseases among bank employees is a

major concern. Thus, there is an urgent need for comprehensive and integrated interventions

to reduce the prevalence of health issues and its risk factors among bank employees in

Gujarat.

ii

Acknowledgement

It could never have been possible to complete this thesis without the help of so many people.

First and foremost, my sincere thanks go to my academic supervisor, Dr. Sampada Kapse

and, DPC members Dr. P. V. Murthy and Dr. Narayan Baser for their knowledge, guidance,

constructive criticism and support over the past years. It is really a pleasure to work with

them.

Special thanks to Dr. Sampada Kapse who has always given me timely feedback and is ever

so willing to help me. But above all, it is her true understanding of a student, which I would

consider makes her the best supervisor I have met so far.

My heartfelt gratitude goes to all informants who have participated in this study, but for the

confidentiality, I will not mention their names here. However, my appreciation goes to those

who gave their valuable time in completing the questionnaire and in allowing me to interview

them. Special thanks to Dr. Manish Pandya for helping me proofread and for his kind

suggestions and guidance during this study.

In addition, my appreciation goes to Dr. Bhavesh Vanparia and Prof. Pratibha Nair for their

suggestions and guidance, and all my friends for their direct and indirect help and assistance

during the research.

My final acknowledgements go to my beloved family for their encouragement, love and

unstinting support throughout my PhD study.

iii

Dedication

This thesis is dedicated to my parents Mr. Bankim Thakar and Mrs. Rama Thakar. Without

their support the completion of this work would not have been possible.

iv

Table of Content

Abstract i

Acknowledgement ii

Table of contents iv

List of Figures vii

List of Tables viii

List of Appendices x

1 Introduction 1

1.1 Background of the Study 2

1.2 Statement of the Problem 3

1.3 Significance of the Study 4

1.4 Purpose and Research Questions 4

1.4.1 Objectives 4

1.4.2 Research Questions 5

1.5 Research Design 7

1.6 Population and Sample Size 7

1.7 Instrument Procedures and Instrumentation 7

1.8 Ethical Considerations 8

1.9 Limitations of the Research 8

1.10 Chapter Summary 9

2 Literature Review 10

2.1 Historical Overview of the Wellness paradigm 10

2.2 Definitions of Wellness 12

2.3 Models of Wellness 12

2.3.1 The National Wellness Institute Model 12

2.3.2 Lifespan Development Model 14

2.3.3 Wheel of Wellness Model 14

2.3.4 Indivisible Self Model 17

2.3.5 Perceived Wellness Model 21

2.3.6 The Wellness/Illness Continuum Model 22

2.3.7 Conclusion 23

2.4 Wellness Measurement Instruments 23

2.4.1 Life Assessment Questionnaire 24

2.4.2 Optimal Living Profile 24

2.4.3 Perceived Wellness Survey 24

2.4.4 Test Well (National Wellness Institute, 1992) 25

2.4.5 Wellness Evaluation of Lifestyle Inventory 25

2.4.6 Five Factor Wellness Inventory 26

2.4.7 Summary 26

v

2.5 Employee Wellness 26

2.5.1 Introduction 26

2.5.2 Employee Wellness Programs 28

2.5.3 Evolution of Employee Wellness Practices 28

2.5.4 Importance of Employee Wellness 30

2.6 Employee Wellness in India 30

2.6.1 Gujarat 31

2.7 Banking Sector in India 31

2.7.1 Historical Overview 31

2.7.2 Structure of the Indian Banking System 34

2.7.3 Reformation of Indian Banking System 36

2.7.4 Need of Employee Wellness in Banking Sector 37

2.8 Dimensions Influencing Bank Employee‘s Wellness 39

2.8.1 Physical Wellness 39

2.8.2 Social Wellness 39

2.8.3 Emotional Wellness 40

2.8.4 Intellectual Wellness 40

2.8.5 Spiritual Wellness 41

2.8.6 Occupational Wellness 41

2.8.7 Environmental Wellness 41


3 Report on the present research 43

3.1 Research Design 43

3.1.2 Population and Sample 43

3.2 Data Collection 44

3.3 Instrument Development Procedures 44

3.3.1 Step 1: Define the concept being measured 44

3.3.2 Step 2: Creation of an item pool 45

3.3.3 Step 3: Choosing the scale type for measurement 45

3.3.4 Step 4: Getting the items reviewed by experts 45

3.3.5 Step 5: Administering items to a development sample 46

3.3.6 Step 6: Evaluation of items 46

3.3.7 Step 7: Optimizing scale length 46

3.4 Instrumentation 46

3.5 Purpose and Research Questions 47

3.5.1 Objectives 47

3.5.2 Research Questions 47

3.6 Statistical techniques for Analysis of collected data 49

3.6.1 Data analysis for Research Question 1, 2 50

3.6.2 Data Analysis for Research Question 3, 4 55

3.6.3 Data Analysis for Research Question 5 57


vi

4 Results and Discussions 59

4.1 Sampling and Data Collection 59

4.2 Sample Demographics and Descriptive Statistics 59

4.2.1 Participant‘s Personal Characteristics 64

4.2.2 Participants‘ Professional Characteristics 65

4.3 Data Analysis and Results Based on Research Question 66

4.3.1 Research Question 1 67


4.3.3 Research Question-3 and 4 80

4.3.4 Research Question-5 92

4.4 Discussion 107

4.4.1 Review of Descriptive Data 107

4.4.2 Research Question Results 107


5 Conclusions, Major Contributions, and Scope of further work 120

5.1 Introduction and Necessity for the Research Investigation 120

5.2 Review of Research Methodology 122

5.2.1 Participants 122

5.2.2 Data collection 123

5.2.3 Instrumentation 123

5.2.4 Data analysis 123

5.3 Result: 124






5.4 Achievements with respect to objectives 134

5.4.1 Objective-1 134




5.5 Limitations of the Research 136

5.5.1 Limitations of the Research Design 136

5.5.2 Limitations of the Questionnaire 137

5.6 Recommendations for Future Research 137

5.7 Implications 138


List of References 193

List of Publications 208

vii

List of Figures

Figure 2.1 Hettler‘s Hexagonal Model 13

Figure 2.2 Wheel of Wellness 15

Figure 2.3 The Indivisible Self Model 18

Figure 2.4 Perceived Wellness Model 21

Figure 2.5 Illness-Wellness Continuum 22

Figure 2.6 Structure of Indian Banking Sector 35

Figure 4.1 District Wise Amount of Samples Received 61

Figure 4.2 Bank wise amount of samples received 63

Figure 4.3 Scree plot for Employee Wellness Scale 72

Figure 4.4 Parallel Analysis for Employee Wellness Scale 73

Figure 4.5 EFA model of Employee Wellness Construct 77

Figure 4.6 CFA model of Employee Wellness Construct 79

Figure 4.7 Prevalence of Health issues among bank employees in Gujarat 93

Figure 4.8 Prevalence of Health issues among Officers and Clerks 95

Figure 4.9 Prevalence of Health issues among Male and Female Employees 97

Figure 4.10 Prevalence of Health issues among Bank employees of different age group

99

Figure 4.11 Prevalence of Health issues among Bank employees with different education qualification

101

Figure 4.12 Prevalence of Health issues among Public sector and Private sector bank employees

103

Figure 4.13 Prevalence of Health issues among Bank employees with different work experience

105

viii

List of Tables

Table 4.1 District wise amount of sample received 60

Table 4.2 Bank wise amount of survey received 62

Table 4.3 Categorical Demographic Variables - Participant Personal Characteristics

64

Table 4.4 Categorical Demographic Variables - Participant Characteristics 65

Table 4.5 Descriptive Analysis 68

Table 4.6 Bartlet‘s test of sphericity 69

Table 4.7 Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy 69

Table 4.8.1 Exploratory Factor Analysis of the Employee Wellness Scale 75

Table 4.8.2 Exploratory Factor Analysis of the Employee Wellness Scale 76

Table 4.9 Correlation coefficient matrix 81

Table 4.10 Tolerance value of independent variables 82

Table 4.11 VIF value of independent variables 82

Table 4.12 Kurtosis and Skewness 83

Table 4.13 MLR for Employee Wellness Score and Demographic Variables 84

Table 4.14 MLR for Factor-1 (Physical Wellness) and Demographic Variables 85

Table 4.15 MLR for Factor-2 (Intellectual Wellness) and Demographic Variables

86

Table 4.16 MLR for Factor-3 (Occupational Wellness) and Demographic Variables

87

Table 4.17 MLR for Factor-4 (Environmental Wellness) and Demographic Variables

88

Table 4.18 MLR for Factor-5 (Social Wellness) and Demographic Variables 89

Table 4.19 MLR for Factor-6 (Emotional Wellness) and Demographic Variables

90

Table 4.20 MLR for Factor-7 (Spiritual Wellness) and Demographic Variables 91

ix

Table 4.21 Prevalence of Health issues among bank employees in Gujarat 92

Table 4.22 Chi Square Analysis – Hypothesis 9 94





Table 4.27 Chi Square Analysis – Hypothesis14 104

Table 4.28 Analysis of Prevalence of Health issues among Bank Employees 106

x

List of Appendices

Appendix I General Demographic Form 140

Appendix II Employee Wellness Scale 142

Appendix III Current Health Issues Questionnaire 145

Appendix IV Employee Wellness Scale Score Guideline 147

Appendix V Histograms 151

Appendix VI Scatterplots 170

Appendix VII Correlation Matrix 191

Chapter-1: Introduction

1

CHAPTER – 1

INTRODUCTION

Definitions of wellness have evolved with the changing conditions of societies. The

current WHO (World Health Organization) definition of wellness, formulated in 1948,

describes wellness as ―a state of physical, mental, and social wellbeing not merely the

absence of disease‖ (WHO). A major feature of the above mentioned definition is that

absence of disease is not equal to being healthy. Hence, even if a person does not have an

illness or disease, he/she may not be holistically healthy. Moreover, some people may be

highly susceptible to be ill. For example, Bank employees are susceptible to wellness

issues (Ganesh Kumar and Deivanai Sundaram, 2014; De Cuyper and Isaksson, 2017;

Manjunatha and Renukamurthy, 2017). Thus, in the current research study, the term

employee involves clerks and officers working in scheduled commercial banks in Gujarat.

Since last two decades, Indian banking system has been going through enormous changes

in terms of operations. Technological innovations and new structure of the operation have

made an impact on the conditions of work and routine lives of bank employees.

Consequently, the employees are experiencing a high level of stress (UNI-Finance, 2013).

Prolonged periods of stress can make workers vulnerable to the issues of health and well-

being (De Cuyper and Isaksson, 2017; Ganesh Kumar and Deivanai Sundaram, 2014;

Manjunatha and Renukamurthy, 2017). In addition, bank employees have higher

propensity to be unwellness, because of the nature of banking job (Giga and Hoel, 2003).

Thus, it is necessary to assess the wellness of bank employees.

It is difficult to assess wellness. However, some assessments for examing wellness are

available within the wellness literature. But, no assessment is formed for a population of

bank employees. Moreover, only a few wellness scales are created according to the

guidelines of the eminent scholars of scale development (e.g., DeVellis, 2012; Crocker

and Algina, 2005; Dimitrov, 2012) and appropriate methods of statistics (e.g., Exploratory

Factor Analysis, Confirmatory Factor Analysis). Due to the above mentioned reasons, the

current research investigation aimed at developing a new employee wellness scale based


2

on the appropriate scale construction procedures. Moreover, the current research

investigation assessed the factor structure, reliability, and validity of the Employee

Wellness Scale with a population of bank employees.

1.1 Background of the study

Wellness is a modern word with ancient origin. The tenets of wellness can be traced to the

ancient civilizations. Moreover, the concept of a wellness/illness continuum is present

since many years, where illness is gaining majority of the focus in treatment-based and

medical domains (Keyes, 2002). However, recently a holistic approach is being adopted

by the helping professions that withstands the traditional medical paradigm (Myers et.al,

2000; Myers and Sweeney; 2004; 2005;). This approach of wellness is based on positive,

health-enriching, and preventive objectives, which encourage optimal human capability

and flourishing (Keyes, 2002; 2007; Fredrickson, 2000; 2001).

The banking sector has been redefined in recent years by substantial pressures, complexity

and change. However, in the current era, when sustainable performance and employer

brand is very important, there is actually limited research into the holistic wellness of bank

employees.

The employers need to understand and embrace the fact that, when employees walk

through the door of the organisation, they bring all aspects of their lives with them. They

bring not only their interests, energies, and passions, but also their personal life pressures,

family issues, and anxieties. So it is a challenge for employers to ensure that the work

environment is conducive to allow the individual employees to manage and balance their

wellness. Thus, it is crucial for organisations to measure employee wellness components

on a routine basis so that they can deploy support to fully harness the potential in each

employee.

Like other situations in life, awareness helps in identifying individual‘s needs and

emotions, and enhancing awareness about personal wellness helps in making decisions

about how to fulfill individual needs (Venart et al., 2007). Hence, making employees more

conscious about their present level of wellness is an essential element in maintaining and

promoting employee wellness, and moving towards holistic employee wellness. Due to

aforementioned reasons, the proposed model of employee wellness aims at improving


3

bank employees‘ level of wellness by examining their current level of wellness

(perceived).

1.2 Statement of the Problem

Banking sector plays a key role in development of the nation‘s economy. During the last

two decades, the banking sector in India is rapidly transformed because of liberalisation,

globalisation, changes in government policies, technological innovations, and profound

market rivalry. From traditional approach banks catapulted to a customer centric,

technology driven, financial supermarket catering to the varied needs of its customers.

Bank employees play a pivotal role in providing good quality services to the customers of

a Bank. Consequently, the bank employees are experiencing intense stress. Many research

studies tell that bank employees are experiencing problems like job burnout, stress, and

job dissatisfaction (Bajpai and Srivastava, 2004; Chen and Lien, 2008).

The National Institute for Occupational Safety and Health (NIOSH) ranked occupations

for stress levels, where 130 occupations were found more stressful. Common issues

among employees of all 130 occupations were, feeling of not being able to control the

work, and feeling of getting stuck into a work where one is treated like a quasi-machine

instead of a human. Manager, Administrator and Supervisor were among the top 12

stressful positions and bank teller was 28th on the list (Michailidis and Georgiou, 2005).

Studies in literature found that occupational stress leads to diseases, and may damage

employees‘ psychological, social, and professional lives. It leads to poor work

performance, a high rate of absenteeism, employee turnover, and violence in the

workplace ( Bhagat et al., 2010; Godin et al., 2005; Dalgaard et al., 2017; Burke, 2010;

Stansfeld and Candy, 2006). Thus, banks should assess employee wellness and try to

increase employee awareness on the components of holistic wellness.


4

1.3 Significance of the study

Bank employees‘ wellness is crucial in providing good service quality and service delivery

to the customers. Developing a psychometrically valid instrument to measure employee

wellness helps in nurturing health and wellbeing among bank employees. Additionally, a

wellness assessment that shows variation in individual wellness score over time can be

also used as a tool to examine personal wellness.

1.4 Purpose and Research Questions

Wellness is a multidimensional concept in nature. (Dunn, 1977, Ardell, 1977; Hettler,

1980, Myers et al., 2004). Moreover, wellness is more than just the absence of illness

(WHO,1958). Wellness is having holistic approach and involves both internal (self) and

external (environmental) factors (Roscoe, 2009). Wellness is dynamic in nature (Roscoe,

2009). Studies show that healthy individuals strive towards optimal functioning. (Roscoe,

2009; Ardell, 1977; Hettler, 1980; Dunn, 1977). Moreover, Wellness depends on personal

motivation (Dunn, 1977; Ardell, 1977; Hettler, 1980) and responsibility at individual level

(Dunn, 1977). Hence, the current research hypothesized that Employee Wellness Scale

will produce a multidimensional model of wellness, that includes internal as well as

external factors. However, due to the exploratory nature of current research , research

questions supporting the exploration of the Employee Wellness Scale were warranted.

Development of the Employee Wellness Scale aims at assessing the psychometric

characteristics of Employee wellness (as measured by the Employee Wellness Scale) in a

population of bank employees (i.e., bank clerks, bank officers).

1.4.1 Objectives

To explore the concept of Employee Wellness in the context of the banking sector.

To develop Employee Wellness Scale for bank employees

To assess the level of Employee Wellness in the banking sector of Gujarat.

To explore the relationship between Employee Wellness and Demographic

variables.


5

1.4.2 Research Questions

The following research questions were investigated in this research:

Research Question 1:

What is the factor structure of the items on the Employee Wellness Scale with a sample of

bank employees?


What is the internal consistency reliability of the Employee Wellness Scale with a sample

of bank employees?


What is the relationship between bank employee‘s Employee Wellness Scale score and

their reported demographic data?

Based on this research question the following hypothesis was framed.

o Hypothesis 1: For the population of Bank employees, there is no linear association

between Total Employee Wellness Score, Age, Designation, Bank Sector, Gender, and

Level of Education.


What is the relationship between bank employee‘s factor wise wellness score and their

reported demographic data?

After looking at the result of research question 1 and 2, the following hypothesis were

framed.


between Total Physical Wellness Score, Age, Designation, Bank Sector, Gender, and

Level of Education


between Total Intellectual Wellness Score, Age, Designation, Bank Sector, Gender,

and Level of Education


6


between Total Occupational Wellness Score, Age, Designation, Bank Sector, Gender,



between Total Environmental Wellness Score, Age, Designation, Bank Sector,

Gender, and Level of Education


between Total Social Wellness Score, Age, Designation, Bank Sector, Gender, and

Level of Education


between Total Emotional Wellness Score, Age, Designation, Bank Sector, Gender, and

Level of Education


between Total Spiritual Wellness Score, Age, Designation, Bank Sector, Gender, and

Level of Education


What are the most common health issues among bank employees in Gujarat?

Based on the research question the following hypothesis were also framed.

o Hypothesis 9: For the population of Bank employees, prevalence of health issues is

independent of employee‘s Designation


independent of employee‘s Gender


independent of employee‘s Age


independent of employee‘s Level of Education


independent of the type of banking sector where employees is working


independent of the Work experience in banking sector.


7

1.5 Research Design

The present research study used a correlational research design, as it assessed how the

variables are associated with each other (Gall, Gall, & Borg, 2007). This research

investigation focused on the study of Employee Wellness by developing the Employee

Wellness Scale (EWS) and assessing the validity of the primary model with a population

of bank employees. The study also investigates the relationship between Employee

Wellness and demographic variables.

1.6 Population and Sample Size

The population for the assessment of the Employee Wellness Scale included clerks and

officers of scheduled commercial banks in Gujarat. The data was collected via face-to-face

administration. For test development and the identified statistical analyses, sample size of

approximately 100 participants is suggested. Moreover, it is suggested that size of the

sample should be minimum five times of the total variables used in the analysis of the

research (Hair et.al, 2006). Hence, the sample size required for assessing the psychometric

properties of the Employee Wellness Scale was based on total participant to total item

ratio (Mvududu and Sink, 2013; Everitt, 1975; Costello and Osborne, 2005). Thus, an N:p

(N = Total participants, p = Total items) formula was used (Hair et al., 2006). In social

sciences, suggested participant/item ratio is 10:1 or 20:1 (Tinsley and Tinsley, 1987; Hair

et al., 2006; Mvududu and Sink, 2013). Though participant to item ratios varies according

to strength of data, researchers should try to achieve high participant to item ratio

(Costello and Osborne, 2005). Thus, this investigation achieved 13:1 ratio.

On the basis of the literature review (Chapter 2), the present research hypothesized that the

statistical analysis (i.e., Factor Analysis) of the data will produce a multidimensional

factor structure. The researcher began with 36 total items or p. Thus, in total 496 samples

were collected (i.e., 496:36 equates to the 13:1 ratio).

1.7 Instrument Procedures and Instrumentation

The major focus of the current research study is to develop the Employee Wellness Scale

and assess its psychometric characteristics with a population of Bank Employees.


8

Moreover, the researcher also developed a general demographic questionnaire and Current

health issue questionnaire for Bank Employees.

The methods of scale development vary within the literature. To fulfill the purpose of

current research investigation, a combination of the different methods is used. The scale

development steps that were followed are: (a) define the concept being measured, (b)

creation of an item pool, (c) choosing the scale type for measurement, (d) getting the items

reviewed by experts, (e) creating a pool of validated items, (f) Administering items to a

development sample, (g) Evaluation of items, and (h) optimizing scale length.

Basically, three data collection questionnaire were utilized in this research. The first

questionnaire was the Employee Wellness Scale, which was designed during current

research. A second questionnaire was administered with a purpose of collecting

demographic information about the participants. A third questionnaire was administered

with a purpose of collecting information about health issues faced by Bank employees.

1.8 Ethical Considerations

The current research investigation followed all the ethical guidelines. All participants

were explained about the research study, the aim of the research, and the research

procedures before data collection. They were also assured that their answers will be kept

anonymous. Additionally, the findings of the research were presented in a way that would

not reveal the identity of the individual participants.

1.9 Limitations of the Research

Although wellness has been explored in other areas and domains, the research of

employee wellness within the context of banking sector is quite new. As such, there are

many areas for improvement and for further research. In particular, the researcher

recognises that this study is subject to some limitations. The present research used a

correlational design (Gall et al., 2007). Hence, it was not able to predict causality. A

second limitation is about the generalisability of the data. The sampling criterion for the

current research defined participants as bank employees (i.e., Clerk , Officers) but equal

representations of them were not achieved.


9

Hence, the current research has limitations that can affect the explanation of the results in

bank employees. But, the limitations also consist of scope for future research.

Consequently, the researcher will try to improve the employee wellness scale by working

on the limitations in future research projects.

1.10 Chapter Summary

The present chapter explained about the development of a psychometrically valid

Employee Wellness Scale with a sample of bank employees. A concise review of literature

on employee wellness is presented. The chapter explored the rationale for an employee

wellness assessment in banking sector. In the end, the chapter concluded with details of

the current research study, including the proposed research methodology and statistical

analysis for developing a psychometrically valid Employee Wellness Scale for bank

employees. Chapter 2 contains a detailed review of literature on the concept of wellness,

models of wellness, wellness assessments, concept of employee wellness, banking sector

in India, and dimensions contributing to wellness of bank employees.

Chapter-2: Literature Review

10

CHAPTER – 2

LITERATURE REVIEW

This chapter explains a historical overview of the wellness paradigm, which also include

the characteristics that distinguish the wellness and illness paradigms. Additionally, this

chapter includes definitions of wellness, Concept of Employee Wellness, Models of

wellness, Wellness assessments, Importance of Employee Wellness, Banking Sector in

India, Banking Sector in Gujarat, and Dimensions influencing wellness of bank

employees.

2.1 Historical Overview of the Wellness paradigm

The concept of wellness is seen from two different perspectives. Scholars of the ―clinical /

Medical‖ tradition assess wellness based on physical or mental illness; while the scholars

of ―psychological‖ tradition assess wellness based on personal satisfaction in life (Keyes,

1998). Since decades, concentration of healthcare is on illness paradigm which gives more

attention to the treatment of illness (Granello, 2013; Myers & Sweeney, 2005; Swarbrick,

2006). Moreover, majority of the healthcare services in India treat illness among people

rather than enabling them for prevention of illness. When we compare the clinical model

with a wellness modal, we can find some innate differences. The clinical model focuses on

depletion of symptom, stabilization, and interventions to treat illness (Swarbrick, 2006).

Moreover, deficit-based nature of the clinical model, views a person in terms of his/her

illness instead of his/her positive characteristics and strengths (Seligman, 2002; Swarbrick,

2006). Additionally, the major difference between clinical model and wellness paradigm is

their primary components.

Wampold, Ahn, and Coleman (2001) describes five elements of the clinical model as

follow: (i) patient appears with a problem/illness, (ii) a clarification for the illness is given,

(iii) enough knowledge of theories and concepts promote a change in the patient, (iv)

clinicians use medicines to illustrate the change, and (v) the improvement and change for

patient is because of the prescribed medicines. So, in simple words, a patient comes up


11

with a problem before clinicians and they prescribe many ―fixes‖ to get rid of it. Hence,

the basic philosophy of the clinical model is that when an individual is having any

problem/disorder, the clinician is responsible for solving it (Keyes, 2002). Thus, focus of

clinical model on sickness limit individual potential to particular disease, which promotes

wellness as an absence of disease. Although, having no disease does not ensure health and

wellness (Foltz, 2006).

Wellness is an energy-based, optimistic, and enabling approach (Myers & Sweeney,

2008). The focus of Wellness models is on prevention of illness and promotion of well-

being among people. Moreover, wellness encourages a positive idea of human potential

and emphasis on positive individual characteristics rather than illness (Swarbrick, 2006).

The concept of wellness encourages people to take responsibility of their own health and

develop a proactive behavior which lead to a healthy balanced lifestyle (Swarbrick, 1997).

The statistics on treatment of diseases and illnesses have exacerbated in India since last

few years. According to the world economic forum, India stands to lose $4.58 trillion

between 2012 and 2030 due to non-communicable diseases. Nearly 60% of deaths

occurring in India are due to Cardiovascular diseases, diabetes, cancers, chronic

respiratory disorders, and mental illness. Nearly half of them occur before the age of 65. It

has been estimated that India lost 9.2 million potentially productive years of life due to

untimely cardiovascular deaths in the age-group of 35-64 years in 2000 (570 per cent more

than the US) and is projected to lose 18 million years in 2030 (900 per cent more than the

US). Thus, a concept wellness, promoting prevention of illness, is necessary to improve

overall health in India. Hence, the following sections of this talks about definitions of

wellness, the importance of employee wellness, models of wellness, wellness assessments,

etc. with a view to support the philosophy of prevention of illness and optimal functioning

in the bank employees.


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2.2 Definitions of Wellness

Many authors have tried to define and identified major concepts connected with meaning

of wellness. The term ‗wellness‘ is considered subjective so it‘s accurate definition and

measurement of construct is difficult (Kelly, 2000; Sarason, 2000). Thus, wellness is

conceptualized on a continuum and not as an end state (Clark, 1996; Dunn, 1977; Jonas,

2005; Lafferty, 1979; Myers, Sweeney, and Witmer, 2005; Sarason, 2000). In 1948 World

health organization gave a holistic definition of health as ―physical, mental and social

well-being and not merely the absence of disease‖ (WHO). Later they defined optimal

health as ―a state of complete physical, mental, and social well-being and not merely the

absence of disease or infirmity‖ (WHO). Halbert Dunn, who is considered as the father of

modern wellness movement defined it as ―An integrated method of functioning which is

oriented toward maximizing the potential of which the individual is capable, within the

environment in which he or she is functioning‖ (1961, P.4). Dr. Bill Hettler defined

wellness as ―an active process through which people become aware of, and make choices

toward a more successful existence‖ (National Wellness Institute). Myers, Sweeney and

Witmer reviewed literature from multiple disciplines and defined wellness as ―a way of

life oriented toward optimal health and well-being, in which body, mind, and spirit are

integrated by the individual to live life more fully within the human and natural

community. Ideally, it is the optimum state of health and well-being that each individual is

capable of achieving‖ (2000, p.252). Thus, wellness is an outcome as well as a process. It

is a multifaceted and multidimensional concept. The subsequent sections of this chapter

give detailed review about models of wellness and wellness assessments.

2.3 Models of Wellness

2.3.1 The National Wellness Institute Model/Hettler’s Hexagonal Model

In 1980, Hettler developed a six-dimensional wellness model for the National Wellness

Institute. It consists of six dimensions as Physical, Social, Intellectual, Occupational,

Emotional, and Spiritual.


13

FIGURE 2.1: Hettler’s Hexagonal Model

Occupational dimension of wellness recognizes importance of personal satisfaction and

enrichment in one‘s life through work. The central idea of occupational dimension is that a

person must be optimistic towards his/her work and he/she should feel that the work is

meaningful and rewarding both (Hettler, 1980). Social dimension of the model highlights

the importance of contribution to the environment and community. It encourages active

involvement in the globe through interaction with other people and contribution to the

common welfare of society (Hettler,1980). Spiritual dimension of wellness give

importance to one‘s search for meaning and purpose in life. According to hettler, people

realize their spiritual wellness when their actions are in consistency with their personal

values and beliefs (Hettler, 1980). Physical dimension of wellness emphasise regular

physical activity. According to the model optimal wellness can be achieved through

combination of good exercise and eating habits (Hettler, 1980). It also gives importance to

learning about balanced nutrition and risky behaviour. Emotional dimension of the model

gives importance to one‘s awareness and acceptance of feelings. It includes being

optimistic and enthusiastic about one‘s self and one‘s life (Hettler, 1980). Intellectual

dimension of model emphasise on one‘s mental activity dealing with the areas like

knowledge, skill, creativity, problem solving, and learning.


14

2.3.2 Lifespan Development Model

Lifespan Development Model (LDM) was created by Sweeney and Witmer in 1991, which

demonstrates the correlation between the traits of a healthy individual (Witmer and

Sweeney, 1992). They utilised Adlerian life tasks (i.e., self, love, work, friendship, and

spirituality) in development of the Lifespan Development Model and gave a holistic aspect

of Wellness. They incorporated different theoretical concepts from psychology, sociology,

education, anthropology, and religion in Lifespan Development Model (Witmer and

Sweeney, 1992). The authors also insisted on the role of life forces like education,

religion, and media and global events like hunger, poverty, etc. in maintaining and

achieving holistic wellness. Fundamentally, the Lifespan Development Model was created

as a human development model that incorporated a holistic aspect of human potential and

wellbeing within the contexts of a person‘s environment. The authors used learning from

the Lifespan Development Model to develop the Wheel of Wellness (Witmer and

Sweeney, 1992).

2.3.3 Wheel of Wellness Model

Wheel of Wellness model was created by Witmer and Sweeney in 1992 to align with

Individual Psychology tenets. It contained factors associated with healthy life, longevity,

and quality of life (Myers and Sweeney, 2005). The healthy living factors included

elements like physical, nutritional, social, occupational, and spiritual. It also included the

impacts of society and other external factors on total wellness. The model is based on

Adlerian life tasks and the correlation of life tasks with one another and with other life

forces in development of overall wellness (Sweeney and Witmer, 1992).


15

FIGURE 2.2: Wheel of Wellness


16

Life task 1- Spirituality:

It involved meaning in life, sanguinity, harmony and values for building the character

(Sweeney and Witmer, 1991).

Life task 2-Self-Regulation:

It consisted of sense of control, sense of worth, realistic beliefs, problem solving and

creativity, emotional awareness and coping, sense of humor, nutrition and physical fitness

(Sweeney and Witmer, 1991). Sense of control and sense of worth emphasise on

individual self-efficacy, self-esteem, and an ability to have practical expectations and

beliefs with a view to achieve healthy lifestyle and stability in life. Creativity and

emotional responsiveness is explained by Witmer and Sweeney with the idea of enhancing

immune function through positive emotional states (Dillon, Minchoff, and Baker, 1985).

Maslo (1970) emphasises on creativity as an essential for fully self-realised behaviours.

Sense of humour is also seen as integral to self-regulation. Moreover, physical health,

nutrition, and exercise, were correlated with good health and longevity (Belloc, 1973,

Sweeney and Witmer, 1991).

Life task 3-Work:

It is described as one of the most basic life tasks by Sweeney and Witmer (1992). It

encompassed everything that an individual do for sustenance of one‘s self and other

individuals (Witmer & Sweeney, 1992). It consists of involvement in jobs, careers,

volunteering, and other activities.

Life task 4-Friendship:

It consists of connections with other people, either in a group or individually. The

friendship connection mentioned here is not physical or intimate in nature (Witmer and

Sweeney, 1992).

Life task 5-Love:

Although friendship and love look alike, they are different as love involved more intimate,

committed relationship between individuals (Witmer and Sweeney, 1992).


17

2.3.4 Indivisible Self Model

In 2004, Myers, Leucht, and Sweeney gave a revised model of the Wheel of Wellness and

named it as the Indivisible Self: An Evidence-Based Model of Wellness (IS-WEL). This

five-dimensional model described wellness as a higher order dimension with sub-

dimensions like physical, coping, social, essential, and creative paradigms. The sub-

dimensions are consisted of 17 third order factors that are as follow:

Coping : leisure, self-worth, realistic belief, stress management

Social : love, friendship

Essential : spirituality, self-care, cultural identity

Physical : exercise, nutrition

Creative : emotions, control, work, humor, thinking

The multidimensional concept of wellness is in accordance with other theories that look at

the person holistically. The concept of wellness has similarity with Adlerian concepts of

holism; meaning making and seeking purpose (Rogers, 1961; Adler, 1956) and achieving

balance in life (Hettler, 1984). The five, sub-dimensions of wellness given above (i.e.,

Creative, Coping, Physical, Essential, and Social) are joined to include the ―whole‖ human

being. Each sub-dimension has third order tenets which gives uniqueness to each wellness

domain.


18

FIGURE 2.3: The Indivisible Self Model


19

Creative:

It consists of how people make sense of their world. This sub-dimension consist of third

order factors like work, emotions, thinking, positive humour, and control (Myers and

Sweeney, 2004) . According to Sweeney and Witmer (1992), the factor emotions consists

of feelings and degree of awareness that enable an individual to experience positive as

well as negative responses. Positive humour consists of laughter, being able to laugh at

mistakes, and being able to use humour in different aspects of life. The factor of work is

defined as contentment with job, career, or vocational choice. It also consists of having

good relationships at work, sense of being appreciated at work, and coping with

occupational stressors (Myers and Sweeney, 2004). The thinking consists of curiosity,

open-mindedness, creativity, and the ability to use them effectively for solving problems

and for coping with stressful situations. The control consists of thoughts about self

competence, internal and external locus of control and assertive expression of wants and

needs (Sweeney and Witmer, 1992). Hence, the Creative dimension consists of creativity

of thoughts and emotions, and expression of humour in various situations of life.

Coping:

It consisted of managing stress, leisure activity, realistic beliefs, and self worth (Myers and

Sweeney, 2004). It is referred to how people manage and react to life events. The ability to

manage life events is paramount in stress management. Leisure time consists of activities

not related to work like personal activities or ―free‖ time, and the balance between work

and leisure. Realistic beliefs consist of accepting reality, recognising the imperfect nature

of life, and accepting the possibility of errors, mistakes, and wrong choices. The worth

consists of self-value and accepting one‘s self (Sweeney and Witmer, 1992).

Physical:

It consists of nutrition and involvement in physical workout leading towards personal

wellness. Nutrition consists of having a balanced food and maintaining a healthy body

mass (Myers and Sweeney, 2004). It also contains prevention techniques like weight

training, eating healthy diet, cardiovascular exercise, and involvement in other physical

tasks to encourage health and wellness.


20

Essential:

It includes cultural identity, gender identity, self-care, and spirituality (Myers and Sweeny,

2004). It consists of meaning in personal life, personal level of satisfaction with gender

and cultural identity, cultural acceptance, individual beliefs, faith in a higher power,

optimism, purpose in life, and personal value.

Social:

It consists of individual communication with others, including how the person is

connected with others. It also consists of love and friendship which indicates the ability to

be in a lasting, committed relationship. Love consists of respect, shared values, growth,

appreciation, and interaction. While friendship is less involved and consists of an

uncritical, empathic association (Myers and Sweeney, 2004).


21

2.3.5 Perceived Wellness Model

FIGURE 2.4: Perceived Wellness Model


22

The Perceived Wellness Model was created by Adams and his colleagues in 1997(Adams,

1995; Adams et. al., 1997). It is a multidimensional model supporting wellness as an

individual characteristic. It promotes experiencing consistent and balanced improvement

in the physical, social, psychological, emotional, intellectual, and spiritual areas of human

life. According to Perceived Wellness Model, when people consider their wellness factors

as equal, their health is better. A limitation of the Perceived Wellness Model is that high

level of wellness can be achieved only when the score on all dimensions are equal.

Consequently, Adams and his colleagues hypothesised that wellness dimensions must be

equal, which is opposed by researchers who think that wellness dimensions are

personalised and certain dimensions may be more important depending on individual.

Hence, an equal dimensions may not show wellness.

2.3.6 The Wellness/Illness Continuum Model

FIGURE 2.5: Illness-Wellness Continuum


23

The wellness/illness continuum model was developed by Travis and Ryan (1981, 1988) on

a wellness/illness continuum, where illness and wellness represent its two opposite poles.

The midpoint of this model, is a neutral point which shows absence of illness or wellness.

They bring up the thought that wellness could be present despite illness or disease. One of

the most significant of contributions of this model to the concept of wellness is a much

greater emphasis on individual responsibility. Additionally, Travis (1978) also explained

wellness by example of iceberg as a metaphor and named it the Iceberg Model of Health

(Myers and Sweeney, 2005). He explained current state of individual health as the top of

the iceberg, which has three underlying levels depicting lifestyle or behavior level,

Psychological/motivational level, and spiritual/meaning/being realm.

2.3.7 Conclusion

Aforementioned section of this chapter reviewed wellness models and the dimensions

influencing holistic wellness. Majority of the wellness models include some holistic

dimensions and emphasise on balancing various dimensions which contribute to overall

wellness. Wellness models were discussed to depict the purpose of different models,

dimensions of wellness, and intentions for use. The following section reviews wellness

measurement instruments. Most of them are derived from the wellness models presented

in the aforementioned section.

2.4 Wellness Measurement Instruments

There are many models of wellness that describe unidimensional wellness construct or

multidimensional wellness factors (i.e., Sweeney and Witmer, 1991; Hettler, 1980). As the

models are used for a pictorial representation rather than assessment, they are not always

enough to assess wellness at personal level. Thus, wellness assessments to assess

individual wellness are needed.

Though many assessments are available for measuring wellness in literature, most of them

are not supported by theory and/or empirical research (Hattie et al., 2004). Additionally,

many of them are not developed according to appropriate scale construction methods

(DeVellis, 2012; Crocker and Algina, 2006; Dimitrov, 2012). In the following section, five

different wellness assessments are explained.


24

2.4.1 Life Assessment Questionnaire

The Life Assessment Questionnaire is derived from Hettler‘s Hexagonal model of

wellness. It was developed by Hettler (1980) to measure the six dimensions of wellness. It

consists of 100 statements that are measured based on a 5 point Likert scale, where higher

scores meaning higher levels of wellness. Palombi (1992) reported total cronbach‘s alpha

of .78 and test-retest reliabilities of sub-dimensions ranged from .57 to .87. According to

her the second study had the test-retest reliabilities ranged from .81 to .94 and internal

consistency reliabilities ranged from .67 to .94. Cooper (1990) assessed the factor structure

of the LAQ, but failed in supporting the six factor structure of the instrument. Thus, there

are differences in factor models being reported by research supporting a factor structure of

the LAQ.

2.4.2 Optimal Living Profile

It was developed by Renger et al. (2000) to measure the six dimensions of wellness:

emotional, spiritual, physical, social, intellectual, and environmental wellness. It contains

135 items that are measured on two different 5 point Likert scales depending on the

language content of item. Cronbach‘s alpha value for various dimension ranged:

.78(Environmental Wellness), .91(Intellectual Wellness), .82 (Spiritual Wellness), .95

(Emotional Wellness), .84 (Social Wellness), and .89 (Physical Wellness). The external

reviewers supported the content validity of the scale and comparison of scale with

interview data supported the concurrent validity. Divergent validity was achieved through

subtraction of items having high correlation with another dimension compared to the one

they were claimed to measure.

2.4.3 Perceived Wellness Survey

Perceived Wellness Survey is based on the Perceived Wellness Model. It was developed

by Adams et al. (1997) to measure the six dimensions of wellness: social, spiritual,

physical, intellectual, emotional, and psychological. It was developed as a

multidimensional measure of perceived wellness focused on health. It contains 36 items

that are measured based on a 6 point Likert scale, with higher scores indicate higher levels

of wellness. Moreover, only four of the six subscales had more than .70 cronbach‘s alpha

score.


25

Adams and colleagues (1997) examined construct validity of Perceived Wellness Survey

through Confirmatory factor analysis on a sample of 359 participants. They reported

Goodness of fit (GFI) as .82 and average standardized residual (ASR) coefficient as .045.

Harari and colleagues examined the psychometric properties of the Perceived Wellness

Scale (Harari et al. 2005). They mentioned the reliability of the total score as .91. They did

not found any support for the existence of separate subscale dimensions. They summarised

that Perceived Wellness Scale is not a satisfactory assessment of the Perceived Wellness

Model.

2.4.4 Test Well (National Wellness Institute, 1992)

It was created to utilize Hettler‘s (1980) six dimensions of wellness. It consists of 100

items that are scored on a 5 point Likert scale. It had a split-half reliability of .87 and 8 out

of the 10 subscales had cronbach alpha value over.71. It had total reliability value of .92

(Owen, 1999).

2.4.5 Wellness Evaluation of Lifestyle Inventory

The Wellness Evaluation of Lifestyle Inventory is derived from the Wheel of Wellness

model. It was developed by Myers and colleagues to measure the five life tasks and the

subtasks of the Wheel of Wellness (Myers et al. 1998). It has been revised many times

since its creation. Initially it was created from a group of more than 500 items. The first

version of the WEL had 114 items. It was administered to sample of 723 individuals.

Myers et al., (1998) reported that out of 16 scales only 9 had reliability alpha above .60.

Thus, many research were conducted to improve the weaker scales with different

populations.

The latest version WEL-S contains 120 items that measure based on a 5 point Likert scale.

Myers et al. (2004) mentioned Cronbach‘s alpha values for 12 subtask ranging from .61

(leisure) to .89(love). It had test-retest reliability coefficients ranging from .68 (cultural

identity) to .88 (nutrition). It had internal consistency ranging from .60 (realistic beliefs) to

.94 (friendship).

Hattie et al. (2004) found support for the psychometric properties of the WEL, but the data

did not support the Wheel of Wellness model. Further investigations of the data lead to

development of the Indivisible Self Model of Wellness (Myers et. al., 2004).


26

2.4.6 Five Factor Wellness Inventory

The Five Factor Wellness Inventory is based on Indivisible Self Model of wellness. It was

developed by Sweeney and Witmer (1992) using factor analysis on the original WEL

assessment. It consists of total 91 items that are scored based on a 5 point Likert scale.

Internal consistency of the Five Factor Wellness Inventory ranges from .80 to .96 (Myers

and Sweeney, 2005). Moreover, the Five Factor Wellness Inventory scale is very lengthy,

so it is difficult to use it in daily life. Another limitation is the cost, where individuals

wanting to use the Five Factor Wellness Inventory scale have to bear the cost for the scale,

the manual, and data analysis.

2.4.7 Summary

After comparing the assessments of wellness, the researcher found that most assessments

were developed to measure multiple factors of wellness. Assessment scales like LAQ,

PWS and WEL were constructed to measure sub-dimensions that contributed to total or

holistic wellness. Moreover most of these assessment scales are not constructed through

appropriate scale construction procedures as defined by DeVellis, (2012), Crocker and

Algina, (2006), and Dimitrov (2012).

2.5 Employee Wellness

2.5.1 Introduction

Employees are prone to various diseases based on their way of living and occupational

habits. These diseases are preventable, and can be lowered with changes in diet, lifestyle,

and environment. Lifestyle diseases are the diseases whose occurrence is primarily based

on daily habits of people, and inappropriate relationship of employees with their

environment. These lifestyle diseases take years to develop, and once encountered do not

lend themselves easily to cure. Lifestyle diseases include hypertension, heart diseases,

stroke, diabetes, obesity, high cholesterol and diseases associated with tobacco use

(smoking and chewing) like chronic bronchitis, COPD, cancer, and excessive use of

alcohol (Pappachan MJ, 2011). These diseases are also called Non-communicable diseases

(NCDs) or Chronic diseases.


27

The major factors contributing to the lifestyle diseases are bad food habits, physical

inactivity, wrong body posture, and disturbed biological clock. Additionally, conditions

like stress, depression and substance abuse are also important factors contributing to

lifestyle related morbidity and mortality like suicides (WHO). There are evidence that diet

and lifestyle is playing a major role in predisposition to various diseases (Key TJ et. al.

2002). WHO have identified that most NCDs are the result of four particular lifestyle

related behavioral risk factors like tobacco use, physical inactivity, unhealthy diet, and the

harmful use of alcohol that lead to four key metabolic/physiological changes e.g., raised

blood pressure (BP), overweight/obesity, raised blood glucose and raised cholesterol

levels (Narayan KM et. al. 2010).

According to The World Health Organization (WHO), India is going to have most of the

lifestyle related disorders in the near future. Moreover, lifestyle diseases are showing a

drastic shift towards the younger population in India.

Organisations are facing great challenges due to economic crisis, changing business

environment, increasing demands for productivity, and rise in chronic diseases. Many

studies have described the negative economic consequences of poor employee wellness in

the form of absenteeism, accidents, and healthcare costs (Mills, Kessler, Copper, and

Sullivan, 2007).

Rise of chronic diseases has left its mark on workplaces. Non-communicable diseases

cause 38 million deaths annually. Eighty percent of it occur in low and middle income

countries. Cardiovascular diseases, diabetes, cancer, and chronic respiratory diseases are

identified as major noncommunicable diseases by WHO. 2.6 million people die due to

overweight or obesity each year (WHO, 2010b). Annually more than two million people

die due to job related accidents or illnesses (ILO, 2005).

The economic consequences of Non-communicable diseases are alarming. The financial

impact of lifestyle-related diseases to India amount to $ 237 billion in 2015 (WHO/WEF,

2008).

Technology, manufacturing processes, products and strategies of competitors can be

replicated by the organizations but human resource management processes cannot be

replicated easily (Pfeffer, 1998). Thus, employees and human resource management

practices are the critical assets of the organization. Many studies have found that HRM


28

practices associated with high-performance workplaces are also associated with healthy

employees and higher level of productivity (Burke and Cooper, 2008; Lowe, 2010). Many

Scholars have explained a link between human resource management practices and

employee health, employee engagement and organizational performance (e.g., Sirota et al.,

2005; Sisodia et al., 2007). Significant evidence has been found indicating the crucial role

of employees in the performance of organizations (O‘Reilly and Pfeffer, 2000; Lawler,

2003). Thus, many organizations are getting interested in Employee wellness (McGinnis,

1993).

2.5.2 Employee Wellness Programs

Employee Wellness Programs are employer initiatives directed at improving the health

and well-being of workers and, in some cases, their dependents. They include programs

designed to avert the occurrence of disease or the progression of disease from its early

unrecognized stage to one that's more severe (Goetzel and Ozminkowski, 2008). It is a

corporate set of strategic and tactical actions that seek to optimize worker health and

business performance through the collective efforts of employees, families, employers,

communities, and society-at-large (IAWHP, 2009). Thus, Employee Wellness Programs

not only target and improve health risks and behaviours of the employees, but also address

the work environment (Kirsten, 2012).

2.5.3 Evolution of Employee Wellness Practices

The notion of employee wellness has attracted considerable interest from business and

consultancy firms since the mid 19th century and has more recently begun to attract wider

academic attention. Analysis of employee wellness literature has enabled the identification

of stages in the evolution of the employee wellness concept, conceptualised here as a

series of waves.

Wave-1:

The first wave era is characterized by recognition for addressing sanitary conditions,

infectious diseases and unsafe conditions in the mid 19th century. The major concern

during this period was occupational safety and health. Due to frequent accidents and the


29

distance from the preexisting medical systems companies made their own health clinics

for their employees and their families (Fertman, 2015).

During World War II the focus of workplace health slowly began to shift from injury

response to preventive medicine (Starr, 1982; Fertman, 2015). Kriser Steel is the prime

example of this shift. The corporation operated a full-service medical program to treat

employees and their families. It was the first company to make health care part of its

organizational policy. Many other companies also hired doctors and made developed

variations of the Kraiser model of company medicine. (Draper, 2005).

Gradually, minimal occupational safety standards and regulations were established to

ensure safer working conditions for the employees. Later it converted into the

Occupational safety standards and regulations. In spite of such measures, work related

injuries and fatalities remain a considerable threat to public health (Fertman, 2015).

Wave-2:

The second wave started in 1970 when Lalonde report (Lalonde, 1974) released in

Canada. It considered improvement of health care system and the prevention of health

problems and promotion of good health as major objectives. It is considered as the first

modern government document emphasizing on the need of looking beyond the traditional

healthcare system. During this period healthier individual behaviour was encouraged

through the provision of support, information and the development of skills. During this

period medical benefits, short and long-term disability, disease management, Worker‘s

compensation, health promotion, pharmacy etc were combined into a single process. The

emphasize was given on improvement of outcomes, measurement, benchmarking,

coordination of services etc. The goal was to manage costs and improve the outcomes for

the employees. (Fabius & Frazee, 2009). During 1980s major companies made a big

investment in the Employee Wellness Programs. The focus of these programs was

healthier lifestyle to encourage healthier employee behaviour. Health risk assessment,

blood screenings, preventive services, wellness education etc. were utilized as strategies.

The top management also showed commitment towards employee wellness during this

period. Companies also started collaborating with health care providers and community

groups. Economic analysis of Employee Wellness Programs began and it indicated that it

is cost effective and a good return on investment (Fertman, 2015).


30

Wave-3:

In the third wave, emphasis is given on the organizational determinants of health.

Disparities in the status of health in organization is the result of determinants (USDHHS,

2000, 2015a). Though genes, behaviour and medical care affect our wellness but the

factors like economic and social condition, culture etc. also affect our mental and physical

health status. Recently the attention has turned to the Employee Wellness in Small

organizations. Small business organizations usually gives less flexibility to their

employees. Such employees have very few employer-sponsored benefits and hardly have

an access to Wellness initiatives at Workplace (Fertman, 2015).

2.5.4 Importance of Employee Wellness

In the current era, when organizations are striving for getting better performance in

competitive global environment, talent management and human resource development

plays crucial role. A healthy and engaged workforce is essential for successful

organisations. Research has found that unhealthy people are usually tired, dissatisfied,

work very slowly, make more mistakes, and are more prone to accidents (Stewart et al.,

2003). Whereas healthy people work harder, have more job satisfaction, are more

productive, and more likely to help others (Wolfe et al., 1994). Employee Wellness

contribute to the achievement of healthy profits (Heaney and Goetzel, 1997; Pelletier et

al., 2004; Pelletier, 2005; Goetzel and Ozminkowski, 2008). Thus, increasing number of

managers are looking at employee wellness as part of company health (Carnethen et al.,

2009).

2.6 Employee Wellness in India

India is one of the most diverse countries in the world. It is the second most populous

country in the world. As of 2009, India‘s workforce was about 765 million (17% of the

World‘s total workforce). Due to sedentary lifestyle, changing dietary habits, and stress

prevalence of chronic diseases such as coronary heart disease, obesity, stroke, and diabetes

is increased. Around 31 million Indians are diabetic, and the number is expected to grow

up to 57 million by 2025 (pricewaterhouseCoopers, 2007a). According to

Pricewaterhousecoopers 2007 report, between 2000 and 2030, India is expected to have

more deaths in the age group of 35-64 than the United States, China or Russia. The report


31

warns that, chronic diseases will reduce the labor supply, savings, and investments within

next 25 years, which will ultimately affect the capital markets.

India is a kaleidoscope of customs, values, beliefs, and traditions. Thus, it is impossible to

generalise the Indian way of life. Each region in India has its own distinct culture,

language, cuisine, etiquette, social norms. However, there are common aspects of the

Indian culture across regions. Collectivism and Verticalness are one of these common

aspects (Triandis, 1998). It is not uncommon to see unequal treatment of employees based

on their social classes and unequal distribution of power among people at the workplace.

Moreover, Indian culture is more relationship based than rule based. So, an individual‘s

behavior is mostly regulated by one‘s superiors, parents, or political leaders (Bhagat,

Steverson, & Segovis, 2007). As most of the models of employee wellness have been

developed in Western countries, primarily the United States, where the culture is

individualistic, rule based, there is a need to study Indian paradigm.

2.6.1 Gujarat

Gujarat is among the ten highest populated states in India (Cencus, 2011). It is one of the

most industrialised states in India. Gujarat's Gross State Domestic Product (GSDP) was

about Rs 11.58 trillion (US$ 172.63 billion) during 2016-17. According to report of ICMR

(2017) non communicable diseases causes 56.7% of premature death or disability among

the 18 to 60 age group in Gujarat. Ischaemic heart disease, chronic obstructive pulmonary

disease, Stroke, and chronic kidney diseases are among the top 15 causes of premature

death in Gujarat. The workplace directly influences the wellness of workers and in turn the

health of their families, communities and society at large (WHO). Thus, there is a need of

research in the field of employee wellness in Gujarat.

2.7 Banking Sector in India

2.7.1 Historical Overview

The indigenous system of banking in India can be traced back to the 4th century BC in the

'Kautilya‘s Arthashastra' , which contains references to creditors and lending. For instance,

it says ―says "If anyone became bankrupt, debts owed to the state had priority over other


32

creditors". Similarly, there is also a reference to "Interest on commodities loaned"

(PRAYOG PRATYADANAM) to be accounted as revenue of the state. Thus, lending

activities were known in the medieval India and the concepts such as 'priority of claims of

creditors' and 'commodity lending' were established business practices. However the real

roots of commercial banking in India can be traced back to the early eighteenth century

with the establishment of the three presidency banks.

Establishment of the three presidency banks in India:

In June 1806, the Bank of Calcutta was established, which was renamed as Bank of

Bengal in January 1809 to fund General Wellesley‘s wars. In July 1843, a joint stock

company, the Bank of Madras was established through the reorganization and

amalgamation of four banks viz., Madras Bank, Carnatic Bank, Bank of Madras, and the

Asiatic Bank. It brought about major innovations in banking such as use of joint stock

system, conferring of limited liability on shareholders, acceptance of deposits from the

general public, etc. After a decade of the India‘s first war of independence, in 1868, the

Bank of Bombay was established.

Establishment of the Imperial Bank of India:

In January 1921, the three Presidency Banks were amalgamated to form the Imperial Bank

of India. The bank took on the triple role of a commercial bank, banker‘s bank, and a

banker to the government.

Emergence of Private Banks:

The first Indian owned bank, the Allahabad Bank was established in Allahabad in 1865,

followed by second, Punjab National Bank established in 1895 in Lahore, and the third,

Bank of India established in 1906 in Mumbai. The Central Bank of India, Bank of Baroda,

Canara Bank, Indian Bank, and Bank of Mysore were established between 1906 and 1913.

By the end of December 1913, the there were 56 commercial banks in the country.


33

Establishment of Reserve Bank of India:

Until 1935 all the banks were owned by the private sector owners. Due to absence of any

regulatory system, they were free to make use of the funds according to their wish.

Consequently, the failure of bank and exploitation of the poor were common issues.

Hence, in order to control and regulate these banks, the Reserve Bank of India was

established on 1st April, 1935 in accordance with the provisions of the Reserve Bank of

India Act, 1934.

The Banking Regulation Act:

With a view to improve the functioning of the commercial banks, the Government of India

introduced a new legislation, known as the Banking Companies Act, 1949. This legislation

was later renamed as the Banking Regulation Act. According to this Act the Reserve Bank

of India was vested with the duties relating to licensing of banks, liquidity of bank‘s

assets, branch expansion, management and working methods, reconstruction,

amalgamation, and liquidation.

Establishment of the State Bank of India:

The All India Rural Credit Survey Committee recommended the creation of a state-

partnered and state-sponsored bank to serve the general economy in and particularly the

rural sector. Thus, in May, 1955, an act was passed in parliament and on 1st July, 1955, the

State Bank of India was established. But, soon the government came to know that State

Bank alone will not be enough to develop the Indian economy. So the plan for

nationalisation was passed 1968.

Nationalisation:

In 1969, Government of India Nationalized 14 banks with a view to serve the mass. Once

again in 1980, the Government of India implemented a second round of nationalisation,

placing six private banks under government control. Thus, only 10% of the bank branches

left in private hands.


34

2.7.2 Structure of the Indian Banking System

Structure of the Indian Banking System comprises a heterogeneous mass ranging from the

unorganized indigenous bankers to the foreign banks. Structure of the Indian Banking

System has at the apex the RBI. It performs as a central bank in India. It has taken

developmental function also. The Indian Banking System is classified in two categories

(See Figure 2.6). The Scheduled Commercial Banks that covers most part of the banking

system in India, is further classified into Public Sector Banks, Private Sector banks,

Regional Rural Banks, and Foreign Banks.

Public Sector Banks are those in which the majority stake is held by the Government of

India. These government lead banks are dominating the banking sector in India. In Private

Sector Banks, the majority of share capital is held by private individuals and corporate.

The Banks that have their registered and head offices in a foreign country but operate

through their branches in India are called Foreign Banks. Regional Rural Banks are an

institution unique to India. They were established to operate exclusively in rural areas to

provide credit to small farmers, agricultural labourers, artisans, and small entrepreneurs.

These banks are governed by the RRB Act, 1976.


35

FIGURE 2.6: Structure of Indian Banking Sector


36

2.7.3 Reformation of Indian Banking System

The financial sector reforms were initiated in the early 1990s in response to financial

sector reforms initiated as a part of structural reforms encompassing trade, industry,

investment and external sector, launched by the Government of India in the backdrop of a

serious balance of payments problem. These reforms can be classified as:

Measures for Promotion of competition:

The measures taken for strengthening competition consists granting less functional

autonomy to public sector banks (PSB); introduction of transparent licensing policy

enabling the entry of private sector , dilution of government stake in the public sector

bank‘s equity allowing them to mobilize capital from the open market; foreign and joint

venture banks; allowing foreign direct investment (FDI) in the financial sector as well as

allowing portfolio investment; issue of guidelines on ownership and governance in private

sector banks.

Measures for Strengthening the role of market forces:

Measures initiated to strengthen the role of market forces consists progressive reduction in

SLR and CRR, deregulation of interest rates, and market determined pricing of

government securities.

Prudential measures:

It covered fulfillment of capital adequacy norms; and new accounting, income recognition,

provision, and exposure norms.

Legal Measures:

Institutional and legal measures were introduced to improve performance of banks in the

area of recovery. For up gradation of asset quality measures like Corporate Debt

Restructuring Mechanism, setting-up Lok Adalats, Asset Reconstruction Companies

(ARC), Debt Recovery Tribunals (DRT), Settlement Advisory Committees (SAC), etc.

were introduced. Enactment of securitization, enforcement of security interest act (Sarfaesi


37

Act), and reconstruction of financial assets was a second major mile stone in reforms.

Setting-up Credit Information Bureau (India) Ltd., (CIBL) for sharing credit information

and establishment of the Clearing Corporation of India Ltd, (CCIL) to act as central

counter party for facilitating payments and settlement systems relating to fixed income

securities and money market instruments extended support to banks.

Measures for strengthening supervision or supervisory controls:

Measures initiated to strengthen supervision or supervisory control included assignment of

risk weights to different categories of assets, norms on connected lending, credit

concentration norms, application of marked – to – market principle for investment

portfolio and fixation of limits for allocation of funds in sensitive factors and activities.

Moreover, know your customer (KYC) guidelines, introduction of capital charge for

market risk, high graded provisioning for non-performing assets (NPA), and anti-money

laundering (AML) standards, were adopted for implementation. In addition supervisory

measures like establishment of an individual board for financial supervision in RBI,

reforming the role of statutory auditors and improvement of internal control through

strong internal audit, strong corporate governance were also initiated.

Measures related to Technology:

The technology related measures included setting-up of Indian Financial Network

(INFINET) as the backbone of communication for the financial sector, beginning of

negotiated delink system for screen based trading in the government securities and

implementation of real time gross settlement (RTGS) system.

2.7.4 Need of Employee Wellness in Banking Sector:

Banking sector is one of the fastest growing service sectors in India. Banks play a pivotal

role in developing the economy of a country. During the past few decades banking sector

of India has undergone a swift change due to liberalization, privatization, globalization,

policy changes, changes in technology and intensive competition.

The conservative approach in all the sectors of banks have changed. Now banks focus

more on customers, providing them convenience, quality of service, innovation and the


38

speed of the services. Bank employees play a crucial role in the service quality and service

delivery of customers.

In past two decades, emergence of a global economy and deregulated markets have

changed the functioning of financial services (Kaur et al., 2017; Hassard et al., 2017).

There is a big change in banking operations and it has a severe effect on the work life of

bank employees who deal with these new structures and technological innovations. The

credit industry is facing a crucial phase because of global economic crisis and major

changes in organizations.

Two types of repercussions in the credit sector were seen. In one hand, there was a

continuous reduction in investment and savings of the clients, and, on the other hand, the

increasing unpredictability of the global economic market. Hence, it is obvious to expect

its impact on the psycho-physical wellness of employees (Frasquilho et al., 2016; Van Hal,

2015).

The International Labor Organization has warned about a number of issues for employees

in financial services; these included high pressure on time, problems of ergonomics, role

conflict, excessive work demands, difficult relationships with customers, and increasing

cases of stress and violence (Giga and Hoel, 2003).

Such changes have affected not only the work life but also in the daily lives of bank

employees. In reality, banking system, where there were no major changes for at least a

century, has been completely redesigned. These changes are implemented in reference of

increasing market competition, implementation of economic plans, reduced inflationary

rates, and institutional changes (Bozdo and Kripa, 2015; Silva and Navarro, 2012). The

new requirements and qualifications is due to unemployment, intensification of the labor

rhythm, and precariousness of work (Hantzaroula, 2015).

It is possible to affirm that the substantial changes that took place with the productive

restructuring were in the sense of implementing strategies such as charging clients for a

greater diversity of services and products, intensification of outsourcing, flexibility of

work, redefinition of tasks and traditional banking activities, and transferring more and

more services to the clients themselves (i.e., through home-banking) (Silva and Navarro,

2012; Blazy et al., 2014). In this new management model, bank employees have

experienced a full redefinition of their tasks, becoming bank sellers (rather than bank


39

employees), working with clients to meet the bank‘s targets in areas such as the sale of

investment funds, bonds, and insurance policies (Adrian and Ashcraft, 2016). Moreover, a

considerable reduction in job positions intensified the volume of work for those who

remained, as well as for new employees (Silva and Navarro, 2012). Studies also reveal that

the employees are facing problems like burnout, tension and lack of satisfaction, etc. in

banking sector (Chen and Lien, 2008; Bajpai and Srivastava, 2004). Thus, organisations

should assess employee wellness and genuinely try to increase awareness among

employees on the holistic dimensions to overall wellness.

2.8 Dimensions Influencing Bank Employee’s Wellness

According to the wellness literature a number of factors that influence holistic wellness.

These factors are like (a) physical, (b) social/relational, (c) occupational, (d) emotional, (e)

intellectual, (f) spiritual, and (g) environmental behaviors.

2.8.1 Physical Wellness

Physical wellness is defined as ―the degree to which one maintains and improves

cardiovascular fitness, flexibility, and strength‖ (Hettler, 1980). It includes maintaining

healthy diet and creating balance and harmony within body through awareness and

monitoring of physical signs, body feelings, tension patterns, internal states, and

reactions (Hettler,1980). It also includes one‘s awareness of physical self-care, activity

level, nutrition needs and use of medical services (Hettler,1980). Renger et al. (2000) also

defined physical wellness as one‘s level of fitness, nutrition and avoidance of harmful

activity. Like Hettler, they also included prevention, early recognition of problems,

perception and use of medical services.

Thus, physical wellness is the continuous and active effort of maintaining one‘s optimum

level of physical activity and awareness of nutrition, self-care and healthy lifestyle

choices. It includes one‘s perception and expectation of wellness. It also includes

acceptance of one‘s physical state.

2.8.2 Social Wellness

Social wellness focuses on one‘s relation to other individuals and the environment

(Hettler,1980). It includes one‘s level of involvement in the activities of the common


40

welfare of the community and environment. It involves the active promotion of a healthy

environment, betterment of community, effective communication and healthy

relationships with others. It focuses on having balance and integration of self with others,

community and nature. Renger et al.(2000) defined social wellness encompassing one‘s

interaction with others. They described it as the degree to which an individual is able to

get along well with people and is able to express personal feelings, needs and opinions.

They included support, intimacy, and fulfilling relationships as major concepts. Like

Hettler, they also considered the social interaction and contribution to the community.

Thus, social wellness is the movement towards balanced and integrated interaction

between the individual, society and nature.

2.8.3 Emotional Wellness

Emotional wellness is defined as ―the awareness and acceptance of a range of feelings in

one‘s self and others, as well as one‘s ability to constructively express, manage, and

integrate feelings‖ (Hettler,1980). It is a continual process consisting of awareness,

management of emotions, positive approach to life, constructive expression, and realistic

self-assessment (Hettler,1980). Renger et al.(2000) defined it as ―one‘s level of anxiety,

depression, well-being, self-control, and optimism‖. They also included feeling of

satisfaction, interest and enjoyment in life, and optimistic outlook. Thus, emotional

wellness is an awareness and acceptance of feelings, as well as a positive attitude about

life, oneself, and the future.

2.8.4 Intellectual Wellness

Intellectual wellness is defined as the level of one‘s mental engagement in creative and

stimulating activity and the use of knowledge resources (Hettler,1980). It emphasize on

the acquisition, development, application and articulation of critical thinking. Renger et al.

(2000) defined it as ―one‘s orientation and achievement toward personal growth, education

and achievement, and creativity‖. Thus, it is the perception and motivation for one‘s

optimal level of stimulating intellectual activity.


41

2.8.5 Spiritual Wellness

Spiritual wellness is defined as ―a worldview that gives unity and goals to thoughts and

actions, as well as the process of seeking meaning, purpose in existence, and actions, as

well as the process of seeking meaning, purpose in existence, and understanding of one‘s

place in the universe‖ (Hettler,1980). Renger et al. (2000) defined it as finding a basic

purpose in life and the pursuit of a fulfilling life; the ability to give and receive love, joy

and peace and one‘s willingness to help others. Thus, spiritual wellness is the indigenous

and continual search for meaning and purpose in life, while accepting and transcending

one‘s place in the complex and interrelated universe.

2.8.6 Occupational Wellness

It is defined as the level of satisfaction and enrichment gained by one‘s work and the

extent to which one‘s occupation allows for the expression of one‘s values (Hettler,1980).

Crose et al.(1992) defined occupational wellness as one‘s attitude towards work and

leisure, as well as one‘s work history, patterns and balance between vocational and leisure

activities, and vocational goals. Thus, occupational wellness is the degree to which one is

able to express individual values and achieve enrichment and personal satisfaction through

paid or unpaid work; individual attitude toward work and ability to manage several roles;

and individual way of using skills and abilities to contribute to the community.

2.8.7 Environmental Wellness

It is defined as the nature of one‘s reciprocal interaction with the environment. It includes

the impact on home and work life as well as balance between the two, and one‘s

relationship with nature and community resources (Renger et al. 2000). Thus,

environmental wellness is about balancing the home and work life, and understanding how

one can have an impact on that environment. It is a reciprocal relationship between the

environment and the individual in various roles and the individual‘s relationship with

nature and community resources.


42

2.9 Chapter Summary

The literature review discussed the history of the wellness paradigm, definitions of

wellness, models of wellness, wellness assessments, employee wellness, need of employee

wellness, banking sector in India, need of employee wellness in banking sector, and

dimensions affecting wellness of bank employees. The reviewed literature talks about a

continued need for a wellness focus, and a psychometrically sound employee wellness

assessment. Chapter 3 presents the research methodologies that were employed within the

present study.

Chapter-3: Report on the present research

43

CHAPTER – 3

REPORT ON THE PRESENT RESEARCH

Chapter 3 explains the research methods used to create the Employee Wellness Scale for

Bank employees, to examine the psychometric properties of the scale, and to assess the

level of wellness among bank employees. Particularly, the chapter reviews the following

information regarding the study: (a) research design, (b) population and sample, (c) data

collection, (d) instrument development procedures, (e) instrumentation, (f) research

purpose and hypotheses, (g) assessing psychometric properties and statistical analysis, and

(h) potential limitations of the study.

3.1 Research Design

The present research adopted a correlational research design as the research examined the

relationships between variables (Gall, Gall, & Borg, 2007). The focus of this research

investigation is to study employee wellness by developing the Employee Wellness Scale

(EWS) for Bank employees, and assessing the reliability and validity of the scale with a

population of Bank employees in Gujarat. The study also investigates the relationship

between Employee Wellness and demographic variables.

3.1.2 Population and Sample

There are 60364 bank employees (clerk, officer) in Gujarat (RBI, 2016). The required

sample size was calculated using 5% margin of error and 95% confidence interval. The

result shows at least 382 samples are required. For development of scale in the social

sciences, appropriate item/participant ratios should be 10:1 or 20:1 (Hair et al., 2006;

Mvududu & Sink, 2013; Tinsley & Tinsley, 1987). In current study total 496 samples were

collected, that equates to the 13:1 ratio.


44

3.2 Data Collection

The data was collected via face-to-face administration. A convenience sample of

participants was recruited from scheduled commercial banks in different districts of

Gujarat. The face-to-face collection began on 1st, November, 2017 and was completed on

1st, March 2018. The researcher administered the Employee Wellness Scale and affiliated

scales (i.e., Demographic Form, Current health issue form) to the employees of scheduled

commercial banks in different districts of Gujarat. For the instances where other

representatives administered the assessment, training was provided to ensure accurate and

reliable data collection procedures.

3.3 Instrument Development Procedures

The research study is aimed at developing the Employee Wellness Scale and assessing the

psychometric properties of it with a sample of Bank Employees. Moreover, the researcher

developed a general demographic questionnaire and Current health issue questionnaire for

Bank Employees. The study also explores the relationship between Employee Wellness

and demographic variables.

The steps for developing a scale vary within the literature. For the purposes of current

research study, a combination of different steps is followed. The specific scale

development steps utilised are as follow. (a) define the concept being measured, (b)


reviewed by experts, (e) creating a pool of validated items, (f) administering items to a


3.3.1 Step 1: Define the concept being measured

The wellness literature was reviewed and definition of wellness was comprised in order to

determine what would be measured. The plethora of definitions in the literature indicates

that it is difficult to define wellness. Hence, the researcher included the most cited

qualities of wellness within the literature to define the concept of employee wellness. In

order to develope the Employee Wellness Scale, the concept is determined as Employee

wellness, which involves the factors that are related to holistic health and wellbeing.


45

Moreover, according to wellness literature the wellness is distinctive and consists of

dimensions like Physical, Emotional, Social, Intellectual, and Spiritual. Hence, for the

purposes of current research study, Employee wellness is defined as the factors consisting

employee‘s wellbeing and leading towards a healthy and balanced life.

3.3.2 Step 2: Creation of an item pool

It contained development of Employee Wellness Scale items that contribute to Employee

wellness theoretically. The literature on wellness was reviewed thoroughly to search for

the e items contributing to Employee wellness. The researcher reviewed instruments that

measured similar constructs as well as diverse models of wellness. While developing the

pool of items, the items were added or deleted on the basis of wellness literature. At the

end, 55 items were chosen based on theory and the literature review.

3.3.3 Step 3: Choosing the scale type for measurement

This scale development step consisted of selecting the suitable scale type for the Employee

Wellness Scale. Likert scale is applicable for factor analysis and usually used in social

sciences researches (Mvududu and Sink, 2013; DeVellis, 2012). So, a five point Likert

scale format is selected. However, to develop Employee Wellness Scale, a verbal

frequency scale was utilised instead of the traditional Likert scale. Because verbal

frequency scale helps in examining the amount of time spent in behaviors and experiences.

It helps to understand what is happening in the lives of Bank employees and allows for an

opportunity to discuss the frequencies of activities. The verbal frequency scale measures

how often a wellness activity is performed while a likert scale measures strength of

agreement (Scarborough,2005).

3.3.4 Step 4: Getting the items reviewed by experts

Following the initial item development of the Employee wellness scale, 55 items were

selected based on theory and a review of the literature. The selected items were given to a

team of experts for review to maximize content validity of the instrument. Items which

were double-barreled, poorly worded, inconsistent with the particular dimension or

duplications were either rewritten or eliminated. At the end 36 items were finalised for the


46

Scale. The expert review process involved academicians working in a prominent business

schools and Senior Bank Managers. Consensus among experts indicates these items cover

the objects of the study and the matters to be measured, indicating the content validity of

the scale.

3.3.5 Step 5: Administering Items to a Development Sample

The Employee Wellness Scale was administered to a development sample. After removing

incomplete samples the researcher ended up with a total sample of 496 participants. Thus,

sample satisfied a 10:1 participant/item ratio.

3.3.6 Step 6: Evaluation of Items

Following administration of the Employee Wellness Scale to the sample of Bank

employees, items were evaluated via a variety of procedures to evaluate validity and

reliability of the Employee Wellness Scale. Validity was assessed by evaluating content

validity and construct validity. Additionally, Reliability of the scale was assessed by

evaluating internal consistency.

3.3.7 Step 7: Optimizing Scale Length

The last step of the scale development process involved optimisation of the scale length.

After data analysis, all items were analysed based on factor loading and inter-item

correlations. Researcher also assessed the overall goodness-of-fit of all the constructs to

determine the validity of the measures.

3.4 Instrumentation

Three data collection questionnaires are utilized in the present research. The first

questionnaire is the Employee Wellness Scale, which was developed during this research.

A second questionnaire is a General demographic form, which was administered with a

view to collect demographic information about the employee. A third questionnaire is a

Current health issue form which was administered with a view to collect information about

health issues faced by bank employees.


47

3.5 Purpose and Research Questions

Wellness is a multidimensional concept in nature. (Ardell, 1977; Hettler, 1980, Dunn,

1977, Myers et al., 2004). Moreover, absence of illness does not ensure wellness

(WHO,1958). Wellness is having holistic approach and involves both internal (self) and

external (environmental) factors (Roscoe, 2009). Wellness is dynamic in nature (Roscoe,

2009). Studies show that healthy individuals strive towards optimal functioning. (Ardell,

1977; Hettler, 1980; Dunn, 1977; Roscoe, 2009). Moreover, Wellness depends upon

personal motivation (Ardell, 1977; Hettler, 1980; Dunn, 1977) and individual

responsibility (Dunn, 1977). Hence, it is hypothesized that the Employee Wellness Scale

will produce a multidimensional factor structure, which includes internal and external

factors. However, due to the nature (exploratory) of the research that involved developing

a new Employee Wellness Scale, research questions supporting the exploration of the

Employee Wellness Scale were framed.

The purpose of developing the employee wellness scale was to assess the psychometric

properties of employee wellness in a sample of Bank employees in Gujarat.

3.5.1 Objectives

To explore the concept of Employee Wellness in the context of the banking sector.

To develop Employee Wellness Scale for bank employees

To assess the level of Employee Wellness in the banking sector of Gujarat.

To explore the relationship between Employee Wellness and Demographic variables.

3.5.2 Research Questions

The specific research questions that were investigated included the following:


What is the factor structure of the items on the Employee wellness Scale with a sample of

Bank employees in Gujarat?


48


What is the internal consistency reliability of the Employee wellness Scale with a sample

of bank employees in Gujarat?


What are the relationships between Bank employee‘s Employee wellness Scale score and


Based on this research question the following hypothesis was framed.



Level of Education.


What are the relationship between Bank employee‘s factor wise wellness score and their




Level of Education








between Total Environmental Wellness Score, Age, Designation, Bank Sector, Gender,




Level of Education


49



Level of Education



Level of Education


What are the most common health issues that Bank Employees experience?


independent of employee’s Designation


independent of employee’s Gender


independent of employee’s Age


independent of employee’s Level of Education





3.6 Statistical techniques for Analysis of collected data

For development of the Employee Wellness Scale, the researcher assessed the validity and

reliability of the instrument in a population of Bank Employees. The research also

explored the relationship between demographic variables and Employee Wellness.

Additionally, health issues among bank employees in Gujarat were also analysed. Data

analysis was conducted in the Statistical Package R and Microsoft Excel.


50

3.6.1 Data analysis for Research Question 1, 2

Validity:

A key component of a vigorous scale development is the validity of the scale with diverse

samples. The scale can be valid only when it is reliable. Validity shows the degree to

which a scale measures what it claims to measure (Dimitrov, 2012). Cronbach (1971)

defined validity as a process through which a researcher goes to collect evidence for

supporting inferences that are to be derived from the scores on a scale. Thus, while

assessing validity it is important to understand that an instrument or an assessment cannot

be deemed valid or invalid. Additionally, validity is about an explanation of data which is

derived from the use of a scale, rather than the scale itself (Dimitrov, 2012). However,

there is a debate among the scholars, how many types of validity should be examined

(DeVellis, 2012).

o Content Validity:

It shows the degree to which a set of items reflects the content of a scale (DeVellis, 2012).

Content validity also includes sampling adequacy (DeVellis, 2012).

A well defined content domain should be established to assess the content validity

(Messick, 1995). Moreover, all items on a scale must describe factors of the construct

being measured (Crocker and Algina, 2006). Hence, to ensure the content validity of the

Employee Wellness Scale, the scale was given to experts for review. Moreover, every item

included in the Employee Wellness Scale was based on the literature and theory of

wellness and health.

o Construct Validity:

Construct validity involves the degree to which a scale measures the construct it claims to

measure (DeVellis, 2012). Construct validity of Employee Wellness Scale was assessed by

conducting Factor Analysis.


51

Factor Analysis:

The validity of Employee Wellness Scale was assessed using factor analysis, which was

conducted by utilising two step wise approaches: (1) Exploratory Factor Analysis (EFA)

and (2) Confirmatory Factor Analysis (CFA).Factor analysis helps identify patterns

amongst several variables to be explored. It is also used to examine construct validity of

the scale (Crocker and Algina, 2006). Factor Analysis involves: (a) finding factors related

to a particular set of variables, (b) identifying what variables load on particular factors, (c)

assessing the correlations among the variables and factors, (e) assessing the correlations

among factors, and (f) determining the maximum variance accounted for by the factors

(Dimitrov, 2012). The final aim of factor analysis is to cover a maximum variance with the

least number of factors and scale items.

o Exploratory Factor Analysis:

Because of the exploratory nature of the research investigation, an exploratory factor

analysis was conducted. An exploratory factor analysis is a method to predict how many

factors underlie variables or which variables comprise a particular factor (DeVellis, 2012).

Additionally, the exploratory factor analysis is an appropriate introductory statistical

method for constructing a scale (DeVellis, 2012; Mvududu and Sink, 2013).

Most statistical software use Principal Component Analysis (PCA) as the default setting.

While conducting an Exploratory Factor Analysis, many times it is used as a factor

extraction method. However, it is not considered the most appropriate method of statistical

analysis for scale development. Additionally, Principal Component Analysis is not

considered a right type of factor analysis (Costello and Osborne, 2005). Hence, it is

suggested that Principal Axis Factoring (PAF), Maximum Likelihood (ML), and/or

Ordinary least Squares (also called ‗Minimum Residuals‘) is chosen for the Factor

Analysis (Costello and Osborne, 2005). So, the researcher employed an Ordinary least

Squares (also called ‗Minimum Residuals‘)to develop the Employee Wellness Scale.

Rotation methods are classified in two broad categories: orthogonal and oblique.

Orthogonal rotations produce factors that are uncorrelated while oblique rotations allow

the factors to correlate. In the social sciences we generally expect some correlation among


52

factors, since behavior is rarely divided into precisely enclosed units that function

independently of one another(Costello and Osborne, 2005). Therefore use of orthogonal

rotation leads to a less useful solution when factors are correlated. Thus, the researcher

chose oblique rotation between orthogonal and oblique rotations.

Eigen values or characteristic roots of each factor are analysed to determine the number of

factors to be retained in an Exploratory Factor Analysis model (DeVellis,2012). A

minimum eigenvalue to retain the factor is 1 (Crocker and Algina, 2008; DeVellis,

2012;Dimitrov, 2012). According to DeVellis (2012), the eigen values are effective if

there is a large sample size and the assessment has less than 40 variables (DeVellis,

2012).Though the eigen values are useful to determine the number of factors to be

retained, the scree test is considered more appropriate method for determining the factors

to be retained in an Exploratory Factor Analysis (DeVellis, 2012; Mvududu & Sink,

2013).However, Horn‘s Parallel Analysis (1965) is also considered effective in

determining the number of factors (Humphreys and Ilgen, 1969; Humphreys and

Montanelli, 1975).

Prior to conducting the Exploratory Factor Analysis the data was cleaned and examined

for irregular, missing, or outlying data. Additionally, there are many assumptions that

were assessed within the data. Particularly: (a) normality of the data; (b) appropriateness

of data;and (c) multicullinearity.

o Normality of the data:

The normality of the data was established by analysing histograms, skewness value and

kurtosis values. A close bell-shaped curvature on a data plot indicates normality of the

data. Additionally, skewness values within ± 3 limit and kurtosis values within ± 10 limit

indicates normality (Pallant, 2013).

o Appropriateness of data:

The Bartlet‘s test of sphericity (Bartlett, 1950) and the Kaiser-Meyer-Olkin (KMO)

Measure of Sampling Adequacy (Kaiser, 1974) was conducted to assess the

appropriateness of the data. The is considered appropriate for an Exploratory Factor


53

Analysis, if the the KMO score is approximately .60 and the Bartlet‘s sphericity test yield

significant results (Crocker and Algina,2006). For conducting Exploratory Factor

Analysis, KMO values of .80 to .90 are considered excellent (Costello and Osborne,2005;

Crocker and Algina, 2006).

o Multicullinearity:

Multicullinearity was examined by inter-item correlation analysis. Correlations of .85 or

higher in datasets suggest multicollinearity (Costello and Osborne,2005).

The results from the Exploratory Factor Analysis in this study provided a number of

factors to retain in the Employee Wellness construct and a clear idea of the factor

structures for the assessment of Employee wellness.

o Confirmatory Factor Analysis:

The EFA provides rudimentary idea for the factor structure of each dimension, but it is not

enough to conclusively set up the appropriate dimensionality of the assessment

(Panuwatwanich K. et.al., 2008; Byrne B.M. 2013). Therefore, Exploratory Factor

Analysis results were affirmed using Confirmatory Factor Analysis.

Confirmatory Factor Analysis is a theory-driven method which is used for testing the

hypotheses to identify a factor structure. It confirms the validity of theoretical structures

by testing the relationships among variables (Gerbing D.W., Anderson J.C.,1988; Kline

R.B.,2015).

Goodness-of-fit indices were examined to determine to determine the validity of the

Employee Wellness Scale. These indices are classified into two groups, namely

incremental fit indices and absolute fit indices. Incremental fit indices involves the degree

to which the proposed model is superior to the alternative baseline models by calculating

the comparison between the baseline model and expected model (Shah R., Goldstein

S.M.,2006). Absolute fit indices assess how well the proposed theory fits the data (Hair

J.F., Black W.C., Babin B.J., Anderson R.E.,2010). Hair et al. (2010) suggested to report


54

at least one incremental index (CFI or TLI) and one absolute index (RMSEA or SRMR).

The researcher here reported following indices in this study.

Chi-square Statistics:

The Chi-square statistic is the most fundamental absolute fit index, which is used to

measure the discrepancy between a hypothesised model and data (Ping R.A. Jr,2004).

However, the chi-squared test is considered to be sensitive and bias to sample size, thus its

value tend to rise with increasing sample size (Kline R.B.,2015). Thus, Chi-square and

degree of freedom are reported as descriptive data in the current research rather than a

strong inferential test to accept or reject a model.

Root Mean Squared Error of Approximation (RMSEA):

It tells us how well the model, with unknown but optimally chosen parameter estimates

would fit the populations covariance matrix (Byrne, 1998). It is regarded as one of the

most informative fit indices (Diamantopoulos and Siguaw, 2000: 85). The value of

RMSEA less than 0.07 shows a good fit (Steiger, 2007). RMSEA values less than 0.05 are

good, values between 0.05 and 0.08 are acceptable, values between 0.08 and 0.1 are

marginal, and values greater than 0.1 are poor (Fabrigar L. R. et.al., 1999).

Standardised Root Mean square Residual (SRMR):

It is the square root of the difference between the residuals of the sample covariance

matrix and the hypothesised covariance model. The value of SRMR less than less than

0.08 are considered acceptable (Hu and Bentler, 1999).

Comparative fit index (CFI):

The Comparative Fit Index compares the improvement of the overall fit of the researcher‘s

model to a null model taking the sample size into account. It assumes that all latent

variables are uncorrelated and compares the sample covariance matrix with this null

model. Values for CFI range between 0.0 and 1.0 with values closer to 1.0 indicating good

fit.


55

Tucker Lewis index (TLI):

The TLI indicates a correlation for model complexity. It is also called Non-normed Fit

Index. The TLI value over.90 or .95 is considered good fit (Hu and Bentler, 1999).

Reliability:

A measurement scale must be reliable in order to be valid (Reynolds, Livingston,

&Willson, 2009). Highly reliable instrument produces consistent scores that are not

influenced by large degrees of instrument error (Reynolds et al., 2009). The reliability of

the Employee Wellness Scale was assessed using internal consistency. To examine the

internal consistency reliability of the Employee Wellness Scale, Cronbach‘s coefficient

alpha was calculated (Cronbach, 1951).

o Cronbach’s Alpha:

Cronbach‘s coefficient alpha (1951) is the most widely used method to assess the

reliability of a scale (Streiner, 2003).It helps in examining the sampling error in a scale to

ensure internal consistency (Dimitrov, 2012). Moreover, it explains the level of correlation

between item values (Dimitrov, 2012). Additionally, highly correlated items usually

measure a same construct (Dimitrov, 2012). While items having a low level of correlation,

are considered a poor representation of the construct being measured. The value of

Cronbach‘s alpha ranged from 0 to 1, where values closer to 1 show higher reliability

(Dimitrov, 2012). A value of .70 or above usually shows high internal consistency of item

scores.

3.6.2 Data Analysis for Research Question 3, 4

The researcher used a Multiple linear regression (MLR) analysis to explore relationships

between a continuous dependent variable (Employee Wellness Scores) and the categorical

independent variables (demographic).

The researcher used Multiple Linear Regression analysis to examine if the demographic

variables predicted certain outcomes. The independent variables that were used included:


56

(a) Designation, (b) Gender, (c) Age, (d) Bank Sector, and (e) Education. The dependent

variables for the MLR were the seven factors (Physical, Intellectual, Occupational,

Environmental, Social, Emotional, Spiritual) of the Employee Wellness Scale and overall

Employee Wellness Score.

Multiple Linear Regression:

Multiple linear regression is an extension of the simple linear regression where multiple

independent variables exist. It is used to analyze the effect of more than one independent

variable on single dependent variable. To conduct regression analysis on categorical

demographic variables dummy variables were used.

The researcher assessed the data for assumption before conducting the Multiple Linear

Regression. The assumption of (a) Sample size, (b) Multicollinearity, (c) Outliers, (d)

Normality, (e) Linearity, and (f) homoscedasticity were examined.

Sample Size:

Assumption of sample size was assessed by the equation suggested by Tabachnick and

Fidell (2013).

N > 50 + 8m ( m = the number of independent variables, N = Sample size)

Multicollinearity:

The researcher assessed multicollinearity based on three criteria: (a) Correlation matrix,

(b) Variance Inflation Factor (VIF), and (c) Tolerance value.

Correlation matrix:

The researcher assessed the correlation coefficient of all independent variable. High

correlation coefficient value shows multicollinearity.


57

Tolerance value:

The tolerance measures the influence of one independent variable on all other independent

variables. Tolerance is defined as T = 1 – R² for these first step regression analysis.

Tolerance value less than 0.1 shows possibility of multicollinearity and less than 0.01

confirms multicollinearity.

Variance Inflation Factor (VIF):

The Variance Inflation Factor is defined as VIF = 1/T.VIF value greater than 10 shows

possibility of multicollinearityand greater than 100 confirms multicollinearity among the

variables.

Outliers, Normality, Linearity, and homoscedasticity:

The researcher generated scatter plots to assess for outliers, normality, linearity and

homoscedasticity. The researcher assessed scatterplots of the standardized residuals of the

variables to assess homoscedasticity. Pattern of association between the variables was

assessed in scatter plots to check linearity.

3.6.3 Data Analysis for Research Question 5:

The researcher used descriptive analysis and chi square analysis to understand common

health issues among bank employees.

In summary, the present research study contained the development of the Employee

Wellness Scale, assessed the psychometric properties of the scale with a sample of bank

employees, assessed relationship between demographic variables and Employee Wellness,

and identified common wellness issues among bank employees.

3.7 Chapter Summary:

The purpose of the present research investigation was to study employee wellness by

developing the Employee Wellness Scale and assess the psychometric properties of it in a

sample of bank employees. The chapter discussed the design of the research, population


58

and sampling methods, data collection methods, scale development method,

instrumentation, purpose of the research and hypothesis, and assessing psychometric

properties and statistical analysis. Chapter 4 builds upon Chapter 3 and presents the results

of the research study.

Chapter-4: Results and Discussions

59

CHAPTER – 4

RESULTS AND DISCUSSIONS

Chapter four discusses the results of the research questions that were assessed in this

study. Particularly, the present research investigated the psychometric features of the

Employee Wellness Scale in a population of Bank employees. The data were analyzed

using the Statistical Package R and Microsoft Excel. The research questions were

examined using: (a) Factor Analysis (b) Cronbach‘s alpha, (c) Multiple Linear Regression,

(d) Chi Square test, and (e) Descriptive Analysis.

4.1 Sampling and Data Collection

The population for the investigation of the Employee Wellness Scale consisted of clerk

and officers of scheduled commercial banks in Gujarat. The data was collected via face-to-

face administration. A convenience sample of participants was recruited from scheduled

commercial banks in different districts of Gujarat. First, the branch managers were

contacted to get the permission for conducting a survey. Once permission was granted, the

researcher actively recruited participants from the branch and offered face-to-face

administration of instrument.

4.2 Sample Demographics and Descriptive Statistics

In total 496 employees participated in the study. The district wise response rate is

presented in Table 4.1. Total percentage of samples received from different districts is

presented in Figure 4.1. The bank wise response rate is presented in Table 4.2. Total

percentage of samples received from different banks is presented in Figure 4.2.


60

TABLE 4.1: District wise amount of sample received

District Wise Amount of Sample Received from Respondents

District Frequency Ratio

Ahmedabad 166 33.47%

Amreli 7 1.41%

Anand 24 4.84%

Bharuch 8 1.61%

Bhavnagar 22 4.44%

Botad 6 1.21%

Dahod 2 0.40%

Deesa 3 0.60%

Gandhinagar 16 3.23%

Gir Somnath 17 3.43%

Jamnagar 15 3.02%

Junagadh 16 3.23%

Kutch 33 6.65%

Morbi 23 4.64%

Porbandar 2 0.40%

Rajkot 75 15.12%

Surat 13 2.62%

Surendranagar 32 6.45%

Vadodara 12 2.42%

Valsad 4 0.81%

Total 496


61

FIGURE 4.1: District Wise Amount of Samples Received

(source: inference from study)

33.47%

1.41% 4.84%

1.61% 4.44%

1.21%

0.40%

0.60%

3.23% 3.43%

3.02%

3.23%

6.65%

4.64%

0.40%

15.12%

2.62% 6.45%

2.42% 0.81%

District Wise Amount of Samples Received

Ahmedabad

Amreli

Anand

Bharuch

Bhavnagar

Botad

Dahod

Deesa

Gandhinagar

Gir Somnath

Jamnagar

Junagadh

Kutch

Morbi

Porbandar

Rajkot

Surat

Surendranagar

Vadodara

Valsad


62

TABLE 4.2: Bank wise amount of survey received

Bank Wise Amount of Survey Received from Respondents

Name of Bank Frequency Ratio

Andhra Bank 7 1.41%

Axis Bank 69 13.91%

Bandhan Bank 7 1.41%

Bank of Maharashtra 4 0.81%

Baroda Gramin Bank 1 0.20%

Bank of Baroda 70 14.11%

Bank of India 44 8.87%

Canara Bank 6 1.21%

Central Bank of India 22 4.44%

Corporation Bank 23 4.64%

Dena Bank 27 5.44%

Federal Bank 7 1.41%

HDFC Bank 25 5.04%

ICICI Bank 21 4.23%

Indian Bank 7 1.41%

IndusInd 21 4.23%

Indian Overseas Bank 4 0.81%

Kotak Mahindra Bank 10 2.02%

Oriental Bank of Commerce 13 2.62%

Panjab National Bank 9 1.81%

Panjab Sindh Bank 4 0.81%

RBL Bank 6 1.21%

State Bank of India 59 11.90%

Syndicate Bank 4 0.81%

UCO Bank 7 1.41%

Union Bank 14 2.82%

Vijya Bank 5 1.01%

Total 496


63

FIGURE 4.2: Bank wise amount of samples received (source: inference from study)

1.41%

13.91%

1.41%

0.81%

0.20%

14.11%

8.87%

1.21%

4.44% 4.64%

5.44%

1.41%

5.04%

4.23%

1.41%

4.23%

0.81%

2.02%

2.62%

1.81%

0.81%

1.21%

11.90%

0.81%

1.41%

2.82%

1.01%

Bank wise amount of samples received

Andhra Bank

Axis Bank

Bandhan Bank

Bank of Maharashtra

Baroda Gramin Bank

Bank of Baroda

Bank of India

Canara Bank

Central Bank of India

Corporation Bank

Dena Bank

Federal Bank

HDFC Bank

ICICI Bank

Indian Bank

IndusInd

Indian Overseas Bank

Kotak Mahindra Bank

Oriental Bank of Commerce

Panjab National Bank

Panjab Sindh Bank

RBL Bank


64

4.2.1 Participant’s Personal Characteristics

The participants (N = 496) reported gender consisted of 400 males (81%) and 96females

(19 %). Marital Status of participants (N = 496) was reported as 386 Married (78%), 106

Single (21%), 3 Divorced (1%), and 1 Widowed (0.20%).Physical disability of

participants (N =496) was reported as 12 Physically challenged (2.42%). The mean age of

participants (N = 496) was 37.80 (S.D. = 8.56) years. The participants‘ personal

characteristics are presented in Table 4.3.

TABLE 4.3: Categorical Demographic Variables - Participant Personal

Characteristics

Data Category Total (n) Percentage

Gender (N =496)

Male 400 81%

Female 96 19%

Marital Status (N = 496)

Single 106 21%

Married 386 78

Divorced 3 01%

Widow 1 0.20%

Physical Disability (N = 496)

Yes 12 2.42%

No 484 97.58%

Age (N=496) 37.80

(S.B.=8.56)


65

4.2.2 Participants’ Professional Characteristics

Regarding specific Bank Employee groups, the participants (N = 496) identified as 191

Clerks (39%) and 305 Officers (61%). Reported banking sector of participants (N = 496)

was 328 Public sector employee (66.13%) and 168 Private sector employee (33.87%).

Reported Education qualification of participants (N = 496) was 289 Graduate (58%) and

207 Post graduate (42%).The mean work experience of the participants (N = 496) was

13.45 (S.D. = 7.38) years.The participants‘ professional characteristics are presented in

Table 4.4.

TABLE 4.4: Categorical Demographic Variables - Participant Characteristics

Data Category Total (n) Percentage

Designation (N =496)

Clerk 191 39%

Officer 305 61%

Banking Sector (N = 496)

Public 328 66.13%

Private 168 33.87%

Education Qualification (N = 496)

Graduate 289 58%

Post Graduate 207 42%

Work Experience (N = 496) 13.45

(S.D.=7.38)


66

4.3 Data Analysis and Results Based on Research Question

The data were analyzed using the Statistical Package R and Microsoft Excel. Before

evaluating the research questions, the researcher cleaned and vetted the data for outliers

and missing data. The researcher also conducted statistical tests to assess the assumptions

for the statistical analyses for each research question.

For research question 1, the researcher begin with Exploratory factor analysis (EFA) to

explore the factor structure of the Employee Wellness Scale data and, examined potential

correlations among variables (Henson & Roberts, 2010). The EFA aims at retaining the

least number of factors, while explaining the maximum variance shared among variables

(Henson & Roberts, 2006). Through EFA analysis, the researcher tried to develop a

model, where the maximum information could be explained with the fewest number of

items and factors (Henson & Roberts, 2006).

The EFA provided rudimentary factor structure of Employee Wellness Construct, but the

analysis is not sufficient to conclusively set up the suitable dimensionality of the

Employee Wellness Scale (Panuwatwanich K. et.al., 2008; Byrne B.M. 2013). Therefore,

Exploratory Factor Analysis results were affirmed using Confirmatory Factor Analysis.

For Research Question 2, the researcher computed Cronbach‘s alpha. Cronbach‘s alpha

was computed to assess the internal consistency reliability. It helps in examining the

sampling error in a scale to ensure internal consistency (Dimitrov, 2012). Moreover, it

explains the level of correlation between item values (Dimitrov, 2012). Additionally,

highly correlated items usually measure a same construct (Dimitrov, 2012). While items

having a low level of correlation, are considered a poor representation of the construct

being measured. The value of Cronbach‘s alpha ranged from 0 to 1, where values closer to

1 show higher reliability (Dimitrov, 2012). A value of .70 or above usually shows high

internal consistency of item scores. The researcher calculated Cronbach‘s alpha values for

all the Employee Wellness Scale items and for all seven factors of the Employee Wellness

Scale to assess overall instrument internal consistency as well as individual factor internal

consistency values.


67

The research question 3 and 4 were assessed using a multiple regression analysis. The

multiple regression analysis aims at exploring the relationship or predictability among

variables (Pallant, 2013; Tabachnick & Fidell, 2013). Particularly, the relationships

between a dependent variable such as one of the factors on the Employee Wellness Scale

and several independent variables such as demographic variables were explored.

Demographic variables (e.g. gender, designation, level of education, bank sector) collected

in the current research investigation were coded with dummy variable, and a multiple

regression was used to analyze if any of the demographic variables predicted any of the

seven factors of Employee Wellness Scale or Overall Employee Wellness Score.

The research question 5 was assessed using chi square analysis and descriptive analysis.

The results for the five research questions are explained below.

4.3.1 Research Question 1


Bank employees in Gujarat?

The researcher begin with Exploratory factor analysis with the 36 item (N = 496) to

examine factor structure of employee wellness construct. Before conducting an

Exploratory factor analysis, numerous statistical assumptions were examined to check if

the data was appropriate for factor analysis. The assumptions that were examined in this

research study included: (a) normality of the data; (b) appropriateness of data; and (c)

multicullinearity.

o Normality of the data:

The normality of the data was established by analysing histograms (see Appendix V),

skewness value and kurtosis values. The descriptive analysis of the data is presented in

Table 4.5. Skewness values within ±3 limit and kurtosis values within ± 10 limit indicate

normality (Pallant, 2013). For the data, skewness and kurtosis values for all items fell

within the acceptable range.


68

TABLE 4.5: Descriptive Analysis

Variable N Mean SD Median Skew Kurtosis

Item 1 496 3.29 1.14 3 -0.66 -0.08

Item 2 496 3.68 1.05 4 -0.44 -0.46

Item 3 496 3.61 1.22 3 -0.34 -0.91

Item 4 496 3.78 1.16 4 -0.47 -0.84

Item 5 496 3.59 1.13 3 -0.22 -0.87

Item 6 496 3.17 1.09 3 0.1 -0.55

Item 7 496 3.56 1.28 3 -0.37 -0.91

Item 8 496 3.81 1.25 4 -0.55 -0.89

Item 9 496 3.45 1.25 3 -0.07 -1.37

Item 10 496 3.47 1.25 3 -0.18 -1.13

Item 11 496 2.67 1.09 2 0.62 -0.41

Item 12 496 3.45 1.21 3 -0.04 -1.24

Item 13 496 3.55 1.27 4 -0.3 -1.15

Item 14 496 3.09 1.32 3 0.08 -1.18

Item 15 496 3.57 1.27 4 -0.37 -1.05

Item 16 496 2.95 1.32 3 0.15 -1.12

Item 17 496 3.59 1.29 4 -0.52 -0.86

Item 18 496 3.51 1.3 4 -0.28 -1.21

Item 19 496 3.78 1.22 4 -0.46 -1.07

Item 20 496 3.49 1.08 3 -0.09 -0.8

Item 21 496 3.79 1.19 4 -0.57 -0.72

Item 22 496 3.71 1.19 4 -0.4 -1.02

Item 23 496 3.71 1.25 4 -0.52 -0.89

Item 24 496 3.84 1.19 4 -0.6 -0.86

Item 25 496 3.85 1.14 4 -0.49 -1.09

Item 26 496 3.8 1.12 4 -0.48 -1.04

Item 27 496 3.69 1.22 2 0.48 -0.65

Item 28 496 3.67 1.23 4 -0.37 -1.19

Item 29 496 3.95 1.13 3 -0.05 -0.87

Item 30 496 3.96 1.03 4 -0.53 -0.81

Item 31 496 3.8 1.15 4 -0.58 -0.71

Item 32 496 3.36 0.94 3 -0.44 -0.15

Item 33 496 3.51 1.27 3.5 -0.34 -0.97

Item 34 496 3.55 1.15 4 -0.22 -1

Item 35 496 3.45 1.32 3 -0.24 -1.18

Item 36 496 3.47 1.17 3 -0.19 -0.99


69

o Appropriateness of data:

The appropriateness of the data was examined byconducting, Bartlet‘s test of sphericity

(Bartlett, 1950) (See Table 4.6) and the Kaiser-Meyer-Olkin (KMO) Measure of Sampling

Adequacy (Kaiser, 1974) (See Table 4.7).

TABLE 4.6:Bartlet’s test of sphericity

Chi Square P. Value Df

9797.81 0 630

TABLE 4.7: Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy

Overall MSA = 0.93

Items MSA Items MSA

I1 0.93 I19 0.93

I2 0.94 I20 0.96

I3 0.94 I21 0.95

I4 0.96 I22 0.94

I5 0.96 I23 0.95

I6 0.95 I24 0.94

I7 0.94 I25 0.89

I8 0.90 I26 0.93

I9 0.90 I27 0.92

I10 0.89 I28 0.95

I11 0.84 I29 0.93

I12 0.87 I30 0.92

I13 0.94 I31 0.96

I14 0.93 I32 0.94

I15 0.94 I33 0.95

I16 0.95 I34 0.93

I17 0.93 I35 0.92

I18 0.93 I36 0.94

In order for the data to be appropriate for an Exploratory Factor Analysis, Bartlet‘s

sphericity test must yield significant results and the KMO score must be approximately .60

(Crocker and Algina,2006). KMO values of .80 to .90 are considered excellent for

Exploratory Factor Analysis (Costello and Osborne,2005; Crocker and Algina, 2006).The

KMO analysis produced an overall MSA value of .93, which is considered sufficient for


70

EFA (Dimitrov, 2012, DeVellis, 2013).Bartlett‘s test of sphericity produced a statistically

significant value, indicating correlated data(Crocker &Algina,2006).

o Multicullinearity:

Multicullinearity was examined by inter-item correlation analysis (See Appendix VII).

Correlations of .85 or higher in datasets suggest multicollinearity (Costello &

Osborne,2005).Item reduction can be done through inter-item correlations (Hinkin, 1998).

Items could be eliminated from the initial pool if the inter-item correlations between the

different items exceed .7. According to Boyle(1991) this could help in avoiding too much

redundancy and artificially inflated estimates of internal consistency. Since in the present

case no inter-item correlation exceeded .7, none of the items were eliminated.

o Exploratory Factor Analysis:

Principal Component Analysis (PCA) is the default setting in most statistical software

when conducting an Exploratory Factor Analysis and it is often used as a factor extraction

method. However, it is not the most appropriate statistical analysis for scale development.

Additionally, Principal Component Analysis is not a true form of factor analysis (Costello

& Osborne, 2005). Thus, it is recommended that Maximum Likelihood (ML), Principal

Axis Factoring (PAF) or Ordinary least Squares (also called ‗Minimum Residuals‘) be

selected for the Factor Analysis method (Costello & Osborne, 2005). So, the researcher

employed an Ordinary least Squares to develop the Employee Wellness Scale.

Rotation methods are classified in two broad categories: orthogonal and oblique.

Orthogonal rotations produce factors that are uncorrelated while oblique rotations allow

the factors to correlate. In the social sciences we generally expect some correlation among

factors, since behavior is rarely divided into precisely enclosed units that function

independently of one another (Costello & Osborne, 2005). Therefore use of orthogonal

rotation leads to a less useful solution when factors are correlated. Thus, the researcher

chose oblique rotation between orthogonal and oblique rotations.

Eigen values or characteristic roots of each factor are analysed to determine the number of

factors to be retained in an Exploratory Factor Analysis model (DeVellis,2012). A cutoff


71

value for factor eigen values is 1 (Crocker & Algina, 2008; DeVellis, 2012;Dimitrov,

2012).Though the eigen values can be useful to determine the number of factors to be

retained ,the scree test is considered as an accurate method for determining the number of

factors in an Exploratory Factor Analysis (DeVellis, 2012; Mvududu& Sink, 2013).

However, Horn‘s Parallel Analysis (1965) is also considered effective in determining the

number of factors (Humphreys and Ilgen, 1969; Humphreys and Montanelli, 1975). Thus,

the researcher used Scree plot (see Figure 4.3), and Parallel analysis (see Figure 4.4)

methods to decide the number of factors that need to be extracted.


72

FIGURE 4.3: Scree plot for Employee Wellness Scale


73

Parallel analysis suggests that the number of factors = 7

FIGURE 4.4: Parallel Analysis for Employee Wellness Scale


74

The Exploratory Factor Analysis with an oblique rotation identified a seven factor solution

(see Table 4.8.1, Table 4.8.2) with eigen values greater than 1.0 within the data. The seven

factor model (see figure 11) accounted for 55 % of the variance, which is satisfactory in

social science research (Hair et al., 2006).

The result of Exploratory Factor Analysis show that the measuring items of each of the

dimensions of Employee Wellness only loads on its purported factor, which supports the

each of the hypothesised dimensions of Employee Wellness.

The factor loadings of the indicator variables on each of the dimensions (factors) of

Employee Wellness are robust and range between 0.44 to 0.84indicate that the selected

measuring items are closely related to the latent variables (dimensions).

Additionally, it can be seen that eight items were loaded in the first factor. These items

measured the wellness pertaining to the physical aspects of employee‘s wellness. Hence

the factor was designated as ‗Physical Wellness‘. Four itemswere intended to measure the

intellectual aspects of employee‘s wellness, and as such termed as ‗Intellectual Wellness‘.

Four items were intended to measure the occupational aspects of employee‘s wellness, so

the factor was designated as ‗Occupational Wellness‘. Seven items were intended to

measure the environmental aspects of employee‘s wellness, so the factor was designated

as ‗Environmental Wellness‘. Four items were intended to measure the social aspects of

employee‘s wellness, so the factor was designated as ‗Social Wellness‘. Five items were

intended to measure the emotional aspects of employee‘s wellness, so the factor was

designated as ‗Emotional Wellness‘. Four items were intended to measure the spiritual

aspects of employee‘s wellness, so the factor was designated as ‗Spiritual Wellness‘.


75

TABLE 4.8.1: Exploratory Factor Analysis of the Employee Wellness Scale

Ph

ysi

cal

En

vir

on

men

tal

Sp

irit

ual

Em

oti

on

al

Soci

al

Inte

llec

t

ual

Occ

up

at

ion

al

I1 0.61 -0.10 0.05 -0.01 0.06 0.13 -0.03

I2 0.66 -0.04 -0.12 0.05 0.00 -0.01 0.08

I3 0.71 0.05 -0.05 -0.01 -0.02 0.00 0.16

I4 0.65 0.07 0.01 0.05 0.01 0.02 0.13

I5 0.64 -0.01 0.10 0.05 0.08 0.04 -0.07

I6 0.59 -0.08 0.04 -0.08 0.14 0.12 0.03

I7 0.75 0.07 0.08 0.06 -0.08 0.01 -0.07

I8 0.68 0.03 0.03 -0.04 0.03 -0.13 -0.10

I9 0.14 0.08 0.04 0.01 0.02 0.50 -0.16

I10 0.08 0.04 -0.02 0.00 0.05 0.72 0.01

I11 -0.06 -0.04 0.07 0.04 -0.05 0.71 0.06

I12 0.00 0.08 -0.04 0.03 0.11 0.54 -0.04

I13 0.09 0.11 0.06 0.03 -0.02 0.05 0.60

I14 0.03 0.02 0.11 0.07 0.11 -0.02 0.71

I15 0.11 0.23 0.07 -0.02 0.04 0.11 0.55

I16 0.06 0.08 0.13 0.04 0.00 0.03 0.51

I17 0.04 0.56 -0.05 0.11 -0.01 0.10 0.16

I18 0.10 0.53 -0.07 0.23 -0.08 0.07 0.17

I19 0.04 0.50 0.02 0.05 0.10 0.24 0.03

I20 -0.05 0.44 0.08 0.09 0.10 0.16 0.06

I21 0.02 0.56 0.08 0.00 0.12 -0.02 0.08

I22 0.05 0.60 0.12 0.00 0.20 -0.04 -0.03

I23 0.03 0.66 0.12 0.01 0.04 -0.02 -0.02

I24 0.05 0.08 0.03 0.11 0.60 -0.07 0.04

I25 0.04 0.00 -0.02 0.01 0.84 0.05 -0.02

I26 0.01 0.09 -0.01 0.10 0.62 -0.08 0.09

I27 -0.08 0.03 0.13 -0.06 0.51 0.19 0.03

I28 0.01 -0.03 0.04 0.62 0.12 0.02 0.30

I29 0.01 -0.07 0.23 0.59 0.09 0.01 -0.06

I30 0.00 0.09 0.04 0.76 0.01 0.02 -0.15

I31 0.05 0.13 0.03 0.64 0.01 0.05 0.10

I32 0.10 -0.03 -0.08 0.52 0.05 0.03 0.06

I33 0.03 0.07 0.69 0.08 -0.07 0.03 0.17

I34 0.00 -0.03 0.73 0.00 0.03 0.08 0.08

I35 0.01 -0.01 0.75 0.02 0.03 0.03 0.03

I36 0.06 0.10 0.69 0.06 0.04 -0.09 -0.13


76

TABLE 4.8.2: Exploratory Factor Analysis of the Employee Wellness Scale

Ph

ysi

cal

En

vir

on

men

tal

Sp

irit

ual

Em

oti

on

al

Soci

al

Inte

llec

tual

Occ

up

ati

on

al

SS loadings 4.06 3.24 2.79 2.83 2.38 2.11 2.35

Proportion

Var 0.11 0.09 0.08 0.08 0.07 0.06 0.07

Cumulative Var

0.11 0.20 0.28 0.36 0.42 0.48 0.55

Proportion

Explained 0.21 0.16 0.14 0.14 0.12 0.11 0.12

Cumulative Proportion

0.21 0.37 0.51 0.65 0.77 0.88 1.0


77

FIGURE 4.5: EFA model of Employee Wellness Construct

MR1= Environmental; MR2= Physical; MR3= Intellectual; MR4= Social; MR5=

Spiritual ; MR6= Emotional ; MR7= Occupational


78

The Exploratory Factor Analysis provides a rudimentary level factor structure of each

construct, but the analysis is not enough to conclusively setup the appropriate

dimensionality of the measures (Panuwatwanich K. et.al., 2008; Byrne B.M. 2013).

Therefore, Exploratory Factor Analysis results were affirmed using Confirmatory Factor

Analysis.

o Confirmatory Factor Analysis:

Goodness-of-fit indices were examined to determine the validity of the Employee

Wellness Scale.

The Confirmatory Factor Analysis yielded an acceptable level of fit: Chi square = 1622.7,

df = 587, RMSEA = 0.060, SRMR = 0.051, CFI = 0.890, and TLI = 0.882. (See Figure

4.6)


79

FIGURE 4.6: CFA model of Employee Wellness Construct

WEL = Wellness; PHY = Physical Wellness; INT = Intellectual Wellness;

OCC = Occupational Wellness; ENW = Environmental Wellness; SOC = Social Wellness;

EMO = Emotional Wellness; SPI = Spiritual Wellness


80

4.3.2 Research Question 2

Internal consistency reliability of the Employee Wellness Scale was assessed by

calculating Cronbach‘s coefficient alpha (Cronbach, 1951).The value of Cronbach‘s alpha

range from 0 to 1, where values closer to 1 shows higher reliability (Dimitrov, 2012). A

value of .70 or above usually shows appropriate internal consistency of item scores.

Cronbach‘s α values were calculated for all the Employee Wellness Scale items (N = 496)

and for all seven factors of the Employee Wellness Scale to assess overall instrument

internal consistency as well as individual factor internal consistency totals.

The Cronbach‘s α value for the 36-item total scale (N = 496) was .94. For Factor 1:

Physical Wellness, Cronbach‘s α value was .88; for Factor 2: Intellectual Wellness,

Cronbach‘s α value was .75; Factor 3: Occupational Wellness, Cronbach‘s α value was

.85; Factor 4: Environmental Wellness, Cronbach‘s α value was .88; Factor 5: Social

Wellness, Cronbach‘s α value was .80; Factor 6: Emotional Wellness, Cronbach‘s α value

was .86; and Factor 5: Spiritual Wellness, Cronbach‘s α value was .86. Therefore, all

Cronbach α values were above the recommended .70 value and indicate strong internal

consistency within the final Employee Wellness Scale 36-item model.

4.3.3 Research Question-3 and 4


between a continuous dependent variable (Employee Wellness Scores) and the categorical

independent variables (demographic).

The independent variables that were used included: (a) Designation, (b) Gender, (c) Age,

(d) Bank Sector, and (e) Education. The dependent variables for the MLR were the seven

factors (Physical, Intellectual, Occupational, Environmental, Social, Emotional, Spiritual)

of the Employee Wellness Scale and overall Employee Wellness Score. To conduct

regression analysis on categorical demographic variables dummy variables were used.





81

o Sample Size:

Assumption of sample size was assessed by the equation suggested by Tabachnick and

Fidell (2013).

N > 50 + 8m ( m = the number of independent variables, N = Sample size)

Because the researcher included five independent variables in the MLR, a minimum of 90

participants was needed to satisfy the sample size requirement. Thus, a sample of N = 496

was appropriate for MLR analysis.

o Multicollinearity:

The researcher assessed multicollinearity based on three criteria: (a) Correlation matrix,

(b) Variance Inflation Factor (VIF), and (c) Tolerance value.

o Correlation matrix:

The researcher assessed the correlation coefficient of all independent variable. High

correlation coefficient value shows multicollinearity. The correlation matrix did not show

high correlation coefficient (See Table 4.9).

TABLE 4.9: Correlation coefficient matrix

DEG SEC AGE GEN EDU

DEG 1.00

SEC 0.00 1.00

AGE 0.06 0.58 1.00

GEN -0.04 -0.04 -0.15 1.00

EDU -0.05 -0.01 -0.08 0.01 1.00

o Tolerance value:

The tolerance measures the influence of one independent variable on all other independent

variables. Tolerance is defined as T = 1 – R² for these first step regression analysis.

Tolerance value less than 0.1 shows possibility of multicollinearity and less than 0.01


82

confirms multicollinearity. The Tolerance values found sufficient for MLR analysis (See

Table 4.10).

TABLE 4.10: Tolerance value of independent variables

Variable Tolerance Value

Designation 0.991365

Sector 0.656702

Age 0.638112

Gender 0.973952

Education 0.990193

o Variance Inflation Factor (VIF):

The Variance Inflation Factor is defined as VIF = 1/T.VIF value greater than 10 shows

possibility of multicollinearity and greater than 100 confirms multicollinearity among the

variables. The VIF values are found sufficient for MLR analysis (See Table 4.11).

TABLE 4.11: VIF value of independent variables

Variable VIF Value

Designation 1.008710

Sector 1.522760

Age 1.567122

Gender 1.026744

Education 1.009904


83

o Outliers, Normality, Linearity, and homoscedasticity:

The researcher generated scatter plots to assess for outliers, normality, linearity and

homoscedasticity (See Appendix VI). The researcher evaluated scatterplots of the

standardized residuals of the variables to assess homoscedasticity. Pattern of association

between the variables was assessed in scatter plots to check linearity. The analysis of

scatter plots shows there is no outlier in the data. All the scatterplots of the standardized

residuals resulted in relatively straight lines that indicate normality (Pallant, 2013) and

fulfill the homoscedasticity assumption. Linearity of data was assessed by checking the

pattern of relationship between the variables by visually examining their scatterplots.

Because there were no issues of non-linearity, the assumption of linearity was met. The

data was found normal when assessed for normality (See Table 4.12)

TABLE 4.12: Kurtosis and Skewness

N mean sd median skew kurtosis

Designation 496 0.62 0.49 1 -0.48 -1.77

Bank Sector 496 0.66 0.47 1 -0.68 -1.54

Age 496 37.80 8.57 37 0.57 -0.51

Gender 496 0.19 0.40 0 1.55 0.39

Education 496 0.42 0.49 0 0.33 -1.89

Total Employee Wellness

Score

496 126.57 25.21 129 -0.50 -0.08

Total Physical Wellness

Score

496 28.49 6.89 30 -0.72 -0.44

Total Intellectual Wellness Score

496 13.04 3.63 13 0.05 -0.82

Total Occupational

Wellness Score

496 13.17 4.30 13 -0.18 -0.87

Total Environmental Wellness Score

496 25.57 6.54 27 -0.61 -0.29

Total Social Wellness Score

496 14.18 3.71 15 -0.30 -0.79

Total Emotional Wellness Score

496 18.15 4.38 19 -0.50 -0.72

Total Spiritual Wellness Score

496 13.97 4.15 15 -0.34 -1.06


84

o Relationship between Employee Wellness Score and Demographic Variables:



Level of Education

TABLE 4.13: MLR for Employee Wellness Score and Demographic Variables

Regression Statistics

Multiple R R Square

Adjusted R

Square Standard Error Observations

0.63 0.40 0.39 19.63 496

ANOVA

df SS MS F Significance

F

Regression 5.00 125726.72 25145.34 65.25 0.00

Residual 490.00 188818.81 385.34

Total 495.00 314545.53

Coefficients

Coefficients

Standard

Error t Stat P-value

Intercept 178.30 4.56 39.08 0.00

Designation -26.69 1.82 -14.66 0.00

Bank Sector -1.39 2.30 -0.60 0.55

Age -0.89 0.13 -6.92 0.00

Gender 4.74 2.26 2.10 0.04

Education -3.70 1.80 -2.06 0.04

As shown in Table 4.13 the linear composite of the predictor variables predicted

approximately (r = .63; r2 = .40) and accounted for 40% of the variance in Employee

Wellness , F (5, 490) = 65.25, p < .05. Except bank sector all independent variables

predicted Employee Wellness Score significantly with designation accounted for highest

level of beta value. The Multiple linear regression has small effect size (Cohen, 1988).


85

o Relationship between Factor-1(Physical Wellness) and Demographic Variables:



Level of Education

TABLE 4.14: MLR for Factor-1 (Physical Wellness) and Demographic Variables


Multiple R R Square Adjusted R

Square Standard

Error Observations

0.66 0.43 0.43 5.21 496.00

ANOVA


F

Regression 5.00 10216.66 2043.33 75.39 0.00

Residual 490.00 13281.32 27.10

Total 495.00 23497.98

Coefficients

Coefficients Standard


Intercept 46.93 1.21 38.79 0.00

Designation -3.95 0.48 -8.18 0.00

Bank

Sector -0.55 0.61 -0.90 0.37

Age -0.42 0.03 -12.24 0.00

Gender 2.54 0.60 4.24 0.00

Education -0.73 0.48 -1.54 0.12


approximately (r = .66; r2 = .43) and accounted for 43% of the variance in Physical

Wellness , F (5, 490) = 75.39, p < .05. Except bank sector and education all independent

variables predicted Physical Wellness Score significantly with designation accounted for

highest level of beta value. The Multiple linear regression has small effect size (Cohen,

1988).


86

o Relationship between Factor-2 (Intellectual Wellness) and Demographic

Variables:




TABLE 4.15: MLR for Factor-2 (Intellectual Wellness) and Demographic Variables



Square Standard

Error Observations

0.33 0.11 0.10 3.45 496.00

ANOVA


F

Regression 5.00 702.84 140.57 11.84 0.00

Residual 490.00 5815.43 11.87

Total 495.00 6518.27

Coefficients



Intercept 17.04 0.80 21.28 0.00

Designation -1.97 0.32 -6.17 0.00

Bank Sector -0.37 0.40 -0.91 0.36

Age -0.07 0.02 -2.89 0.00

Gender -0.20 0.40 -0.50 0.62

Education -0.07 0.32 -0.23 0.82


approximately (r = .33; r2 = .11) and accounted for 11% of the variance in Intellectual

Wellness , F (5, 490) = 11.84, p < .05. Except bank sector and Gender all independent

variables predicted Intellectual Wellness Score significantly with designation accounted

for highest level of beta value. The Multiple linear regression has low effect size (Cohen,

1988).


87

o Relationship between Factor-3 (Occupational Wellness) and Demographic

Variables:




TABLE 4.16: MLR for Factor-3 (Occupational Wellness) and Demographic

Variables


Multiple R R Square

Adjusted R

Square

Standard

Error Observations

0.74 0.55 0.54 2.91 496.00

ANOVA

df SS MS F

Significance

F

Regression 5.00 5006.16 1001.23 118.04 0.00

Residual 490.00 4156.29 8.48

Total 495.00 9162.44

Coefficients

Coefficients

Standard


Intercept 20.62 0.66 30.46 0.00

Designation -6.26 0.27 -23.16 0.00

Bank

Sector 0.02 0.34 0.07 0.94

Age -0.09 0.02 -4.77 0.00

Gender -0.02 0.34 -0.05 0.96

Education -0.38 0.27 -1.42 0.16


approximately (r = .74; r2 = .55) and accounted for 55% of the variance in Occupational

Wellness , F (5, 490) = 118.04, p < .05. Except bank sector, Gender, and Education all

independent variables predicted Occupational Wellness Score significantly with

designation accounted for highest level of beta value. The Multiple linear regression has

small effect size (Cohen, 1988).


88

o Relationship between Factor-4 (Environmental Wellness) and Demographic

Variables:




TABLE 4.17: MLR for Factor-4 (Environmental Wellness) and Demographic

Variables


Multiple R R Square

Adjusted R

Square

Standard

Error Observations

0.50 0.25 0.25 5.68 496.00

ANOVA

df SS MS F

Significance

F

Regression 5.00 5405.47 1081.09 33.53 0.00

Residual 490.00 15798.06 32.24

Total 495.00 21203.53

Coefficients

Coefficients

Standard


Intercept 35.21 1.32 26.68 0.00

Designation -5.75 0.53 -10.92 0.00

Bank

Sector -0.49 0.66 -0.73 0.46

Age -0.15 0.04 -3.91 0.00

Gender 1.38 0.65 2.10 0.04

Education -1.25 0.52 -2.40 0.02


approximately (r = .50; r2 = .25) and accounted for 25% of the variance in Environmental

Wellness , F (5, 490) = 33.53, p < .05. Except bank sector all independent variables

predicted Environmental Wellness Score significantly with designation accounted for

highest level of beta value. The Multiple linear regression has small effect size (Cohen,

1988).


89

o Relationship between Factor-5 (Social Wellness) and Demographic Variables:



Level of Education

TABLE 4.18: MLR for Factor-5 (Social Wellness) and Demographic Variables



Square Standard

Error Observations

0.35 0.12 0.11 3.49 496.00

ANOVA


F

Regression 5.00 820.13 164.03 13.44 0.00

Residual 490.00 5980.90 12.21

Total 495.00 6801.03

Coefficients



Intercept 17.59 0.81 21.66 0.00

Designation -2.28 0.32 -7.04 0.00

Bank

Sector 0.02 0.41 -0.05 0.96

Age -0.05 0.02 -2.23 0.03

Gender 0.75 0.40 1.87 0.06

Education -0.54 0.32 -1.69 0.09


approximately (r = .35; r2 = .12) and accounted for 12% of the variance in Social Wellness,

F (5, 490) = 13.44, p < .05. Except Bank sector and Gender all independent variables

predicted Social Wellness Score significantly with designation accounted for highest level

of beta value. The Multiple linear regression has low effect size (Cohen, 1988).


90

o Relationship between Factor-6 (Emotional Wellness) and Demographic

Variables:



Level of Education

TABLE 4.19: MLR for Factor-6 (Emotional Wellness) and Demographic Variables



Square Standard

Error Observations

0.44 0.19 0.19 3.96 496.00

ANOVA


F

Regression 5.00 1839.09 367.82 23.49 0.00

Residual 490.00 7671.87 15.66

Total 495.00 9510.96

Coefficients



Intercept 23.93 0.92 26.02 0.00

Designation -3.56 0.37 -9.70 0.00

Bank Sector -0.02 0.46 -0.04 0.97

Age -0.08 0.03 -3.21 0.00

Gender -0.22 0.46 -0.49 0.63

Education -0.88 0.36 -2.44 0.02


approximately (r = .44; r2 = .19) and accounted for 19% of the variance in Emotional

Wellness, F (5, 490) = 23.49, p < .05. Except Bank sector and Gender all independent

variables predicted Emotional Wellness Score significantly with designation accounted for

highest level of beta value. The Multiple linear regression has low effect size (Cohen,

1988).


91

o Relationship between Factor-7 (Spiritual Wellness) and Demographic Variables:



Level of Education

TABLE 4.20: MLR for Factor-7 (Spiritual Wellness) and Demographic Variables



Square Standard

Error Observations

0.36 0.13 0.12 3.89 496.00

ANOVA


F

Regression 5.00 1126.70 225.34 14.93 0.00

Residual 490.00 7397.96 15.10

Total 495.00 8524.66

Coefficients



Intercept 16.99 0.90 18.82 0.00

Designation -2.92 0.36 -8.11 0.00

Bank

Sector -0.01 0.45 -0.02 0.98

Age -0.04 0.03 -1.42 0.16

Gender 0.50 0.45 1.13 0.26

Education 0.15 0.36 0.43 0.67


approximately (r = .36; r2 = .13) and accounted for 13% of the variance in Emotional

Wellness, F (5, 490) = 14.93, p < .05. Except Designation no independent variables

predicted Spiritual Wellness Score significantly. The Multiple linear regression has low

effect size (Cohen, 1988).


92

4.3.4 Research Question-5

The researcher used descriptive analysis to understand common health issues among bank

employees. Additionally, chi square analysis was used to analyse the relationship between

demographic variables and prevalence of health issues. Prevalence of health issues among

bank employees is given in Table 4.21 (also see Figure 4.7).

TABLE 4.21: Prevalence of Health issues among bank employees in Gujarat

Health issues among bank employees Frequency Percentage

Heart and Cardiovascular disease 15 3.02%

Diabetes 29 5.85%

Cancer 0 0.00%

Overweight/ Obesity 32 6.45%

Tobacco / Alcohol addiction 73 14.72%

Neck pain /Back pain/ Joint pain 128 25.81%

Digestive disorder 27 5.44%

Anemia 28 5.65%

Eye problems 0 0.00%

Other health issues 22 4.44%

Total 354 71.37


93

FIGURE 4.7: Prevalence of Health issues among bank employees in Gujarat


Among other health issues it was found that 17 employees were suffering from frequent

headache. Moreover other health issues like Thyroid, Asthma and Allergic Cold were

reported by some employees.

0 20 40 60 80 100 120 140

Heart and Cardiovascular disease

Diabetes

Cancer

Overweight/ Obesity

Tobacco / Alcohol addiction

Neck pain /Back pain/ Joint pain

Digestive disorder

Anemia

Eye problems

Other health issues

Prevalence of Health issues among bank employees in

Gujarat

Frequency


94

Prevalence of Health issues and Employee’s Designation:



TABLE 4.22: Chi Square Analysis – Hypothesis 9

Designation Prevalence of Health Issues

Yes No Total

Officer 140 165 305

Clerk 56 135 191

Total 196 300 496

Chi Square 13.5122

P Value 0.000237

Result Hypothesis is Rejected

Analysis of health issues among Bank officers and Clerks are given in Figure 4.8 (also see

Table 4.28).


95

FIGURE 4.8: Prevalence of Health issues among Officers and Clerks


0 20 40 60 80 100

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Officers and

Clerks

Clerk (N = 191) Officer (N = 305)


96

Prevalence of Health issues and Employee’s Gender:




Gender Prevalence of Health Issues

Yes No Total

Male 167 233 400

Female 29 67 96

Total 196 300 496

Chi Square 4.3149

P Value 0.03778


Analysis of health issues among Male and Female employees are given in Figure 4.9 (also

see Table 4.28).


97

FIGURE 4.9: Prevalence of Health issues among Male and Female Employees


0 20 40 60 80 100 120

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Male and

Female Employees

Female (N = 96) Male (N = 400)


98

Prevalence of Health issues and Employee’s Age:




Age Prevalence of Health Issues

Yes No Total

21 to 30 Years 9 103 112

31 to 40 Years 77 159 236

> 40 Years 110 38 148

Total 196 300 496

Chi Square 126.1511

P Value 0.00001


Analysis of health issues among employees of different age group is given in Figure 4.10

(also see Table 4.28).


99

FIGURE 4.10: Prevalence of Health issues among Bank employees of different age

group (source: inference from study)

0 20 40 60 80 100

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Bank

employees of different age group

> 40 Years (N = 148) 31 to 40 Years ( N = 236)

21 to 30 Years ( N = 112)


100

Prevalence of Health issues and Employee’s level of education:



Table 4.25: Chi Square Analysis – Hypothesis 12

Education Prevalence of Health Issues

Yes No Total

Graduate 107 182 289

Post Graduate 89 118 207

Total 196 300 496

Chi Square 1.7991

P Value 0.179819

Result Hypothesis is Accepted

Analysis of health issues among employees with different education qualification is given

in Figure 4.11 (also see Table 4.28).


101

FIGURE 4.11: Prevalence of Health issues among Bank employees with different

education qualification (source: inference from study)

0 20 40 60 80

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Bank

employees with different education

qualification

Post graduate (N = 207) Graduate (N = 289)


102

Prevalence of Health issues and the type of banking sector where employees is

working:




Bank Sector Prevelance of Health Issues

Yes No Total

Public 164 164 328

Private 32 136 168

Total 196 300 496

Chi Square 44.5323

P Value 0.00001

Result Hypothesis is Accepted

Analysis of health issues among employees of Public sector banks and Private sector

banks is given in Figure 4.12 (also see Table 4.28).


103

FIGURE 4.12: Prevalence of Health issues among Public sector and Private sector

bank employees (source: inference from study)

0 20 40 60 80 100 120

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Public sector

bank and Private sector bank employees

Private (N = 168) Public (N = 328)


104

Prevalence of Health issues and Employee’s work experience in Banking sector:



TABLE 4.27: Chi Square Analysis – Hypothesis14

Prevelance of Health Issues

Yes No Total

<=10 Years 40 180 220

11 to 20 Years 66 102 168

> 20 Years 90 18 108

Total 196 300 496

Chi Square 128.655

P Value 0.00001


Analysis of health issues among bank employees with different work experience is given

in Figure 4.13 (also see Table 4.28).


105

FIGURE 4.13: Prevalence of Health issues among Bank employees with different

work experience (source: inference from study)

0 20 40 60 80 100

Cardiovascular

Diabetes

Overweight

Tobacco/Alcohol

Body pain

Digestive disorder

Anemia

Headache

Other

Prevalence of Health issues among Bank employees

with different work experience

> 20 years (N = 108) 11 to 20 years (N = 168) <=10 years (N = 220)


106

TABLE 4.28: Analysis of Prevalence of Health issues among Bank Employees


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4.4 Discussion

4.4.1 Review of Descriptive Data

In total 496 employees of 27 scheduled commercial banks, participated from 20 districts

of Gujarat in the study. The participants (N = 496) reported gender consisted of 400 males

(81%) and 96 females (19 %). Marital Status of participants (N = 496) was reported as 386

Married (78%), 106 Single (21%), 3 Divorced (1%), and 1 Widowed (0.20%). Physical

disability of participants (N =496) was reported as 12 Physically challenged (2.42%). The

mean age of participants (N = 496)was 37.80 (S.D. = 8.56) years. Regarding specific

Bank Employee groups, the participants (N = 496) identified as 191 Clerks (39%) and 305

Officers (61%). Reported banking sector of participants (N = 496) was 328 Public sector

employee (66.13%) and 168 Private sector employee (33.87%). Reported Education

qualification of participants (N = 496) was 289 Graduate (58%) and 207 Post graduate

(42%).The mean work experience of the participants (N = 496) was 13.45 (S.D. = 7.38)

years.

The researcher did not find any previous employee wellness-related research studies where

the sample consisted of bank employees. The current study remains unique in the

sampling methodology used as well as in the population. Descriptive data results from this

research investigation were consistent the banking population in India (RBI), supporting

the generalisability of the findings to similar populations.

4.4.2 Research Question Results

o Research Question 1: What is the factor structure of the items on the Employee

wellness Scale with a sample of Bank employees in Gujarat?

For Research Question 1, the researcher conducted Factor Analysis. The researcher begin

with an exploratory factor analysis (EFA) to examine the factor structure of the Employee

Wellness Scale data as well as examine potential correlations between variables (Henson

& Roberts, 2010).


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Prior to conducting the Exploratory Factor Analysis, many assumptions were explored

within the data. Particularly: (a) normality of the data; (b) appropriateness of data; and (c)

multicullinearity.

The researcher conducted an Exploratory Factor Analysis that identified a seven-factor

solution with eigen values greater than 1.0 within the data. The seven factors accounted

for 55% of the variance, which is satisfactory in social science research (Hair et al., 2006).

Factor 1 represented Physical Wellness and accounted for 11% of the variance, Factor 2

represented Intellectual Wellness and accounted for 6% of the variance, Factor 3

represented Occupational Wellness and accounted for 7% of the variance, Factor 4

represented Environmental Wellness and accounted for 9% of the variance, Factor 5

represented Social Wellness and accounted for 7% of the variance, Factor 6 represented

Emotional Wellness and accounted for 8% of the variance, and Factor 7 represented

Spiritual Wellness and accounted for 8% of the variance.

Confirmatory factor analysis (CFA) was conducted to examine the overall goodness-of-fit

of all the constructs to assess the validity of the measures. Model yielded an acceptable

level of fit: RMSEA = 0.06, CFI = 0.89, and TLI = 0.89. The CFA model fit well with the

collected data and the relationships between the observed variables and latent variables

were significant.

The final Employee Wellness Scale model includes some factors that were consistent with

other wellness related assessments. For example, the Physical Wellness factor (i.e. items

1,2,3,4,5,6,7,8) found in the Employee Wellness Scale model was consistent with other

wellness scales and models such as Hettler‘s hexagonal model (Hettler, 1980), 5F-Wel

(Myers et al., 2004) , and the Wheel of Wellness Model (WEL; Myers et al., 1998),

supporting physical wellness as a key component of holistic wellness. The Intellectual

Wellness factor (i.e. items 9,10,11,12) found in the Employee Wellness Scale model was

consistent with other wellness scales and models such as Hettler‘s hexagonal model

(Hettler, 1980), 5F-Wel (Myers et al., 2004) , and the PWS (Adams et al., 1997),

supporting Intellectual wellness as a key component of holistic wellness. The

Occupational Wellness


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factor (i.e. items 13,14,15,16) found in the Employee Wellness Scale model was consistent

with other wellness scales and models such as Hettler‘s hexagonal model (Hettler, 1980),

Wheel of Wellness Model (WEL; Myers et al., 1998), supporting Occupational wellness

as a key component of holistic wellness. The Environmental Wellness factor (i.e. items 17,

18, 19, 20, 21, 22, 23) found in the Employee Wellness Scale model was consistent with

other wellness scales such as optimal living profile (Renger et al. 2000), supporting

Environmental wellness as a key component of holistic wellness. The Social Wellness

factor (i.e. items 24, 25, 26, 27) found in the Employee Wellness Scale model was

consistent with other wellness scales and models such as Hettler‘s hexagonal model

(Hettler, 1980), Wheel of Wellness Model (WEL; Myers et al., 1998), 5F-Wel (Myers et

al., 2004) , and the PWS (Adams et al., 1997), supporting Social wellness as a key

component of holistic wellness. The Emotional Wellness factor (i.e. items 28, 29, 30, 31,

32) found in the Employee Wellness Scale model was consistent with other wellness

scales and models such as Hettler‘s hexagonal model (Hettler, 1980), and the PWS

(Adams et al., 1997), supporting Emotional wellness as a key component of holistic

wellness. The Spiritual Wellness factor (i.e. items 33, 34, 35, 36) found in the Employee

Wellness Scale model was consistent with other wellness scales and models such as

Hettler‘s hexagonal model (Hettler, 1980), Wheel of Wellness Model (WEL; Myers et al.,

1998), and the PWS (Adams et al., 1997), supporting Spiritual wellness as a key

component of holistic wellness.

o Research Question 2: What is the internal consistency reliability of the Employee

wellness Scale with a sample of bank employees?

In order to assess internal consistency reliability of the Employee Wellness Scale,

Cronbach‘s coefficient alpha was used (Cronbach, 1951).The value of Cronbach‘s alpha

range between 0 and 1, with values closer to 1 representing higher reliability (Dimitrov,

2012). A value of .70 or above generally indicates appropriate internal consistency of item

scores. Cronbach‘s α values were calculated for all the Employee Wellness Scale items (N

= 496) and for all seven factors of the Employee Wellness Scale to assess overall

instrument internal consistency as well as individual factor internal consistency totals.

The Cronbach‘s α value for the 36-item total scale (N = 496) was .94. For Factor 1:

Physical Wellness, Cronbach‘s α value was .88; for Factor 2: Intellectual Wellness,


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Cronbach‘s α value was .75; Factor 3: Occupational Wellness, Cronbach‘s α value was

.85; Factor 4: Environmental Wellness, Cronbach‘s α value was .88; Factor 5: Social

Wellness, Cronbach‘s α value was .80; Factor 6: Emotional Wellness, Cronbach‘s α value

was .86; and Factor 5: Spiritual Wellness, Cronbach‘s α value was .86. Therefore, all

Cronbach α values were above the recommended .70 value and indicate strong internal

consistency within the final Employee Wellness Scale 36-item model.

o Research Question 3: What are the relationships between Bank employee’s

Employee wellness Scale score and their reported demographic data?


between a continuous dependent variable (Employee Wellness Scores) and the

demographic independent variables on the General Demographic Questionnaire. The

independent variables that were used included: Designation (Clerk/Officer), Gender

(Male/Female), Age, Bank Sector (Public/Private), and Education (Graduate/PG). To

conduct regression analysis on categorical demographic variables they were coded with

dummy variables.






Level of Education

Multiple Linear Regression: F (5, 490) = 65.25, p-value < 0.00 , R = 0.63, R2 = 0.40

Result: Hypothesis is Rejected

Designation, Bank Sector, Age, Gender, and Education explain 40% of the variability in

Total Employee Wellness Score. Designation, Age, Gender, and Level of Education

predicted Total Employee Wellness Score significantly with designation accounted for

highest level of beta value. As the designation changes from clerk to officer, on average,

the Total Employee Wellness Score decreases by 26.69, after adjusting for Age, Gender,

Bank sector, and education. Female, on average, has 4.74 point higher Total Employee


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Wellness Score compared to males, after adjusting for Designation, Age, Bank sector, and

education. As the level of education changes from graduate to post graduate, on average,

the Total Employee Wellness Score decreases by 3.70, after adjusting for Designation,

Age, Bank sector, and Gender. For a one-unit change in age, on average, the Total

Employee Wellness Score decreases by 0.89, after adjusting for Designation, Gender,

Bank sector, Level of Education. The Multiple linear regression has large effect size f 2 =

0.67 (Cohen, 1988).

o Research Question 4: What is the relationship between Bank employee’s factor

wise wellness score and their reported demographic data?


between a continuous dependent variable (Factors of Employee Wellness Scale) and the

demographic independent variables on the General Demographic Questionnaire. The

independent variables that were used included: Designation (Clerk/Officer), Gender

(Male/Female), Age, Bank Sector (Public/Private), and Education (Graduate/PG).



Level of Education


Result: Hypothesis is rejected

Designation, Age, and Gender predicted Total Physical Wellness Score significantly with

designation accounted for highest level of beta value. As the Designation changes from

clerk to officer, on average, the Total Physical Wellness Score decreases by 3.95, after

adjusting for Age, Gender, Bank sector, and Education. Females, on average, has 2.54

point higher Total Physical Wellness Score, after adjusting for Age, Gender, Bank sector,

and Education. For a one-unit change in age, on average, the Total Physical Wellness

Score decreases by 0.42, after adjusting for Designation, Gender, Bank sector, Level of

Education. The Multiple linear regression has large effect size f 2 = 0.75 (Cohen, 1988).


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Designation and Age predicted Total Intellectual Wellness Score significantly with


clerk to officer, on average, the Total Intellectual Wellness Score decreases by 1.97, after

adjusting for Age, Gender, Bank sector, and Education. For a one-unit change in age, on

average, the Total Intellectual Wellness Score decreases by 0.07, after adjusting for

Designation, Gender, Bank sector, Level of Education. The Multiple linear regression has

small effect size f 2 = 0.12 (Cohen, 1988).




Multiple Linear Regression: F (5, 490) = 118.04, p-value < 0.00, R = 0.74, R2 = 0.55


Designation and Age predicted Total Occupational Wellness Score significantly with


clerk to officer, on average, the Total Occupational Wellness Score decreases by 6.26,

after adjusting for Age, Gender, Bank sector, and Education. For a one-unit change in age,

on average, the Total Occupational Wellness Score decreases by 0.09, after adjusting for


large effect size f 2 = 1.22 (Cohen, 1988).


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Designation, Age, Gender, and Education predicted Total Environmental Wellness Score

significantly with designation accounted for highest level of beta value. As the

Designation changes from clerk to officer, on average, the Total Environmental Wellness

Score decreases by 5.75, after adjusting for Age, Gender, Bank sector, and Education.

Females, on average, has 1.38 point higher Total Environmental Wellness Score, after


average, the Total Environmental Wellness Score decreases by 0.15, after adjusting for

Designation, Gender, Bank sector, Level of Education. As the Level of Education changes

from graduate to post graduate, on average, the Total Environmental Wellness Score

decreases by 1.25, after adjusting for Designation, Age, Gender, and Bank sector. The

Multiple linear regression has medium effect size f 2 = 0.33 (Cohen, 1988).



Level of Education



Designation, Age, Gender, and Education predicted Total Social Wellness Score


Designation changes from clerk to officer, on average, the Total Social Wellness Score

decreases by 2.28, after adjusting for Age, Gender, Bank sector, and Education. For a one-

unit change in age, on average, the Total Social Wellness Score decreases by 0.05, after

adjusting for Designation, Gender, Bank sector, Level of Education. The Multiple linear

regression has small effect size f 2 = 0.14 (Cohen, 1988).


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Level of Education



Designation, Age, and Education predicted Total Emotional Wellness Score significantly

with designation accounted for highest level of beta value. As the Designation changes

from clerk to officer, on average, the Total Emotional Wellness Score decreases by 3.56,


on average, the Total Emotional Wellness Score decreases by 0.08, after adjusting for


medium effect size f 2 = 0.23 (Cohen, 1988).



Level of Education



Only Designation predicted Total Spiritual Wellness Score significantly with designation

accounted for highest level of beta value. The Multiple linear regression has medium

effect size f 2 = 0.15 (Cohen, 1988).

o Research Question 5: What are the most common health issues that Bank Employees

experience?

The descriptive statistics of the data collected for research question 4 shows that 25.81%

employees reported that they are suffering from joint pain/Neck pain/Back pain. 14.72%

reported that they have tobacco/alcohol addiction. 6.45% employees reported that they are

overweight. 5.85% employees reported they are suffering from diabetes. 5.65% reported

that they have anemia. 3.02% reported they have cardiovascular disease. 4.44% reported

they have other health issues. Among other health issues it was found that 3.4%


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employees are suffering from frequent headache. The result of chi square analysis is given

below:



Chi square = 13.51, P-Value < 0.00


The result shows that there is a significant relationship between employee‘s designation

and prevalence of health issue. Additionally, descriptive data analysis shows that 140

(45.90%) Bank Officers and 56 (29.32%) Clerks are suffering from some kind of health

issues. Moreover, 10 (3.28%) Bank officers and 5 (2.62%) Clerks are suffering from

cardiovascular diseases. 21 (6.89%) Bank officers and 8 (4.19%) Clerks are diabetic. 25

(8.20%) Bank officers and 7 (3.66%) Clerks are Overweight. 58 (19.02%) Bank officers

and 15 (7.85%) Clerks are having tobacco/alcohol addiction. 90 (29.51%) Bank officers

and 38 (19.90%) Clerks are suffering from some kind of Body pain. 20 (6.56%) Bank

officers and 7 (3.66%) Clerks are suffering from digestive disorder. 16 (5.25%) Bank

officers and 12 (6.28%) Clerks are having anemia. 15 (4.92%) Bank officers and 2

(1.05%) Clerks are suffering from frequent headaches. 3 (0.98%) Bank officers and 2

(1.05%) Clerks are having other health issues. Thus, Bank Officers are suffering from

more health issues compared to Clerks.





The result shows that there is a significant relationship between employee‘s gender and

prevalence of health issue. Additionally, descriptive data analysis shows that 167

(41.75%) Males and 29 (30.21%) Females are suffering from some kind of health issues.

Moreover, 15 (3.75%) Males are suffering from cardiovascular diseases, and 29 (7.25%)

Males are diabetic. Though, no females were suffering from cardiovascular diseases or

diabetes. 20 (5%) Males and 12 (12.50%) Females are Overweight. Thus, problem of

overweight was high among females. 17 (18%) Males and 1 (1.04%) Females are having


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tobacco/alcohol addiction. 111 (27.75%) Males and 17 (17.71%) Females are suffering

from some kind of Body pain, making it the major health issue among the bank

employees. 19 (4.75%) Males and 8 (8.33%) Females are suffering from digestive

disorder. 22 (5.50%) Males and 6 (6.25%) Females are having anemia. 15 (3.75%) Males

and 2 (2.08%) Females are suffering from frequent headaches. 2 (0.50%) Males and 3

(3.13%) Females are having other health issues. Thus, prevalence of cardiovascular

diseases, diabetes, tobacco/alcohol addiction, Body pain, and frequent headaches is higher

among male employees compared to female employees. While, prevalence of Overweight,

digestive disorder, anemia, and other health issues is higher among female employees

compared to male employees.





The result shows that there is a significant relationship between employee‘s age and

prevalence of health issue. Additionally, descriptive data analysis shows that 9 (8.04%) 21

to 30 years old, 77 (32.63%) 31 to 40 years old, and 110 (74.32%) more than 40 years old

bank employees are suffering from some kind of health issues. Moreover, 3 (1.27%) 31 to

40 years old, and 12 (8.11%) more than 40 years old bank employees are suffering from

cardiovascular diseases. 8 (3.39%) 31 to 40 years old, and 21 (14.19%) more than 40 years

old bank employees are diabetic. 2 (1.79%) 21 to 30 years old, 17 (7.20%) 31 to 40 years

old, and 13 (8.78%) more than 40 years old bank employees are Overweight. 3 (2.68%)

21 to 30 years old, 24 (10.17%) 31 to 40 years old, and 46 (31.08%) more than 40 years

old bank employees are having tobacco/alcohol addiction. 4 (3.57%) 21 to 30 years old, 35

(14.83%) 31 to 40 years old, and 89 (60.14%) more than 40 years old bank employees are

suffering from some kind of Body pain, making it the major health issue among the bank

employees. 2 (1.79%) 21 to 30 years old, 11 (4.66%) 31 to 40 years old, and 14 (9.46%)

more than 40 years old bank employees are suffering from digestive disorder. 1 (0.89%)

21 to 30 years old, 17 (7.20%) 31 to 40 years old, and 10 (6.76%) more than 40 years old

bank employees are having anemia. 2 (1.79%) 21 to 30 years old, 8 (3.39%) 31 to 40 years

old, and 7 (4.73%) more than 40 years old bank employees are suffering from frequent

headaches. 2 (0.85%) 31 to 40 years old, and 3 (2.03%) more than 40 years old bank


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employees are having other health issues. Thus, prevalence of health issues is higher

among employees of more than 40 years of age.




Result: Hypothesis is accepted

The result shows that there is no significant relationship between employee‘s level of

education and prevalence of health issue. However, descriptive data analysis shows that

107 (37.02%) Graduates and 89 (43.00%) Post Graduates bank employees are suffering

from some kind of health issues.


independent of the type of banking sector where employee is working



The result shows that there is a significant relationship between the type of banking sector

where employee is working and prevalence of health issue. Additionally, descriptive data

analysis shows that 164 (50%) Public sector bank employees, and 32 (19.05%) Private

sector bank employees are suffering from some kind of health issues. Moreover, 14

(4.27%) Public sector bank employees, and 1 (0.60%) Private Sector bank employees are

suffering from cardiovascular diseases. 27 (8.23%) Public sector bank employees, and 2

(1.19%) Private sector bank employees are diabetic. 25 (7.62%) Public sector bank

employees, 7 (4.17%) Private sector bank employees are Overweight. 65 (19.82%) Public

sector bank employees, and 8 (4.76%) Private sector bank employees are having

tobacco/alcohol addiction. 113 (34.45%) Public sector bank employees, and 15 (8.93%)

Private sector bank employees are suffering from some kind of Body pain, making it the

major health issue among the bank employees. 21 (6.40%) Public sector bank employees,

and 6 (3.57%) Private sector bank employees are suffering from digestive disorder. 19

(5.79%) Public sector bank employees, and 9 (5.36%) Private sector bank employees are

having anemia. 11 (3.35%) Public sector bank employees, and 6 (3.57%) Private sector

bank employees are suffering from frequent headaches. 4 (1.22%) Public sector bank


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employees, and 1 (0.60%) Private sector bank employees are having other health issues.

Thus, prevalence of health issues is higher among Public sector bank employees compared

to Private sector bank employees.





The result shows that there is a significant relationship between employee‘s work

experience in banking sector and prevalence of health issue. Additionally, descriptive data

analysis shows that 40 (18.18%) employees with less than or equal to 10 years of work

experience, 66 (39.29%) employees with 11 to 20 years of work experience, and 90

(83.33%) employees with more than 20 years of work experience are suffering from some

kind of health issues. Moreover, 1 (0.45%) employees with less than or equal to 10 years

of work experience, 4 (2.38%) employees with 11 to 20 years of work experience and 10

(9.26%) employees with more than 20 years of work experience are suffering from

cardiovascular diseases. 1 (0.45%) employees with less than or equal to 10 years of work

experience, 10 (5.95%) employees with 11 to 20 years of work experience, and

18(16.67%) employees with more than 20 years of work experience are diabetic. 8

(3.64%) employees with less than or equal to 10 years of work experience, 15 (8.93%)

employees with 11 to 20 years of work experience, and 9 (8.33%) employees with more

than 20 years of work experience are Overweight. 14 (6.36%) employees with less than or

equal to 10 years of work experience, 24 (14.29%) employees with 11 to 20 years of work

experience, and 35 (32.41%) employees with more than 20 years of work experience are

having tobacco/alcohol addiction. 20 (9.09%) employees with less than or equal to 10

years of work experience, 28 (16.67%) employees with 11 to 20 years of work experience,

and 80 (74.07%) employees with more than 20 years of work experience are suffering


employees. 5 (2.27%) employees with less than or equal to 10 years of work experience,

11 (6.55%) employees with 11 to 20 years of work experience, and 11 (10.19%)

employees with more than 20 years of work experience are suffering from digestive

disorder. 9 (4.09%) employees with less than or equal to 10 years of work experience, 12

(7.14%) employees with 11 to 20 years of work experience, and 7 (6.48%) employees with


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more than 20 years of work experience are having anemia. 6 (2.73%) employees with less

than or equal to 10 years of work experience, 5 (2.98%) employees with 11 to 20 years of

work experience, and 6 (5.56%) employees with more than 20 years of work experience

are suffering from frequent headaches. 4 (2.38%) employees with 11 to 20 years of work


having other health issues. Thus, prevalence of health issues is higher among employees

with more than 20 years of work experience in banking sector.

4.5 Chapter Summary

Chapter four discussed the results for the current research. The research questions were

analyzed using a various statistical methods: (a) Factor analysis, (b) Internal Consistency

testing using Cronbach‘s Alpha, (c) Multiple Linear Regression, (d) Descriptive Analysis,

and (e) Chi square analysis. Chapter 5 talks about the findings of the research as well as

the future scope of the research and implications for bank employees.

Chapter-5: Conclusions, Major Contributions, and Scope of further work

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CHAPTER – 5

CONCLUSIONS, MAJOR CONTRIBUTIONS,

AND SCOPE OF FURTHER WORK

Chapter 5 presents a review of the research study, research methodology utilised, and

findings from the investigation. Additionally, the findings regarding the five research

questions and implications for the bank employees are discussed. Moreover, Chapter 5

offers: (a) the limitations of the research investigation, (b) future scope of the research,

and (c) implications for the bank employees.

5.1 Introduction and Necessity for the Research Investigation

Banking sector is one of the fastest growing service sectors in India. Banking sector plays

a key role in developing the economy of a nation. During the last two decades, the banking

sector in India has experienced a rapid change due to liberalisation, globalisation, policy

changes, innovations in technology, and profound competition. From conservative

approach banks catapulted to a customer centric, technology driven, financial supermarket

catering to the varied needs of its customers. These changes have its impact on the work

life as well as the daily life of the bank employees. In reality, banking system, where there

were no major changes for at least a century, has been completely restructured. In this new

management model, bank employees have experienced a full redefinition of their tasks,

becoming bank sellers (rather than bank employees), working with clients to meet the

bank‘s targets in areas such as the sale of investment funds, bonds, and insurance policies

(Adrian and Ashcraft, 2016). Moreover, a considerable reduction in job positions

intensified the volume of work for those who remained, as well as for new employees

(Silva and Navarro, 2012).


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The International Labor Organization has warned about a number of issues for employees

in financial services; these included high pressure on time, problems of ergonomics, role

conflict, excessive work demands, difficult relationships with customers, and increasing

cases of stress and violence (Giga and Hoel, 2003). The National Institute for

Occupational Safety and Health (NIOSH) ranked occupations for stress levels, where 130

occupations found to be more stressful. Employees having insufficient control over the

work, and employees feel like being trapped in jobs where they are regarded as quasi-

machines rather than as humans, were common in all these stressful occupations.

Manager, Administrator and Supervisor were among the top 12 stressful positions and

bank teller was 28th on the list (Michailidis and Georgiou, 2005). Many studies reported

that employees are experiencing problems like stress, job burnout, and job dissatisfaction

in banking sector (Bajpai and Srivastava, 2004; Chen and Lien, 2008). Studies in literature

found that occupational stress leads to diseases, and may damage employees‘

psychological life as well as their professional, social, and affective lives. It leads to poor

work performance, a high rate of employee turnover, absenteeism, and workplace violence

(Bhagat et al., 2010; Burke, 2010; Dalgaard et al., 2017; Godin et al., 2005; Stansfeld and

Candy, 2006).

Bank employees play a key role in providing the quality service to the customers. Thus,

organisations should assess employee wellness and consistently strive for increasing

awareness among employees on the holistic components to overall wellness.

India is a kaleidoscope of customs, values, beliefs, and traditions. Thus, it is impossible to

generalise the Indian way of life. Each region in India has its own distinct culture,

language, cuisine, etiquette, social norms. As most of the models of employee wellness

have been developed in Western countries, primarily the United States there is a need to

study Indian paradigm.

Moreover, there are few scales and assessments for measuring wellness within the

literature. But, none of them is formed for bank employees. Additionally, very few

wellness scales are created according to the scale development procedures suggested by

eminent scholars of scale construction like DeVellis, 2012; Crocker and Algina, 2005;

Dimitrov, 2012 and applicable statistical analyses (e.g., Factor Analysis). Due to

aforementioned reasons, this research investigation assessed the psychometric properties

of Employee Wellness in a sample of bank employees.


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5.2 Review of Research Methodology

The following section presents a review of the research methodology utilised in the

present research. The detailed description of the research methodology is given in Chapter

3. The correlational research design is utilised this research (Gall et al., 2007). The major

research questions included as following:

o Research Question 1:


Bank employees?


What is the internal consistency reliability of the Employee wellness Scale with a sample

of bank employees?


What are the relationships between Bank employee‘s Employee wellness Scale score and



What are the relationship between Bank employee‘s factor wise wellness score and their



What are the most common health issues that Bank Employees experience?

5.2.1 Participants

The sampling procedures involved convenience sampling consisted of clerk and officers of

scheduled commercial banks in Gujarat.


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5.2.2 Data collection

The data was collected via face-to-face administration. The researcher administered the

Employee Wellness Scale and affiliated scales (i.e., Demographic Form, current health

issue form) to the employees of scheduled commercial banks in different districts of

Gujarat.

5.2.3 Instrumentation

The present research aimed at developing the Employee Wellness Scale and assessing the

psychometric properties of it with a sample of Bank Employees. Moreover, the researcher

developed a general demographic questionnaire and Current health issue questionnaire for

Bank Employees.

The steps for developing a scale vary within the literature. For the purposes of current

research study, a combination of different steps is followed. The specific scale

development steps utilised are as follow. (a) define the concept being measured, (b)


reviewed by experts, (e) creating a pool of validated items, (f) Administering items to a


There were three data collection questionnaire utilized within this study. The first

questionnaire was the Employee Wellness Scale, which was developed during this

research. A second questionnaire was developed with a view to collect demographic

information about the employees. A third questionnaire was developed with a view to

collect information about health issues faced by Bank employees.

5.2.4 Data analysis

The step of data analysis for the research involved data cleaning by assessing the presence

of outliers and/or missing data. The next step involved examination of statistical

assumption to assess the appropriateness of statistical analyses to investigate the research

questions. Statistical assumptions vary for each research question. However, the statistical

assumptions tested for current research included:


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(a) normality, (b) multicollinearity, (c) KMO value, (d) skewness, (e) kurtosis, and (f)

homoscedasticity. The researcher used the Statistical Package ‗R‘ and Microsoft Excel for

all data analyses.

5.3 Result

5.3.1 Research Question 1: What is the factor structure of the items on the

Employee wellness Scale with a sample of Bank employees in Gujarat?

The researcher conducted an Exploratory Factor Analysis that identified a seven-factor

solution with eigen values greater than 1.0 within the data. The seven factors accounted

for 55% of the variance, which is satisfactory in social science research (Hair et al., 2006).

Factor 1 represented Physical Wellness and accounted for 11% of the variance, Factor 2

represented Intellectual Wellness and accounted for 6% of the variance, Factor 3

represented Occupational Wellness and accounted for 7% of the variance, Factor 4

represented Environmental Wellness and accounted for 9% of the variance, Factor 5

represented Social Wellness and accounted for 7% of the variance, Factor 6 represented

Emotional Wellness and accounted for 8% of the variance, and Factor 7 represented

Spiritual Wellness and accounted for 8% of the variance.

Confirmatory factor analysis (CFA) was performed to assess the overall goodness-of-fit of

all the constructs to determine the validity of the measures. Model yielded an acceptable

level of fit: RMSEA = 0.06, CFI = 0.89 , and TLI = 0.88. The CFA model fit well with

the collected data and the relationships between the observed variables and latent variables

were significant.

5.3.2 Research Question 2: What is the internal consistency reliability of the

Employee wellness Scale with a sample of bank employees?

For Research Question 2, the researcher computed Cronbach‘s alfa to analyse the internal

consistency reliability of the Employee Wellness Scale with sample data. Computing

Cronbach‘s alpha helps to examine the degree of correlation among the items on the

Employee Wellness Scale. The Cronbach‘s α value for the 36 items (N = 496) was

calculated as .94. The factor wise Cronbach‘s α value range from .75 to .88.


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5.3.3 Research Question 3: What are the relationships between Bank employee’s

Employee wellness Scale score and their reported demographic data?



Level of Education

o Multiple Linear Regression: F (5, 490) = 65.25, p-value < 0.00 , R = 0.63, R2 = 0.40

o Result: Hypothesis is Rejected

Designation, Bank Sector, Age, Gender, and Education explain 40% of the variability in

Total Employee Wellness Score. Designation, Age, Gender, and Level of Education

predicted Total Employee Wellness Score significantly with designation accounted for

highest level of beta value. As the designation changes from clerk to officer, on average,

the Total Employee Wellness Score decreases by 26.69, after adjusting for Age, Gender,

Bank sector, and education. Female, on average, has 4.74 point higher Total Employee

Wellness Score compared to males, after adjusting for Designation, Age, Bank sector, and

education. As the level of education changes from graduate to post graduate, on average,

the Total Employee Wellness Score decreases by 3.70, after adjusting for Designation,

Age, Bank sector, and Gender. For a one-unit change in age, on average, the Total

Employee Wellness Score decreases by 0.89, after adjusting for Designation, Gender,

Bank sector, Level of Education. The Multiple linear regression has large effect size f 2 =

0.67 (Cohen, 1988).

5.3.4 Research Question 4: What is the relationship between Bank employee’s

factor wise wellness score and their reported demographic data?

Hypothesis 2: For the population of Bank employees, there is no linear association


Level of Education


o Result: Hypothesis is rejected


126

Designation, Age, and Gender predicted Total Physical Wellness Score significantly with


clerk to officer, on average, the Total Physical Wellness Score decreases by 3.95, after

adjusting for Age, Gender, Bank sector, and Education. Females, on average, has 2.54

point higher Total Physical Wellness Score, after adjusting for Age, Gender, Bank sector,

and Education. For a one-unit change in age, on average, the Total Physical Wellness

Score decreases by 0.42, after adjusting for Designation, Gender, Bank sector, Level of

Education. The Multiple linear regression has large effect size f 2 = 0.75 (Cohen, 1988).






Designation and Age predicted Total Intellectual Wellness Score significantly with


clerk to officer, on average, the Total Intellectual Wellness Score decreases by 1.97, after


average, the Total Intellectual Wellness Score decreases by 0.07, after adjusting for


small effect size f 2 = 0.12 (Cohen, 1988).




o Multiple Linear Regression: F (5, 490) = 118.04, p-value < 0.00, R = 0.74, R2 = 0.55



127

Designation and Age predicted Total Occupational Wellness Score significantly with


clerk to officer, on average, the Total Occupational Wellness Score decreases by 6.26,


on average, the Total Occupational Wellness Score decreases by 0.09, after adjusting for


large effect size f 2 = 1.22 (Cohen, 1988).


between Total Environmental Wellness Score, Age, Designation, Bank Sector,

Gender, and Level of Education



Designation, Age, Gender, and Education predicted Total Environmental Wellness Score


Designation changes from clerk to officer, on average, the Total Environmental Wellness

Score decreases by 5.75, after adjusting for Age, Gender, Bank sector, and Education.

Females, on average, has 1.38 point higher Total Environmental Wellness Score, after


average, the Total Environmental Wellness Score decreases by 0.15, after adjusting for

Designation, Gender, Bank sector, Level of Education. As the Level of Education changes

from graduate to post graduate, on average, the Total Environmental Wellness Score

decreases by 1.25, after adjusting for Designation, Age, Gender, and Bank sector. The

Multiple linear regression has medium effect size f 2 = 0.33 (Cohen, 1988).



Level of Education



128


Designation, Age, Gender, and Education predicted Total Social Wellness Score


Designation changes from clerk to officer, on average, the Total Social Wellness Score

decreases by 2.28, after adjusting for Age, Gender, Bank sector, and Education. For a one-

unit change in age, on average, the Total Social Wellness Score decreases by 0.05, after

adjusting for Designation, Gender, Bank sector, Level of Education. The Multiple linear

regression has small effect size f 2 = 0.14 (Cohen, 1988).



Level of Education



Designation, Age, and Education predicted Total Emotional Wellness Score significantly

with designation accounted for highest level of beta value. As the Designation changes

from clerk to officer, on average, the Total Emotional Wellness Score decreases by 3.56,


on average, the Total Emotional Wellness Score decreases by 0.08, after adjusting for


medium effect size f 2 = 0.23 (Cohen, 1988).



Level of Education




129

Only Designation predicted Total Spiritual Wellness Score significantly with designation

accounted for highest level of beta value. The Multiple linear regression has medium

effect size f 2 = 0.15 (Cohen, 1988).

5.3.5 Research Question 5: What are the most common health issues that Bank

Employees experience?


employees reported that they are suffering from joint pain/Neck pain/Back pain. 14.72%

reported that they have tobacco/alcohol addiction. 6.45% employees reported that they are

overweight. 5.85% employees reported they are suffering from diabetes. 5.65% reported

that they have anemia. 3.02% reported they have cardiovascular disease. 4.44% reported

they have other health issues. Among other health issues it was found that 3.4%

employees are suffering from frequent headache. The result of chi square analysis is given

below:

Hypothesis 9: For the population of Bank employees, prevalence of health issues is

independent of employee‘s Designation

o Chi square = 13.51, P-Value < 0.00


The result shows that there is a significant relationship between employee‘s designation

and prevalence of health issue. Additionally, descriptive data analysis shows that 140

(45.90%) Bank Officers and 56 (29.32%) Clerks are suffering from some kind of health

issues. Moreover, 10 (3.28%) Bank officers and 5 (2.62%) Clerks are suffering from

cardiovascular diseases. 21 (6.89%) Bank officers and 8 (4.19%) Clerks are diabetic. 25

(8.20%) Bank officers and 7 (3.66%) Clerks are Overweight. 58 (19.02%) Bank officers

and 15 (7.85%) Clerks are having tobacco/alcohol addiction. 90 (29.51%) Bank officers

and 38 (19.90%) Clerks are suffering from some kind of Body pain. 20 (6.56%) Bank

officers and 7 (3.66%) Clerks are suffering from digestive disorder. 16 (5.25%) Bank

officers and 12 (6.28%) Clerks are having anemia. 15 (4.92%) Bank officers and 2

(1.05%) Clerks are suffering from frequent headaches. 3 (0.98%) Bank officers and 2


130

(1.05%) Clerks are having other health issues. Thus, Bank Officers are suffering from

more health issues compared to Clerks.


independent of employee‘s Gender



The result shows that there is a significant relationship between employee‘s gender and

prevalence of health issue. Additionally, descriptive data analysis shows that 167

(41.75%) Males and 29 (30.21%) Females are suffering from some kind of health issues.

Moreover, 15 (3.75%) Males are suffering from cardiovascular diseases, and 29 (7.25%)

Males are diabetic. Though, no females were suffering from cardiovascular diseases or

diabetes. 20 (5%) Males and 12 (12.50%) Females are Overweight. Thus, problem of

overweight was high among females. 17 (18%) Males and 1 (1.04%) Females are having

tobacco/alcohol addiction. 111 (27.75%) Males and 17 (17.71%) Females are suffering


employees. 19 (4.75%) Males and 8 (8.33%) Females are suffering from digestive

disorder. 22 (5.50%) Males and 6 (6.25%) Females are having anemia. 15 (3.75%) Males

and 2 (2.08%) Females are suffering from frequent headaches. 2 (0.50%) Males and 3

(3.13%) Females are having other health issues. Thus, prevalence of cardiovascular

diseases, diabetes, tobacco/alcohol addiction, Body pain, and frequent headaches is higher

among male employees compared to female employees. While, prevalence of Overweight,

digestive disorder, anemia, and other health issues is higher among female employees



independent of employee‘s Age




131

The result shows that there is a significant relationship between employee‘s age and

prevalence of health issue. Additionally, descriptive data analysis shows that 9 (8.04%) 21

to 30 years old, 77 (32.63%) 31 to 40 years old, and 110 (74.32%) more than 40 years old

bank employees are suffering from some kind of health issues. Moreover, 3 (1.27%) 31 to

40 years old, and 12 (8.11%) more than 40 years old bank employees are suffering from

cardiovascular diseases. 8 (3.39%) 31 to 40 years old, and 21 (14.19%) more than 40 years

old bank employees are diabetic. 2 (1.79%) 21 to 30 years old, 17 (7.20%) 31 to 40 years

old, and 13 (8.78%) more than 40 years old bank employees are Overweight. 3 (2.68%)

21 to 30 years old, 24 (10.17%) 31 to 40 years old, and 46 (31.08%) more than 40 years

old bank employees are having tobacco/alcohol addiction. 4 (3.57%) 21 to 30 years old, 35

(14.83%) 31 to 40 years old, and 89 (60.14%) more than 40 years old bank employees are

suffering from some kind of Body pain, making it the major health issue among the bank

employees. 2 (1.79%) 21 to 30 years old, 11 (4.66%) 31 to 40 years old, and 14 (9.46%)

more than 40 years old bank employees are suffering from digestive disorder. 1 (0.89%)

21 to 30 years old, 17 (7.20%) 31 to 40 years old, and 10 (6.76%) more than 40 years old

bank employees are having anemia. 2 (1.79%) 21 to 30 years old, 8 (3.39%) 31 to 40 years

old, and 7 (4.73%) more than 40 years old bank employees are suffering from frequent

headaches. 2 (0.85%) 31 to 40 years old, and 3 (2.03%) more than 40 years old bank

employees are having other health issues. Thus, prevalence of health issues is higher

among employees of more than 40 years of age.


independent of employee‘s Level of Education


o Result: Hypothesis is accepted

The result shows that there is no significant relationship between employee‘s level of

education and prevalence of health issue. However, descriptive data analysis shows that

107 (37.02%) Graduates and 89 (43.00%) Post Graduates bank employees are suffering

from some kind of health issues.


132





The result shows that there is a significant relationship between the type of banking sector

where employee is working and prevalence of health issue. Additionally, descriptive data

analysis shows that 164 (50%) Public sector bank employees, and 32 (19.05%) Private

sector bank employees are suffering from some kind of health issues. Moreover, 14

(4.27%) Public sector bank employees, and 1 (0.60%) Private Sector bank employees are

suffering from cardiovascular diseases. 27 (8.23%) Public sector bank employees, and 2

(1.19%) Private sector bank employees are diabetic. 25 (7.62%) Public sector bank

employees, 7 (4.17%) Private sector bank employees are Overweight. 65 (19.82%) Public

sector bank employees, and 8 (4.76%) Private sector bank employees are having

tobacco/alcohol addiction. 113 (34.45%) Public sector bank employees, and 15 (8.93%)

Private sector bank employees are suffering from some kind of Body pain, making it the

major health issue among the bank employees. 21 (6.40%) Public sector bank employees,

and 6 (3.57%) Private sector bank employees are suffering from digestive disorder. 19

(5.79%) Public sector bank employees, and 9 (5.36%) Private sector bank employees are

having anemia. 11 (3.35%) Public sector bank employees, and 6 (3.57%) Private sector

bank employees are suffering from frequent headaches. 4 (1.22%) Public sector bank

employees, and 1 (0.60%) Private sector bank employees are having other health issues.

Thus, prevalence of health issues is higher among Public sector bank employees compared

to Private sector bank employees.






133

The result shows that there is a significant relationship between employee‘s work

experience in banking sector and prevalence of health issue. Additionally, descriptive data

analysis shows that 40 (18.18%) employees with less than or equal to 10 years of work

experience, 66 (39.29%) employees with 11 to 20 years of work experience, and 90

(83.33%) employees with more than 20 years of work experience are suffering from some

kind of health issues. Moreover, 1 (0.45%) employees with less than or equal to 10 years

of work experience, 4 (2.38%) employees with 11 to 20 years of work experience and 10

(9.26%) employees with more than 20 years of work experience are suffering from

cardiovascular diseases. 1 (0.45%) employees with less than or equal to 10 years of work

experience, 10 (5.95%) employees with 11 to 20 years of work experience, and

18(16.67%) employees with more than 20 years of work experience are diabetic. 8

(3.64%) employees with less than or equal to 10 years of work experience, 15 (8.93%)

employees with 11 to 20 years of work experience, and 9 (8.33%) employees with more

than 20 years of work experience are Overweight. 14 (6.36%) employees with less than or

equal to 10 years of work experience, 24 (14.29%) employees with 11 to 20 years of work


having tobacco/alcohol addiction. 20 (9.09%) employees with less than or equal to 10

years of work experience, 28 (16.67%) employees with 11 to 20 years of work experience,

and 80 (74.07%) employees with more than 20 years of work experience are suffering


employees. 5 (2.27%) employees with less than or equal to 10 years of work experience,

11 (6.55%) employees with 11 to 20 years of work experience, and 11 (10.19%)

employees with more than 20 years of work experience are suffering from digestive

disorder. 9 (4.09%) employees with less than or equal to 10 years of work experience, 12

(7.14%) employees with 11 to 20 years of work experience, and 7 (6.48%) employees with

more than 20 years of work experience are having anemia. 6 (2.73%) employees with less

than or equal to 10 years of work experience, 5 (2.98%) employees with 11 to 20 years of

work experience, and 6 (5.56%) employees with more than 20 years of work experience

are suffering from frequent headaches. 4 (2.38%) employees with 11 to 20 years of work


having other health issues. Thus, prevalence of health issues is higher among employees

with more than 20 years of work experience in banking sector.


134

5.4 Achievements with respect to objectives

The aim of the research was to develop an Employee Wellness Scale and examine its

psychometric properties in the sample of bank employees. In pursuit of this aim, four

objectives were developed, which were addressed through the research questions which

acted as a focus for data collection and analysis.

5.4.1 Objective-1: To explore the concept of Employee Wellness in the context of

the banking sector

The investigation of this objective through review of literature reveals many issues faced

by bank employees; these included high time pressure, ergonomics problems, role

conflicts, excessive work demands, difficult customer relationships, and a high rate of

stress and violence (ILO, Giga and Hoel, 2003). Consequently, bank employees are

experiencing problems like job burnout, stress, job dissatisfaction, etc. (Bajpai and

Srivastava, 2004; Chen and Lien, 2008). Additionally, the risk for chronic disease is

increased among bank employees in India due to the sedentary nature of their jobs (Sarkar

et.al. 1999, S Ganesh Kumar et al 2013). Thus, organisations should assess employee

wellness and consistently strive for increasing awareness among employees on the holistic

components to overall wellness.

5.4.2 Objective-2: To develop Employee Wellness Scale for bank employees

The findings yielded after analysis of Research Question 1 justify the concept of a seven

factor wellness scale that enables the bank employees to assess their wellness in Factor 1

(Physical), Factor 2 (Intellectual), Factor 3 (Occupational), Factor 4(Environmental),

Factor 5 (Social), Factor 6 (Emotional), and Factor 7 (Spiritual). The statistical analysis

used in Research Question 1 and 2 yielded a strong support for the Employee Wellness

Scale. Thus, a sound 36-item scale for examining employee wellness was created for use

in the banking sector.

5.4.3 Objective-3: To assess the level of Employee Wellness in the banking sector

of Gujarat.


of the bank employees are suffering from some kind of health issues. 24.71% of them are


135

21 to 40 years old. Prevalence of health issues was higher among officers. Male

employees were suffering from more health issues compared to female employees. The

result of chi square analysis reveals that Level of designation, Age, Gender, and Type of

bank sector where employee is working were associated with the prevalence of health

issues among the population of bank employees in Gujarat.

5.4.4 Objective-4: To explore the relationship between Employee Wellness and

Demographic variables.

The findings of Research Question 3 reveals, that demographic variable Designation, Age,

Gender, and Education are associated with Total Employee Wellness Score significantly

with designation accounted for highest level of beta value. The result also reveals that age,

level of designation, and level of Education has a negative relationship with Total

Employee Wellness Score. Additionally, Female employees had better Total Employee

Wellness Score compared to male employees.

The findings of multiple linear regression under Research Question 4 reveals, that

demographic variable Designation, Age and Gender are associated with Total Physical

Wellness Score significantly with designation accounted for highest level of beta value.

The result also reveals that age and level of designation has a negative relationship with

Total Physical Wellness Score. Additionally, Female employees had better Total Physical

Wellness Score compared to male employees.


demographic variable Designation and Age are associated with Total Intellectual Wellness

Score significantly with designation accounted for highest level of beta value. The result

also reveals that age and level of designation has a negative relationship with Total

Intellectual Wellness Score.


demographic variable Designation and Age are associated with Total Occupational

Wellness Score significantly with designation accounted for highest level of beta value.

The result also reveals that age and level of designation has a negative relationship with

Total Intellectual Wellness Score.


136


demographic variable Designation, Age, Gender and level of Education are associated

with Total Environmental Wellness Score significantly with designation accounted for

highest level of beta value. The result also reveals that age, level of designation, and level

of education has a negative relationship with Total Environmental Wellness Score.

Additionally, Female employees had better Total Environmental Wellness Score



demographic variable Designation and Age are associated with Total Social Wellness

Score significantly with designation accounted for highest level of beta value. The result

also reveals that age and level of designation has a negative relationship with Total Social

Wellness Score.


demographic variable Designation, Age, and Education are associated with Total

Emotional Wellness Score significantly with designation accounted for highest level of

beta value. The result also reveals that age, level of designation, and level of education has

a negative relationship with Total Emotional Wellness Score.


demographic variable Designation is associated with Total Spiritual Wellness Score

significantly. The result also reveals that level of designation has a negative relationship

with Total Spiritual Wellness Score.

5.5 Limitations of the research

5.5.1 Limitations of the Research Design

For the present research a correlational design is used (Gall et al., 2007). Thus, the

researcher was not able to predict causality (Tabachnick and Fidel,2013). Hence, the

employees‘ scores on the Employee Wellness Scale and answers to particular items on the

Employee Wellness Scale do not indicate that they are the cause of wellness or illness.

Additionally, the seven factors on the EWS (Physical, Intellectual, Occupational,

Environmental, Social, Emotional, and Spiritual) are not necessarily the cause of bank


137

employees‘ wellness or illness. In future researchers could use the Employee Wellness

Scale to investigate causality.

The self-report nature of the questionnaire was another limitation of the current research.

Participants gave answers for all three questionnaires (i.e., general demographic form,

Employee Wellness Scale and Current health issue form) directly. Hence, the answers

might be influenced, if participants were answering in a socially acceptable way.

5.5.2 Limitations of the questionnaire

Three questionnaires were used in the current research study: (a) General demographic

form; (b)Employee Wellness Scale; and (c) Current health issue form that were developed

by the researcher. Hence, the questionnaire that was administered to the bank employees

contained a total of 46 items. Consequently, it may be possible that the participants were

feeling tired while filling out the questionnaire, which could have resulted in participants

falsely responding to items. However, the researcher attempted and noted the time

required to complete the assessment before sending to the bank employees and found it

took around 10 – 20 minutes. Hence, the length of the questionnaire could have been a

limitation of the study.

5.6 Recommendations for Future Research

In future the research that could be conducted with the EWS are (a) testing the EWS in

diverse population, (b) doing an Exploratory Factor Analysis with a larger sample; (c)

cross-validating the EWS with other wellness assessments; (d) doing a qualitative research

on a theory; and (e) doing a longitudinal study to examine weather the EWS is sensitive to

change over time.

It is suggested that the EWS is used with various populations with a view to assess the

model fit and know the validity of seven current factors with a different sample.

Third, the sample size for the EWS could be increased to have a strong (i.e., 20:1)

participant to item ratio for a factor analysis. Fourth, in future researchers could conduct a

grounded theory investigation in order to build up a theory surrounding the EWS model

from the ground up.


138

Additionally, convergent and discriminant validity of the EWS can be assessed by

examining its validity with other wellness instruments. Finally, in future a longitudinal

study could be conducted to assess the EWS with a population of bank employees over a

period of time and examine if employees scores on the EWS are sensitive to change.

5.7 Implications

The findings of the present research contribute to the existing literature on employee

wellness in the banking sector. The present research developed a theoretically and

methodologically sound scale for assessing employee wellness in banking sector. Thus,

using the EWS allows for individuals and organisations to assess employee‘s areas of

wellness strengths and wellness areas for growth.

The findings yielded after analysis of Research Question 1 justify the concept of a seven

factor wellness scale that enables the bank employees to assess their wellness in Factor 1

(Physical), Factor 2 (Intellectual), Factor 3 (Occupational), Factor 4(Environmental),

Factor 5 (Social), Factor 6 (Emotional), and Factor 7 (Spiritual). The statistical analysis

used in Research Question 1 and 2 yielded a strong support for the Employee Wellness

Scale. Thus, a sound 36-item scale for examining employee wellness was created for use

in the banking sector.

Findings from the research reveals that, bank employees need to be conscious about their

physical, intellectual, occupational, environmental, social, emotional, and spiritual level of

wellness and how it affects their performance and different aspects of life.

Ultimately, the EWS could be used as a tool to improve employee‘s awareness about

different dimensions of well-being and helps them in not only examining their personal

wellness but also helps in inspiring positive lifestyle changes where necessary. Moreover,

increasing awareness and personal knowledge on wellness can promote an autogenic

nature among the bank employees and helps to encourage prevention of employee burnout

or illness, rather than the timely, exhaustive, and expensive pathogenic philosophy of

treating diseases/unwellness after they occur.


139

5.8 Chapter Summary

Chapter 5 summarizes the findings of the research for the five research questions

discussed in depth in Chapter 4. The development and validation of the EWS with a

sample of bank employees was completed. However, after looking at the limitations of the

study, caution should be used while considering use of the EWS with populations other

than the bank employees.

Moreover, the findings from the research are directing towards future scope of research

focused on employee wellness in banking and across other professions. The results of the

research study provide implications for the bank employees and add to the current

literature on employee wellness.

Appendix-I

140

APPENDIX – I

GENERAL DEMOGRAPHIC FORM

Appendix I

141

GENERAL DEMOGRAPHIC

QUESTIONNAIRE

General Information:

Designation: Clerk / Officer Bank Name:

Bank Address (only District): Total work experience in Banking: _______ Years

Age: Gender: Male / Female Highest Education: SSC HSC/Diploma Graduate Post

Graduate PhD

Marital Status: Single Married Divorced Widowed

Are you physically challenged (any disability)?

Yes / No

Appendix-II

142

APPENDIX – II

EMPLOYEE WELLNESS SCALE

Appendix-II

143


Read the following questions and select your most appropriate answer. Please mark only one option per row.

Sr

No

Almost

Never

O ccasionally O ften Very

O ften

Almost

Always

1 How often do you go for age appropriate general health check up?

2 How often do you need any medical treatment/ medicine to function in your daily life? (e.g. tablet for diabetes/ blood pressure/headache)

3 How often are you satisfied with your sleep?

4 How often are you satisfied with your ability to perform your daily living activities?

5 How often do you eat healthy balanced diet (fruits, grains, vegetables, protein, dairy item)?

6 How often do you engage in sweat producing physical activity for minimum 30 minutes?

7 How often do you follow safety measures in daily life?

8 How often do you consume tobacco or alcohol?

9 How often do you keep yourself informed about social, political and current issues?

10 How often do you seek opportunities to learn new things?

11 How often do you participate in activities such as attending conference, exhibitions, workshops, seminars, webinars/ online lectures?

12 How often do you gather information from several sources before making important decisions?

13 How often do you enjoy your work?

14 How often are you satisfied with the balance between your work time and relaxation time?

15 How often are you satisfied with your ability to manage and control your workload?

16 How often do you feel that the level of stress in your work environment is comfortable to you?

17 How often do you feel safe in your daily life?

18 How often is your physical environment healthy?

Appendix-II

144

Sr

No.

Almost Never

O ccasionally O ften Very O ften

Almost Always

19 How often do you try to act in environment friendly way?

20 How often the information that you need in your day to day life is available to you?

21 How often are you satisfied with the conditions of your living place?

22 How often are you satisfied with your access to health services?

23 How often are you satisfied with your transport facility?

24 How often are you satisfied with your personal relationships?

25 When you notice something that is dangerous to others, how often do you take action to correct it?

26 How often are you satisfied with the support you get from your friends?

27 How often do you contribute time or money to the organisations that strives to better the community where you live? (e.g. NGO, Community Service )

28 How often do you enjoy life?

29 How often do you express your feeling of unpleasantness in ways that are not hurtful to others?

30 How often do you accept responsibility for your own action?

31 How often are you satisfied with yourself? 32 How often do you have negative feelings

such as anger, despair, anxiety, depression?

33 How often do you feel that your life has a meaningful purpose?

34 How often your actions are guided by your own beliefs, rather than the beliefs of others?

35 How often do you engage in prayer or meditation or personal reflection?

36 How often are you tolerant of the values and beliefs of others?

Appendix-III

145

APPENDIX – III

CURRENT HEALTH ISSUES

QUESTIONNAIRE

Appendix-III

146

CURRENT HEALTH ISSUES QUESTIONNAIRE If you are having any health issues then Please mark the top three health issues that are high priority for you to improve your health.

1. Heart and Cardiovascular disease

6. Body pain (Neck, Back, Joint)

2. Diabetes 7. Digestive disorder (ex. Acidity/gastritis)

3. Cancer 8. Anemia

4. Overweight or Obesity 9. Eye Problem 5. Tobacco / Alcohol addiction

Other health issues (Please Specify)

Appendix-IV

147

APPENDIX – IV

EMPLOYEE WELLNESS SCALE SCORE

GUIDELINE

Appendix-IV

148


Read the following questions and select your most appropriate answer. Please mark only one option per row.

Sr

No

Almost

Never

O ccasionally O ften Very

O ften

Almost

Always

1 How often do you go for age appropriate general health check up?

1 2 3 4 5

2 How often do you need any medical treatment/ medicine to function in your daily life? (e.g. tablet for diabetes/ blood pressure/headache)

5 4 3 2 1

3 How often are you satisfied with your sleep?

1 2 3 4 5

4 How often are you satisfied with your ability to perform your daily living activities?

1 2 3 4 5

5 How often do you eat healthy balanced diet (fruits, grains, vegetables, protein, dairy item)?

1 2 3 4 5

6 How often do you engage in sweat producing physical activity for minimum 30 minutes?

1 2 3 4 5

7 How often do you follow safety measures in daily life?

1 2 3 4 5

8 How often do you consume tobacco or alcohol?

5 4 3 2 1

9 How often do you keep yourself informed about social, political and current issues?

1 2 3 4 5

10 How often do you seek opportunities to learn new things?

1 2 3 4 5

11 How often do you participate in activities such as attending conference, exhibitions, workshops, seminars, webinars/ online lectures?

1 2 3 4 5

12 How often do you gather information from several sources before making important decisions?

1 2 3 4 5

13 How often do you enjoy your work? 1 2 3 4 5

14 How often are you satisfied with the balance between your work time and relaxation time?

1 2 3 4 5

15 How often are you satisfied with your ability to manage and control your workload?

1 2 3 4 5

16 How often do you feel that the level of stress in your work environment is comfortable to you?

1 2 3 4 5

17 How often do you feel safe in your daily life?

1 2 3 4 5

18 How often is your physical environment healthy?

1 2 3 4 5

Appendix-IV

149

Sr

No.

Almost Never

O ccasionally O ften Very O ften

Almost Always

19 How often do you try to act in environment friendly way?

1 2 3 4 5

20 How often the information that you need in your day to day life is available to you?

1 2 3 4 5

21 How often are you satisfied with the conditions of your living place?

1 2 3 4 5

22 How often are you satisfied with your access to health services?

1 2 3 4 5

23 How often are you satisfied with your transport facility?

1 2 3 4 5

24 How often are you satisfied with your personal relationships?

1 2 3 4 5

25 When you notice something that is dangerous to others, how often do you take action to correct it?

1 2 3 4 5

26 How often are you satisfied with the support you get from your friends?

1 2 3 4 5

27 How often do you contribute time or money to the organisations that strives to better the community where you live? (e.g. NGO, Community Service )

1 2 3 4 5

28 How often do you enjoy life? 1 2 3 4 5

29 How often do you express your feeling of unpleasantness in ways that are not hurtful to others?

1 2 3 4 5

30 How often do you accept responsibility for your own action?

1 2 3 4 5

31 How often are you satisfied with yourself? 1 2 3 4 5 32 How often do you have negative feelings

such as anger, despair, anxiety, depression? 5 4 3 2 1

33 How often do you feel that your life has a meaningful purpose?

1 2 3 4 5

34 How often your actions are guided by your own beliefs, rather than the beliefs of others?

1 2 3 4 5

35 How often do you engage in prayer or meditation or personal reflection?

1 2 3 4 5

36 How often are you tolerant of the values and beliefs of others?

1 2 3 4 5

Appendix-IV

150

Domain Assigned Questions

Physical Wellness Q1+Q2+Q3+Q4+Q5+Q6+Q7+Q8

Intellectual Wellness Q9+Q10+Q11+Q12

Occupational Wellness Q13+Q14+Q15+Q16

Environmental Wellness Q17+Q18+Q19+Q20+Q21+Q22+Q23

Social Wellness Q24+Q25+Q26+Q27

Emotional Wellness Q28+Q29+Q30+Q31+Q32

Spiritual Wellness Q33+Q34+Q35+Q36

Total Employee Wellness Q1+Q2+Q3+Q4+Q5+Q6+Q7+Q8+ Q9+Q10+Q11+Q12+ Q13+Q14+Q15+Q16+ Q17+Q18+Q19+Q20+Q21+Q22+Q23+

Q24+Q25+Q26+Q27+ Q28+Q29+Q30+Q31+Q32+

Q33+Q34+Q35+Q36

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APPENDIX – V

HISTOGRAMS


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APPENDIX – VI

SCATTER PLOTS


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Scatterplot-1:

Independent Variable: Designation ( 0 = Clerk, 1 = Officer)

Dependent Variable: Total Employee Wellness Score (EWS)

Scatterplot-2:

Independent Variable: Bank Sector ( 0 = Private Sector Bank, 1 = Public Sector Bank)


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Scatterplot-3:

Independent Variable: Age


Scatterplot-4:

Independent Variable: Gender ( 0 = Male, 1 = Female)


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Scatterplot-5:

Independent Variable: Education ( 0 = Graduate, 1 = Post Graduate)


Scatterplot-6:


Dependent Variable: Total Physical Wellness Score (PWS)

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Scatterplot-7:


Dependent Variable: Total Physical Wellness Score (PW)

Scatterplot-8:



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Scatterplot-9:



Scatterplot-10:



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Scatterplot-11:


Dependent Variable: Total Intellectual Wellness Score (IW)

Scatterplot-12:



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Scatterplot-14:



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Scatterplot-16:


Dependent Variable: Total Occupational Wellness Score (OW)

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Scatterplot-21:


Dependent Variable: Total Environmental Wellness Score (ENW)

Scatterplot-22:



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Scatterplot-23:



Scatterplot-24:



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Scatterplot-25:



Scatterplot-26:


Dependent Variable: Total Social Wellness Score (SOW)

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Scatterplot-27:



Scatterplot-28:



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Scatterplot-29:



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Scatterplot-31:


Dependent Variable: Total Emotional Wellness Score (EMW)

Scatterplot-32:



Appendix-VI

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Scatterplot-33:



Scatterplot-34:



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Scatterplot-35:



Scatterplot-36:


Dependent Variable: Total Spiritual Wellness Score (SPW)

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Scatterplot-37:



Scatterplot-38:



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Scatterplot-39:



Scatterplot-40:



Appendix VII

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Appendix VII

Correlation Matrix

Appendix-VII

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Correlation Matrix

List of References

193

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gujarat technological university ahmedabad [february … · employee wellness: a study of banking...

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