Introduction to Thesis · Web viewSuch a conclusion, however, is limited by a notable difference between the mean score for neuroticism reported for the comparison sample in this

PREDICTING SUBJECTIVE QUALITY OF LIFE:

THE CONTRIBUTIONS OF PERSONALITY AND

PERCEIVED CONTROL

By

Rachel Cousins

B.B.Sc. Hons

Submitted in fulfilment of the requirements for the degree of

Doctorate of Psychology (Clinical)

Deakin University

October 2001

DEAKIN UNIVERSITY

CANDIDATE DECLARATION

I certify that the thesis entitled:

Predicting Subjective Quality of Life: The Contributions of Personality and

Perceived Control

submitted for the degree of Doctor of Psychology (Clinical) is the result of my own

research, except where otherwise acknowledged, and that this thesis in whole or in

part has not be submitted for an award, including a higher degree, to any other

university or institution.

Full Name: RACHEL LOUISE COUSINS

Signed: ………………………………….

Date: ………………………………….

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ACKNOWLEDGEMENTS

I would firstly like to acknowledge the support and encouragement of my

family and friends. Thank you to my partner, Ashley, the last three years would not

have been possible without his love and support. Thank you to my mother for her

constant prayers, and thank you to my Grandmother, who frequently has me in her

thoughts. Thank you to Alana for her support throughout my tertiary education and

for all those lessons in grammar. Thank you also to Garrick for proof reading the final

copy. I would also like to thank my classmates and friends who have been a great

support over the years, and never seem to tire of listening to me talking about my

studies.

This project could not have been undertaken and completed without the

guidance of my supervisor, Professor Bob Cummins, whose positivity was a great

source of motivation. Thank you.

I would also like to thank the contribution of the Schizophrenia Fellowship of

Victoria and all the carers who, despite their burden, found time to participate in the

study. Thank you also to the schools involved for providing me with access to

participants. To all the participants who completed the questionnaires, thank you for

your contribution.

Finally, thank you to all those who over the past ten years have inspired me to

study psychology.

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ABSTRACT

Subjective quality of life is remarkably stable within populations and it has

been proposed that this us due to the operation of a homeostatic system. It has been

proposed also that central to the operation of such homeostasis, and the key to system

stability, is the strong relationship between subjective quality of life and personality.

This prompts questions about what other psychological processes are involved in this

relationship, and the literature indicates that perceived control has important links to

both constructs. Hence, in order to develop further understanding about these

relationships, this research primarily examines the relationships between personality,

conceptualised as extroversion and neuroticism, perceived control, conceptualised as

approach control and avoidant control, and subjective quality of life. Two linked

studies are described.

The first examines these relationships in a sample of carers of people with

mental illness, in comparison with a sample of people from the general population

who do not care for someone with a disability. It was found that carers had

significantly lower subjective quality of life, particularly in the domains of health and

emotional well-being, significantly lower approach control and extroversion, and

significantly higher neuroticism, than the comparison sample. In the carer sample,

regression analyses showed that with all variables in the equation, neuroticism,

approach control and avoidant control significantly predicted subjective quality of life,

whilst extroversion made no significant contribution to the equation. Additionally,

neuroticism significantly predicted approach control. In the comparison sample,

regression analyses showed that with all variables in the equation, only approach

control significantly predicted subjective quality of life, whilst neuroticism,

extroversion and avoidant control made no significant contributions to the equation.

Additionally, neuroticism significantly predicted approach control. It was concluded

that when subjective quality of life homeostasis is being challenged, as in the carer

sample, its maintenance becomes more complicated.

The second study examines these relationships in a sample of public secondary

school teachers, in comparison with a sample of people from the general population.

There were no significant differences between the two samples, therefore the samples

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were combined. The results of the regression analyses showed that with all variables

in the equation, neuroticism and approach control significantly predicted subjective

quality of life, whilst avoidant control approached significance and extroversion made

no significant contribution to the equation. Additionally, neuroticism significantly

predicted avoidant control and extroversion significantly predicted approach control.

It was concluded that extroversion and approach control together impact positively on

subjective quality of life and neuroticism and avoidant control together impact

negatively on subjective quality of life. Moreover, further support was given for the

conclusion that when subjective quality of life homeostasis is being challenged its

maintenance becomes more complicated.

Overall, there is some support for a model whereby personality, primarily

neuroticism, and perceived control, primarily approach control, contribute to

subjective quality of life. Furthermore, the three samples used in this research

represent different levels of subjective quality of life. The comparison sample in

Study One had high normal subjective quality of life, the combined sample in Study

Two had normal subjective quality of life and the carer sample in Study One had low

normal subjective quality of life. The resultant model of relationships for each of

these samples demonstrates that the management of subjective quality of life

homeostasis becomes more complicated as it is challenged.

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TABLE OF CONTENTS

CHAPTER 1..............................................................................................................................................1

1 INTRODUCTION TO STUDY ONE..............................................................................................1

1.1 SUBJECTIVE QUALITY OF LIFE...........................................................................................21.1.1 The historical development of life quality research............................................................21.1.2 Definitions of various indicators of life quality..................................................................31.1.3 The definition and measurement of subjective quality of life.............................................51.1.4 Conclusion..........................................................................................................................7

1.2 PERSONALITY.........................................................................................................................81.2.1 Introduction.........................................................................................................................81.2.2 The relationships between extroversion and neuroticism, positive and negative affect,

and life quality....................................................................................................................91.2.3 The relationships between personality and other psychological processes that may

impact on subjective quality of life...................................................................................111.2.4 Conclusion........................................................................................................................13

1.3 PERCEIVED CONTROL.........................................................................................................141.3.1 Introduction.......................................................................................................................141.3.2 Developing a definition of primary and secondary control..............................................151.3.3 Addressing the interaction between primary and secondary control...............................171.3.4 The literature on primary, secondary and relinquished control,and various indicators

of well-being......................................................................................................................201.3.5 The measurement of primary, secondary and relinquished control.................................211.3.6 Conclusion........................................................................................................................23

1.4 INTEGRATING PERSONALITY, PERCEIVED CONTROL AND SUBJECTIVE QUALITY OF LIFE...................................................................................................................23

1.4.1 Maintaining subjective quality of life...............................................................................231.4.2 Rationale for a hypothesised model of personality, perceived control and subjective

quality of life.....................................................................................................................251.4.3 Focus of the current research...........................................................................................27

1.5 SUBJECTIVE QUALITY OF LIFE: CARERS OF PEOPLE WITH MENTAL ILLNESS . 281.5.1 The historical development of research into carers of people with mental illness...........281.5.2 The impact of the caregiving role on subjective quality of life.........................................291.5.3 The role of perceived control in coping with the impact of mental illness on the family

and maintaining subjective quality of life.........................................................................341.5.4 Conclusion........................................................................................................................371.5.5 Focus of the current research...........................................................................................37

CHAPTER 2............................................................................................................................................39

2 STUDY ONE: AIMS AND HYPOTHESES.................................................................................39

CHAPTER 3............................................................................................................................................40

3 STUDY ONE: METHOD...............................................................................................................40

3.1 SAMPLE ...................................................................................................................................403.2 PROCEDURE...............................................................................................................................413.3 MEASUREMENT TOOLS................................................................................................................42

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CHAPTER 4............................................................................................................................................44

4 STUDY ONE: RESULTS...............................................................................................................44

4.1 AIM ONE ...................................................................................................................................444.2 DESCRIPTIVE INFORMATION........................................................................................................474.3 AIM TWO ...................................................................................................................................514.4 AIM THREE ................................................................................................................................53

CHAPTER 5............................................................................................................................................58

5 STUDY ONE: DISCUSSION.........................................................................................................58

5.1 AIM ONE ...................................................................................................................................585.2 AIM TWO ...................................................................................................................................595.3 AIM THREE ................................................................................................................................635.4 SUMMARY ...................................................................................................................................66

CHAPTER 6............................................................................................................................................68

6 INTRODUCTION TO STUDY TWO..........................................................................................68

6.1 APPROACH AND AVOIDANT DIMENSIONS OF PERCEIVED CONTROL...................696.1.1 Theoretical support for approach and avoidant control..................................................696.1.2 Empirical support for approach and avoidant control.....................................................716.1.3 The measurement of approach and avoidant control.......................................................746.1.4 Conclusion........................................................................................................................76

6.2 PERSONALITY, APPROACH AND AVOIDANT CONTROL AND SUBJECTIVE QUALITY OF LIFE...................................................................................................................76

6.2.1 The literature on approach and avoidant control and subjective quality of life..............766.2.2 The findings from Study One on approach and avoidant control and subjective

quality of life.....................................................................................................................786.2.3 Personality and approach and avoidant control..............................................................806.2.4 Integrating personality, approach and avoidant control and subjective quality of life. . .816.2.5 Focus of the current research...........................................................................................82

6.3 SUBJECTIVE QUALITY OF LIFE IN SECONDARY SCHOOL TEACHERS...................826.3.1 The stressors associated with teaching.............................................................................826.3.2 The impact of stress on teachers' subjective quality of life and the role of

coping strategies...............................................................................................................836.3.3 Conclusion and focus of the current research..................................................................85

CHAPTER 7............................................................................................................................................87

7 STUDY TWO: AIMS AND HYPOTHESES................................................................................87

CHAPTER 8............................................................................................................................................88

8 STUDY TWO: METHOD..............................................................................................................88

8.1 SAMPLE ...................................................................................................................................888.2 PROCEDURE...............................................................................................................................898.3 MEASUREMENT TOOLS................................................................................................................90

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CHAPTER 9............................................................................................................................................92

9 STUDY TWO: RESULTS..............................................................................................................92

9.1 AIM ONE ...................................................................................................................................929.2 AIM TWO ...................................................................................................................................979.3 AIM THREE...............................................................................................................................1009.4 ADDITIONAL ANALYSES..............................................................................................................102

CHAPTER 10........................................................................................................................................105

10 STUDY TWO: DISCUSSION.....................................................................................................105

10.1 AIM ONE...................................................................................................................................... 105

10.2 AIM TWO......................................................................................................................................106

10.3 AIM THREE.............................................................................................................................10710.4 ADDITIONAL ANALYSES............................................................................................................11010.5 SUMMARY...............................................................................................................................110

CHAPTER 11........................................................................................................................................112

11 SYNTHESIS AND CONCLUSIONS..........................................................................................112

12 REFERENCES..............................................................................................................................118

13 APPENDICES...............................................................................................................................129

APPENDIX A: INFORMATION LETTER FOR QUESTIONNAIRE 1.............................................................APPENDIX B: QUESTIONNAIRE 1.........................................................................................................APPENDIX C: INFORMATION LETTER FOR QUESTIONNAIRE 2.............................................................APPENDIX D: QUESTIONNAIRE 2.........................................................................................................APPENDIX E: SCALES AND ITEMS OF THE COPING RESPONSES INVENTORY......................................

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TABLE OF FIGURES

Figure 1: The direct and indirect prediction of subjective quality of life (SQOL) by personality and perceived control...............................................................................................................................25

Figure 2: Hypothesised model of subjective quality of life, personality and perceived control.............27

Figure 3: Model of the significant relationships among the variables neuroticism, approach control, avoidant control and total subjective quality of life (SQOL) in the carer sample, including standardised regression coefficients and correlations.......................................................................64

Figure 4: Model of the significant relationships among the variables neuroticism, approach control, avoidant control and total subjective quality of life (SQOL) in the carer sample incorporating a latent construct for perceived control...............................................................................................65

Figure 5: Model of the significant relationships among the variables neuroticism, approach control and total subjective quality of life (SQOL) in the comparison sample, including standardised regression coefficients......................................................................................................................65

Figure 6: Model of the significant relationships among the variables, neuroticism, ............extroversion, approach control, avoidant control, and total subjective quality of life (SQOL), in the combined sample, including standardised regression coefficients and correlations.......................108

Figure 7: Model of the significant relationships among the variables for the comparison sample in Study One, representing high normal subjective quality of life (reproduction of Figure 5)..........115

Figure 8: Model of the significant relationships among the variables for the combined sample in Study Two, representing normal subjective quality of life (reproduction of Figure 6)............................116

Figure 9: Model of the significant relationships among the variables for the carer sample, representing low normal subjective quality of life (reproduction of Figure 3)...................................................116

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TABLE OF TABLES

Table 1: Demographic information.........................................................................................................41

Table 2: Two factor solution for the Perceived Control Questionnaire, with primary control items (PC) and secondary control items (SC) identified...........................................................................46

Table 3: Means (M), standard deviations (SD) and bi-variate correlations for the variables total subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the carer sample and the comparison sample.............................................................................48

Table 4: Multivariate Analysis of Variance examining the differences between the carer and comparison samples for the variables: total subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion...............................................................................50

Table 5: Multivariate analysis of covariance with group (carer or comparison) as the independent variable, the seven SQOL domains as the dependent variables, and ....neuroticism and extroversion as the covariates...................................................................................................53

Table 6: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the carer sample...................................................................................54

Table 7: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the comparison sample.........................................................................55

Table 8: Regression of neuroticism and extroversion on approach control and avoidant control for the carer sample..........................................................................................................................56

Table 9: Regression of neuroticism and extroversion on approach control and avoidant control for the comparison sample...............................................................................................................57

Table 10: Background information.........................................................................................................89

Table 11: Description of the scales in the Coping Response Inventory.................................................91

Table 12: Means, standard deviations (SD) and internal consistencies (Alpha) of the Coping Responses Inventory........................................................................................................................96

Table 13: Factor solution for the eight scales of the Coping Responses Inventory................................97

Table 14: Means (M), standard deviations (SD) and bi-variate correlations for the variables subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the combined teacher and comparison sample (n=171)........................................99

Table 15: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the combined sample.........................................................................101

Table 16: Regression of neuroticism and extroversion on approach control and avoidant control for the combined sample................................................................................................................102

Table 17: Means, standard deviations and bi-variate correlations for the variables subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the two subgroups, high and low subjective quality of life........................................................................103

Table 18: Multivariate Analysis of Variance examining the differences between the subgroups, high and low subjective quality of life, for the variables approach control, avoidant control, neuroticism and extroversion.........................................................................................................103

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CHAPTER 1- Study One: Introduction

CHAPTER 1

1 INTRODUCTION TO STUDY ONE

The focus of Study One is to develop understanding of how subjective

quality of life is maintained. The relevant literature is first reviewed. This begins

by tracing the development of the subjective quality of life concept and evidence

that this variable is actively maintained. Following this, the psychological

processes that may contribute to the maintenance of subjective quality of life are

considered. The literature indicates that personality and perceived control are

important processes to consider. In particular, the personality characteristics

extroversion and neuroticism have been consistently shown in the literature to

predict various concepts of subjective life quality. Perceived control is also

indicated in the literature to have a predictive relationship with subjective quality

of life. Perceived control is conceptualised as involving primary, secondary and

relinquished control processes. A model of personality, perceived control and

subjective quality of life is then proposed.

The population selected to be the focus of Study One is carers of people

with mental illness. Carers make an informative population in which to investigate

these three variables, as they are likely to have low subjective quality of life and

may be vulnerable to losses in perceived control. Hence, the stress and coping

literature on carers is also reviewed. This introductory section of Study One

concludes with a brief statement concerning the focus of the current research.

The aims and hypotheses highlight the three parts of the study: 1) an

investigation of the factor structure of perceived control, 2) an investigation of the

differences between samples of carers of people with mental illness and people

from the general population, and 3) an examination of the relationships between

personality, perceived control and subjective quality of life. The method section

provides information about the characteristics of the two samples, the recruitment

procedures and the measurement tools used. The results and discussion sections

reflect the three parts of the aims and hypotheses. The results are discussed in

comparison with the literature and preliminary conclusions are drawn.

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1.1 SUBJECTIVE QUALITY OF LIFE

1.1.1 The historical development of life quality researchThe quality of life concept arose from research in America on social

indicators. In the 1960’s it became evident that, in order to facilitate broader

analyses of the costs and benefits of various programs and policies, there was a

need to develop a means for assessing social change beyond that afforded by the

economic indexes already monitored (Land, 1999). Influential publications, such

as “Toward a Social Report” by the Johnson administration (1969; cited in Land,

1999), addressed major social issues, such as health, income, safety, education

etc., and introduced the idea of systematically reporting the state of these issues for

the purpose of informing the public. These initial social indicators were

objectively measured and reflected normative interest in populations or groups,

such as unemployment rates or mortality rates. Then, in the 1970’s the social

indicators movement gathered pace. It was at this time the concept of measuring

individuals' subjective judgements of their own well-being was introduced in

published works such as those by Andrews and Withey (1976), and Campbell,

Converse and Rodgers (1976). The movement then slowed in the political climate

of the 1980’s in America, but research on subjective quality of life had been

launched as the subjective indicator of social change (Land, 1999).

From this point it was recognised that economic growth at the population

level was not necessarily the only valid goal of societal progress and that the

subjective life quality of populations was also a valid and relevant goal (Shea,

1976). The measurement of social indicators became focused on understanding

individuals’ feelings of satisfaction with life-as-a-whole or with a number of

relevant areas or domains, such as family, housing etc. It has now become well

accepted that both objective variables and subjective variables are important social

indicators and a large volume of research around these concepts has now

developed (Cummins, 1997a).

2


1.1.2 Definitions of various indicators of life quality Definitions of subjective well-being, life satisfaction, subjective quality of

life are somewhat confused in the literature. For the purpose of this thesis, the

following taxonomy will be adopted.

Subjective well-being is considered to have two components: a cognitive

judgement of life satisfaction and an evaluation of affect (Diener, 1998).

Measures of subjective well-being usually reflect these two parts. The first part,

life satisfaction, can be measured in two ways. It can be measured with one

question, which asks the respondent “How do you feel about your life as a whole?”

(Andrews & Withey, 1976). Alternatively, it can be measured with a series of

questions that gauge the respondent’s satisfaction with a variety of different life

domains. However, the unitary approach to measuring life satisfaction is limited,

as it yields only a crude measure of perceived well-being that lacks the variety of

information about various aspects of life that a domain-based measure of life

satisfaction can provide. The domain-based measure of life satisfaction is often

referred to in the literature as subjective quality of life and the specific domains

measured vary. Extensive argument and evaluation of the life domains that should

be included in the measurement of subjective quality of life has been provided by

Cummins (1997a) and will be detailed shortly.

The second part of the subjective well-being construct involves an affective

evaluation. This evaluation usually comprises a measure of positive and negative

emotional feelings. Yet, there are problems with the definition and measurement

of positive and negative affect. The debate, over whether positive and negative

affect should be viewed as bipolar opposites of the one construct or two

independent constructs, is ongoing. Russell and Carroll (1999) give a detailed

account of this debate and some steps towards resolution. They propose a

circumplex model of positive and negative affect that incorporates six clusters of

affect items defined by valence and activation. These include, positive affect/high

activation (eg. excited, elated, ebullient) opposed by negative affect/low activation

(eg. depressed, bored, lethargic), positive affect/medium activation (eg. happy,

pleased, content) opposed by negative affect/medium activation (eg. miserable,

unhappy, discontent), and positive affect/low activation (eg. calm, serene, tranquil)

3


opposed by negative affect/high activation (eg. tense, nervous, upset). This model

highlights a glaring deficiency in the measure of positive and negative affect by

the Positive Affect and Negative Affect Schedule (Watson, Clark & Tellegen,

1988), which is commonly used when evaluating subjective well-being. This

measure evaluates only positive affect/high activation and negative affect/high

activation, leaving out the range of low activation emotions that are potentially

important when considering subjective well-being. The usefulness of this

circumplex model of affect is highlighted by Larsen and Diener (1992), who also

point out that those researchers who use the Positive Affect and Negative Affect

Schedule may not be investigating the particular emotion concept that they hope

to. Hence, whilst the definition of subjective well-being is clear, as life

satisfaction plus affect, its operationalisation is complicated.

A further problem with subjective well-being is that it is often confused in

the literature with other terms such as psychological well-being and happiness.

For example, Friedman (1993) and Francis (1999) both measure subjective well-

being but refer to their measured constructs as psychological well-being and

happiness respectively. More accurately, psychological well-being is a term used

to reflect measures of psychological symptoms such as depression and anxiety, in

conjunction with measures of life satisfaction and in some instances positive and

negative affect. For example, Lipkus, Dalbert & Seigler (1996) use measures of

depression, stress and life satisfaction to reflect psychological well-being.

Happiness is a term more accurately used to describe a balance of positive and

negative affect. For example, Mroczeck and Kolarz (1998) measure happiness

using positive and negative affect, while Costa and McCrae (1980) measure

happiness using the difference between positive and negative affect.

In summary, subjective well-being provides a higher order construct than

subjective quality of life by incorporating life satisfaction plus positive and

negative affect. However, subjective quality of life can provide a construct that is

similar to subjective well-being when satisfaction with emotional well-being is

included in the life domains, making an additional measure of affect unnecessary.

Furthermore, the definition and measurement of positive and negative affect,

commonly used in the measurement of subjective well-being, is deficient in the

4


range of emotions encompassed as it often only measures positive affect/high

activation and negative affect/high activation. Also the construct of subjective

well-being is often confused in the literature with psychological well-being and

happiness. This makes subjective quality of life a more attractive measure than the

popularly used and confused subjective well-being.

To recap the terms used in this thesis:

Subjective well-being will be used to refer to composite measures of

life satisfaction and affect.

Subjective quality of life will be used to refer to measures of life

satisfaction involving several life domains.

Life satisfaction will be used to refer to measures of life satisfaction

derived from one global question.

1.1.3 The definition and measurement of subjective quality of lifeThe definition and measurement of quality of life has been

comprehensively developed by Cummins (1997a):

Quality of life is both objective and subjective, each axis being the aggregate of

seven domains: material well-being, health, productivity, intimacy, safety,

community and emotional well-being. Objective domains comprise culturally

relevant measures of objective well-being. Subjective domains comprise domain

satisfaction weighted by their importance to the individual. (p. 132)

This definition is consistent with the Comprehensive Quality of Life Scale

(ComQol) also developed by Cummins (1997b) and thus warrants further

explanation.

Firstly, this definition highlights an important difference between objective

and subjective quality of life. Objective quality of life is measured using sources

of information external to the individual. For example, income or physical health.

In contrast, subjective quality is measured using the individual as the source of

information. For example, the individual may be asked how satisfied they are with

their income or health. The degree to which these two constructs are interrelated

has long been debated (Andrews & Withey, 1976; Felce & Perry, 1995). But,

there appears to be a general consensus that the two are generally unrelated, as

5


satisfaction with life is considered a separate and more important indicator of

individual welfare (Edgerton, 1990).

Secondly, this definition specifies seven domains, material well-being,

health, productivity, intimacy, safety, community and emotional well-being, of

which quality of life is the aggregate. These seven domains represent the common

areas of life used in the literature to measure quality of life. Four of these domains

were shown by Campbell, et al. (1976) to be those rated as the most important of a

larger set of domains found most consistently in the literature. Their results

showed subjects rated most importance, expressed as a percentage, for Health

91%, Intimacy 89%, Material Well-being 73%, and Productivity 70%. In a review

of fifteen key literature sources, Felce and Perry (1995) found these four domains

plus emotional well-being to be the most commonly used domains of life quality.

Hence, five of the seven domains used in the definition have been consistently

used in the literature and are considered important aspects of life.

The two additional domains, safety and place in community, have been

included to encompass a broader range of life domains. The domain ‘safety’ is

intended to be inclusive of such constructs as security, personal control, privacy,

independence, autonomy, competence, knowledge of rights and residential

stability. Aspects of this domain are encompassed by Felce and Perry’s (1995)

conceptualisation of material well-being, whereby, security is considered to be

related to income, stability of tenure and housing. However, it is often included as

a separate domain in the literature (Borthwick-Duffy, 1990; Schalock, Kieth,

Hoffman & Karan, 1989; Stark & Goldsbury, 1990). The domain ‘place in

community’ is intended to be inclusive of the constructs of (objective) social class,

education, job status, community integration, community involvement and

(subjective) a sense of self-esteem, self-concept and empowerment within the

community, in addition to feelings associated with the objective components.

Aspects of this domain are encompassed by Felce and Perry’s (1995)

conceptualisation of social well-being. However, Cummins (1997a) has specified

the two aspects of social well-being, intimacy and place in community, as two

separate domains, which is often done in the literature (Borthwick-Duffy, 1990;

Schalock, et al., 1989; Stark & Goldsbury, 1990). With these seven domains

6


included, the definition and measurement of quality of life effectively covers a

broad spectrum of life quality.

Lastly, this definition introduces the notion that subjective quality of life

should be measured with reference to the value or importance that the domain has

to the relevant individual. This notion, that subjective quality of life refers to the

subjective evaluations of various domains weighted by a personal set of values,

has been supported theoretically (Felce & Perry, 1995; Cummins, 1997a) and more

recently the important role of values has been demonstrated empirically by Oishi,

Diener, Suh, and Lucas (1999). These authors found that values mediated the

relationship between domain satisfaction and life satisfaction. Using regression

analysis they found that the stronger the values of achievement, the stronger the

relation between satisfaction with grades and global life satisfaction. Similarly,

the stronger the benevolence values are, the stronger the relation between

satisfaction with social life and life satisfaction, and the stronger the conformity

values, the stronger the association between satisfaction with family and life

satisfaction. The appeal of this ‘satisfaction weighted by importance’ definition is

obvious. Most people would not value each domain equally and those domains

that they do value more will have a greater impact on how satisfied they are with

life. Hence, the ComQol provides a score of subjective quality of life for each

domain which is the product of item importance by satisfaction, and the seven

domains can be summed together to provide an overall score of life satisfaction

(Cummins 1997b).

1.1.4 ConclusionHistorically, social indicators have been developed to evaluate the

effectiveness of programs and policies by using objective and subjective indicators

to describe populations and monitor change within them. The definition and

measurement of social indicators is complex and can involve a number of terms

and concepts. One of these is subjective quality of life conceptualised as the

product of seven domains and involving domain satisfaction weighted by

importance (Cummins, 1997a, 1997b). This construct is similar in nature to the

more popular subjective well-being but does not incorporate some of the problems

7


associated with the operationalisation of subjective well-being. In particular it

avoids the problems of measuring separately positive and negative emotional

feelings.

With subjective quality of life established as a valid and useful social

indicator, it then becomes important to better understand this measure by

considering the psychological processes that contribute to an individual's

satisfaction with different areas of their life. The notion that subjective quality of

life is remarkably stable within populations (a point that will be later elaborated)

indicates that personality, also a stable psychological process, may play an

important role in the maintenance of subjective quality of life.

1.2 PERSONALITY

1.2.1 Introduction There is substantial evidence that subjective well-being is predicted by

personality. For the purposes of empirical research, personality refers to

“characteristic response tendencies” which are considered to have both “biological

and learned components” (Diener, 1998, p. 314). It is thought that around 50

percent of personality variance is attributed to genetic variance and around 30

percent is attributed to environmentally based trait variance (or learned) with the

remainder attributable to measurement error (Tellegen, et al., 1988).

The evidence that personality predicts subjective well-being across time

and situations has been used to support the causal role in the relationship between

personality and subjective well-being (Diener, 1998). This however is questioned

by those who argue that subjective well-being is, in fact, a personality trait itself

(Lykken & Tellegen, 1996). Evidence from twin studies has suggested that about

80 percent of the stable variance in subjective well-being is heritable (Lykken &

Tellegen, 1996). However, the most compelling argument against the notion that

subjective well-being is a personality trait is that it is variable in the short-term

(Diener, 1996). It has been found that major life events impact on subjective well-

being for up to three months, after which subjective well-being returns to a

8


baseline measure (Suh, Diener & Fujita, 1996). It is also argued by Diener (1996)

that trait explanations of psychological constructs like subjective well-being are

not sufficient, because they do not provide any understanding about the process by

which traits influence subjective well-being.

However, before examining other psychological processes, it is first

necessary to develop a better understanding of the relationship between personality

and various constructs of life quality by considering how personality is commonly

measured.

1.2.2 The relationships between extroversion and neuroticism, positive and negative affect, and life quality

A popular typology of personality traits is the five-factor model (Goldberg,

1992). These factors are neuroticism, extroversion, openness to experience,

agreeableness and conscientiousness, and they have been substantiated extensively

in the literature (Costa & McCrae, 1998). Yet, investigations have shown that it is

extroversion and neuroticism that provide the most pervasively significant

correlations with subjective well-being. Extroversion and subjective well-being

correlate positively ranging from .35 to .49; and neuroticism and subjective well-

being correlate negatively ranging from -.31 to -.57 (Costa & McCrae, 1980;

Francis, 1999; Francis, Brown, Lester & Philipchalk, 1998; Lu & Shih, 1997).

Similarly, a few researchers have investigated the relationship between

extroversion and neuroticism, and subjective quality of life or life satisfaction.

Morrison (1997) did this with a sample of business owners and Heaven (1989)

with a sample of adolescents. The correlational results between life satisfaction

and extroversion were .31 and .17, and neuroticism were -.44 and -.37, for the two

studies respectively (Morrison, 1997; Heaven, 1989).

Furthermore, it is extroversion and neuroticism that have received long

standing support in many typological conceptualisations of personality, including

Eysenck’s factor analytic research (Eysenck & Eysenck, 1985). They are

popularly conceptualised in terms of sociability (extroversion) and emotional

instability (neuroticism). More specifically extroversion describes a personality

9


disposition that reflects sociability, stimulus seeking, dominance, high activity and

warmth (Diener, 1998). Neuroticism is a term used to describe a personality

disposition that reflects anxiety, pessimism, irritability, bodily complaints and

interpersonal sensitivity (Diener, 1998). Hence, it may be concluded that

subjective quality of life is associated with sociability and emotional stability.

Further evidence for the significant relationship between extroversion and

neuroticism and subjective quality of life is provided by research on positive and

negative affect and life satisfaction. The relationship between these two concepts

are frequently reported in the subjective well-being literature as they are the two

components of subjective well-being. It has been found repeatedly that

extroversion correlates highly with positive affect, ranging from .20 to .63, and

that neuroticism correlates highly with negative affect, ranging from .36 to .75

(Costa & McCrae, 1980; Fogarty, et al., 1999; Francis, et al., 1998; Fujita, 1993

unpublished masters thesis provided by the author; Mroczeck & Kolarz, 1998;

Wilson, Gullone & Moss, 1998). This finding is not surprising considering the

common definition and measurement of extroversion and neuroticism, and positive

and negative affect, used in the literature.

The measurement of extroversion and neuroticism is primarily based on the

definition given previously. This is in many ways similar to the common

definition and measurement of positive and negative affect using the Positive and

Negative Affect Schedule. Here, positive affect refers to an affective disposition

that encompasses feelings such as happiness and joy and is often assessed by

feelings of interest, excitement, inspiration, enthusiasm and activity; negative

affect refers to an affective disposition that encompasses unpleasant emotions such

as sadness and is often assessed by subjective distress incorporating anger, fear,

guilt and nervousness (Wilson, et al., 1998).

Considering the similarities in definition and measurement, and the high

correlations between extroversion and positive affect, and neuroticism and

negative affect, it is possible that the personality and affect constructs are

measuring similar things. In fact, some authors have concluded that the constructs

are interchangeable (Fogarty, et al., 1999) or indistinguishable (Fujita, 1993). This

10


casts some doubt on whether positive and negative affect should be considered an

outcome variable along with life satisfaction, or a predictive variable such as

personality. Hence, investigating the relationship between positive and negative

affect and life satisfaction is similar to investigating the relationship between

extroversion and neuroticism and life satisfaction. The correlations reported in the

literature between life satisfaction and positive affect range from .23 to .52, and

life satisfaction and negative affect range from -.36 to -.48 (Brief, Butcher, George

& Link, 1993; Cooper, Okamura & Gurka, 1992; Friedman, 1993; Lucas, Diener

& Suh, 1996). Similar ranges to those between extroversion and neuroticism and

subjective well-being.

In conclusion, it is clear that personality is strongly linked to subjective

judgements about quality of life and, because personality is an enduring

characteristic and subjective quality of life is more variable, it is likely this role is

a predictive one. Furthermore, one approach to simplifying research in this area is

to avoid the complicated positive and negative affect component of the subjective

well-being construct, so that the relationship between personality and subjective

quality of life or life satisfaction can be more clearly understood.

1.2.3 The relationships between personality and other psychological processes that may impact on subjective quality of lifeThe literature in this field introduces numerous psychological processes

that may be involved with subjective quality of life. For example, McQuillen,

Licht and Licht (2001) found that identity structure predicted life satisfaction.

Identity structure refers to the hierarchical ordering of the multiple aspects of one's

self-concept (eg husband is a higher level aspect than friend or athlete as the

former encompasses the later). In another example, Pavot, Fujita and Diener

(1997) found that self-aspect congruence, that is congruence between ideal and

real self, was positively correlated with subjective well-being. However,

congruence was negatively correlated with neuroticism and when the effects of

neuroticism were controlled for, self-aspect congruence did not reliably predict

subjective well-being. This finding highlights the importance of identifying

psychological processes that make a unique contribution to the variance in

subjective quality of life after the effects of personality are removed.

11


A similar psychological process that has received much attention in the

literature is satisfaction with self, which is considered to be a major predictor of

life satisfaction (Campbell, 1981; Argyle & Lu, 1990; Diener & Diener, 1995).

However, investigating the relationship between how satisfied people are with

themselves (self-satisfaction) and how satisfied they are with their life (life

satisfaction) is problematic, considering the great deal of overlap between the two

‘satisfaction’ constructs. More information may be provided by reducing the

global self-satisfaction construct and investigating three aspects of self-

satisfaction, which are self-esteem, optimism and control (Cummins & Nistico, in

press).

Self-esteem refers to a sense of self-worth or value, and this construct has

been found to have a strong positive correlation with life satisfaction (Boschen,

1996; Hong & Giannakopoulos, 1994; Kwan, Bond & Singelis, 1997; Lucas, et al.,

1996). In fact, in some studies the correlation has been so high that Lucas, et al.

(1996) tested whether the two constructs were discriminable from each other, and

found that they were. Kwan, et al. (1997) agree, and suggest that self-esteem is a

useful mediator of the variance in life satisfaction attributed to personality.

However, self-esteem is one of the traits that inversely contribute to neuroticism

(Eysenck & Eysenck, 1985); and the two constructs correlate highly in student

samples in both the U.S. (-.69) and Hong Kong (-.63) (Kwan, et al., 1997). Hence,

it is likely that if the effects of neuroticism were controlled for, self-esteem may

not make a unique contribution to the variance in subjective quality of life.

Optimism refers to a sense of positivity about the future and there is some

evidence for a positive relationship between optimism and life satisfaction

(Christensen, Parris-Stephens & Townsend, 1998; Lucas, et al., 1996). As with

self-esteem, Lucas et al. (1996) tested whether the two constructs were

discriminable and found that they were. However, optimism has also been found

to correlate highly with neuroticism by Smith, Pope, Rhodewalt and Poulton,

(1989), who conclude that it is difficult to distinguish between optimism, measured

with the Life Orientation Test, from measures of neuroticism and negative

affectivity. Hence, it is again likely that if the effects of neuroticism were

12


controlled for, optimism may not make a unique contribution to the variance in

subjective life quality.

Finally, control conventionally refers to a sense that one can change the

environment in accordance with one’s wishes (this definition will be elaborated

later) and this construct has also been found to correlate with life-satisfaction,

although generally not as strongly as self-esteem (Boschen, 1996; Christensen, et

al., 1998; Schulz & Decker, 1985). There is generally little research in the

literature on the association between control and the personality dimensions,

extroversion and neuroticism. Still, some studies have shown control correlates

positively with extroversion and negatively with neuroticism (Darvill & Johnson,

1991; Morrison, 1997). Although the extent of these relationships is highly

variable and likely dependent on the definition and measurement of control used.

This issue clearly needs further investigation to identify whether or not control is a

psychological process that makes a unique contribution to the variance in

subjective quality of life. Furthermore, much of the literature on control and life

satisfaction is based on populations with spinal injury (eg. Boschen, 1990;

Boschen, 1996) and there is a need for investigation of normal populations to

assess whether control plays a role in life satisfaction in the absence of obvious

losses of control.

1.2.4 Conclusion There is both theoretical and empirical support for the notion that

personality, primarily extroversion and neuroticism, predicts subjective quality of

life. There is also theoretical and empirical support for the notion that other

psychological processes may have a strong association with subjective quality of

life. Yet, it is not clear whether these processes would make a unique contribution

to subjective quality of life if the effects of personality were controlled for. In fact,

similar to self-aspect congruence, it is likely that self-esteem and optimism will not

make a unique contribution. As the relationship between personality and

perceived control is not well documented and its ability to make a unique

contribution to subjective quality of life unknown, it is the most compelling of

these processes for investigation.

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1.3 PERCEIVED CONTROL

1.3.1 IntroductionA diverse literature suggests a sense of control is important to well-being.

Such perceptions of control are defined as “the judgements we each make about

the extent to which we can achieve desired outcomes and protect ourselves from

the misfortunes of life” (Thompson et al., 1998, p. 584). When making these

judgements, individuals will assess and use the control strategies they consider

available to them. These control strategies are divided into two processes of

perceived control, termed primary and secondary, by Rothbaum, Weisz and

Snyder (1982). This two-process model of perceived control provides a basic

understanding of the underlying structure of many terms and concepts in the

control and coping literature, such as behavioural and cognitive control (see

Thompson, 1981), emotion-focused and problem-focused coping (see Folkman,

1984) and learned helplessness (see Rothbaum, et al., 1982).

In fact, it was inadequacies in ideas about uncontrollability in the learned

helplessness and locus of control literature that motivated Rothbaum, et al. (1982)

to conceptualise two processes of control. They felt that this literature

inappropriately considers inward behaviours such as passivity, withdrawal and

submissiveness as a result of perceptions of uncontrollability and argued that:

the motivation to feel in control may be expressed not only in behaviour that is

blatantly controlling but also, subtly, in behaviour that is not. In some cases inward

behaviour may reflect a relinquishing of the powerful motive for perceived control.

In other cases, however, such behaviour may be initiated and maintained in an effort

to sustain perceptions of control. This effort is particularly likely when the inward

behaviour helps prevent disappointment, when it leads to a perception of alignment

with forces such as chance or powerful others, and when it is accompanied by

attempts to derive meaning from a situation. The uncontrollability model does not

explain any of these phenomena. (p. 9)

What these authors suggest is that an individual may exercise control over an event

not only by manipulating the external environment, but also by manipulating their

own internal environment; a perception of control that had gone largely ignored in

the literature. This is exampled by the earlier definitions of control that focus on

‘changing events’ (Brickman et al., 1982) or ‘behaviours’ (Glass & Carver, 1980)

14


and give little consideration of the role that cognitions play in control. When

cognitions are acknowledged it becomes evident that passivity, withdrawal and

submissiveness may in some circumstances be effective responses that serve to

maintain a perception of control and do not necessarily reflect perceived

uncontrollability as is suggested by the learned helplessness literature.

1.3.2 Developing a definition of primary and secondary controlTo include cognitions into the concept of control, Rothbaum, et al. (1982)

introduced the concept of primary and secondary control. Primary control is

defined as “attempts to change the world to fit in with the self’s needs”

(Rothbaum, et al., 1982, p. 8). Secondary control is defined as “attempts to fit in

with the world and to ‘flow with the current’” (Rothbaum, et al., 1982, p. 8). Both

primary control and secondary control may involve behaviours and cognitions.

However, typically primary control is characterised by behaviour which engages

the external world, and secondary control is characterised by cognitions within the

individual (Schulz & Heckhausen, 1996). Although these definitions are vague,

especially that of secondary control, the concepts are sound and subsequent

literature has provided clearer definitions. For example, Heckhausen and Schulz

(1995) have used the primary and secondary control concepts in a life span theory

of control. These authors defined primary and secondary control by the target of

the control. Primary control is defined as “bringing the environment into line with

one’s wishes … targets the external world and attempts to achieve effects in the

immediate environment external to the individual” (Heckhausen & Schulz, 1995,

p. 286). Secondary control is defined as “bringing the self in line with the

environment … targets the self and attempts to bring changes directly within the

individual” (Heckhausen & Schulz, 1995, p. 286).

Primary and Secondary control can be further understood by considering

some examples. In attempting to maintain a perception of control an individual

may use primary control strategies, such as asking others for help or advice,

developing new skills to deal with the situation, or working hard and investing

time into the situation. In attempting to maintain a perception of control an

individual may also use secondary control strategies, such as downward social

15


comparison (remembering one is better off than others), positive re-interpretation

(considering that something good will come of it) and active avoidance (ignoring

the event by thinking about other things). The above quotation from Rothbaum, et

al. (1982) provides examples of three other secondary control strategies: illusory

control (associating with chance), vicarious control (associating with powerful

others) and interpretive control (deriving meaning from the event).

Perceived control and the primary and secondary control processes that

form this perception are fundamental to coping with difficult circumstances.

Authors from the coping literature suggest that perceived control is necessary so

that the individual is assured a situation will not become so formidable that it

cannot be endured (see Thompson, 1981). Hence, Thompson (1981) defines

control as “the belief that one has at one’s disposal a response that can influence

the aversiveness of an event” (p. 89). This conceptualisation of control is related

to the compensatory function of primary and secondary control that Heckhausen

and Schulz (1995), and Schulz and Heckhausen (1996), promote in their life-span

theory of control. What these authors suggest is that an individual uses primary

and secondary control strategies to compensate for failure experiences. These

failure experiences include: “(a) normative developmental failure experiences

encountered when individuals attempt to enlarge their competencies, (b)

developmental declines characteristic of late life, and (c) non-normative or random

negative events” (Schulz & Heckhausen, 1996, p. 710). Furthermore, these

compensation mechanisms serve to “maintain, enhance and remediate

competencies and motivational resources” that are necessary for successful

experiences (Schulz & Heckhausen, 1996, p. 710). Hence, primary and secondary

control processes are used to cope with negative experiences or aversive

circumstances, and function to maintain a perception of control that will serve to

sustain competencies and motivation. Therefore, perceived control can be likened

to coping when considered in response to difficult circumstances.

However, perceived control also works in a way that makes it different

from coping. Primary and secondary control also have a selective function, where

they serve to assist goal selection and channel resources into the selected goals

(Heckhausen & Schulz, 1995). This selection concept taps into the notion that

16


primary and secondary control processes are not used exclusively in response to

aversive circumstances. In more subtle ways primary and secondary control may

be used to maintain perceived control in the more general negotiation of the

environment, to maintain a person-environment fit. Yet, the distinction between

selection and compensation is difficult to support as goal selection and resource

allocation can also be immediate responses to failure and have a compensatory

role. In fact, the notion that primary and secondary control strategies may be used

to achieve a person-environment fit encompasses both those circumstances where

strategies are used in response to a negative circumstance and where they are

simply a part of the general negotiation of the environment.

A more operational definition of control would involve a number of these

concepts and definitions. By using Thompson’s (1981) idea that control is a

‘belief’, control is restricted to the realm of perception. By using Heckhausen and

Schulz’s (1995) idea that a definition of primary and secondary control should

focus on the target of control, the distinction between the two types of control is

clearer. By including the aim of control, as person-environment fit, a better

understanding of the concept is provided. Hence, primary control may be referred

to as ‘the belief that one has at one’s disposal a response that can change the

external environment to achieve a person-environment fit’ and secondary control

may be referred to as ‘the belief that one has a one’s disposal a response that can

change the internal environment to achieve a person-environment fit’.

1.3.3 Addressing the interaction between primary and secondary controlPerson-environment fit can be likened to the term ‘optimal adaptation’ that

Rothbaum, et al. (1982) use to describe the successful coordination of the

intertwined primary and secondary control processes. Alternatively, Heckhausen

and Schulz (1995) conceive the relationship between primary and secondary

control not as two intertwined processes but as one, where primary control has

functional primacy over secondary control. They argue that:

Because primary control is directed outward, it enables individuals to shape their

environment to fit their particular needs and developmental potential. Without

engaging the external world, the developmental potential of the organism cannot be

realised. As a result, it is both preferred and has greater adaptive value to the

17


individual. … (Hence,) the major function of secondary control is to minimise

losses in, maintain, and expand existing levels of primary control.

(Heckhausen & Schulz, 1995, p. 286)

There are, however, problems associated with this view of primary and secondary

control processes. Just as the learned helplessness theories ignore the adaptive

value of cognitions (Rothbaum, et al., 1982), this theory excludes the adaptive

value of secondary control in and of itself. It is conceivable that individuals need

to shape both themselves and their environment to fit their particular needs and

developmental potential, and that without engaging both the internal and external

worlds their developmental potential cannot be realised.

Moreover, the adaptive value and preference for primary control over

secondary control is likely to be restricted to specific circumstances. For example

age, culture and ethnicity provide circumstances in which primary control does not

necessarily have primacy over secondary control. Heckhausen and Schulz (1996)

point out themselves that after the age of fifty the availability and use of secondary

control strategies is greater than that of primary control strategies, and that

successful aging is dependent on utilising secondary control strategies.

Furthermore, the importance of changing the external environment is bound to

Western cultures. Eastern cultures are likely to place more emphasis on accepting

the external environment and relying on control strategies that change the internal

environment. (Weiz, Rothbaum & Blackburn, 1984). Like culture, studies on

ethnicity have shown that primary control does not necessarily have primacy over

secondary control. African American HIV-positive male state prison inmates did

not show the same association between primary control and decreased distress that

white inmates showed. Furthermore, secondary control did not function as a back-

up to primary control regardless of ethnicity (Thompson, Collins, Newcomb &

Hunt, 1996). Thus, in some life stages, cultures and ethnic backgrounds,

secondary control processes may be more adaptive and preferred than primary

control processes.

Additionally, it is likely that there are other factors that may influence

whether primary or secondary control is preferred. Personality may be one such

factor. It is conceivable that some individuals may possess enduring

18


characteristics or predispositions that promote their reliance on primary control

over secondary and visa versa. Not all individuals will have the intrinsic

motivation to always change the environment to achieve a perception of control.

Some will be more resigned to accept their environment and change themselves to

fit within it. The extroversion and neuroticism dimensions of personality may

provide some insight into this hypothesis. For example, Alloy, Abramson and

Viscusi (1981) found that negative moods reduce feelings of control. Considering

the strong relationship between negative affect and neuroticism, it is possible that

this personality dimension will also influence an individual’s perception of control.

Likewise, positive affect or extroversion may also influence an individual’s

perception of control. However, at this stage, such speculation requires empirical

support.

In summary, there is good argument and evidence to suggest that primary

control does not necessarily have functional primacy over secondary control. It

may therefore be more useful to consider primary and secondary control as two

complimentary processes where, in given individuals, circumstances, and

environments, one process may be preferred and have greater adaptive value over

the other, and that each process may serve to compliment the other to maintain

perceived control.

This complimentary interaction between primary and secondary control

cannot be considered without acknowledging a third process in perceptions of

control, that is, a loss of control. While secondary control does replace much of

what was traditionally thought of as perceptions of uncontrollability, the

perception of uncontrollability still exists, although it is not always given attention

in the literature on primary and secondary control. In fact, there are large

segments of society that are at special risk for low feelings of control (Thompson

& Spacapan, 1991). When primary or secondary control is perceived not to be

available, an individual may relinquish control. That is, they may perceive the

event as uncontrollable and abandon the motivation for control (Rothbaum, et al.,

1982). Relinquished control is manifested in passivity and helplessness (Skinner,

1996). Examples of relinquished control are where an individual may respond to

an event or circumstance by not doing anything, spending time by his/her-self , or

19


letting feelings out, maybe by crying or yelling (Thurber & Weisz, 1997). Hence,

primary, secondary and relinquished control are important constructs to consider in

developing an understanding of perceived control.

Overall, there is a sense that primary and secondary control are closely

intertwined and the use of one over the other to achieve a person-environment fit

may be dependent upon a number of factors. Furthermore, some individuals may

not have the motivation to use primary or secondary control to achieve a person-

environment fit and may relinquish control altogether, experiencing a period of

perceived uncontrollability and person-environment misfit. Hence, an individual’s

perceived control may be maintained by a fluid combination of primary, secondary

and relinquished control processes.

1.3.4 The literature on primary, secondary and relinquished control, and various indicators of well-beingThe literature on primary and secondary control has followed two paths.

There is literature, stimulated by Heckhausen and Schulz (1995), which identifies

primary and secondary control processes in theories of life span development and

there is literature that identifies primary and secondary control processes as useful

strategies for coping with stressful or aversive situations or events. It is in this

latter path that I am mostly interested.

There are a number of studies by Weisz and collegues that focus on

children’s coping using primary, secondary and relinquished control strategies.

For example, research has shown that children cope with everyday stress by using

primary and secondary control processes (Band & Weisz, 1988). Research has

also shown that when children are in stressful situations in which few primary

control strategies may be available to them, secondary control is an adaptive

coping mechanism. For example, children undergoing treatment for leukemia

showed better adjustment if they used secondary control strategies than primary or

relinquished control strategies (Weisz, McCabe & Dennig, 1994); children at

summer camp showed the most frequent and effective way to cope with

homesickness was to use secondary control strategies (Thurber & Weisz, 1997).

These findings are congruent with the notion that secondary control is commonly

20


used after primary control has failed or, in this case, when it is not available.

However, this conclusion has not been supported with adults. For example,

Burton and Sistler (1996) found that spousal caregivers of people with dementia

used a combination of primary and secondary control in stressful situations.

Overall, the evidence shows that primary, secondary and relinquished control

strategies are used in aversive or stressful situations.

A broader range of literature shows that an individual’s perception of

control is likely to have a significant impact on their subjective life quality. It has

been proposed that both primary and secondary control processes are required to

maintain a perception of control that is necessary for optimal adaptation

(Rothbaum, et al., 1982), successful development (Heckhausen & Schulz, 1995),

to feel confident that a situation will not become so aversive it cannot be endured

(Thompson, 1981), and to achieve a sense of person-environment fit. Thompson

and Spacapan (1991) highlight evidence that suggests perceived control: 1) is

essential to emotional well-being, 2) can reduce the stress associated with stressful

events or situations, 3) contributes to adaptive coping with life stressors, 4) is

associated with better health outcomes, 5) promotes better ability to change

behaviours, and 6) can lead to improved performance. More specifically, Weisz,

Thurber, Sweeney, Proffitt and LeGagnoux (1997) found significant decreases in

the symptomatology of children with mild to moderate depressive symptoms when

treated with an 8-session primary and secondary control enhancement training

program. Also, as highlighted earlier, control has been found to correlate with life

satisfaction (Boschen, 1996; Christensen, et al., 1998; Schulz & Decker, 1985).

Considering this, the relationship between perceived control and subjective quality

of life is likely to be significant.

1.3.5 The measurement of primary, secondary and relinquished controlSince the development of the concepts of primary and secondary control is

relatively recent, there is no widely accepted tool for their measurement. Some

researchers (eg. Band & Weisz, 1988; Burton and Sistler, 1996; Thompson et al.,

1996; Weisz et al., 1994) have measured primary and secondary control by

obtaining responses about how difficult situations were coped with, and coding

21


these responses as reflecting either primary or secondary control, and sometimes

relinquished control. The coding system is based on the Rothbaum et al., (1982)

model of primary and secondary control (Weisz et al., 1994). In general, primary

control coping responses are those that involve attempts to directly interact with

the environment so as to modify objective circumstances. Secondary control

coping responses are those involving primarily internal responses aimed at

attempting to adjust oneself (eg. one’s beliefs, hopes, goal interpretations,

attributions) to objective circumstances. Finally, relinquished control consists of

the absence of attempts at primary or secondary control (eg. giving up or

concluding that there is nothing I can do). Thurber and Weisz (1997) have applied

this coding method to an already established coping scale for children. This

method of coding coping responses into primary and secondary control has been

effective and allows for various sample populations to provide responses that are

relevant to their own experiences. However, this also limits the generalisability of

the results and the comparison of results from different samples. Furthermore,

there may be coding biases, especially as some responses may contain elements of

both primary and secondary control making them more difficult to categorise.

A more systematic tool for the measurement of primary and secondary

control has been developed Heeps (2000). This questionnaire asks respondents to

rate the degree to which they agree with statements that reflect either primary or

secondary control. For example, “When I fail to meet a goal: I look for different

ways to achieve the goal” (primary control), “When something bad happens that I

cannot change, I can see that something good will come of it” (secondary control).

The statements were developed by reviewing the variety of types of primary and

secondary control described in the current literature. A total of seven primary

control items and seventeen secondary control items were developed. This tool is

still in the early stages of development and requires further validation and

assessment of reliability. Furthermore, the tool does not include any relinquished

control items.

Relinquished control has been measured by Thurber and Weisz (1997),

who developed the Ways of Coping with Homesickness Questionnaire by taking a

well-established questionnaire and coding the items in terms of primary, secondary

22


and relinquished control. The items on relinquished control included “I spent time

by myself”, “I just let my feelings out, maybe by crying or yelling”, and “I didn’t

do anything. Nothing would have helped”. While these items were used with

children, their content seems appropriate for the measurement of relinquished

control in adults.

1.3.6 Conclusion There is substantial theory and empirical evidence to suggest that perceived

control may be directly associated with subjective quality of life. Primary and

secondary control processes provide a contemporary conceptualisation of

perceived control that has received increasing support in the literature. With the

addition of relinquished control there are three control processes that interact with

each other to form a perception of control that may impact on an individual’s

subjective quality of life.

1.4 INTEGRATING PERSONALITY, PERCEIVED CONTROL AND SUBJECTIVE QUALITY OF LIFE

1.4.1 Maintaining subjective quality of lifeThe importance of understanding the psychological processes involved

with making judgements of life quality is highlighted by the recent proposition that

subjective quality of life is held under some kind of homeostatic control

(Cummins, 1995, 1998, 2000). This proposition is based on meta-analytic

research that has shown life satisfaction data to be consistent both between and

within Western populations. The research has converted life satisfaction data from

numerous studies to a percentage of scale maximum (%SM), which expresses any

Likert scale value as though it had been scored on a scale measured over the range

0 to 100. In examining the distribution of data both between and within various

Western populations, it has been consistently found that life satisfaction was

negatively skewed and clustered around three quarters of the scale maximum. It

was concluded that the average life satisfaction mean score of Western populations

is 75 2.5%SM, and that this average is held under homeostatic control.

23


Further support for the homeostatic model has been found by analysing the

changing relationship between population means and variance across 62 studies on

both Western and non-Western populations (Cummins, 2000). It was found that as

means approach 70%SM, the distribution becomes increasingly leptokurtic, and

therefore has lower variance. Then as the population mean values drop below

70%SM, the distribution become increasingly platykurtic as their ranges extend

downward, with a consequential increase in variance. These observations were

used to reinforce the conclusion that life satisfaction is not free to vary over its

theoretical range of 0-100%SM, but is held under homeostatic control which

attempts to maintain the life satisfaction of populations above 70%SM.

This homeostatic model compels us to question further how subjective

quality of life is maintained above 70%SM. Cummins and Nistico, (in press)

suggest that positively biased cognitions regarding aspects of the self may

constitute an adaptive mechanism that maintains life satisfaction. The aspects of

the self that the authors refer to are self-esteem, optimism and control. Cognitive

biases are beliefs based in reality but with a positive bias in favour of the

individual, as opposed to delusions that are incongruent with reality. Positive

cognitive biases have two essential properties. They are non-specific, in that they

refer to nebulous ideas that cannot readily be discerned from reality, and they are

empirically unfalsifiable as there is a lack of objective referents with which to

compare nebulous personal qualities. Despite the difficulties in empirically

validating positive cognitive biases, there is evidence to suggest that they exist in

direct relation to enhancing the self, enhancing one’s perception of control and

keeping optimistic about the future (see Taylor & Brown, 1988) and that they

contribute to life satisfaction (Cummins & Nistico, in press). Hence, perceived

control is indicated as an important psychological process involved in maintaining


When trying to understand how subjective quality of life is maintained,

personality must also be considered, given that it has been consistently shown to

correlate strongly with various indicators of life quality. The literature has

demonstrated that the two personality dimensions, extroversion and neuroticism,

can predict subjective well-being across time and various situations. Hence, the

24


same predictive relationship is expected of personality and subjective quality of

life. By definition, personality is an enduring characteristic or predisposition and

it is this quality that may contribute to the maintenance of subjective quality of

life. More specifically, it is an individual’s enduring qualities of sociability and

positive affect (ie. extroversion) and the absence of emotional instability and

negative affect (ie. neuroticism) that maintain subjective quality of life.

Furthermore, it is likely that these enduring personality characteristics will also

impact on other psychological processes found to maintain life satisfaction, such

as perceived control. The prediction of subjective quality of life by personality

and perceived control may occur in either of two ways. Personality may indirectly

predict subjective quality of life via perceived control (see Figure 1a), or

personality may continue to directly predict subjective quality of life in addition to

an indirect prediction through perceived control (see Figure 1b). Given the

strength of the relationship between personality and subjective quality of life, I

propose the latter model to be more accurate.

1(a) Indirect prediction 1(b) Direct and indirect prediction

Figure 1: The direct and indirect prediction of subjective quality of life (SQOL)

by personality and perceived control.

1.4.2 Rationale for a hypothesised model of personality, perceived control and subjective quality of life

The three concepts, personality, perceived control and subjective quality of

life, depicted in Figure 1, have been selected for investigation for a number of

reasons.

25

Personality

Perceived Control

SQOL

Perceived Control

SQOL

Personality


Firstly, the definition and measurement of each of these concepts is sound.

Subjective quality of life is a concept free from the problems surrounding

subjective well-being which incorporates the problematic conceptualisation and

measurement of positive and negative affect. Furthermore, the definition and

measurement of subjective quality of life has been soundly developed by Cummins

(1997a, 1997b) and incorporates the notion that judgements of satisfaction with

life domains are weighted by the importance of that particular life domain to the

individual. Extroversion and neuroticism are well known dimensions of

personality that have long been upheld in the literature in both theory and

measurement. Perceived control formed by the interaction of primary, secondary

and relinquished control processes is a relatively recent conceptualisation, but it

has gained impressive theoretical support and provides a basic understanding of

the underlying structure of many terms and concepts in the wider control literature.

The measurement of primary, secondary and relinquished control is, however, in

the process of development.

Secondly, the definition and measurement of these three constructs allows

for their relationships to be explored without running the risk of including

constructs that are in essence identifying the same phenomena. This problem is

likely to be inherent in investigations of the relationship between personality and

two of the three dimensions of self-satisfaction, self-esteem and optimism, where

there is a strong association between neuroticism and these two dimensions.

Hence, subjective quality of life, the personality dimensions of extroversion and

neuroticism, and the self-satisfaction dimension of perceived control and the

primary, secondary and relinquished control processes associated with it, are ideal

variables for the current investigation, as they are likely to be relatively free from

confounding overlapping variance.

Finally, there is theory and evidence to suggest that the relationships

between these three concepts are meaningful and contribute to the maintenance of

life satisfaction. Personality has long been established to predict constructs of life

quality. Perceived control has been more recently introduced as an important

factor in the maintenance of life satisfaction. It is hypothesised that personality

26


will play a dual role in influencing subjective quality of life both directly and

indirectly through impacting on perceived control (see Figure 2).

Figure 2: Hypothesised model of subjective quality of life, personality and

perceived control.

1.4.3 Focus of the current researchThe current study will examine the hypothesised model of relationships,

depicted in Figure 2, between the personality dimensions of extroversion and

neuroticism, perceived control and the associated processes of primary, secondary

and relinquished control and subjective quality of life. The model will be tested on

a general population as well as a population of people caring for a relative with a

mental illness.

27

Subjective Quality of

Life

Perceived Control

Personality

Extroversion Neuroticism

Primary Control

Secondary Control

Relinquished Control


1.5 SUBJECTIVE QUALITY OF LIFE: CARERS OF PEOPLE WITH MENTAL ILLNESS

1.5.1 The historical development of research into carers of people with mental illnessThe process of deinstitutionalisation and the introduction of community

focused psychiatric care has placed increasing responsibility on families for the

care of people with psychiatric disabilities. In response to this, research on people

with a psychiatric disability began to include their families. Initially the research

focused on the negative impact the family had on the person with mental illness

leading to families being viewed as the cause of mental illness throughout the

1960’s and 1970’s (Yamashita & McNally-Forsyth, 1998).

In an example of this negative view, Brown, Birley and Wing (1972) refer

to the following ‘facts’ about the course of Schizophrenia: close emotional ties

with family members indicated poor prognosis; patients discharged from hospital

to live with family members who were highly emotionally involved with them

were more likely to suffer a relapse; a raised level of tension in the home made

relapse more likely. With these ‘facts’ about the negative impact of families on

people with mental illness in mind, the authors then go on to investigate the

relationship between family members' expressed emotion and patient relapse.

Expressed emotion was measured by hostility, dissatisfaction, warmth, emotional

over-involvement and the number of critical comments. Patient relapse was

measured by either, a change from normal to a state of schizophrenia, or a marked

exacerbation of persistent schizophrenic symptoms. The authors found that

expressed emotion was independently associated with relapse and could not be

explained away by the action of any other factor investigated such as age, sex,

previous occupational record, length of clinical history, type of illness, etc.

Concluding, “the level of relatives’ expressed emotion must be taken into account

as one of the factors that cause relapse” (Brown, et al., 1972, p. 254).

While such conclusions did receive some empirical support (such as

Vaughn & Leff, 1976), the adoption of these conclusions by clinicians by far

outweighed that which would be warranted by the empirical evidence. The

research was largely atheoretical, and while the association between high

28


expressed emotion and relapse was clearly established, causality was not.

Furthermore, there were methodological problems; the most measurable

component of expressed emotion was the number of critical comments made by

the family member about the patient (Brown, et al., 1972). It is possible that

family members have more to be critical about with patients who are not fully

recovered and who are therefore more likely to relapse. It is also possible that

family members perceived the research interviews as an opportunity to express the

problems they perceived in their mentally ill relative.

The notion that families were the causative agents in the development of

mental illness inspired a body of research that investigated the impact that mental

illness had on the family. Advocacy groups for families of people with a mental

illness argued that this high expressed emotion was a direct response to the trauma

of caring for a mentally ill relative. This trauma began to be investigated by

researchers who referred to it as the ‘burden’ of care, and distinctions were made

between objective and subjective burden; objective burden refers to the tangible or

observable costs to the family and subjective burden refers to the personal

suffering or negative psychological impact on the family member (Maurin &

Boyd, 1990; Lefley, 1987a; Webb et al., 1998). Whilst these two concepts are

closely associated, as objective burden is likely to contribute to subjective burden,

it is the literature on subjective burden that is most relevant to subjective quality of

life.

1.5.2 The impact of the caregiving role on subjective quality of life A number of literature reviews have concluded that mental illness produces

significant burden and distress in family members (eg. Fadden, Bebbington &

Kuipers, 1987; Maurin & Boyd, 1990). The psychological distress of carers, as

measured with the General Health Questionnaire is reported to be high. It was

reported by Vaddadi, Soosai, Gilleard and Adlard (1997) that 79% of carers had

scores indicating a significant level of emotional/psychiatric disorder. Whilst,

Barrowclough and Parle (1997) found 57% of carers had significant levels of

psychological distress at the time of the patient’s hospital admission and that in

30% of carers this distress remained when the patient was discharged back home.

29


In a review of the literature by Cummins (2001) on carers of people with a range

of severe disabilities, all of the 17 studies analysed reported higher than normal

levels of distress in carers. A key theme in these studies was higher than normal

levels of anxiety and depression.

The emotional impact of caring for people with mental illness has also

been reported descriptively. In a qualitative study conducted in Iceland,

Sveinbjarnardottir and Dierckx de Casterle, (1997) found that family members

expressed a wide range of emotionally painful and disturbing feelings such as

anger, disappointment, fatigue, distress, anxiety and sadness, all of which they

found overwhelming at times. Lefley (1987b) adds bewilderment, fear, denial,

rage, self-blame, pain, sorrow, empathic suffering and grieving to this list.

Moreover, the introduction of mental illness into the family has been described as

a traumatic and catastrophic event which primarily gives rise to a powerful

grieving process (Baxter & Diehl, 1998; Collings & Seminuik, 1998; Fadden et al.,

1987; Lefley, 1987b; Marsh et al., 1996; Winefield, 1998). Family members often

experience feelings of grief over the loss of the former personality and the future

potential of the individual with mental illness. Along with this grief often comes a

significant sense of guilt or self-blame. There are four types of guilt frequently

described: 1) guilt associated with the belief that they may have done something to

cause the mental illness or that they did not recognised the symptoms and seek

help early enough, 2) guilt about having hostile feelings toward the person with the

mental illness, even though such feelings may be a legitimate response to

provocative or intolerable behaviour, 3) guilt about leaving a loved one in

unpleasant surrounds, such as when the person must stay in hospital or other

residential services, and 4) guilt about making self-protective life decisions, such

as deciding not to care for the person in the family home (Lefley, 1987b).

Clearly the emotional impact of caring for someone with a mental illness is

great. So great in fact that many carers experience clinically significant levels of

psychological distress, primarily anxiety and depression, as well as a more

descriptive range of emotional experiences. There are a variety of elements

associated with caregiving that may be a source of this burden and distress.

30


The burden and distress of caregiving often occurs in the context of

permanent shifts in family roles and considerable unanticipated responsibility

falling consistently to one carer (Perring, Twigg & Atkin, 1990). It is this

individual who often finds themself in a position where the needs and wishes of

the person with mental illness are constantly put before the needs of the primary

caregiver and other family members (Maurin & Boyd, 1990; Webb et al., 1998).

This individual may also feel isolated as they try to cope with the impact of mental

illness in the family. In fact social isolation has been found to be widespread

among families affected by mental illness. Fadden et al., (1987) suggest “one of

the most damaging consequences of living with a relative with a persistent mental

illness is the detriment to social and leisure activities” (p. 286). A huge amount of

time is taken up by the caring role and carers often find it difficult to leave the

house unattended for longer than a few hours at a time (Perring et al., 1990). This

makes time for the pursuit of social, leisure and employment activities difficult to

find, resulting in increased social isolation. Social isolation may also be a result of

the stigma of mental illness (Fadden et al., 1987) and discrimination against

individuals with mental illness (Sveinbjarnardottir & Dierckx de Casterle, 1997).

The now somewhat historical notion that families are causative agents in the

development of mental illness and schizophrenia has left in its wake a stigma that

still remains (Ferris & Marshall, 1987). Many families still experience this stigma

in their interactions with mental health professionals, encountering a lack of

recognition or appreciation from professionals, and this can be the source of a

great deal of stress for family members (Winefield, 1998).

Along with these more general problems, carers must cope with the

relapsing and remitting nature of mental illness and difficult symptom behaviours.

The unpredictability of the episodic characteristics of mental illness are reported to

be the most difficult aspect of living with someone with such a condition

(Sveinbjarnardottir & Dierckx de Casterle, 1997), as the carer is required to

constantly readjust the caring role in response to this unpredictability (Collings &

Seminuik, 1998). Difficult symptom behaviours include both positive and

negative symptoms. Positive symptoms reflect an excess or distortion of normal

functions, such as delusions, hallucinations, disorganised speech or disorganised

behaviour (American Psychological Association, 1994). Negative symptoms

31


reflect a diminution or loss of normal functions, such as affective flattening and

avolition (American Psychological Association, 1994). Researchers have found

mixed results for the role these symptom types play in contributing to carer

burden. Webb et al. (1998) cite research that has found positive symptoms to

contribute to burden (eg. Winefield & Harvey, 1993) and others that have found

negative symptoms to be most burdensome (eg. Oldridge & Hughes, 1992).

Positive symptoms often result in problematic psychotic and socially

unacceptable behaviours. When families are not able to manage these behaviours,

the quality of life for all family members declines as they experience

overwhelming tension in anticipation of the dreaded behaviours (Swan & Lavitt,

1988). When the individual with mental illness demonstrates these behaviours in

the community, it adds to the families sense of social stigma, embarrassment and

isolation (Lefley, 1987b). In addition, some individuals display a number of

threatening, intimidating and violent behaviours, with which the family carers

must deal. Caregiving families with violent members have reported significantly

lower adjustment scores than families with nonviolent members (Swan & Lavitt,

1988). Furthermore, Vaddadi et al., (1997) found the type and frequency of abuse

experienced positively correlated with relatives' General Health Questionnaire

scores, as did the number of types of abuse.

Negative symptoms also appear to be problematic for carers. In interviews

with 124 carers, Tucker, Barker and Gergoire (1998) found that depressed or

anxious behaviour in the mentally ill person accounted for 43% of the variance in

carers' negative scores on the Experience of Caregiving Inventory (Szmukler,

Wykes & Parkman, 1998). Furthermore, the resultant tension and anxiety that

carers experience in response to negative symptoms is sometimes intensified by

the fear that the individual with mental illness may commit suicide (Perring, et al.,

1990; Sveinbjarnardottir & Dierckx de Casterle, 1997).

Contrary to this research that suggests symptomatology and behaviour play

key roles in the burden experienced by carers, other researchers have found this

may not be the case. Szmukler et al., (1998) found that the ability of a wide range

of individual characteristics, including features of the illness, symptomatic state

32


and social functioning, to predict caregiver distress was poor. These authors

suggest that conflicting results have often resulted from an assessment of the

person’s symptomatology and behaviour using carer reports, rather than using

independent assessments. This may mean that it is carers’ perception of their ill

relatives’ disability, rather than actual disability, that impacts on their distress.

Alternatively, it may mean that carers have a more accurate picture of their ill

relatives’ disability. Still, the notion that carers’ perception of their ill relative’s

disability impacts on their distress provides an interesting avenue for reducing the

amount of distress carers experience.

Overall, it is clear that there are many negative elements associated with

the caregiving role which may have a negative impact on carers’ subjective quality

of life. In his review of the literature on carers of people with a range of severe

disabilities, Cummins (2001) converted life satisfaction scores from eight studies

into %SM and found the mean of the combined data was 615.9%SM, well below

the standard score of 752.5%SM. These studies investigated carers of

intellectually disabled children or adults and the elderly with dementia, yet from

the above discussion similar results would be expected of carers of people with

mental illness. Likewise, Browne and Bramston (1996) found that families of

young people with intellectual disabilities had significantly lower subjective

quality of life, particularly in the domains of health and productivity, than those

without offspring with an intellectual disability. Hence, the negative impact of

caregiving is likely to be evident regardless of the characteristics of the individuals

receiving the care.

It is also important to highlight the positives of caregiving, although little

work has been done on this area in the field of mental illness. Marsh et al. (1996)

researched evidence for resilience, which refers to “the ability to rebound from

adversity and prevail over the circumstances of our lives” (p. 4). The researchers

asked 131 close relatives of people with mental illness a series of open-ended

questions, which were coded to establish three variables: family resilience,

personal resilience and consumer resilience. Family resilience refers to family

bonds, family strengths and family growth. Personal resilience refers to personal

contributions, improved personal qualities and personal growth. Consumer

33


resilience refers to the person with mental illness and their positive personal

qualities, recovery, and contributions to the family. Family resilience was reported

by 87.8% of participants, personal resilience was reported by 99.2% and consumer

resilience by 75.6%. Unfortunately, the research provides no information on these

resilience factors in the normal population making interpretation of the findings

difficult. However, the research highlights the need to maximise resilience in

order to reduce carer burden and distress.

1.5.3 The role of perceived control in coping with the impact of mental illness on the family and maintaining subjective quality of lifeHow families respond and cope with the negative impact of mental illness

in the family is vital to identifying how subjective quality of life can be

maintained. Coping among carers of people with mental illness has recently

gained increased attention in the literature and the effectiveness of various coping

strategies in reducing burden and distress has been consistently found (for reviews

see Collings & Seminuik, 1998; Maurin & Boyd, 1990).

The theory of stress and coping developed by Lazarus and Folkman (1984)

has been advocated as a useful theory to apply to family burden (Maurin & Boyd,

1990). The Lazarus and Folkman (1984) model proposes that the negative effects

of stress on health are mediated by the person’s coping style and their cognitive

appraisals of the situation (primary appraisal) and of the resources available to

them (secondary appraisal). Coping styles are the characteristic strategies an

individual uses to handle stress. The model differentiates between two coping

styles: problem-focused coping (the process of managing the problem itself) and

emotion focused coping (the process of managing one’s emotions associated with

the problem). This theory is conceptually similar to the primary and secondary

processes of perceived control. Both theories address an individual’s perception of

his/her ability to deal with a situation and the strategies he/she uses in response to

the situation. Problem-focused coping is in many ways similar to primary control

where the problem is clearly being addressed by making changes in the person’s

environment. Emotion-focused coping has similarities with secondary control, as

managing one’s emotions is a process of making changes within the person’s

34


internal environment. Hence, primary and secondary control may be a useful way

of investigating how carers cope with the burden of caregiving.

In an investigation of families’ reactions to their relative’s mental illness,

by Yamashita and McNally-Forsyth (1998) who analysed qualitative data from

two studies (a Canadian and an American sample), four key themes were found to

demonstrate a developing sense of control within carers. Firstly, they found that a

primary task of family members was the acceptance of the mental illness

diagnosis. Family members reported that accepting mental illness, accepting the

uncertainty of the situation, understanding their relative’s behaviour as part of the

illness, and accepting the relative as he or she is, was a turning point in their

caregiving. Furthermore, it is apparent that telling their stories about the illness

and the relative’s symptoms, fostered this acceptance of the new reality of mental

illness and empowered them to move on with their lives. Secondly, they found

once families accepted the illness, they sought information about the illness from a

variety of sources. Some family members sought information in books; others

talked to knowledgable staff; some sought out other sources of information such as

physicians. Thirdly, further acceptance of the illness was signalled by the families'

attempt to maintain normalcy in their day to day living. Families indicated that

this was an important strategy for dealing with mental illness in the family.

Finally, the authors found that families realised how important it was to be open

and honest about their relatives’ condition to facilitate acceptance and normalcy.

In fact, families found that when they did relate to others in this way they were

surprised by the understanding and support they received. This process of

responding and coping with mental illness in the family outlined by Yamashita and

McNally-Forsyth (1998) demonstrates many primary and secondary control

strategies. The first theme, acceptance, is a secondary control process that appears

necessary to enable carers to use primary control processes, such as the second and

third themes, seeking information about mental illness and maintaining normalcy

in their daily lives. The fourth theme, being open and honest about mental illness

in the family is also a secondary control process that appears to foster further

primary (normalcy) and secondary (acceptance) control.

35


Similarly, Stern, Doolan, Staples, Szmukler and Eisler (1999) provide

evidence that carers use a range of primary and secondary control strategies, as

well as relinquished control, by evaluating narrative constructions about serious

mental illness in the family. These authors divided the narratives into two types,

those that provided stories of restitution or reparation and those that did not; the

latter they describe as being chaotic or frozen stories. The stories of restitution or

reparation involved a variety of primary and secondary control themes: making use

of resources like support groups (primary control), taking care of oneself (primary

control), seeing positives and being amused at times (secondary control; positive

re-interpretation) and viewing the mental illness as an occasion for learning and

knowing more in spite of the difficulties (secondary control; interpretive control).

The stories that were described as being chaotic or frozen involved themes of

relinquished control: difficulty making use of resources like support groups,

feeling flat and nebulous, hoping to get used to mental illness, and not knowing

what more to do or how to go about it.

These qualitative studies highlight the importance of both primary and

secondary control in coping with the impact of mental illness in the family. Yet,

research of a more quantitative nature has largely ignored secondary control

processes and focused only on themes of primary control. For example, in a

sample of 225 family members of persons with serious mental illness, Solomon

and Draine (1995) measured a wide array of adaptive coping strategies, which they

defined as “the application of behavioural strategies to reduce actual or potential

stress” (p. 1156). These adaptive coping strategies can be likened to primary

control, as behavioural strategies are most likely to achieve change in the person’s

external environment. The results found that social support, another form of

primary control, explained the largest portion of variance (17%) in adaptive

coping. More extensive adaptive coping was associated with membership in a

support group for families, a larger social network and more affirming support

from social network members. This indicates that primary control is an important

strategy for carers of people with mental illness. However, Webb et al. (1998) did

not find social support significantly related to subjective burden. In a study of 59

caregivers of patients with schizophrenia, these authors found that burden was

related to the inappropriate use of primary control. They found that burden was

36


increased in individuals who had a tendency to use problem-focused coping for

dealing with negative symptom behaviours and a tendency not to use problem-

focused coping for dealing with positive symptom behaviours. Hence, the

effectiveness of primary and secondary control may be dependent upon the

situation in which it is being applied. Furthermore, an individual’s personality or

tendency to use a particular type of control strategy may result in inappropriate

control strategies being used and thus hinder the effectiveness of the strategy.

1.5.4 ConclusionIn conclusion, it can be seen that the caregiving role may have a negative

impact on subjective quality of life. Carers of people with mental illness

experience considerable burden and distress. In fact, the introduction of mental

illness into the family has often been described as a traumatic and catastrophic

event that gives rise to an array of emotionally painful and disturbing feelings

including anger, guilt, anxiety, sadness and grief. As carers cope with difficult

symptom behaviours and the relapsing and remitting nature of mental illness, they

often find themselves in a position where the needs and wishes of the person with

mental illness are constantly put before their own. Consequently, carers’

opportunity for work may become limited and their social and leisure activities

reduced, which may lead to social isolation. The research on coping with this

negative impact of mental illness in the family indicates that both primary and

secondary control strategies may be useful in the maintenance of carers' subjective

quality of life.

1.5.5 Focus of the current researchThe current research intends to examine the impact of the caregiving role

on the subjective quality of life and perceived control of carers of people with

mental illness. These data will be compared with a comparison sample of people

who do not care for someone with a disability. In this comparison the effects of

personality on the variance in subjective quality of life will be removed to provide

a purer understanding of the differences between the two samples in their

satisfaction with life. The two samples will also be used to examine the

relationships, outlined in the model in Figure 2, between the variables of interest,

37


subjective quality of life, perceived control conceptualised as primary, secondary

and relinquished control strategies, and personality conceptualised as neuroticism

and extroversion.

38

CHAPTER 2 - Study One: Aims and Hypotheses

CHAPTER 2

2 STUDY ONE: AIMS AND HYPOTHESES

Aim One:

To develop a valid and reliable tool for the measurement of perceived

control by examining the factor structure of questionnaire items reported to reflect

primary control, secondary control and relinquished control.

Aim Two:

To examine the differences in perceived control and subjective quality of

life between a sample of carers of people with mental illness and a comparison

sample of people who do not care for someone with a disability.

It is hypothesised that carers of people with mental illness will have lower

subjective quality of life and perceived control than people who do not

care for someone with a disability, after the effects of personality have

been removed.

Aim Three:

To examine the relationships between personality, perceived control and

subjective quality of life in a sample of carers of people with mental illness and in

a comparison sample of people who do not care for someone with a disability.

It is hypothesised that perceived control will improve the prediction of

subjective quality of life beyond that afforded by personality and that

personality will also predict perceived control.

39

CHAPTER 3 - Study One: Method

CHAPTER 3

3 STUDY ONE: METHOD

3.1 SampleThe carer sample was recruited from the Schizophrenia Fellowship of

Victoria (SFV), an organisation that has provided a variety of services to people

with mental illness and their families for the past 21 years. From beginnings in

peer support, the organisation has expanded to include face-to-face and telephone

contact providing individual information and support, library services and the

development and publication of resource materials, and the provision of

educational courses. The sample was taken from a total of 178 questionnaires that

were voluntarily completed by participants in educational courses and forums run

by SFV for relatives of people with mental illness. Forty-five of those were

deleted from the subsequent analyses because the respondent had indicated that

they were not the primary carer of someone with a psychiatric disability. A further

six were deleted due to a significant number of incomplete items. This left a total

of 127 questionnaires for the subsequent analyses. Most of the carers (75%)

described themselves as the primary carer of someone, usually their child (70%),

with a diagnosed mental illness, mostly a psychotic disorder (58%).

The comparison sample was taken from a total of 250 questionnaires that

were sent to potential participants randomly selected from a list of individuals who

had previously participated in Deakin University research. A total of 139

questionnaires were returned following one reminder letter, a response rate of

56%. Seventeen of those questionnaires were returned but not completed. A

further eight of those were deleted from the subsequent analyses because the

respondent had indicted that they were the primary carer of someone with a

disability. Subsequently, 114 questionnaires were used in the analyses.

Sample demographics are displayed in Table 1 as percentages. The two

samples were reasonably comparable on the range of demographic variables

examined. The only noticeable differences being in income and location. A

greater percentage of the carer sample had an income less than $40,999 and a

40


greater percentage of the comparison sample had an income greater than $41,000.

The carer sample was recruited from metro and regional areas, whilst the

comparison sample was only recruited from metro areas.

Table 1: Demographic information.Carer

(n=127)Comparison

(n=114)SexMale 31.7% 36.0%Female 68.3% 64.0%Age20-29 years 0.8% 4.4%30-39 years 5.6% 9.6%40-49 years 26.4% 25.4%50-59 years 44.0% 29.8% >60 years 23.2% 30.7%Income<$10,999 17.9% 11.9%$11,000-$25,999 25.6% 22.0%$26,000-$40,999 24.8% 15.6%$41,000-$55,999 9.4% 14.7%>$56,000 22.2% 35.8%EducationPrimary educated 4.0% 3.5%Secondary educated 49.6% 55.8%Tertiary educated 46.4% 40.7%LocationMetro 49.7% 100%Hume (regional area) 22.0%Gippsland (regional area) 28.4%

3.2 ProcedureA letter of information outlining the study and ethical safeguards, and a

questionnaire booklet were distributed to all participants in the study. (See

Appendix A and B respectively for an example of the information letter and

questionnaire given to carers, that received by the comparison sample was

virtually identical, minus any specific references to carers, and therefore has not

been included). Consent to participate in the study was implied by the voluntary

completion of the questionnaire. The carer sample received their questionnaires

when they attended an SFV educational course or forum, from the researcher, or a

staff member of SFV. They completed their questionnaires prior to partaking in

the educational course or forum and returned them to the researcher or to the SFV

staff member, who then forwarded them onto the researcher. The comparison

41


sample received their questionnaires via the mail and returned them directly to the

researcher in the prepaid envelope provided. The names and addresses of each

participant were kept separate from the questionnaires by assigning a code number

that corresponded to their questionnaire. This was necessary to follow-up

participants who had not returned their questionnaire within two weeks with a

reminder letter, after which no further contact was made.

3.3 Measurement ToolsSubjective quality of life was measured using the subjective scale of the

Comprehensive Quality of Life Scale developed by Cummins (1997b). A copy of

this scale is included in Appendix B. This tool assesses the individual’s

satisfaction with seven life domains weighted by the importance he/she places on

each of these domains. The seven domains are material well-being, health,

productivity, intimacy, safety, place in community and emotional well-being. The

aggregate of these domains provides a total subjective quality of life score.

Respondents were asked to rate the importance they place on each domain on a ten

point Likert scale and how satisfied they are with each domain on an eleven point

Likert scale. For example respondents were asked “How important to you is your

own happiness?” and “How satisfied are you with your own happiness?” This tool

was selected because it has been demonstrated to be valid, reliable and sensitive

based on evidence presented in the manual. The tool has good content validity as

its development has been based on sound theory and empirical review of the

literature. Internal reliability has been shown in numerous studies including

Cummins, McCabe, Romeo and Gullone (1994) who reported Cronbach’s alpha

for the importance subscales at .65 and for the satisfaction subscale at .73. The

tools sensitivity has been demonstrated through the findings reported in the manual

of significant differences between various populations, such as those with high and

low strength in spiritual beliefs. Furthermore, Cummins et al. (1994) found that

each of the seven subjective quality of life domains significantly discriminated

between groups classified as either high or low subjective quality of life.

Personality was measured using the extroversion and neuroticism scales of

the Revised Eysenck Personality Questionnaire (Eysenck & Eysenck, 1991). A

42


copy of these scales is included in Appendix B. Respondents were asked to

provide yes/no responses to 12 questions on each scale. An example from the

neuroticism scale is “Does your mood often go up and down?” An example from

the extroversion scale is “Are you a talkative person?” The scales were selected

because they are widely accepted and used personality scales that have been

developed over nearly fifty years of personality research and theory development,

including extensive factor analytic research by both the scales developers (see

Eysenck & Eysenck, 1985) and many others, such as Royce and Powell (1983).

The scale manual reports reliability with alpha coefficients for the extroversion

scale at .88 for males and .84 for females, and for the neuroticism scale at .84 for

males and .80 for females. Reliability has also been tested by Francis et al. (1998)

for an Australian sample who reported Cronbach’s alpha on the extroversion scale

at .85 and on the neuroticism scale at .80.

Perceived control was measured using a modified version of the primary

and secondary control scale developed by Heeps (2000) and relinquished control

items taken from Thurber and Weisz, (1997). A copy of the modified scale is

included in Appendix B. The original version of the primary and secondary

control scale used the same statement, “When something bad happens:” to precede

all of the secondary control items and a variety of statements to precede the

primary control items. This format may have produced an artificial distinction

between the primary and secondary control items. Hence, the primary and

secondary control scale was modified by preceding all items with the statement

“When something bad happens:” There were a total of 28 items on the Perceived

Control scale comprising seven primary control items, 17 secondary control items

and four relinquished control items. Respondents were asked to rate the extent to

which they agreed with each statement on a 10 point Likert scale. An example of

a primary control item is “When something bad happens: I put lots of time into

overcoming it.” An example of a secondary control item is “When something bad

happens: I can see that something good will come of it.” An example of a

relinquished control item is “When something bad happens: I just let my feelings

out, maybe by crying or yelling”. While the scale has good face validity and its

development has been based on a thorough review of the literature, the reliability

of this modified version is unknown.

43

CHAPTER 4 - Study One: Results

CHAPTER 4

4 STUDY ONE: RESULTS

4.1 Aim OneTo refine the reliability and validity of the tool for the measurement of

perceived control for use in the subsequent analyses, a series of factor analyses and

other data reduction methods were conducted on the data from the combined carer

and comparison samples, totalling 241 people. A combined sample was used in

order to ensure generalisability of the results to both samples and to provide an

adequate sample size for the analysis. Refer to Appendix B for item numbering

and content to inform the following discussion.

The data adequately met the necessary assumptions for testing. The

sample size was greater than the criterion of a minimum of five subjects per

variable outlined by Tabachnick and Fidell (1996). Twelve missing cases were

detected and replaced with the variable mean. The distributions of each of the

variables were examined for normality, linearity, and univariate and multivariate

outliers. An examination of the skewness and kurtosis statistics indicated six items

were not normally distributed, items 8 and 10 being mildly negatively skewed and

items 18, 24, 25 and 27 being mildly positively skewed. No transformations were

made because of the mild nature of the skewness, because skewness is likely to be

meaningful to the data, and because factor analysis is robust to mild violations of

normality.

Examination of the scatterplots revealed the data generally met the

assumption of linearity. Mahalanobis distance was used to check for multivariate

outliers using a cutoff criterion of p<.001, none were found. Twenty-six

univariate outliers were recoded using the method outlined by Tabachnick and

Fidell (1996) which specifies “assign the outlying case(s) a raw score on the

offending variable that is one unit larger (or smaller) than the next most extreme

score in the distribution” (p. 69).

44


An initial factor analysis extracting Eigenvalues over the value of one was

performed on both the original data and the recoded data. No substantial

differences were found between the resultant solutions so it was decided to use the

original data for the analysis. Similarly, an initial factor analysis extracting

Eigenvalues over the value of one was performed on each of the samples. No

substantial differences were found between the resultant solutions deeming the

combined sample appropriate for the analysis.

Principal components factor analysis with oblique rotation was performed

on the 28 items of the control scale for the combined sample of 241. The data met

the assumptions of factorability of the correlation matrix. Most items correlated

greater than .3 with at least one other item and partial correlations were all low.

Items 13, 18 and 22 failed to correlate greater than .3 with at least one other item,

however, these items were retained as the correlations were close to .3 and they all

represented the relinquished control scale and deleting them would have deleted

the whole scale. The Kaiser-Myer-Olkin measure of sampling adequacy for each

variable was greater than .5 except for item 13. It was therefore decided to delete

item 13 from the subsequent analyses. The matrix as a whole was factorable as

indicated by a significant result for Bartletts test of sphericity, 2(378) =2519.11,

p=.000, and a Kaiser-Myer-Olkin score of .87, which was greater than .6.

The initial factor analysis extracted eight factors with Eigenvalues over

one. Four factors explained more than 5% of the variance each and altogether

accounted for 48.08% of the variance. However, the scree plot clearly indicated

that there were only two factors with sufficient difference between them, together

accounting for 36.44% of the variance. A second factor analysis was performed

extracting two factors. Examination of the factor loadings revealed four items (16,

17, 18 and 19) that loaded greater than .3 on both factors. These items were

removed to obtain simple structure and a third factor analysis, extracting two

factors, was performed on the remaining 24 items. Examination of the factor

loadings revealed a further two items (11 and 12) that loaded greater than .3 on

both factors; these items were removed and a fourth factor analysis was performed.

The results showed that the two factors were independent (r= .278) and together

45


accounted for 36.17% of the variance with Factor 1 accounting for 25.05% and

Factor 2 accounting for 11.11%.

Internal consistency for each of the factors was assessed using Cronbach’s

Alpha. Internal consistency was high for Factor 1 (=.83) and moderate for Factor

2 (=.68). Pearson correlation coefficients for each item for Factor 1 ranged

from .37 to .69 and for Factor 2 ranged from .18 to .51. Factor 1 consisted of 12

items that included seven primary control items and five secondary control items.

Factor 2 consisted of nine items that included six secondary control items and

three relinquished control items. In order to reduce the number of items in the

scale and to eliminate some of the items with poor scale reliability, items that

loaded on a factor less than .4 were deleted and a final factor analysis was

performed. The results of the final factor analysis are displayed in Table 2.

Table 2: Two factor solution for the Perceived Control Questionnaire, with primary control items (PC) and secondary control items (SC) identified.

Questionnaire Items ApproachControl

AvoidantControl

28. I work hard to overcome it (PC) .8110. I look for different ways to achieve the goal (PC) .7915. I put lots of time into overcoming it (PC) .7221. I work out what caused it (PC) .6726. I learn the skills to overcome it (PC) .67 2. I make an effort to make good things happen (PC) .65 9. I do something vigorous to take my mind off it (SC) .52 3. I remember you can’t always get what you want (SC) .47 8. I remember I am better off than many other people (SC) .46 1. I can see that something good will come of it (SC) .42

25. I ignore it by thinking about other things (SC) .7727. I tell myself it doesn’t matter (SC) .7624. I relax and don’t think about it (SC) .7623. I realise I didn’t need to control it anyway (SC) .5920. I don’t feel disappointed because I knew it might happen (SC) .54

Correlation between each factor .28Percent of variance explained 29.80 14.00Range of item-total correlations .41-.61 .41-.56Cronbach’s Alpha .82 .73

The resultant factor analysis showed that the two factors were independent

(r= .28) and together accounted for 43.80% of the variance with Factor 1

accounting for 29.80% and Factor 2 accounting for 14.00%. Internal consistency

for each of the factors was assessed using Cronbach’s Alpha. Internal consistency

46


was high for Factor 1 (=.82) and for Factor 2 (=.73). Pearson correlation

coefficients for each item for Factor 1 ranged from .41 to .61 and for Factor 2

ranged from .41 to .56. The two factors were meaningful and reflected different

perceptions of control. Factor 1 consisted of 10 items, six primary control and

four secondary control items. It is interesting to note that all of the primary control

items loaded first on this factor, indicating a preference for primary control over

secondary control. Factor 2 consisted of five secondary control items. Effectively

the factor analysis suggests that there is a distinction in the secondary control

items, where some are similar to primary control and some are similar to

relinquished control. In examining the content of the items, it is evident that the

first factor reflects items where the problem is being positively addressed or

acknowledged in some way, even if to allow for temporary distraction. For

example, item 28 "I work hard to overcome it", item 26 "I learn the skills to

overcome it", item 9 "I do something vigorous to take my mind off it", and item 1

"I can see that something good will come of it". This description is less obvious

for item 3 "I remember you can't always get what you want" and item 8 "I

remember I am better off than many other people", but these items still indicate

that the problem is being acknowledged. Therefore, this factor has been termed

approach control. The second factor reflects items where the problem is being

avoided or disregarded. For example, item 25 “I ignore it by thinking about other

things”, item 24 "I relax and don't think about it" and item 20 "I don't feel

disappointed because I knew it might happen". Therefore, this factor has been

termed avoidant control.

4.2 Descriptive informationDescriptive information, including means, standard deviations and bi-

variate correlations for each of the variables of interest, were calculated for each

sample to inform the subsequent analyses. The variables included, total subjective

quality of life, the two variables of perceived control (approach control and

avoidant control) and the two personality variables (neuroticism and extroversion).

Table 3 displays the means, standard deviations and bi-variate correlations, for the

carer and comparison samples.

47


Table 3: Means (M), standard deviations (SD) and bi-variate correlations for the variables total subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the carer and the comparison samples.

Total SQOL

Appr Control

Avoid Control Neuro Extro

Carer sample (n = 127)Total SQOL -- .42b .33b -.50b .22a

Approach Control -- .42b -.26b .19a

Avoidant Control -- -.15 .12Neuroticism -- -.18a

Extroversion --M 68.14 58.11 32.44 5.79 5.84

SD 50.87 14.46 13.90 3.11 3.18Comparison sample (n = 114)

Total SQOL -- .50b .11 -.26b .23a

Approach Control -- .12 -.20a .18Avoidant Control -- .03 -.03Neuroticism -- -.13Extroversion --

M 76.58 65.33 36.00 3.34 7.39SD 25.91 12.34 13.33 2.74 3.12

a p < .05 (2-tailed), b p <.01 (2-tailed)

The mean total quality of life scores displayed in Table 3 are the product of

importance scores by satisfaction scores, expressed as a percentage of scale

maximum. These scores were used in the subsequent analyses, however, means

were also calculated for satisfaction scores only, to be used in comparison with

other life satisfaction data and the standard score range of 70-80%SM (Cummins,

2000). The satisfaction only mean for the carer sample was 71.3714.61%SM

and for the comparison sample was 80.689.98%SM. Approach control and

avoidant control scores are also expressed as a percentage of scale maximum in

Table 3. It can be seen that the comparison sample scored higher on total

subjective quality of life, approach control and avoidant control than the carer

sample. Extroversion and neuroticism scores can be compared with those from the

scale’s manual. However, these comparisons are difficult to make as the manual

provides separate scores for males and females. The manual reported the mean

extroversion score for females at 7.603.27 and males at 6.363.80 and the mean

neuroticism score for females at 5.903.14 and males at 4.953.44. The

neuroticism and extroversion scores for the carer and comparison samples were

compared, using z scores, with the scale norms for both males and females

separately. The only consistent finding for both male and female norms was that

the comparison sample scored significantly lower on neuroticism (p<.001). It

48


should be noted that the means reported for a sample of Australian students by

Francis, et al. (1998), are slightly higher for both neuroticism and extroversion

than those in the scale's manual.

The correlation matrix in Table 3 displays some interesting relationships

between the variables of interest and some notable differences between the two

samples in these relationships. In the carer sample, total subjective quality of life

correlated strongly with neuroticism, approach control and avoidant control, and

moderately with extroversion. In the comparison sample, total subjective quality

of life correlated strongly with approach control, moderately with neuroticism and

extroversion, and nonsignificantly with avoidant control. The two perceived

control variables correlated strongly with each other in the carer sample, but

nonsignificantly in the comparison sample. Approach control was moderately

correlated with neuroticism and weakly correlated with extroversion in the carer

sample. In the comparison sample approach control correlated weakly with

neuroticism and nonsignificantly with extroversion.

The data were screened for the subsequent multivariate analyses assessing

the differences between the samples and the relationships between the key

variables. There were no missing data and group sizes were comparable (carer

n=127, comparison n=114). The data for each dependent variable were screened

by group. The carer data showed avoidant control was positively skewed and had

five univariate outliers; total subjective quality of life had two univariate outliers.

The comparison data showed neuroticism was positively skewed and had four

univariate outliers; extroversion had two univariate outliers; approach control had

two univariate outliers; avoidant control had four univariate outliers; total

subjective quality of life had three univariate outliers. No multivariate outliers

were found using Mahalanobis distance. Univariate outliers were recoded as

before. Resultant data screening showed avoidant control was no longer

significantly skewed in the carer sample and neuroticism was now only marginally

skewed in the comparison sample. Hence, the recoded data were used for the

subsequent analyses as multivariate analysis of variance is reported to be

extremely sensitive to outliers (Tabachnick & Fidell, 1996). Examination of the

scatterplots revealed the data met the assumption of linearity. Examination of the

49


correlation matrix revealed that the assumption of multicollinearity and singularity

was met.

Initially a multivariate analysis of variance was performed to explore any

differences between the two groups, carer and comparison samples, on each of the

variables of interest: total subjective quality of life, approach control, avoidant

control, neuroticism and extroversion. Box’s M suggested the data had met the

assumption of homogeneity of variance-covariance matrices, F(15,224278)=2.34,

p=.002, which was not significant at the alpha level of .001 recommended for this

test (Coakes and Steed, 1999). The univariate tests for homogeneity of variance

for each of the dependant variables indicated that homogeneity of variance had not

been violated for the variables avoidant control, neuroticism and extroversion.

However, for the variables approach control and total subjective quality of life, the

Levene’s test of equality of variances was significant, F(1,239)=4.01, p=.046 and

F(1,239)=17.57, p=.000 respectively, indicating a more conservative alpha level

should be used in the interpretation of findings associated with these variables.

Pillai’s Trace multivariate test of significance revealed there was a

significant group difference on one or more of the dependent variables

F(1,5)=11.13, p=.000. The univariate tests for each of the dependent variables are

displayed in Table 4.

Table 4: Multivariate Analysis of Variance examining the differences between the carer and comparison samples for the variables: total subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion.

F(1,237) Sig. Eta Squared

Observed Power

Total SQOL 29.19 .000 .11 1.00Approach Control 12.00 .001 .05 .93Avoidant Control 2.25 .135 .01 .32Neuroticism 41.58 .000 .15 1.00Extroversion 14.40 .000 .06 .97

The univariate tests displayed in Table 4 revealed that there were

significant main effects on every variable, except avoidant control, even with a

more stringent criterion of .01 to account for the violation of assumptions.

Examination of the means showed that carers had significantly lower subjective

50


quality of life, approach control and extroversion, and significantly higher

neuroticism than the comparison group. Eta squared showed the strength of

association between the independent and dependent variables was moderate to

large and the power of the test to detect a true difference was high.

4.3 Aim Two A multivariate analysis of covariance was used to test the hypothesis, that

carers of people with mental illness will have lower subjective quality of life and

perceived control than people who do not care for someone with a disability, after

the effects of personality have been removed. The analysis was performed using

the carer sample and the comparison sample as the independent variable, group;

the dependent variables were total subjective quality of life, approach control and

avoidant control; the personality covariates were extroversion and neuroticism.

Further assumptions, required for the use of covariates in multivariate

analysis of variance, were tested. The covariates were deemed reliable. However,

the data did not meet the assumption of homogeneity of regression for total

subjective quality of life. More specifically, the relationship between neuroticism

and total subjective quality of life was significantly different between the two

samples. However, Maxwell and Delaney (1990) suggest that “the effects of

heterogeneity of regression when present will typically be small and in a

conservative direction” (p. 419). Hence, it was deemed acceptable to proceed

cautiously with the analysis. Box’s M also suggested the data had violated the

assumption of homogeneity of variance-covariance matrices, F(6,401078)=5.47,

p=.000. Furthermore, whilst Levene’s test of equality of variances was non-

significant for approach and avoidant control, it was significant for total subjective

quality of life, F(1,239)=8.31, p=.004, indicating caution should be taken with

interpretation of any significant findings.

Pillai’s Trace multivariate test of significance revealed that with effects of

neuroticism and extroversion controlled for, there were no significant group

differences on a linear combination of the dependent variables F(1,3)=1.91,

p=.128. Hence, no further interpretation of these findings was made.

51


Given that the negative impact of caregiving may be more evident on some

life domains than others, the possible differences between the two samples on

subjective quality of life were further investigated by using each of the seven

domains. Hence, a second multivariate analysis of covariance was used to

examine the differences between the two groups (carer or comparison) on each of

the seven subjective quality of life domains with the effects of personality

(extroversion and neuroticism) removed.

The data met the assumption of homogeneity of regression for every

domain except safety and emotional wellbeing. Given the conservative impact this

is likely to have, the proceeding analyses were, again, cautiously undertaken.

Box’s M suggested the data had violated the assumption of homogeneity of

variance-covariance matrices, F(28,194281)=4.23, p=.000. Furthermore, whilst

Levene’s test of equality of variances was non-significant for health, it was

significant for each of the remaining six domains, indicating further caution should

be taken with interpretation of any significant findings.

Pillai’s Trace multivariate test of significance revealed that with effects of

neuroticism and extroversion removed, there were significant differences between

the two groups on one or more of the dependent variables F(1,3)=2.22, p=.034.

Table 5 displays the results for the univariate tests for each of the dependent

variables.

Examination of the univariate tests, displayed in Table 5, revealed that

there was a significant main effect of group for the domains health, F(1,237)=4.52,

p=.035 and emotional well-being F(1,237)=6.58, p=.011. Examination of the

means showed that carers had significantly lower satisfaction with their health and

emotional well-being than the comparison group after the effects of personality

had been removed. Eta squared showed the strength of association between the

independent and dependent variables was small and the power of the test to detect

a true difference was moderate. Due caution in the acceptance of these differences

is noted due to the caveats previously stated.

52


Table 5: Multivariate analysis of covariance with group (carer or comparison) as the independent variable, the seven SQOL domains as the dependent variables, and neuroticism and extroversion as the covariates.

Carer Control F(1,237) Sig. Eta Squared

Observed Power

Material Well-being

M SD

67.5258.39

M SD

72.7137.87 2.89 .091 .01 .40

Health M SD

65.8784.87

M SD

77.1851.02 4.52 .035 .02 .56

Productivity M SD

67.3164.00

M SD

73.1841.97 .14 .713 .00 .07

Intimacy M SD

74.5160.86

M SD

83.3132.90 3.28 .072 .01 .44

Safety M SD

70.9269.00

M SD

79.2236.77 1.10 .295 .01 .18

Place in Community

M SD

64.2984.41

M SD

70.1448.23 .07 .796 .00 .06

Emotional Well-being

M SD

65.7655.44

M SD

78.8134.07 6.58 .011 .03 .72

It is interesting to note that each domain mean is lower for the carer sample

than the comparison sample, yet each domain standard deviation is higher for the

carer sample than the comparison sample. It should also be noted that the large

standard deviations are a function of the subjective quality of life measure being a

composite of importance scores by satisfaction scores. To examine the impact of

these large standard deviations, the same analysis was run using satisfaction scores

only. The results showed no substantial differences and the same trends were

evident in the data, indicating that the importance by satisfaction scores, despite

their large standard deviations, can be interpreted with confidence.

4.4 Aim ThreeA series of regression analyses were used to test the hypothesis that

perceived control will improve the prediction of subjective quality of life beyond

that afforded by personality, and that personality would predict perceived control.

The data have already been shown to meet most of the necessary assumptions for

testing, including outliers, multicollinearity and singularity, normality and

linearity. The sample sizes were adequate and additional assumptions of

homoscedasticity and independence of residuals were also examined and met.

53


To test the first part of this hypothesis, a sequential multiple regression was

used for each of the two samples, carer and comparison. The dependent variable

was total subjective quality of life and the independent variables were entered in

two steps, where the two personality variables (neuroticism and extroversion) were

entered in the first step and the two perceived control variables (approach control

and avoidant control) were entered in the second step. Tables 6 and 7 display the

results for each sample, carer and comparison respectively, including the

unstandardised regression coefficients (B), the standardised regression coefficients

(), squared semipartial correlations (sr2), and R, R2, and adjusted R2 after entry of

all independent variables.

Table 6: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the carer sample

B t sr2

Neuroticism -2.55 -.48 -6.07c .23Extroversion .71 .14 1.73 .02Neuroticism -2.13 -.40 -5.26c .18Extroversion .45 .09 1.17 .01Approach Control 2.58 .24 2.91b .07Avoidant Control 1.54 .16 1.95a .03

R2 Adj. R2 R .37 .35 .61c

ap<.05, bp<.01, cp<.001

The results for the carer sample showed after Step 2 with all of the

variables in the equation 37% of the variance in carers subjective quality of life

was explained, which was highly significant, R=.61, F(4,122)=17.73, p=.000.

After Step 1, with neuroticism and extroversion in the equation 27% of the

variance in total subjective quality of life was explained, which was significant,

R=.52, Finc(2,124)=22.46, p=.000. Examination of the regression coefficients at

Step 1 indicated that only neuroticism significantly predicted total subjective

quality of life. At Step 2, approach and avoidant control added to the prediction of

subjective quality of life by an additional 10% of the variance, which was a

significant increase Finc(2,122)=9.81, p=.000. Examination of the regression

coefficients at Step 2 indicated that neuroticism, approach control and avoidant

control were significant predictors of total subjective quality of life when all

variables were entered into the equation together, extroversion made no significant

54


contribution to the equation. The regression coefficients also showed that

neuroticism was the strongest predictor followed by approach control and that

avoidant control only just reached significance; the value for neuroticism was only

marginally reduced from Step 1 to Step 2. The results demonstrate that even when

the variance in subjective quality of life attributed to neuroticism is accounted for,

approach control and avoidant control still make significant contributions.

Table 7: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the comparison sample.

B t sr2

Neuroticism -.93 -.23 -2.57a .06Extroversion .69 .20 2.18a .04Neuroticism -.62 -.15 -1.88 .03Extroversion .46 .13 1.61 .02Approach Control 3.67 .44 5.21c .20Avoidant Control .49 .07 .86 .01

R2 Adj. R2 R .30 .27 .55c

ap<.05, bp<.01, cp<.001

The results for the comparison sample showed after Step 2 with all of the

variables in the equation 30% of the variance in subjective quality of life was

explained, which was highly significant, R=.55, F(4,109)=11.50, p=.000. After

Step 1, with neuroticism and extroversion in the equation 11% of the variance in

total subjective quality of life was explained, which was significant, R=.32,

Finc(2,111)=6.52, p=.002. Examination of the regression coefficients at Step 1

indicated that both neuroticism and extroversion significantly predicted total

subjective quality of life. At Step 2, approach and avoidant control added to the

prediction of subjective quality of life by an additional 19% of the variance, which

was a significant increase Finc(2,109)=14.85, p=.000. Examination of the

regression coefficients at Step 2 indicated that only approach control was a

significant predictor of total subjective quality of life when all variables were

entered into the equation together, neuroticism and extroversion no longer made a

significant contribution to the equation and avoidant control did not add a

significant contribution. The results demonstrate that even when the variance in

subjective quality of life attributed to neuroticism and extroversion is accounted

for, approach control can still make a significant contribution.

55


To test the second part of the hypothesis, that personality would predict

perceived control, two standard multiple regressions were performed for each

sample testing the prediction of the personality variables (neuroticism and

extroversion) on approach and avoidant control separately. Hence, Table 8

displays the results for the carer sample and Table 9 displays the results for the

comparison sample, including the unstandardised regression coefficients (B), the

standardised regression coefficients (), squared semipartial correlations (sr2), and

R, R2, and adjusted R2.

Table 8: Regression of neuroticism and extroversion on approach control and avoidant control for the carer sample.

B t sr2

Approach ControlNeuroticism -.12 -.24 -2.74b .06Extroversion .07 .15 1.66 .02

R2 Adj. R2 R .09 .08 .30b

Avoidant ControlNeuroticism -.07 -.14 -1.54 .02Extroversion .05 .09 1.03 .01

R2 Adj. R2 R .03 .02 .18

ap<.05, bp<.01, cp<.001

The results of the first regression equation for the carer sample showed that

together neuroticism and extroversion accounted for 9% of the variance in

approach control, which was significant R=.30, F(2,124)=6.11, p=.003. However,

examination of the regression coefficients indicated that neuroticism was the only

significant predictor, explaining 6% of the variance in approach control. The

results of the second regression equation for the carer sample showed that neither

neuroticism nor extroversion significantly predicted avoidant control, R=.18,

F(2,124)=2.05, p=.133.

Table 9: Regression of neuroticism and extroversion on approach control and avoidant control for the comparison sample.

56


B t sr2

Approach ControlNeuroticism -.09 -.18 -1.97a .03Extroversion .06 .15 1.67 .02

R2 Adj. R2 R .06 .05 .25a

Avoidant ControlNeuroticism .02 .03 .31 .00Extroversion -.01 -.03 -.31 .00

R2 Adj. R2 R .00 -.02 .04

ap<.05, bp<.01, cp<.001

The results of the first regression equation for the comparison sample

showed that together neuroticism and extroversion accounted for 6% of the

variance in approach control, which was significant R=.25, F(2,109)=3.81, p=.025.

However, examination of the regression coefficients indicated that neuroticism

was the only significant predictor, just reaching significance and explaining 3% of

the variance in approach control. The results of the second regression equation for

the comparison sample showed that neither neuroticism nor extroversion

significantly predicted avoidant control, R=.04, F(2,109)=.11, p=.897.

57

CHAPTER 5 - Study One: Discussion

CHAPTER 5

5 STUDY ONE: DISCUSSION

5.1 Aim OneThe result of the exploratory factor analysis performed on the perceived

control scale promotes a reconceptualisation of perceived control and the

constructs of primary, secondary and relinquished control. The resultant two-

factor structure (see Table 2) included one factor termed approach control that

reflected items that addressed the problem in some way, and one factor termed

avoidant control that reflected items that avoided the problem. This factor

structure did not differentiate between primary, secondary and relinquished control

items. Rather, the approach control factor included both primary and secondary

control items, and the avoidant control factor included secondary control items

and, before the more stringent cut off criterion was used, relinquished control

items. Hence, the distinction between primary and secondary control, evident in

the original version of the scale developed by Heeps (2000) appears to have been

artificially produced by the context in which the items were embedded. In the

original scale, all the secondary control items were preceded with the one

statement “When something bad happens”, whilst the primary control items were

preceded with varying statements. When this artificial distinction was eliminated,

by modifying the scale so that all the items were preceded with the same statement

“When something bad happens”, the primary and secondary control distinction

was no longer evident in the factor structure.

The lack of empirical distinction between primary and secondary control

has two important implications for the literature on primary and secondary control.

Firstly, the finding supports the notion that the two processes are closely

intertwined (Rothbaum et al., 1982); so intertwined indeed, that a distinction could

not be found statistically in the factor structure. Hence, the notion that primary

control has functional primacy over secondary control (Heckhausen & Schulz,

1995) is challenged. A clear distinction in the factor structure would be needed to

support such a notion of primacy. Similarly, the notion that cognitions (ie.

secondary control) as well as behaviour (ie. primary control) play an important

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role in perceived control, and that theories that do not acknowledge this are

inadequate (Rothbaum et al., 1982), is supported. Secondly, the finding questions

the theoretical relevance of these constructs when conceptualised as coping

strategies. Imposing this theoretical distinction on various coping strategies, as has

been done by many researchers (eg. Burton & Sistler, 1996; Thompson et al.,

1996; Weisz et al., 1994), is problematic if the distinction cannot be empirically

supported. Moreover, extreme caution must be taken not to treat all types of

secondary control in the same manner. It is clear that some types of secondary

control, such as downward social comparison and positive reinterpretation, along

with primary control, are used to acknowledge the problem and address it by

making changes in the way the problem is perceived, and some types of secondary

control, such as cognitive avoidance and self-protective responses, are used to

avoid the problem.

Overall, when something bad happens, the current data set indicates that

approach and avoidant control appear to be more relevant constructs than primary

and secondary control. That is, when an individual is faced with a difficult

situation, the key issue appears to be whether they believe they can address the

problem or avoid it, not whether they believe they can make changes to their

external environment or within their own internal environment to deal with the

problem. Further investigation of the coping literature has revealed both

theoretical and empirical support for this approach/avoidant distinction (Ebata &

Moos, 1991; Roth & Cohen, 1986; Herman-Stahl, Stemmler & Peterson, 1995). A

more detailed account of this literature follows in the introduction to Study Two.

Hence, the approach and avoidant control factor structure appears to be a valid and

reliable distinction between various strategies for maintaining perceived control,

for use in the subsequent analyses.

5.2 Aim Two The results did not provide clear support for the hypothesis that carers of

people with mental illness will have lower subjective quality of life and perceived

control than people who do not care for someone with a disability, after the effects

of personality have been removed. However, the findings should be interpreted

59


with caution given that the data violated some of the assumptions for testing and

there is some doubt over the use of the personality variables as covariates, as will

be discussed later. Despite this, subsequent analysis on each of the seven domains

of subjective quality of life, revealed that carers had significantly lower

satisfaction with their health and emotional well-being than the comparison sample

(see Table 5). This finding provided some evidence of lowered subjective quality

of life in the carer sample, even after the effects of personality had been removed.

An examination of the differences between the two samples without the

removal of the effects of personality, however, showed that carers had

significantly lower total subjective quality of life and approach control than the

comparison sample, as well as significantly lower extroversion and significantly

higher neuroticism (see Table 4). Not only did the two samples differ on their

scores for the personality variables. But, a difference was found, when testing the

assumptions for the covariate analysis, in the strength of the relationship between

neuroticism and subjective quality of life between the two groups. The regression

of neuroticism onto subjective quality of life was stronger in the carer sample than

the comparison sample. These factors together may have acted to mask

differences between the two samples when personality was used as a covariate. A

point that will be reiterated.

These findings of lowered subjective quality of life in the carer sample

show some consistencies with the literature. The mean total subjective quality of

life (satisfaction only) score for the carer sample was 71.37%SM. Whilst this

value is not as low as the 615.9%SM found for carers of people with a range of

severe disabilities (Cummins, 2001), it is still notably low, and borders on the

range in which life satisfaction is proposed to be no longer held under homeostatic

control (Cummins, 2000). Alternatively, the mean total subjective quality of life

(satisfaction only) score for the comparison sample was 80.68%SM which is just

within the normative range of 70-80%SM identified in the scale's manual and by

Cummins' (1995, 1998, 2000) extensive research. Furthermore, the data provided

support for the notion that carers' homeostatic control of subjective quality of life

was being challenged (Cummins, 2000). There was a trend in the data where the

means for the subjective quality of life domains were consistently found to be

60


lower in the carer sample than the comparison sample, and also the standard

deviations were consistently greater. This demonstrates the increase in variance

that is reported to be an indicator of subjective quality of life being held under

homeostatic control. As samples approach 70%SM, increasing numbers of

individual values represent homeostatic failure, that is below 70%SM, hence

increased variance is evident in these samples.

Overall, there is support for the conclusion that the caregiving role has a

negative impact on carers’ subjective quality of life. The finding that the impact of

the caregiving role is most prominent on health and emotional well-being, even

though these differences were marginally significant, is consistent with research

that has concluded caring for someone with a mental illness has a substantial

negative emotional impact (Sveinbjarnardottir & Dierckx de Casterle, 1997;

Lefley, 1987b) and that carers experience significant levels of distress when

measured by the General Health Questionnaire (Vaddadi, et al., 1997;

Barrowclough & Parle, 1997). Clearly, health and emotional well-being are two

important areas that must be addressed when trying to improve the subjective

quality of life of carers of people with mental illness.

Some interesting conclusions about the impact of caregiving can also be

drawn from the findings for the two variables of perceived control (approach and

avoidant control).

First, the inability of the analysis to detect a difference between the

samples in avoidant control, either with or without the effects of personality

removed (see Tables 5 and 4 respectively), suggests that carers are comparable to

the comparison sample in their use of this form of control. Avoidant control is a

complex variable to understand. It is positively correlated with subjective quality

of life, indicating that it does have a positive function and may be assumed to be

lower in samples with low subjective quality of life. However, it might be

expected that the immoderate use of avoidant control when confronted with

difficult or problematic situations may have a negative impact on subjective

quality of life, as the problem is not being addressed in any way. Hence, there

may be an optimal level of avoidant control that is strongly dependent upon given

61


circumstances. Moreover, the finding that carers have similar levels of avoidant

control as the comparison sample does not necessarily mean that they have optimal

use of avoidant control for the circumstances of caregiving.

Second, the analysis was also unable to detect a difference between the two

samples on approach control, with the variance attributed to personality removed

(see Table 5). A difference that was evident before the variance attributed to

personality was removed (see Table 4). The mere fact that the carers sampled had

contacted an organisation seeking support and assistance, suggests the use of

approach control over and above that of carers who have not had contact with such

organisations. Hence, a difference in approach control, with the variance

attributed to personality removed, may have been evident if a sample of carers

who had not had contact with such supportive organisations was used. However, it

is more likely that the difference between the two samples in approach control was

masked by the problems associated with using personality as a covariate and that

the experience of caregiving does limit carers' approach control.

It could be concluded that the differences in personality suggest that the

experience of caring for someone with a mental illness may increase carers’

emotional instability (neuroticism) and decrease their sociability (extroversion).

The validity of this conclusion is supported by the notion that 30% of personality

is environmentally based or learned (Tellegen et al., 1988). Whilst, this learned

component is generally considered to occur in childhood, it does indicate a more

variable aspect of adult personality as compared to the genetic component. It thus

seems likely that the experience of caregiving may have a negative effect on

carers' personality, increasing their emotional instability and limiting their

sociability. This conclusion is also consistent with the literature that highlights

caregiver burden and distress (eg. Fadden, et al., 1987; Maurin & Boyd, 1990).

Such a conclusion, however, is limited by a notable difference between the

mean score for neuroticism reported for the comparison sample in this study, and

that reported in the scale’s manual (Eysenck & Eysenck, 1991) and in another

Australian sample (Francis, et al., 1998). The comparison sample scored

significantly lower on the neuroticism scale. This, along with their subjective

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quality of life score of 80.68%SM, suggests that the comparison sample may not

be an accurate ‘normal population’. It is possible that the comparison sample,

which consisted of individuals who have previously volunteered to participate in

Deakin University student research, may be more emotionally stable than the

general population. Hence, the difference between the two samples may be due to

this, and not the impact of the caregiving role. Yet, given that comparisons have

not been made with a sample of Australian adults, the conclusion that caregiving

impacts on carers' personality has some merit. This is true especially when the

difference between the two samples in the relationship between neuroticism and

subjective quality of life is also considered.

These findings again highlight that the use of the personality variables as

covariates in this analysis was problematic. Not only did the personality variables

violate the assumptions for testing and differ from the scale's norms. But, if

personality is susceptible to environmentally induced change, then removing the

variance in subjective quality of life and perceived control attributed to personality

may also be removing valid variance in subjective quality of life attributed to the

differential life experience of each sample.

In summary, the results showed that carers' experienced lower subjective

quality of life, approach control and extroversion, and greater neuroticism, than the

comparison sample. These results are consistent with the literature, regardless of

the doubt over the comparison sample's representativeness of the general

population, and highlight the negative impact of caring for someone with a mental

illness.

5.3 Aim ThreeThe regression analyses enabled the examination of the relationships

between the relevant concepts, personality, perceived control and subjective

quality of life. The results of the regressions for both the carer sample (see Tables

6 and 8) and comparison sample (See Tables 7 and 9) provided support for the

hypothesis that perceived control will improve the prediction of subjective quality

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of life beyond that afforded by personality, and that personality will predict

perceived control.

In the carer sample, the regression analysis showed that with all variables

in the equation, neuroticism, approach control and avoidant control significantly

predicted subjective quality of life, whilst extroversion made no significant

contribution to the equation. This equation accounted for 37% of the variance in

carers' subjective quality of life. Additionally, neuroticism was found to

significantly predict approach control, and approach and avoidant control

correlated highly with each other. By incorporating these significant relationships

between the variables into a model (see Figure 3), a better understanding of the

carer data is provided.

Figure 3: Model of the significant relationships among the variables neuroticism, approach control, avoidant control and total subjective quality of life (SQOL) in the carer sample, including standardised regression coefficients and correlations.

This model demonstrates that, in the carer sample, neuroticism predicts

subjective quality of life, both directly and indirectly via approach control. If a

latent construct for perceived control is introduced to describe the relationship

between approach and avoidant control (see Figure 4), the model becomes similar

to that initially proposed (see Figure 2). This model differs from the original

model in that the variables approach and avoidant control have replaced the

variables primary, secondary and relinquished control, and the variable

extroversion has been excluded as it failed to produce any significant relationships,

making the latent construct of personality unnecessary.

64

.42 .16

.24

Neuroticism

Approach Control

Avoidant Control

Total SQOL

-.24 -.40


Figure 4: Model of the significant relationships among the variables neuroticism, approach control, avoidant control and total subjective quality of life (SQOL) in the carer sample incorporating a latent construct for perceived control.

In the comparison sample, the regression analysis showed that with all

variables in the equation, only approach control significantly predicted subjective

quality of life, whilst neuroticism, extroversion and avoidant control made no

significant contributions to the equation. This equation accounted for 30% of the

variance in the comparison sample's subjective quality of life. Additionally,

neuroticism significantly predicted approach control. A model of these significant

relationships is displayed in Figure 5.

Figure 5: Model of the significant relationships among the variables neuroticism, approach control and total subjective quality of life (SQOL) in the comparison sample, including standardised regression coefficients.

It is also interesting to compare these findings with the literature. The

correlations reported in the empirical studies reviewed previously ranged from -.31

to -.57 between measures of subjective well-being and neuroticism, and from .17

to .49 for extroversion (Costa & McCrae, 1980; Francis, 1999; Francis, et al.,

65

Neuroticism

Approach Control

Avoidant Control

Total SQOLPerceived Control

Neuroticism

Approach Control

Total SQOL

-.18

.44


1998; Heaven, 1989; Lu & Shih, 1997; Morrison, 1997). The bi-variate

correlations in the carer sample were -.50 for subjective quality of life and

neuroticism, and .22 for subjective quality of life and extroversion. The bi-variate

correlations in the comparison sample were -.26 for subjective quality of life and

neuroticism, and .23 for subjective quality of life and extroversion. These

correlations are all within the ranges reported in the literature. However, the

differences in the relationships between neuroticism and subjective quality of life

reported for the two samples in this study, highlight the importance of considering

the nature of the sample when reviewing these relationships in the literature. This

is because the nature of the sample may have a significant impact on the results.

Overall, it is apparent that the relationships between the variables

personality, perceived control and subjective quality of life, differ between the two

samples. This difference suggests that when homeostasis is challenged, as in the

carer sample, the maintenance of subjective quality of life becomes more

complicated. This is clearly demonstrated by comparing the complexity of the

models developed for each sample. Still, both samples provide support for the

hypothesis that perceived control will improve the prediction of subjective quality

of life beyond that afforded by personality, and that personality will predict

perceived control. However, it is important to note that this applies only to the

personality variable, neuroticism, and the perceived control variable, approach

control.

5.4 Summary Some important conclusions can be drawn from the differences between

the two samples and the relationships between the key variables. It is apparent that

higher levels of neuroticism have a substantial negative impact on subjective

quality of life. In the carer sample, where the neuroticism scores were

significantly higher than those of the comparison sample, neuroticism had a strong

direct negative impact on subjective quality of life as well as an indirect impact

through approach control. In the comparison sample, neuroticism had only an

indirect impact on subjective quality of life, through approach control.

Considering that the comparison sample had unusually low neuroticism scores

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when compared to the scale's norms, it is possible that the findings for the carer

sample, whose neuroticism scores resembled those in the scales' manual, may also

apply to a broader range of the population. Alternatively, the well documented

burden and distress of caregiving may have resulted in a change in carers'

personality. More specifically, the circumstances of caregiving have resulted in

increased emotional instability or negative affectivity, which has impacted

negatively on subjective quality of life both directly, and indirectly through

reducing their approach control.

Another effect of caregiving appears to be the use of both approach control

and avoidant control to maintain subjective quality of life. In the carer sample,

which had significantly lower approach control than the comparison sample,

approach and avoidant control correlated strongly with each other and both made

an additional contribution to the variance in subjective quality of life after the

effects of personality had been removed. In the comparison sample only approach

control made an additional contribution to the variance in subjective quality of life

additional to personality. The ability of approach and avoidant control to predict

subjective quality of life in the carer sample demonstrates the importance of both

of these constructs when considering the maintenance of subjective quality of life.

Overall, there is preliminary support for the model of personality,

perceived control and subjective quality of life depicted in Figure 2. This indicates

that personality and perceived control may be important processes to consider

when trying to understand how subjective quality of life is maintained, or held

under homeostatic control. However, given the differences between the carer and

comparison samples, this model may be dependent upon characteristics of the

sample and the notion that when homeostasis is being challenged the maintenance

of subjective quality of life becomes more complicated. Therefore, the model

needs to be substantiated by testing it on other populations.

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CHAPTER 6 - Study Two: Introduction

CHAPTER 6

6 INTRODUCTION TO STUDY TWO

The focus of Study Two is to provide further support for the model of

relationships between personality, perceived control and subjective quality of life,

whereby personality predicts subjective quality of life both directly and indirectly

via perceived control (See Figure 2). The findings from Study One prompted a

reconceptualisation of perceived control as being reflected by dimensions of

approach and avoidant control, rather than primary, secondary and relinquished

control. Hence, Study Two begins with a review of the literature on approach and

avoidant control, outlining the theoretical and empirical support for these

dimensions and their measurement. This is followed by a brief review of the

literature on the relationships between personality, approach and avoidant control,

and subjective quality of life. The population selected to be the focus of Study

Two is secondary school teachers. Teachers make an interesting population to

study as there are a number of stressors reported to be associated with teaching,

which may negatively impact on their subjective quality of life and perceived

control. Hence, the stress and coping literature on teachers is also reviewed. This

introductory section of Study Two concludes with a brief statement concerning the

focus of the current research.

As in Study One, the aims and hypotheses highlight the three parts of the

study: 1) an investigation of the factor structure of perceived control, 2) an

investigation of the differences between a sample of secondary school teachers and

a sample from the general population, and 3) an examination of the relationships

between personality, perceived control and subjective quality of life. The method

section provides information about the characteristics of the two samples, the

recruitment procedures and the measurement tools used. The results and

discussion sections are also divided into the three parts reflected in the aims and

hypotheses. These results are discussed in comparison with the literature and the

findings of Study One.

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6.1 APPROACH AND AVOIDANT DIMENSIONS OF PERCEIVED CONTROL

The results of the exploratory factor analysis on the perceived control scale

in Study One introduced the notion of two dimensions of control which were

termed approach and avoidant. The approach control factor reflected items where

the problem was being addressed or acknowledged in some way. Alternatively,

the avoidant control factor reflected items where the problem was being avoided or

disregarded altogether. This finding prompted a re-evaluation of the literature. As

previously outlined the concepts of control and coping are relatively similar when

considered in the context of difficult, problematic or stressful situations. However,

it is in the stress and coping literature that the terms approach and avoidance are

mostly found. This literature demonstrates further theoretical and empirical

support for the approach and avoidant dimensions of perceived control found in

Study One.

6.1.1 Theoretical support for approach and avoidant control Some of the theoretical antecedents of coping concepts have been briefly

outlined by Moos and Schaefer (1993), who used them to develop a model of

stress and coping. These antecedent theories included evolutionary theory and

behavioural adaptation, psychoanalytic concepts and personal growth,

developmental life cycle theories and research on coping with life crises and

transitions. Yet, it is primarily the behavioural adaptation and psychoanalytic

concepts that provide an informative basis for understanding approach and

avoidant control.

Theories of behavioural adaptation traditionally posited that goal directed

behavioural problem-solving activities enhance individual and species survival

(Moos & Schaefer, 1993). This notion is fundamental to approach control. In

Study One, items reflecting goal directed problem solving activities, such as "I

work hard to overcome it" and "I look for different ways to achieve the goal"

loaded most strongly on the approach control factor. Yet, the more recent

development of cognitive-behavioural theory has highlighted the role of cognition

in effective adaptation (Moos & Schaefer, 1993). Cognitive-behavioural theory

merges behaviour theory with cognitive theory. Cognitive theory states that

69


dysfunctional or negative thinking about the self, experiential events, and the

future, accounts for disordered affect and behaviour, and that realistic or positive

thinking can promote positive change in affect and behaviour (Beck, 1997). This

cognitive element of coping is reflected in the items that loaded least strongly on

the approach control factor, such as "I remember I am better off than many other

people" and "I can see that something good will come of it". Hence, cognitive-

behavioural theory provides a sound basis for approach control.

Psychoanalytic concepts also provide understanding to the cognitive

element of approach and avoidant control. Freud introduced the notion of ego

processes that serve to resolve conflict between an individual's impulses and the

constraints of external reality (Moos & Schaefer, 1993). These ego processes are

primarily self-protective cognitive defence mechanisms (though they may be

expressed behaviourally) that can be likened to both approach and avoidant

control. Vaillant, Bond and Vaillant (1986) have developed a hierarchy of three

levels of ego defences. At the bottom of the hierarchy are immature defences,

such as projection and unrealistic fantasy. Next are neurotic defences, such as

repression and reaction formation. At the top of the hierarchy are mature defences,

such as suppression and realistic anticipation. An examination of the approach

control items in the factor analysis performed in Study One shows that these items

resemble mature defences. For example, "I do something vigorous to take my

mind off it" may be a form of suppression and "I remember you can't always get

what you want" a form of realistic anticipation. An examination of the avoidant

control items in the factor analysis shows that these items may resemble immature

and neurotic defences. For example, "I tell myself it doesn't matter" can be

likened to unrealistic fantasy and "I ignore it by thinking about other things" may

resemble repression. Hence, psychoanalytic theory also informs the approach and

avoidant dimensions of control.

These cognitive-behavioural and psychoanalytic theories demonstrate that

approach and avoidant control is a complex mix of goal directed behavioural

problem-solving activities, cognitive appraisals of the self, events and the future,

and a range of defence strategies. Yet, whilst these theories highlight important

differences in coping, clear theoretical support for the division of coping strategies

70


into approach and avoidant dimensions has not been provided. It is apparent that

these dimensions have been established more from an apparent coherence in the

literature than from any true theoretical basis. Basically, the approach and

avoidant dimensions represent an attractive division of coping with stress into two

basic orientations, either toward or away from threat (Roth & Cohen, 1986). This

can be likened to the well-known fight or flight response to anxiety provoking

situations and appears to represent a basic human instinct. However, support for

the approach and avoidant division of control is grounded more in empirical

research than theory.

6.1.2 Empirical support for approach and avoidant controlMany researchers have employed exploratory factor analysis to explore the

structure of coping strategies without dictating any theoretical distinction. A

number of researchers have conducted an exploratory factor analysis on the 12

subscales of the COPE inventory developed by Carver, Scheier and Weintraub

(1989). Carver et al. (1989) and Finset and Andersson (2000) conducted the

analysis on a sample of undergraduate students; Phelps and Jarvis (1994)

conducted the analysis on a community sample of adolescents. Each of these

studies found four similar, although not always identical, factors. These factors

reflected: 1) behavioural coping subscales such as active coping and planning, 2)

cognitive coping subscales such as acceptance and positive reinterpretation, 3)

socio-emotional coping subscales such as seeking social support and focus on and

venting of emotions, and 4) avoidant coping subscales such as denial and

behavioural disengagement. The first three factors are forms of approach control

with the last clearly being avoidant control.

The notion that the first three factors are forms of approach control was

supported by Finset and Andersson (2000) who found, in a sample of people with

acquired brain injury, the first three factors loaded together on one higher level

factor that reflected approach control. Similarly, a two factor structure has been

supported by Herman-Stahl, Stemmler and Petersen (1995) who conducted an

exploratory factor analysis on 18 different coping strategies in a community

sample of adolescents and found two factors that reflected approach and avoidant

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control. Exploratory and confirmatory factor analyses by different authors on

these same coping strategies in a group of adolescents found three factors which

resembled cognitive approach coping, behavioural approach coping and avoidance

coping (Gomez & Gomez, submitted for publication; cited in Gomez, Holmberg,

Bounds, Fullarton & Gomez, 1999).

In summary, there has been some exploratory factor analytic support for

the approach and avoidant conceptualisation of control. Yet, none of these studies

have demonstrated the division in a sample of adults.

Confirmatory factor analysis has also been used to test the approach and

avoidant dimensions of coping. This procedure tests the goodness of fit of

theoretically constructed dimensions. A detailed study on children's coping by

Ayers, Sandler, West and Roosa (1996), used this technique to compare the

goodness of fit of three different models of coping. They used the same set of 10

coping strategies to reflect three different models of coping, a problem-focused

and emotion-focused model (Lazarus and Folkman, 1984), an approach and

avoidant model (Billings and Moos, 1981) and a four-factor model developed by

the authors themselves.

The problem-focused and emotion-focused model tested by Ayers et al.

(1996) involved dividing the strategies into two groups, those that focus on

managing the problem itself (problem-focused) and those that focus on managing

the emotions associated with the problem (emotion-focused). Goodness of fit

indices showed that this model did not adequately fit the data. The likely problem

with this model is that it considers all emotion-focused coping strategies to be the

same. In fact, it is apparent that there is an important distinction between two

different types of emotion-focused strategies, those that are used to address the

problem and those that are used to avoid it. This is similar to the findings in Study

One where the exploratory factor analysis divided secondary control strategies into

two groups.

The approach and avoidant model tested by Ayers et al. (1996) also

involved dividing the strategies into two groups, those that reflect cognitive or

72


behavioural attempts to understand or resolve the problem (approach) and

cognitive or behavioural attempts to avoid the problem (avoidant). Goodness of fit

indices showed that this model also did not adequately fit the data. One reason

may have been the inappropriate classification of avoidant strategies. Whilst

cognitive avoidance and avoidant actions are clearly avoidant strategies,

distraction strategies such as distracting actions and physical release of emotions

are not. These later strategies may provide temporary relief from the problem

before it is addressed; they do not necessarily mean that the problem will be

avoided in the long term. This is supported by the finding in Study One that the

item "I do something vigorous to take my mind off it" loaded on the approach

control factor. However, it is important to note that Billings and Moos (1981) do

not make this distinction in their construction of approach and avoidant coping.

Finally, the four factor model of coping developed and tested by Ayers et

al. (2000) consisted of active coping strategies, distraction strategies, support

seeking strategies and avoidance strategies. The data adequately fit the model.

This model is attractive. It clearly identifies avoidant coping strategies as only

those that totally avoid the problem and it includes both cognitive and behavioural

attempts to deal directly with the problem in the active coping factor. These two

aspects are consistent with the findings in Study One. Hence, Ayers et al. (2001)

do provide some confirmatory factor analytic support for the approach and

avoidant dimensions, but they found that approach control fits the data better when

divided into subcategories.

Confirmatory factor analysis has also been used by Anshel, Williams and

Williams (2000) to test a different four-factor model of coping that combines the

emotion-focused and problem-focused model with the approach and avoidant

coping model. These authors divided coping strategies into approach-emotion,

approach-problem, avoidant-emotion and avoidant-problem and tested the model

on a sample of athletes from the USA and Australia who were coping with acute

stress in competitive sport. The results showed only moderate goodness of fit

indices which did not provide clear support for the model, either in the combined

sample or when the two samples were treated separately. Yet, the low correlations

between the four dimensions do indicate the independence of these dimensions.

73


The inability of the analysis to confirm the model may be a result of the notion that

when faced with difficult situations, the key issue appears to be whether the

individual can address the problem or avoid it, and not whether they use emotion-

focused or problem-focused methods to do this.

Lastly, Sorlie and Sexton (2001) used a sample of adult surgical patients to

conduct a confirmatory factor analysis on the Ways of Coping Questionnaire,

developed and refined by Folkman and Lazarus (1985). The confirmatory factor

analysis showed adequate goodness of fit for two factors, one active coping factor

consisting of goal oriented coping and seeking support and one passive coping

factor consisting of wishful thinking, avoidance and thinking it over. These two

factors can be likened to approach and avoidant control.

Overall, there appears to be adequate exploratory and confirmatory factor

analytic research to support the approach and avoidant dimensions of control or

coping. However, there is some suggestion, both theoretically and empirically,

that approach control may be more meaningful if divided into subcategories. The

literature providing empirical support for approach and avoidant control also gives

examples of how these dimensions are commonly measured.

6.1.3 The measurement of approach and avoidant controlTypically, the measurement of approach and avoidant dimensions of

coping is done by creating these distinctions in general coping scales that have

been designed to measure the entire spectrum of coping responses such as the

COPE inventory (Carver et al. (1989). Alternatively, some researchers select

specific scales from broader coping inventories to reflect the dimensions. For

example, Gomez, (1997) selected the 'focus on solving the problem' factor and the

'ignore the problem' factor from the Adolescent Coping Scale (Frydenberg &

Lewis, 1993) to reflect approach and avoidant coping respectively. There appears

to be few coping scales that have been purposefully constructed to reflect the

approach and avoidant dimensions of adult coping, which is what makes the

Coping Responses Inventory (Moos, 1993) appealing.

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Moos and colleagues constructed the Coping Responses Inventory by

giving detailed consideration of how people cope with a broad range of life crises

and transitions, and by classifying these into theoretically derived categories or

coping dimensions (Moos, 1993). A classification system was established, which

considered the focus of the coping strategy as approach or avoidant, and the

method of the coping strategy as cognitive or behavioural. Hence, coping

strategies could have either an approach focus using cognitive or behavioural

methods or an avoidant focus using either cognitive or behavioural methods. The

authors then undertook a process of refinement that used both conceptual and

empirical criteria.

The resultant 48-item Coping Responses Inventory consists of eight

subscales. Approach coping consists of two cognitive scales, logical analysis and

positive reappraisal, and two behavioural scales, problem solving and seeking

guidance/support. Avoidant coping consists of the cognitive scales, cognitive

avoidance and acceptance or resignation, and the behavioural scales, seeking

alternative rewards and emotional discharge. Each of the eight subscales showed

sound internal reliability with alpha coefficients ranging from .58 to .71. Whilst

internal reliability has not been shown for the approach and avoidant dimensions,

intercorrelations among the subscales show that the approach scales and the

avoidant scales do cluster together, with the exception of one subscale (seeking

alternative rewards) which appears to correlate more strongly with the approach

scales. It is likely that seeking alternative rewards is a form of approach coping as

it acknowledges that there is a problem and seeks to deal with the negative

consequences of that problem by balancing it with other positive experiences.

Unfortunately, the items and subscales of the Coping Responses Inventory have

not been subject to factor analysis and compelling statistical confirmation of the

approach and avoidant distinction has not been provided. Yet, the theoretical basis

is attractive. The approach/avoidant and cognitive/behavioural dimensions

represent basic orientations either toward or away from threat when in stressful

situations, and encompass cognitive-behavioural theory that recognises the role of

behaviours and cognitions in adaptive functioning.

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6.1.4 ConclusionIn conclusion, there is some theoretical and empirical support for the

dimensions of approach and avoidant control. This is largely provided by

exploratory and confirmatory factor analytic research and within this literature

there is some suggestion that approach control may be better conceptualised if

divided into subcategories. There is also a clear need to further investigate these

concepts in adult samples. Further support for the approach and avoidant

dimensions of control can be gained by examining how these dimensions relate to

concepts of adjustment and well-being.

6.2 PERSONALITY, APPROACH AND AVOIDANT CONTROL AND SUBJECTIVE QUALITY OF LIFE

6.2.1 The literature on approach and avoidant control and subjective quality of life Approach and avoidant coping strategies, like primary and secondary

control processes, function to maintain a perception of control. Therefore, the

theory and evidence outlined in the introduction to Study One, which suggests that

the relationship between perceived control and subjective quality of life is likely to

be significant, also applies to approach and avoidant control. Theoretically,

perceived control is necessary for optimal adaptation (Rothbaum, et al., 1982),

successful development (Heckhausen & Schulz, 1995) and to feel confident that a

situation will not become so aversive it cannot be endured (Thompson, 1981).

These are all concepts that can be likened to subjective quality of life.

Furthermore, empirical research has shown that perceived control has been found

to correlate with life satisfaction (Boschen, 1996; Chistensen, et al., 1998; Schulz

& Decker, 1985).

There appears to be no specific research on approach and avoidant control

and concepts of subjective quality of life or life satisfaction. Yet, Moos (1997) has

concluded, from his own extensive research on approach and avoidant coping

responses among adults and youth, that "individuals who rely more on approach

and less on avoidance coping tend to experience better health and well-being" (p.

58). However, this conclusion was drawn from literature that focuses mainly on

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depression. Some examples of this research follow. Billings and Moos (1984)

investigated coping strategies among adults entering treatment for depression and

found that approach coping was associated with less severe dysfunction and

avoidant coping was associated with greater dysfunction. Dysfunction was

conceptualised in terms of depression, physical symptoms, such as headaches and

trembling, and lack of self-confidence. Similarly, Ebata and Moos (1991) found

that depressed adolescents, as well as those with conduct disorder, used

significantly more avoidance coping than those with rheumatic disease or healthy

adolescents. Finally, in a sample of adults residing in the community, Holahan

and Moos (1990) found that stable psychological functioning, measured with a

depression scale only, was predicted by approach coping. However avoidant

coping was not assessed in this study. Clearly these studies demonstrate that

depression is associated with low approach coping and high avoidant coping.

The relationship between depression and approach and avoidant coping has

also been supported by other researchers. Herman-Stahl et al., (1995) researched

coping and depression amongst a community sample of adolescents. The authors

used a median split method to form four groups, approachers (high approach

coping, low avoidant coping), avoiders (low approach coping, high avoidant

coping), high generic copers (high on both approach and avoidant coping) and low

generic copers (low on both approach and avoidant coping). The results showed

that avoiders reported significantly higher levels of depressive symptoms than all

other groups and approachers reported significantly fewer symptoms of depression

than all other groups. Furthermore, high generic copers reported significantly

fewer depressive symptoms than the low generic copers, indicating the usefulness

of avoidant control in conjunction with approach control.

Using longitudinal data Herman-Stahl et al., (1995) grouped their

participants into another seven groups. The first four groups resembled those

whose coping styles were stable across time: approachers, avoiders, high generic

copers, low generic copers. Three additional groups were created for those whose

coping styles changed across time: change positive (subjects who changed from

avoiders to approachers), change negative (subjects who changed from

approachers to avoiders), and flexible copers (subjects who did not reveal rigid

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adherence to a single mode of coping). Consistent with the above results,

adolescents who changed from approach to avoidant coping demonstrated a

significant increase in their level of depression and adolescents who changed from

avoidant to approach coping reported significant decreases in depression.

Interestingly, subjects classified as flexible copers also demonstrated a significant

decrease in depression, again indicating the usefulness of both approach and

avoidant control. However, this conclusion should be interpreted with caution as

their depression scores still remained higher than those classified as approachers.

Departing from this sole focus on depression, Finset and Andersson (2000)

found, in a sample of patients with acquired brain injury, that low approach coping

was associated with apathy and high avoidant coping was associated with

depression. These results, unlike the others, indicate the differential effect of the

two coping dimensions, suggesting that it is the avoidant dimension that is more

closely associated with depression.

Overall, the specific literature on approach and avoidant coping focuses

mainly on depression, providing little clear support for the relationship of

approach and avoidant control and concepts of subjective well-being or life

quality. However, the research does provide sound evidence of a strong

association between approach and avoidant coping and depression. Therefore, it is

likely that there will also be a significant relationship between approach and

avoidant control and subjective quality of life, as individuals who are more

depressed are also likely to be less satisfied with their lives. Moreover, there is

both theoretical and empirical support, outlined in the introduction to Study One,

that general concepts of perceived control are associated with concepts of

subjective well-being or life quality. The findings in Study One provide further

support to this conclusion.

6.2.2 The findings from Study One on approach and avoidant control and subjective quality of lifeThe relationship between approach and avoidant control and subjective

quality of life has already been supported in Study One. In the sample of carers of

people with mental illness, approach and avoidant control significantly correlated

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with subjective quality of life (.42 and .33 respectively). In the comparison

sample, drawn from the general population, only approach control significantly

correlated with subjective quality of life (.50). These differential results for the

two samples raise the notion that the relative usefulness of approach and avoidant

control may be dependent on the situation. Carers, who are presumably faced with

more stressors, may need both approach and avoidant control to maintain their

subjective quality of life; the comparison sample, with presumably less stressors,

needs only approach control.

Such a hypothesis is supported by Roth and Cohen (1986). These authors

suggest that approach coping is preferable when the situation is controllable, the

source of stress is known or the outcome measures are long-term. Avoidant

coping is considered preferable when emotional resources are limited, the source

of the stress is not clear, the situation is uncontrollable or outcome measures are

immediate. This is based on the notion that there are costs and benefits to both

approach and avoidant coping and that the usefulness of these strategies is

dependent upon the context in which they are used. However, Roth and Cohen's

(1986) description of the costs and benefits indicate that approach coping is

associated with more benefits, such as appropriate action and ventilation of affect,

and fewer costs, such as increased distress. Alternatively, avoidant coping is

associated with fewer benefits, such as stress reduction, and more costs, such as

interference with appropriate action and emotional numbness.

Hence, it appears from the findings in Study One and from Roth and

Cohen's (1986) conceptualisation of the costs and benefits, that approach control

may be predominantly useful in maintaining subjective quality of life and avoidant

control may be useful only to a certain extent and only in certain circumstances,

such as when faced with more stressors of an unpredictable nature. While it is true

that differing circumstances influence the use of approach and avoidant control,

other factors, such as an individual's personality, are also likely to be involved.

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6.2.3 Personality and approach and avoidant controlThere appears to be little specific research in the literature on the

relationships between extroversion and neuroticism, and approach and avoidant

control or coping. Still, it has been demonstrated in one study on adolescents'

coping styles by Gomez, et al. (1999), that neuroticism significantly correlated

with avoidance coping and extroversion significantly correlated with cognitive and

behavioural approach coping. Furthermore, extroversion significantly predicted

cognitive and behavioural approach coping, and both neuroticism and extroversion

significantly predicted avoidance coping. Likewise, there is evidence, in the

results reported on the predictors of coping in adult surgical patients by Sorlie and

Sexton (2001), that extroversion predicted active (approach) coping and both

neuroticism and extroversion predicted passive (avoidant) coping. Hence, the

relationship between extroversion and neuroticism, and approach and avoidant

control has been established but requires further investigation. A number of

studies have also supported the relationship between personality and coping in

more general terms.

There are two studies that have investigated the relationship between

different personality dimensions and approach and avoidant control or coping.

Gomez (1997) investigated the personality dimensions locus of control and Type

A behaviour pattern and Carver et al. (1989) investigated a number of dimensions,

some more reflective of personality than others. One of the personality

dimensions both studies used was internal/external locus of control, i.e. whether or

not the individual believes that life's events are either under one's own control or

the result of external factors. Gomez (1997) found that this personality dimension

significantly related to both approach and avoidant coping, whilst Carver et al.

(1989) found it significantly correlated to only one of the approach COPE scales.

It seems that an internal locus of control is virtually identical to approach coping

and the belief that one can address the problem, making the separate measurement

of these two concepts somewhat redundant. Another personality dimension used

by both studies was a Type A behaviour pattern, characterised by competitive-

achievement striving, time urgency, hostility-aggression and impatience. Whilst

Gomez (1997) found this personality dimension was not significantly related to

either approach or avoidant coping, Carver et al. (1989) found a significant

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relationship between two of the approach COPE scales and one of the avoidant

COPE scales. Whilst the Type A behaviour pattern provides interesting

information, it is not as well established and investigated as the neuroticism and

extroversion personality dimensions. Trait anxiety is in many ways similar to

neuroticism and Carver et al. (1989) found a number of significant relationships

between this and a number of the COPE scales, indicating the importance of

investigating the personality dimension of neuroticism when considering approach

and avoidant control.

Other studies have shown that extroversion and neuroticism have

significant relationships with various coping strategies. For example, neuroticism

and extroversion, along with openness to experience and conscientiousness,

significantly predicted daily coping strategy use in adult males (David & Suls,

1999). Similarly, neuroticism and extroversion significantly predicted a range of

seven coping strategies used in response to job stress by electricians working at

power plant construction sites in the United States (Mayes, Johnson & Sadri,

2000). In adolescents, extroversion was shown to have a direct positive effect on

problem and emotion-focused coping, while neuroticism had a direct positive

effect on avoidance coping (Kardum & Krapic, 2001). However, in undergraduate

university students coping with exam stress, neuroticism correlated positively and

significantly with emotion-focused coping (Halamandaris & Power, 1999).

Overall, these studies demonstrate more generally the direct effect of personality

on coping, which can be likened to perceived control.

6.2.4 Integrating personality, approach and avoidant control and subjective quality of lifeThe proposed relationships between personality, perceived control and

subjective quality of life outlined in the introduction still apply for approach and

avoidant control. Personality has long been established to predict constructs of life

quality. Personality is also likely to predict subjective quality of life indirectly

through its influence on other psychological processes that have been reported to

maintain subjective quality of life, such as perceived control. Furthermore,

support for these relationships has been provided in Study One. In the carer

sample, the personality variable, neuroticism, was found to significantly predict

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subjective quality of life both directly and indirectly via approach control. In the

comparison sample neuroticism indirectly predicted subjective quality of life

through approach control. Interestingly, the other personality variable measured,

extroversion, was not significantly related to either approach or avoidant control or

subjective quality of life; nor did avoidant control have a significant relationship

with personality in either of the samples. This suggests that the personality

variable neuroticism and approach control are most relevant to the maintenance of


6.2.5 Focus of the current researchThe literature on approach and avoidant coping is lacking in its support of

these dimensions of perceived control in adults and in the relationship with

subjective quality of life, or life satisfaction constructs, and personality. Still, the

theory and findings of Study One demonstrated that there are important

relationships between personality, perceived control and subjective quality of life

that are useful to understand how subjective quality of life is maintained. More

specifically, it appears neuroticism and approach control, and to a lesser degree

avoidant control, are theoretically and conceptually sound ways of understanding

and investigating these relationships. Consistent with Study One, it is

hypothesised in Study Two that personality will play a dual role in influencing

subjective quality of life both directly and indirectly through perceived control.

Study Two aims to support this hypothesis with a different group, a sample of

secondary school teachers.

6.3 SUBJECTIVE QUALITY OF LIFE IN SECONDARY SCHOOL TEACHERS

6.3.1 The stressors associated with teachingConsiderable emphasis has been placed on teacher stress and burnout in

Australia over the last 10 years. Like the 'burden of care' that is associated with

carers of people with mental illness, the 'cost of caring' is associated with teachers.

Although teachers may not experience the significant trauma related to having

mental illness in the family, they are considered to experience numerous stressors.

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Some of these stressors consistently highlighted in the literature are excessive

workloads and lack of resources, inadequate salary and limited career prospects,

student misbehaviour, difficult interactions with parents, poor professional

relationships with colleagues and demands of the broader educational context

(Churchill, Williamson & Grady, 1996, 1997; Griffith, Steptoe & Cropley, 1999;

Hart & Conn, 1996; Punch & Tuetteman, 1996; Sarros & Sarros, 1990).

It is on the demands of the broader educational context that Churchill et al.,

(1996, 1997) have focused their research. These authors have identified change

within the educational environment in the 1990's to be characterised by

unpredictability and dynamic complexity. In extensive interviews with primary

and secondary school teachers from Tasmanian and South Australian schools, they

found that the educational changes teachers saw as having the greatest impact on

their working lives included systemic cuts to education funding, the introduction

of national curricula, increased accountability requirements, new models for

assessing and reporting on students' work and social-justice policy initiatives.

Teachers also reported that these educational changes had resulted in an

unwelcome intensification of their work and an unwanted shift in the focus of their

work. Overall, they had negative feelings about those changes that affected the

organisational domain of their work.

Clearly, teachers face significant amounts of stress in their work lives and

this stress has been related to burnout (Pierce and Molloy, 1990; Sarros & Sarros,

1990), psychological distress (Punch & Tuetteman, 1996) and low quality of work

life (Churchill, et al., 1996; Hart & Conn, 1996).

6.3.2 The impact of stress on teachers' subjective quality of life and the role of coping strategiesBurnout is defined as physical and emotional exhaustion, detachment and

cynicism towards the people with whom one works and a loss of personal

accomplishment (Sarros & Sarros, 1990). It has been shown by Sarros and Sarros

(1990) that, when compared with Canadian and American samples, Australian

teachers demonstrated relatively low to moderate levels of emotional exhaustion

and depersonalisation burnout, but high levels of personal accomplishment

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burnout. Furthermore, these authors consider burnout to be the result of

unsuccessful attempts to cope with the stressors associated with their work. This

is supported by Pierce and Molloy (1990) who found that higher levels of burnout

in teachers, from both government and non-government schools in Victoria, were

associated with a number of variables, the most relevant of which was the more

frequent use of regressive (ie. avoidant) coping strategies. Hence, burnout,

particularly loss of personal accomplishment, has been associated with teachers'

ability to cope with workplace stressors.

Psychological distress has also been related to workplace stressors in a

sample of West Australian secondary school teachers (Punch & Tuetteman, 1996).

Distress was measured using the General Health Questionnaire and it was found to

correlate positively and significantly to four key stressors: 1) inadequate access to

facilities, 2) the intrusion of school work into out of hours time, 3) student

misbehaviour and 4) excessive society expectations. Additionally, these authors

found that two types of support, colleaguial support and praise and recognition, the

seeking of which would be considered approach control strategies, were negatively

and significantly correlated to psychological distress. Furthermore, using

contingency table analysis the authors showed that support ameliorates the distress

teachers experience as a result of the four identified stressors. Hence, like burnout,

psychological distress is also associated with a failure to cope with stressors.

Furthermore, burnout and psychological distress indicate that teachers' subjective

quality of life may also be low.

Quality of work life is the measure used in the teaching literature that is

most similar to subjective quality of life. It is defined as "the judgements that

teachers make about the extent to which their work is satisfying and meeting their

needs" (Hart & Conn, 1996, p. 26). In an investigation of teachers' satisfaction

with key aspects of their work lives, Churchill et al. (1996) found that whilst

teachers were relatively satisfied with their relationships, they were dissatisfied

with areas where they were subject to the regulations and expectations of the

education system, and with their capacity to exert some degree of influence over

educational and social matters which affect their work. It is apparent from these

findings that the circumstances of teachers' work may limit their opportunity to use

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approach control strategies, which may then impact negatively on their subjective

quality of life. The relevance of approach control strategies in maintaining quality

of work life has been highlighted by Hart and Conn (1996). These authors not

only identify the negative factors or stressors that are associated with quality of

work life, but also a range of positive factors, such as curriculum consultation,

effective school policies, feedback, goal congruence and participative decision-

making, which are conceptually related to approach control strategies.

Few studies appear to have specifically examined the use of approach and

avoidant control strategies by teachers. However, Griffith, Steptoe and Cropley

(1999) have investigated the effects of coping on stress in a sample of teachers in

London. Coping was measured with a selection of items from the COPE inventory

that reflect the four coping strategies: active planning, seeking social support,

suppression of competing activities, and behavioural and mental disengagement.

The results showed that disengagement and suppression significantly predicted

work stress independently of age, gender, class size, occupational grade and

negative affectivity. Clearly, disengagement is an avoidant control strategy and

thus it is not surprising that it was related to stress. However, suppression of

competing activities is measured with items focusing on preventing distraction and

concentrating on the problem and appears to be an approach control strategy.

Therefore, it is surprising that it is related to stress. It is possible that preventing

distraction and concentrating on the problem may exclude the use of any cognitive

approach control strategies, such as positive reinterpretation and distraction, and

that without cognitive strategies approach control may not be as useful.

Unfortunately, the authors do not include cognitive approach control strategies in

their study.

6.3.3 Conclusion and focus of the current researchOverall, it is apparent that teachers face a variety of stressors within an

inherently complex and unstable educational environment within which they must

learn to cope in order to maintain their subjective quality of life. This will

probably require the use of both approach and avoidant control strategies. Given

85


the ongoing workplace stressors associated with teaching, and the need to cope

with these stressors, teachers make an interesting population to investigate.

This second study will continue to examine the relationships between

subjective quality of life, perceived control conceptualised as approach and

avoidant control strategies, and personality conceptualised as neuroticism and

extroversion. The study aims to explore the factor structure of a different set of

coping strategies representing perceived control and to test the finding from the

first study, that personality predicts subjective quality of life both directly and

indirectly through perceived control.

86

CHAPTER 7 - Study Two: Aims and Hypotheses

CHAPTER 7

7 STUDY TWO: AIMS AND HYPOTHESES

Aim One:

To develop a valid and reliable tool for the measurement of perceived

control by examining the factor structure of the Coping Response Inventory, which

was developed to reflect approach and avoidant coping.

Aim Two:

To examine differences in personality, perceived control and subjective

quality of life between a sample of secondary school teachers and a comparison

sample of people from the general population.

It is hypothesised that secondary school teachers will have lower

subjective quality of life and perceived control than people from the

general population, after the effects of personality have been removed.

Aim Three:

To examine the relationships between personality, perceived control and

subjective quality of life in a sample of secondary school teachers and in a

comparison sample of people from the general population.

It is hypothesised that perceived control will improve the prediction of

subjective quality of life beyond that afforded by personality and that

personality will predict perceived control.

87

CHAPTER 8 - Study Two: Method

CHAPTER 8

8 STUDY TWO: METHOD

8.1 SampleThe teacher sample was recruited from a total of 170 questionnaires sent to

nine public Secondary Colleges in the Eastern metropolitan region of Melbourne,

Australia. A total of 85 questionnaires were voluntarily completed by qualified

secondary school teachers following one reminder letter, a response rate of 50%.

Most of these teachers were employed full time (93.7%) and had worked an

average of 20 years in the field.

The comparison sample was taken from a total of 150 questionnaires that

were sent to potential participants that were recruited via a word of mouth method,

who also primarily lived in the Eastern suburbs of metropolitan Melbourne. A

total of 88 questionnaires were returned following one reminder letter, a response

rate of 58%. One of those questionnaires was returned but not sufficiently

completed. Subsequently, 87 questionnaires were used in the analyses. Most of

these participants worked in the business sector (32.9%), a number worked in

education (18.8%) mainly as primary school teachers, in special education settings

or as childcare workers. The remaining participants were spread across the

government and health sectors, the retail/service and labour industry, and

participants who fulfilled home duties, were students or retired.

Background information is displayed in Table 10 as percentages. The two

samples were reasonably comparable on the range of demographic variables

examined. However, the comparison sample was generally younger in age and

more evenly distributed across the income categories than the teacher sample.

There were notable differences between the samples in two of the areas of

difficulty identified. (Note: percentages do not sum to 100% as they represent the

percentage of people who identified each area as one of their three areas of

difficulty). A greater percentage of the teacher sample identified difficulty with

time management and work than the comparison sample. Furthermore, the teacher

88


sample showed significantly greater frequency of difficulties overall than the

comparison sample, t=2.40, p=.018.

Table 10: Background information.Teacher(n=85)

Comparison(n=87)

SexMale 42.4% 39.1%Female 57.6% 60.9%Age<20 years 0.0% 3.5%20-29 years 21.2% 42.4%30-39 years 10.6% 12.9%40-49 years 35.3% 7.1%50-59 years 30.6% 20.0% >60 years 2.4% 14.1%Income<$10,999 0.0% 12.8%$11,000-$25,999 3.5% 15.1%$26,000-$40,999 14.1% 15.1%$41,000-$55,999 37.6% 20.9%>$56,000 44.7% 36.0%Areas of difficultyTime management 78.82% 62.07%Motivation 30.59% 36.78%Interpersonal relationships 29.41% 29.89%Work 48.24% 36.78%Health 40.00% 49.43%Finances 31.76% 42.53%Safety 1.18% 4.60%Other 15.29% 20.69%Frequency of difficultyMeana 48.00 39.56Standard Deviation 19.49 17.18

ap<.05

8.2 ProcedureA letter of information outlining the study and ethical safeguards, together

with a questionnaire booklet, were distributed to all participants in the study (See

Appendix C and D respectively). Consent to participate in the study was implied

by the voluntary completion of the questionnaire. The teacher sample received

their questionnaires from the assistant principal at the school in which they worked

and returned them directly to the researcher in the prepaid envelope provided. The

comparison sample received their questionnaires via the mail and returned them

directly to the researcher in the prepaid envelope provided. The names and

addresses of each participant were kept separate from the questionnaires by

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assigning a code number that corresponded to their questionnaire. This was

necessary to follow-up participants who had not returned their questionnaire

within two weeks with a reminder letter, after which no further contact was made.

8.3 Measurement ToolsSubjective quality of life was measured using the subjective scale of the

Comprehensive Quality of Life Scale developed by Cummins (1997b) as detailed

in Study One. A copy of this scale is included in Appendix D. It was decided that

only the satisfaction scores would be used in this study as it has become apparent

that the practice of using satisfaction scores weighted by importance scores is

statistically problematic (see Evans, 1991; Trauer & Mackinnon, in press). This

was also evidenced by the inflated standard deviations in the total and domain

subjective quality of life scores used in Study One. Furthermore, it is possible that

respondents cognitively make value judgements when completing the satisfaction

questions.

Personality was measured using the extroversion and neuroticism scales of

the Revised Eysenck Personality Questionnaire (Eysenck & Eysenck, 1991) as

detailed in Study One. A copy of this scale is included in Appendix D.

Perceived control was measured using the Coping Responses Inventory -

Adult form (Moos, 1993). A copy of the scale is included in Appendix D. Some

minor modifications were made to the introduction to the scale. The original

version asked respondents to identify one problem and complete the questionnaire

with this problem in mind. In order to make the responses more indicative of

perceived control this part was deleted and respondents were prompted to think of

three aspects of their lives that they have difficulties or problems with, following

which they rated the frequency of these difficulties on a 10 point Likert scale. The

respondents then indicated the extent to which they used each of the 48 items of

the Coping Responses Inventory on a 4 point Likert scale anchored with: No Not

at all, Yes Once or Twice, Yes Sometimes, and Yes Fairly Often. This was

consistent with the original version of the scale. These 48 items have been grouped

into 8 subscales. A description of these scales, as outlined in the manual, is

90


provided in Table 11, and the items which comprise these scales are provided in

Appendix E.

Table 11: Description of the scales in the Coping Response InventoryScale Description

Approach Coping

1. Logical Analysis Cognitive attempts to understand and prepare mentally for a stressor and its consequences

2. Positive Reappraisal Cognitive attempts to construe and restructure a problem in a positive way while still accepting the reality of the situation

3. Seeking Guidance & Support

Behavioural attempts to seek information, guidance, or support

4. Problem Solving Behavioural attempts to take action to deal directly with the problem

Avoidant Coping

5. Cognitive Avoidance Cognitive attempts to avoid thinking realistically about a problem

6. Acceptance or Resignation Cognitive attempts to react to the problem by accepting it

7. Seeking Alternative Rewards

Behavioural attempts to get involved in substitute activities and create new sources of satisfaction

8. Emotional Discharge Behavioural attempts to reduce tension by expressing negative feelings

Reproduced from Moos (1993) p. 15.

The scale's manual reports reliability with alpha coefficients for males and

females for each of these scales, as well as means and standard deviations. The

alpha coefficients range from .61 to .74 for males and .58 to .71 for females. The

manual also reports data to show that the eight scales are moderately stable over

time, with the average correlation of the eight scales for males and females

respectively, .45 and.43 at a 12 month follow-up.

91

CHAPTER 9 - Study Two: Results

CHAPTER 9

9 STUDY TWO: RESULTS

9.1 Aim OneIn order to explore the factor structure of the Coping Responses Inventory

(Moos, 1993) and to refine the reliability and validity of the perceived control

variables used in the following analyses, a series of factor analyses and other data

reduction methods were conducted on the data from the combined teacher and

comparison samples, totalling 172 people. As in Study One a combined sample

was used in order to ensure generalisability of the results to both samples and to

provide a larger sample size for the factor analyses. Refer to Appendix D or E for

item numbering and content to inform the following discussion.

The data did not adequately meet all of the necessary assumptions for

testing. The sample size was less than the criterion of a minimum of five subjects

per variable outlined by Tabachnick and Fidell (1996). The distributions of each of

the variables were examined for normality, linearity and univariate and

multivariate outliers. Thirteen missing cases were detected and replaced with the

variable mean. An examination of the skewness and kurtosis statistics indicated

five items were not normally distributed, item 17 being mildly negatively skewed

and items 19, 24, 45 and 46 being mildly positively skewed. No transformations

were made because of the mild nature of the skewness, because skewness is likely

to be meaningful to the data, and because factor analysis is robust to mild

violations of normality. Examination of the scatterplots revealed the data

generally met the assumption of linearity. Mahalanobis distance was used to

check for multivariate outliers using a cutoff criterion of p<.001. None were

found. Univariate outliers were detected. However, these were not recoded. As

the scale only had four points this would have reduced the variance in the

distributions considerably. In order to create a factorable correlation matrix and to

reduce the sample size needed for the factor analysis Items 7, 17, 21, 39, 40, 48,

were deleted as they failed to correlate greater than .3 with any other item.

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A principal components factor analysis with oblique rotation was

performed on the 42 items, extracting eight factors to represent the number of

scales in the Coping Responses Inventory. All items correlated greater than .3

with at least one other item and partial correlations were all low. Inspection of the

Anti-Image correlation matrix revealed that the measure of sampling adequacy

was greater than the acceptable level of .5 for all of the items. The Kaiser-Myer-

Olkin measure of sampling adequacy was greater than .6 at .71. Bartlett's test of

sphericity was significant 2(861)=2304.92, p=.000. The eight factors together

explained 47.36% of the variance. Only two of these factors explained more than

5% of the variance and the scree plot indicated two clear factors. However, six of

these factors did explain more than 4% of the variance and although the scree plot

indicated two clear factors, there was a distinction evident in the plot for six

factors. In an attempt to support the theoretical construct of the original tool, it

was decided to conduct a six-factor solution as well as a two-factor solution.

A second factor analysis on the 42 items was conducted extracting two

factors. Together the two factors accounted for only 24.81% of the variance and

examination of the communalities for each of the items revealed that the variance

accounted for by the two factors was low in most of the items. Examination of the

factor loadings revealed items 24, 3, 19, 38 did not load greater than .3 on either

factor and item 23 loaded greater than .3 on both factors. These items were

deleted to create simple structure and a third factor analysis was completed.

In the final analysis the two factors together accounted for 26.55%, with

Factor 1 accounting for 14.55% and Factor 2 accounting for 10.23%. The two

factors were independent, correlating -.05, and internal consistency was high for

each factor with Cronbach's Alpha for Factor 1 at .84 and for Factor 2 at .80.

Factor 1 consisted of 25 items that consistently reflected the items from the four

approach coping scales in the Coping Responses Inventory. However there were

three items (15, 31 and 47) from the avoidant coping scale, selecting alternative

rewards, that loaded on this factor. This result was expected as it was already

highlighted that this scale did not really reflect avoidant coping. Item 16 "Did you

take a chance and do something risky?", from the emotional discharge scale, also

loaded on this factor. This item clearly does not reflect emotional discharge, but is

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more similar to seeking alternative rewards. Factor 2 consisted of 12 items that

consistently reflected items from three avoidant coping scales, cognitive

avoidance, acceptance or resignation and emotional discharge. Given that the two

factors only accounted for a relatively small amount of the variance and the

communalities for most of the items were low, the decision to try and find a six

factor solution was further supported.

A factor analysis on the 42 items was performed extracting six factors.

Together the six factors accounted for 43.53% of the variance and examination of

the communalities for each of the items revealed that the variance the six factors

accounted for was reasonable for most of the items. Examination of the factor

loadings revealed items 1, 25, 41, 45, 37, 8, 18, 27, 36, 32, loaded greater than .3

on more than one factor and item 44 loaded did not load greater than .3 on any

factor. These items were deleted to create simple structure and a second factor

analysis extracting six factors was performed. Examination of the factor loading

again revealed that a number of items loaded on more than one factor. Items 22,

43, 35, 9, 4, 19, loaded greater than .3 on more than one factor and item 31 loaded

did not load greater than .3 on any factor. These items were deleted and a third

factor analysis extracting six factors was conducted on the remaining 24 items.

The factor loadings showed item 33 loaded greater than .3 on more than one

factor, it was deleted and a final factor analysis extracting six factors was

conducted. Simple structure was obtained.

Together the six factors accounted for 53.71% of the variance. The six

factors were independent of each other with the highest correlation being between

Factor 1 and Factor 5 at -.23. Factor 1 consisted of five items that explained

16.32% of the variance and showed internal consistency (=.68). All of these

items were from the positive reappraisal scale of the Coping Responses Inventory.

Factor 2 consisted of six items that explained 13.59% of the variance and showed

internal consistency (=.75). Three of these items were from the acceptance or

resignation scale, and three were from the cognitive avoidance scale, overall the

items clearly represented avoidant control. Factor 3 consisted of two items that

explained 6.51% of the variance and showed internal consistency (=.62). Both of

these items were from the seeking guidance and support scale. Factor 4 consisted

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of three items that explained 6.16% of the variance and showed internal

consistency (=.54). All of these items were from the problem solving scale.

Factor 5 consisted of five items that explained 5.76% of the variance and showed

internal consistency (=.65). Three of these items were from the seeking

alternative rewards scale and the fourth item was item 16 "Did you take a chance

and do something risky?" labelled on the emotional discharge scale but clearly not

reflecting emotional discharge. Factor 6 consisted of three items that explained

5.37% of the variance and showed internal consistency (=.62). Two of these

items were from the seeking alternative rewards scale (item 46 "Did you lose hope

that things would ever be the same?" and item 38 "Did you expect the worse

possible outcome?) and one was from the emotional discharge scale (item 24 "Did

you keep away from people in general?). The content of these items revealed that

the scale reflected acceptance and resignation in a very negative sense, whereas the

acceptance and resignation items in Factor 2 had a more positive sense (eg item 6

"Did you feel that time would make a difference-that the only thing to do was

wait?").

The two-factor solution indicated that there were approach and avoidant

factors within the data. The six-factor solution indicated some support for the

scales of the Coping Response Inventory. However, neither of these factor

solutions appeared to provide valid and reliable factors to use in the subsequent

analyses. Therefore, it was decided to construct scores for each of the eight scales

of the Coping Responses Inventory and use these in a factor analysis extracting

two factors to reflect approach and avoidant control. The advantages of this are

that there would be more variability in the variables than the four point scales of

the individual items, and there would be less variables in the analysis making the

sample size adequate.

Hence, scores for each of the eight scales of the Coping Responses

Inventory were computed in accordance with the manual by scoring them on a

scale of 0 to 3 and adding the relevant items together. Cronbach's Alpha was

calculated to assess the internal consistency for each scale before conducting the

factor analysis. Internal consistencies, means and standard deviations are

displayed in Table 12 for comparison with the scale's manual.

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Table 12: Means, standard deviations (SD) and internal consistencies (Alpha) of the Coping Responses Inventory Scale Mean SD Alpha

Approach Coping

Logical Analysis 12.20 2.86 .63

Positive Reappraisal 11.55 3.35 .71

Seeking Guidance & Support 9.15 3.20 .58

Problem Solving 12.34 2.81 .65

Avoidant Coping

Cognitive Avoidance 6.56 3.62 .71

Acceptance or Resignation 6.01 3.23 .52

Seeking Alternative Rewards 9.22 3.27 .62

Emotional Discharge 5.72 2.67 .39

These results are generally comparable to those in the scale's manual. The

means for the each of the approach coping scales were marginally higher than in

the manual and those for the avoidant coping scales were comparable for cognitive

avoidance, marginally lower acceptance or resignation, marginally higher for

emotional discharge and substantially higher for seeking alternative rewards.

Internal consistency was comparable with that in the scale's manual with the

exception of emotional discharge, which was somewhat low. However, internal

consistency is acceptable for all of the scales according to Boyle (1991) who

argues that the optimal range for internal consistency is between .3 and .7.

A principal components factor analysis with oblique rotation was

performed on the eight scales extracting two factors. The data adequately met all

the necessary assumptions for testing. The sample size was adequate. The

distributions of each of the variables were examined and normality and linearity

was evident. No multivariate outliers were detected using Mahalanobis distance

and a cutoff criterion of p<.001. Univariate outliers were detected. However,

these were not recoded into the distribution. The correlation matrix was deemed

factorable. Each variable correlated greater than .3 with at least one other variable.

Inspection of the Anti-Image correlation matrix revealed that the measure of

sampling adequacy was greater than the acceptable level of .5 for all of the items.

The Kaiser-Myer-Olkin measure of sampling adequacy was greater than .6 at .72.

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Bartlett's test of sphericity was significant 2(28)=360.36, p=.000. Communalities

appeared sufficient.

The two factors together explained 58.60% of the variance. The first factor

accounted for 33.79% and the second factor accounted for 24.81%. Examination

of the scree plot indicated that two factors fit the data best. Examination of the

factor loadings revealed that the variable, seeking alternative rewards, loaded most

strongly on the first factor but also greater than .3 on the second factor. It was

deleted and the analysis re-run. Table 13 displays the resultant factor structure.

Table 13: Factor solution for the eight scales of the Coping Responses Inventory. Scale Approach

ControlAvoidant Control

Logical Analysis .80Positive Reappraisal .80Problem Solving .77Seeking Guidance & Support .64

Cognitive Avoidance .86Acceptance or Resignation .79Emotional Discharge .69

Correlation between each factor -.04Percent of Variance explained 34.34 26.29Range of item-total correlations .20-.42 .16-.40Cronbach's Alpha .75 .69

The resultant factor analysis showed that the two factors were independent

(r=-.04) and together accounted for 60.62% of the variance with Factor 1

accounting for 34.34% and Factor 2 accounting for 26.29%. Internal consistency

for each of the factors was adequate. The two factors were meaningful and

reflected approach and avoidant control.

9.2 Aim TwoTo begin, a multivariate analysis of variance was used to examine

differences between the sample of teachers and the comparison sample on all of

the variables, subjective quality of life, approach control, avoidant control,

extroversion and neuroticism.

The data for each dependent variable were screened by group in

preparation for the subsequent analyses. There were no missing data and the

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group sizes were comparable (teacher sample n=85, comparison sample n=87).

Examination of the skewness and kurtosis statistics revealed that the data were

normally distributed. Univariate outliers were detected and recoded by "assigning

the outlying case a raw score on the offending variable that is one unit larger (or

smaller) than the next most extreme score" as multivariate analysis of variance is

reported to be extremely sensitive to outliers (Tabachnick & Fidell, 1996, p. 69).

In the teacher sample one outlying case was recoded on the subjective quality of

life variable, two on approach control and one on avoidant control. In the

comparison sample two outlying cases were recoded on the subjective quality of

life variable, one on neuroticism and one on avoidant control. One multivariate

outlier were detected using Mahalanobis distance and a criterion cutoff p<.001,

this case was deleted from the analysis, reducing the comparison sample to n=86.

Examination of the correlation matrix revealed that the assumption of

multicollinearity and singularity was met. Box's M suggested that the data had

met the assumption of homogeneity of variance-covariance matrices.

F(15,114961)=8.16, p=.928, which was non-significant. The univariate tests for

homogeneity of variance indicated that this assumption had not been violated for

any of the dependent variables.

Pillai's Trace multivariate test of significance revealed there was no

significant group difference on one or more of the dependent variables

F(5,165)=.58, p=.713. Hence, no further investigation of these findings was made,

as the two samples did not differ on any of the variables of interest. Accordingly,

the hypothesis that secondary school teachers will have lower subjective quality of

life and perceived control than people from the general population, after the effects

of personality have been removed could not be supported and it was deemed

unnecessary to proceed with the analysis of covariance. Furthermore, there were

problems evident in Study One where the use of the personality covariates

appeared to mask important differences between the two samples in subjective

quality of life and perceived control.

The two samples were combined to examine the relationships between the

variables and to compare the means and correlations to those reported in the scales'

manuals and in Study One. Table 14 displays the means, standard deviations and

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bi-variate correlations for the variables subjective quality of life, approach control,

avoidant control, neuroticism and extroversion for the combined teacher and

comparison sample to inform the subsequent analyses.

Table 14: Means (M), standard deviations (SD) and bi-variate correlations for the variables subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the combined sample (n=171).

Total SQOL

Appr Control


Total SQOL -- .38b -.25b -.44b .24b

Approach Control -- -.08 -.08 .19a

Avoidant Control -- .30b -.08Neuroticism -- -.27b

Extroversion --M 76.49 45.02 22.14 4.82 7.15

SD 11.60 8.92 8.83 3.49 3.59a p < .05 (2-tailed), b p <.01 (2-tailed)

The mean subjective quality of life score (76.49%SM) was within the

standard score range of 70-80%SM (Cummins 2000). Approach and avoidant

control scores are also expressed as a percentage of scale maximum. It can be

seen that approach control (45.02%SM) is used more than avoidant control

(22.14%SM). It is also interesting to note that these scores are lower than those in

Study One for both the carer sample (approach control 58.11%SM and avoidant

control 32.44%SM) and the comparison sample (approach control 65.33%SM and

avoidant control 36.00%SM). The extroversion (7.15) and neuroticism (4.82)

means are comparable with those in the scale's manual, which reported the mean

extroversion score for females at 7.60 and for males at 6.36 and the mean

neuroticism score for females at 5.90 and males at 4.95. Again, z scores were

calculated to assess the differences between the sample and both the male and

female norms separately. No significant differences with both the male and female

norms were found. These results are more consistent with the scale's norms than

those in the comparison sample in Study One.

The correlation matrix in Table 14 displays some interesting relationships

between the variables of interest and some notable differences between these

relationships and those found in Study One. Subjective quality of life correlates

significantly with all of the variables, neuroticism, extroversion, approach control

and avoidant control. Consistent with Study One the strongest correlations are

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between subjective quality of life and neuroticism and approach control.

Extroversion showed a weak positive relationship with approach control and

neuroticism showed a moderate relationship with avoidant control. Interestingly,

avoidant control appeared to be relating to the other variables differently from

Study One. It correlated significantly and negatively with subjective quality of life

and positively with neuroticism, which is opposite to the non-significant

correlations in Study One. Furthermore avoidant control and approach control

correlate very weakly. This indicates that this measure of avoidant control is quite

different to that used in Study One.

9.3 Aim Three A series of regression analyses were used to test the hypothesis that

perceived control will improve the prediction of subjective quality of life beyond

that afforded by personality, and that personality would predict perceived control.

The data have already been shown to meet most of the necessary assumptions for

testing, including outliers, multicollinearity and singularity, normality and

linearity. The sample sizes were adequate and additional assumptions of

homoscedasticity and independence of residuals were also examined and met.

To test the first part of this hypothesis, a sequential multiple regression was

used for the combined sample. The dependent variable was total subjective quality

of life and the independent variables were entered in two steps, where the two

personality variables (neuroticism and extroversion) were entered in the first step

and the two perceived control variables (approach control and avoidant control)

were entered in the second step. Tables 15 displays the results, including the

unstandardised regression coefficients (B), the standardised regression coefficients

(), squared semipartial correlations (sr2), and R, R2, and adjusted R2 after entry of

all independent variables.

Table 15: Regression of neuroticism, extroversion, approach control and avoidant control on subjective quality of life in the combined sample

B t sr2

Neuroticism -1.04 -.40 -5.66c .16

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Extroversion .29 .13 1.77 .02Neuroticism -.92 -.36 -5.18c .14Extroversion .16 .07 1.00 .01Approach Control 1.31 .33 5.05c .13Avoidant Control -.44 -.12 -1.76 .02

R2 Adj. R2 R .33 .31 .57c

ap<.05, bp<.01, cp<.001

The results for the combined sample showed after Step 2 with all of the

variables in the equation 33% of the variance in subjective quality of life was

explained, which was highly significant, R=.57, F(4,166)=20.14, p=.000. After

Step 1, with neuroticism and extroversion in the equation 21% of the variance in

subjective quality of life was explained, which was significant, R=.45,

Finc(2,168)=21.86, p=.000. Examination of the regression coefficients at Step 1

indicated that only neuroticism significantly predicted total subjective quality of

life. At Step 2, approach and avoidant control added to the prediction of

subjective quality by an additional 12% of the variance, which was a significant

increase Finc(2,166)=14.82, p=.000. Examination of the regression coefficients at

Step 2 indicated that neuroticism and approach were the only significant predictors

of subjective quality of life when all the variables were entered into the equation

together, with avoidant control approaching significance and extroversion making

no significant contribution to the equation. The results demonstrate that even

when the variance in subjective quality of life attributed to neuroticism is

accounted for, approach control can still make a significant contribution.

To test the second part of the hypothesis, that personality would predict

perceived control, two standard multiple regressions were performed for the

combined sample testing the prediction of the personality variables (neuroticism

and extroversion) on approach and avoidant control separately. Hence, Table 16

displays the results including the unstandardised regression coefficients (B), the

standardised regression coefficients (), squared semipartial correlations (sr2), and

R, R2, and adjusted R2.

Table 16: Regression of neuroticism and extroversion on approach control and avoidant control for the combined sample.

B t sr2

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Approach ControlNeuroticism -.02 -.04 -.46 .00Extroversion .10 .18 2.28a .03

R2 Adj. R2 R .04 .03 .19a

Avoidant ControlNeuroticism .21 .29 3.85c .08Extroversion -.03 -.00 -.05 .00

R2 Adj. R2 R .09 .08 .30c

ap<.05, bp<.01, cp<.001

The results of the first regression equation showed that together

neuroticism and extroversion accounted for 4% of the variance in approach

control, which was significant R=.19, F(2,168)=3.23, p=.042. However,

examination of the regression coefficients indicated that extroversion was the only

significant predictor explaining 3% of the variance in approach control. The

results of the second regression equation showed that together neuroticism and

extroversion accounted for 9% of the variance in avoidant control, which was

significant, R=.30, F(2,168)=8.04, p=.000. However, examination of the

regression coefficients indicated that neuroticism was the only significant predictor

explaining 8% of the variance in avoidant control.

9.4 Additional analysesThe same analyses for Aim Two and Three were re-run on the sample

divided into two subgroups, those with low subjective quality of life, less than

70%SM, and those with high subjective quality of life, greater than 70%SM.

Table 17 displays the means, standard deviations and bi-variate correlations for the

variables subjective quality of life, approach control, avoidant control, neuroticism

and extroversion for the two subgroups, high and low subjective quality of life, to

inform the subsequent analyses.

Table 17: Means, standard deviations and bi-variate correlations for the variables subjective quality of life (SQOL), approach control, avoidant control, neuroticism and extroversion for the two subgroups, high and low subjective quality of life.

Total SQOL

Appr Control


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High SQOL (n = 125)Total SQOL -- .19a -.19a -.30b .12Approach Control -- .03 .06 .10Avoidant Control -- .18a -.04Neuroticism -- -.22a

Extroversion --M 82.13 46.99 21.04 4.09 7.66

SD 7.18 9.08 8.21 3.39 3.81Low SQOL (n = 46)

Total SQOL -- .25 -.22 -.24 .08Approach Control -- -.19 -.06 .24Avoidant Control -- .48b -.08Neuroticism -- -.17Extroversion --

M 61.16 39.65 25.11 6.83 5.78SD 7.44 6.37 10.05 2.95 3.81

a p < .05 (2-tailed), b p <.01 (2-tailed)

A multivariate analysis of variance was used to examine any differences

between the two subgroups approach control avoidant control, extroversion and

neuroticism. Box's M suggested that the data had met the assumption of

homogeneity of variance-covariance matrices. F(10,34143)=1.64, p=.089, which is

non-significant. The univariate tests for homogeneity of variance indicated that

this assumption had not been violated for any of the dependent variables. Pillai's

Trace multivariate test of significance revealed there was a significant group

difference on one or more of the dependent variables F(4,166)=11.95, p=.000.

The univariate tests for each of the dependent variables are displayed in Table 18.

Table 18: Multivariate Analysis of Variance examining the differences between the subgroups, high and low subjective quality of life for the variables approach control, avoidant control, neuroticism and extroversion.

F(1,169) Sig. Eta Squared

Observed Power

Approach Control 21.18 .000 .11 1.00Avoidant Control 5.10 .025 .03 .61Neuroticism 23.43 .000 .12 1.00Extroversion 8.13 .005 .05 .81

The univariate tests displayed in Table 18 revealed that there were

significant main effects on every variable. Examination of the means reported in

Table 17 showed that those with high subjective quality of life had significantly

higher approach control and extroversion and significantly lower neuroticism and

avoidant control than those with low subjective quality of life. Eta squared

showed the strength of association between the independent and dependent

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variables was moderate to large and the power of the test to detect a true difference

was high.

A series of regression analyses were used to examine the relationships

between the variables for each group, high and low subjective quality of life.

However, the results were mostly non-significant and therefore will not be

reported in detail. The results for the high subjective quality of life group showed

that neuroticism and approach control significantly predicted subjective quality of

life, however only 15% of the variance in subjective quality of life was accounted

for. The results for the low subjective quality of life group showed that

neuroticism significantly predicted avoidant control, accounting for 23% of the

variance in avoidant control.

However, some interesting trends in the data between the two groups can

be found by examining the correlation matrix in Table 17. In the low subjective

quality of life group the correlation between approach and avoidant control is

stronger, and these variables correlate marginally stronger with subjective quality

of life, than in the high subjective quality of life group. Furthermore, in the low

subjective quality of life group extroversion correlates marginally stronger with

approach control and neuroticism correlates much stronger with avoidant control

than in the high subjective quality of life group.

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CHAPTER 10 - Study Two: Discussion

CHAPTER 10

10 STUDY TWO: DISCUSSION

10.1 Aim OneThe result of the exploratory factor analyses performed on the Coping

Responses Inventory (Moos, 1993) showed clear support for the approach and

avoidant distinction and some support for the subscales. The approach and

avoidant distinction was supported by two-factor solutions for both the 48 items

and for the eight subscales of the Coping Responses Inventory. These two-factor

solutions demonstrated a distinction in the types of strategies people use to cope

with their difficulties, in that they either approach or acknowledge the problem in

some way, or they avoid or ignore the problem. These two factors are consistent

with the literature (Ebata & Moos, 1991; Herman-Stahl et al., 1995; Roth &

Cohen, 1996) and with the findings from Study One.

A six-factor solution was also found, which provided some support for the

subscales of the Coping Responses Inventory. Three clear factors were evident for

positive reappraisal, problem solving, and seeking guidance/support. Cognitive

avoidance and acceptance or resignation items, with a positive slant, combined to

make an avoidant control factor. Seeking alternative rewards made another factor

with the inclusion of one emotional discharge item, which seems better placed

with these items. The last factor was made up of acceptance and resignation items

with a negative slant, and one emotional discharge item. Interestingly, all of the

items in the logical analysis scale were eliminated in the data reduction process.

These items consistently loaded on a number of the factors, perhaps suggesting

that logical analysis must occur in conjunction with all different types of control or

coping. This six-factor solution also suggests that there are important distinctions

between different types of approach control and one type of avoidant control,

which is consistent with the factor analytic literature on the COPE inventory

(Carver et al., 1989; Finset & Andersson, 2000; Phelps & Jarvis, 1994). Yet,

given that there were only two or three items in many of the factors they were not

adequate to use in the subsequent analysis.

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The two-factor solution for the eight subscales was used in the subsequent

analyses (see Table 13), as it did not contain some of the methodological problems

evident in the two-factor solution for the 48 items; such as an inadequate sample

size, low communalities, and a low percentage of variance explained by the two-

factor solution. Furthermore, each of the eight subscales of the Coping Responses

Inventory had good internal reliability and the means were comparable to those

published in the scale's manual (see Table 12). The approach control factor

included the subscales: logical analysis, positive reappraisal, problem solving and

seeking guidance/support. The avoidant control factor included the subscales:

cognitive avoidance, acceptance or resignation, and emotional discharge. The

factor, seeking alternative rewards, was not included in the final factor solution as

it loaded on both factors, although most strongly on the approach control factor,

which is in contrast to its inclusion in the avoidant coping scale of the Coping

Responses Inventory. The items in the seeking alternative rewards subscale

represent getting on with life, which although it does not specifically address the

specific difficulties it does perhaps acknowledge their existence and the need to

overcome them by having positive experiences. Overall, the approach and

avoidant control scales based on scores for each subscale of the Coping Responses

Inventory appear to be valid and reliable scales, that highlight an important

distinction between various strategies for maintaining perceived control, to use in

the subsequent analyses.

10.2 Aim TwoThe results did not show any differences between the teacher and

comparison samples on any of the variables of interest, subjective quality of life,

approach and avoidant coping, or extroversion and neuroticism. These results

suggest that the stressors that are reported to be associated with teaching

(Churchill, Williamson & Grady, 1996, 1997; Griffith, Steptoe & Cropley, 1999;

Hart & Conn, 1996; Punch & Tuetteman, 1996; Sarros & Sarros, 1990) are not

impacting negatively on teachers' subjective quality of life. Alternatively,

teachers' use of approach and avoidant control may be buffering the impact of

stress on subjective quality of life, as coping has been shown to be related to stress

(Griffith et al., 1999), burnout (Pierce & Molloy, 1990) and psychological distress

106


(Punch & Tuetteman, 1996) in teachers. However, teachers' scores on approach

and avoidant coping did not differ from the comparison sample. It could be

concluded that Australian teachers do not experience any greater workplace stress

than that of the general population. However, the finding that teachers

experienced a significantly greater frequency of difficulties and greater difficulty

in the areas of time management and work does not support this conclusion (see

Table 10). Overall, it appears that teachers' workplace stressors may not be

significant enough to defeat the homeostatic maintenance of their subjective

quality of life or to promote a change in their perceived control. Yet, it should be

highlighted that this conclusion is based on a small sample of teachers in Eastern

metropolitan Melbourne, and it is possible that there is response bias in the results

whereby only those teachers who were less stressed had the time and motivation to

participate in the research.

10.3 Aim ThreeGiven that there were no significant differences between the two samples

on any of the variables of interest, the samples were combined to investigate the

relationships between the variables, subjective quality of life, approach and

avoidant control, and extroversion and neuroticism. The mean scores for each of

these variables (see Table 14) were consistent with population norms found in the

literature and the scales' manuals. The mean total subjective quality of life

(satisfaction only) score was 76.49%SM which is within the normative range of

70-80%SM identified in the scales manual and by Cummins' (1995, 1998, 2000)

extensive research. The extroversion (7.15) and neuroticism (4.82) means were

comparable with those in the scale's manual, which reported the mean extroversion

score for females at 7.60 and for males at 6.36 and the mean neuroticism score for

females at 5.90 and males at 4.95. Overall, these results appear to be more

indicative of a normal population than those in Study One, increasing the

generalisability of the analysis of the relationships between the variables.

As in Study One, regression analyses were used to examine the

relationships between the relevant concepts (see Tables 15 and 16). Consistent

with Study One the results provide support for the hypothesis that perceived

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control will improve the prediction of subjective quality of life beyond that

afforded by personality, and that personality will predict perceived control.

The results of the regression analyses showed that with all variables in the

equation, neuroticism and approach control significantly predicted subjective

quality of life, whilst avoidant control approached significance and extroversion

made no significant contribution to the equation. This equation accounted for 33%

of the variance in the subjective quality of life of the combined sample.

Additionally, neuroticism significantly predicted avoidant control and extroversion

marginally but significantly predicted approach control, and extroversion and

neuroticism significantly correlated with each other. By incorporating these

relationships into a model (see Figure 6) a better understanding of the data for

Study Two is provided and comparisons can be made with Study One.

Figure 6: Model of the significant relationships among the variables, neuroticism, extroversion, approach control, avoidant control, and total subjective quality of life (SQOL), in the combined sample, including standardised regression coefficients and correlations.

In some ways this model represents a mix of the models in Study One for

the carer and comparison samples. In Study Two neuroticism predicted subjective

quality of life directly and possibly indirectly via avoidant control, although

avoidant control was only approaching significance in its prediction of subjective

quality of life with all other variables in the equation. This is similar to the carer

sample in Study One except approach control, rather than avoidant control, played

108

-.12.33

-.27

Total SQOL

Approach control

Avoidant Control

ExtroversionNeuroticism

.18.29-.36


the mediating role. Additionally, in Study Two extroversion indirectly predicted

subjective quality of life via approach control. This is similar to the comparison

sample in Study One except extroversion rather than neuroticism predicted

subjective quality of life indirectly via approach control.

A key reason for these differences is probably the different measure of

approach and avoidant control used, which, unlike Study One, has resulted in

avoidant control relating negatively with all other variables except neuroticism,

and it not being significantly correlated with approach control. This finding does

not support the conclusion from Study One and the literature (Roth & Cohen,

1986) that avoidant control is a beneficial coping strategy, and that when

individuals are faced with more stressors, both approach and avoidant control are

useful in maintaining their subjective quality of life. Importantly, any statement in

this regard is likely to be dependent on exactly how avoidant control is measured.

Essentially the results for Study Two show that neuroticism and avoidant

control together have a negative impact on subjective quality of life, whilst

extroversion and approach control together have a positive impact on subjective

quality of life. This conclusion is intuitively sound and is supported by the

literature and the findings of Study One that has shown neuroticism to

significantly and negatively correlate with subjective well-being, and extroversion

to significantly and positively correlate with subjective well-being (Costa &

McCrae, 1980; Francis, 1999; Francis et al., 1998; Lu & Shih, 1997).

Unfortunately, there is little literature to support the conclusions regarding the

relationships between approach and avoidant control and subjective quality of life.

However, it has been shown that depression is associated with low approach

coping, and that high avoidant coping is related to increased dysfunction and

depression, which can be assumed to be indicative of low satisfaction with life

(Billings & Moos, 1984; Ebata & Moos, 1991; Finset & Andersson; Herman-Stahl

et al., 1995; Holahan & Moos, 1990). Such findings are generally consistent with

the proposed model. It is concluded that perceived control improves the prediction

of subjective quality of life beyond that afforded by personality, with the most

significant variables being neuroticism and approach control.

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10.4 Additional analyses The additional analyses, applied after separating the sample into groups

representing high subjective quality of life (greater than 70%SM) and low

subjective quality of life (less than 70%SM), provided some interesting

information about the differences between the groups on the personality and

perceived control variables (see Table 17). Those with high subjective quality of

life had significantly higher approach control and extroversion and significantly

lower neuroticism and avoidant control than those with low subjective quality of

life. This provides further support for the notion that neuroticism and avoidant

control together have a negative impact on subjective quality of life, whilst

extroversion and approach control together have a positive impact on subjective

quality of life. Unfortunately, the regression analyses provided few significant

relationships. This may have been due to low subject numbers and the reduced

range of variance in subjective quality of life, resulting from the creation of high

and low subgroups within the sample, which attenuated the correlations.

However, the low subjective quality of life group did show trends consistent with

the pattern that approach and avoidant control correlated stronger with each other

and with subjective quality of life, and that extroversion correlated stronger with

approach control and neuroticism correlated stronger with avoidant control, than in

the high subjective quality of life group. This provides some support for the

conclusion in Study One, that when homeostasis is challenged the maintenance of

subjective quality of life becomes more complicated.

10.5 SummarySome important conclusions can be drawn from the findings of Study Two.

Firstly, the approach and avoidant dimensions of perceived control have

been supported as a valuable way to understand the structure of the Coping

Responses Inventory, both in terms of its items and its subscales, and the way

people deal with their problems and difficulties in general. There is some

suggestion that approach control could be meaningful if divided into subscales

reflecting positive reappraisal, problem solving and seeking guidance/support.

However, it appears that it fits the data best if these subscales are considered to

110


reflect one factor, approach control, which can be used in contrast to the second

factor, avoidant control.

Secondly, the analyses demonstrated no significant differences between the

teacher and comparison samples. This suggests that the stressors reported in the

literature to be associated with teaching are not significant enough to impact

negatively on teachers' subjective quality of life, or to promote change in their

approach and avoidant control. However, it should be highlighted that this

conclusion is based on a small sample of teachers in Eastern metropolitan

Melbourne.

Thirdly, the results of the analyses examining relationships within the

combined teacher and comparison sample, supported the conclusion that

neuroticism and avoidant control together impact negatively on subjective quality

of life, and extroversion and approach control together impact positively on

subjective quality of life. The finding that those with high subjective quality of

life had significantly higher approach control and extroversion, and significantly

lower neuroticism and avoidant control than those with low subjective quality of

life, further supported this conclusion. Still, it is important to note that neuroticism

and approach control were the strongest predictors of subjective quality of life.

Furthermore, there was some indication that when homeostasis is challenged the

maintenance of subjective quality of life becomes more complicated. The

generalisability of these results is supported by mean scores which closely

resembled the population norms in the scales' manuals.

Overall, there is continuing support for the model of personality, perceived

control and subjective quality of life depicted in Figure 2. This may help to

explain how subjective quality of life is maintained, or held under homeostatic

control. However, the support is preliminary and, given the differences between

the samples used in Study One and Study Two, requires further substantiation.

Inclusion of latent constructs for the personality and perceived control variables,

tested via structural equation modelling, may be an important next step.

111

CHAPTER 11 - Conclusions

CHAPTER 11

11 SYNTHESIS AND CONCLUSIONS

Both studies offer some support for a model of subjective quality of life

maintenance that involves personality and perceived control. The model under

consideration proposes that personality plays a dual role in contributing to

subjective quality of life, both directly, and indirectly through perceived control.

Fundamental to this model is the hypothesis that perceived control will improve

the prediction of subjective quality of life beyond that afforded by personality, and

that personality will predict perceived control.

Personality was selected for investigation as it has been consistently shown

in the literature to have a significant relationship with subjective quality of life,

which may help to understand homeostasis. Personality was measured using the

dimensions of extroversion and neuroticism, which were interpreted to reflect

enduring characteristics of emotional instability and sociability, respectively.

Perceived control was selected for investigation as it was indicated in the literature

to potentially be an important psychological process that may play a role in the

relationship between personality and subjective quality of life. Perceived control

was conceptualised, following the findings of the factor analytic research in this

thesis, in terms of approach and avoidant dimensions.

The aim of this thesis was to develop a better understanding of these three

key variables by: 1) investigating the factor structure of perceived control, 2)

investigating the differences between the general population and those whose

subjective quality of life and perceived control may be challenged, and 3)

examining the relationships between the variables.

It has been concluded that perceived control is best understood by dividing

it into approach and avoidant dimensions rather than the initially proposed

primary, secondary and relinquished control strategies. The factor analyses

performed on the two different control and coping scales in Study One and Study

Two have supported this conclusion. Approach control reflects addressing or

112


acknowledging the problem in some way and may involve strategies such as

positive reappraisal, problem solving and seeking guidance/support. Avoidant

control reflects avoiding or disregarding the problem and may involve strategies

such as cognitive avoidance, acceptance or resignation and emotional discharge.

Interestingly, in Study One, the measure of avoidant control appeared to be

an adaptive coping strategy as it correlated positively with subjective quality of

life, and negatively with neuroticism. However, in Study Two it appeared to be a

maladaptive coping strategy as it correlated negatively with subjective quality of

life, and positively with neuroticism. This highlights the significant impact that

measurement can have on the understanding of various concepts and more

specifically, the complexity of measuring avoidant control.

Overall, the Coping Responses Inventory (Moos, 1993) used in Study Two,

was developed for the purpose of identifying the use of approach and avoidant

strategies and it appears to be a reasonably valid and reliable tool. With the

exception of the seeking alternative rewards subscale, which loaded on both

approach and avoidant dimensions and thus was excluded from these analyses.

Hence, the approach and avoidant dimensions provided a meaningful

understanding of perceived control, which was used in the subsequent analyses of

differences between samples and of relationships among variables.

Some interesting conclusions were drawn from the differences that were

evident between the carer and comparison samples investigated in Study One. It

was indicated from the results that caring for someone with a mental illness

impacts negatively on caregivers' subjective quality of life, particularly on their

satisfaction with their health and emotional well-being. The carer sample also had

significantly higher neuroticism scores and significantly lower extroversion scores

than the comparison sample. This suggests that the negative impact of caring for

someone with a mental illness is not only evident in subjective quality of life, but

also in differences in carers' personality characteristics, resulting in higher

emotional instability and decreased sociability. Furthermore, there was some

indication that carers had less approach control than the comparison sample,

signifying that carers' belief that they can address their difficulties may be more

113


limited. However, there is some question over the representativeness of the

comparison sample in Study One, as their subjective quality of life scores were

placed on the upper end of the normative range and their neuroticism scores were

significantly lower than those in the scale's manual. It is possible that people who

are interested in participating in university research are more satisfied with their

lives and have less emotional instability than those from the general population,

highlighting that some caution should be taken in considering these conclusions.

Whilst there were differences between the two samples used in Study One,

there were no differences between the teacher and comparison samples in Study

Two on any of the subjective quality of life, personality or perceived control

variables. However, the background information revealed that a greater

percentage of the teacher sample identified difficulties with time management and

work than the comparison sample, and that teachers showed a significantly greater

frequency of difficulties. Hence, it was concluded that these workplace stressors

were not significant enough to defeat the homeostatic maintenance of teachers'

subjective quality of life or to promote change in their perceived control.

However, it should again be highlighted that this conclusion is based on a small

sample of teachers in a relatively affluent area of metropolitan Melbourne.

The most consistent results across both studies in the analyses of

relationships amongst the variables, were that perceived control improved the

prediction of subjective quality of life beyond that afforded by personality, and

that personality predicted perceived control. This finding was concordant with the

proposed model. However, it was predominantly based on the personality variable

neuroticism, which negatively contributed to subjective quality of life, and the

perceived control variable approach control, which made a positive contribution.

Some further conclusions, about the maintenance of subjective quality of

life, can also be drawn from the findings in Study One and Study Two by

comparing the model of relationships developed for each sample within these

studies. The three samples used in this research represent three groups of people

with differing levels of subjective quality of life, high normal, normal and low

normal. The developing complexity of the models for these groups as they move

114


from high normal, to normal, to low normal demonstrates that the management of

subjective quality of life homeostasis becomes more complicated as it is

challenged.

The comparison sample in Study One represents a group of people with

high normal subjective quality of life (80.68%SM). The model of relationships

between the variables developed for this group is reproduced in Figure 7. This

model was based on the regression equation which found that with all of the

variables in the equation, only approach control significantly predicted subjective

quality of life, accounting for 30% of the variance in subjective of quality life.

Figure 7: Model of the significant relationships among the variables for the comparison sample in Study One, representing high normal subjective quality of life (reproduction of Figure 5).

The combined sample in Study Two represents a group of people with

normal subjective quality of life (76.49%SM). The model of relationships



variables in the equation, neuroticism and approach control significantly predicted

subjective quality of life, accounting for 33% of the variance in subjective of

quality life.

115

Neuroticism

Approach Control

Total SQOL

-.18

.44


Figure 8: Model of the significant relationships among the variables for the combined sample in Study Two, representing normal subjective quality of life (reproduction of Figure 6).

The carer sample in Study One represents a group of people with low

normal subjective quality of life (71.37%SM). The model of relationships



variables in the equation, neuroticism, approach control and avoidant control

significantly predicted subjective quality of life, accounting for 37% of the

variance in subjective of quality life.

Figure 9: Model of the significant relationships among the variables for the carer sample, representing low normal subjective quality of life (reproduction of Figure 3).

116

-.12.33

-.27

Total SQOL

Approach control

Avoidant Control

ExtroversionNeuroticism

.18.29 -.36

.42 .16

.24

Neuroticism

Approach Control

Avoidant Control

Total SQOL

-.24 -.40


Hence, it can be seen that as the samples move from a homeostatic position

of over-exuberance, to normal, to one of avoiding depression, the personality and

perceived control variables account for more of the variance in subjective quality

of life, and the number of variables that significantly predict it increase. This

indicates that, as the management of subjective quality of life becomes more

difficult, individuals must draw on more processes to maintain their subjective

quality of life. Furthermore, these processes become more important to the

maintenance of subjective quality of life. However, it should be highlighted that

different measures of perceived control were used in the two studies, limiting the

interpretation of these findings somewhat. Nevertheless, the patterns evident do

demonstrate that when subjective quality of life homeostasis is being challenged

the maintenance of it becomes more complicated.

In conclusion, it is clear from the literature and the findings outlined in this

thesis, that perceived control is an important psychological processes to consider

when investigating the relationship between personality and subjective quality of

life, and when trying to understand how subjective quality of life is maintained. In

particular, neuroticism and approach control are indicated as the most important

variables, as they have been shown to predict subjective quality of life consistently

across the samples investigated. In addition, there is compelling evidence to

suggest that subjective quality of life homeostasis becomes more complicated as it

is challenged. Further investigation is needed to support these conclusions. It is

apparent that the workings of the homeostatic system of subjective quality of life,

can be most effectively revealed by studying samples who have a severely

challenged homeostatic system.

117

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Appendices

13 APPENDICES

Appendix A: Information Letter for Questionnaire 1

Appendix B: Questionnaire 1

Appendix C: Information Letter for Questionnaire 2

Appendix D: Questionnaire 2

Appendix E: Scales and Items of the Coping Responses Inventory

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Documents

Introduction to Thesis · Web viewSuch a conclusion, however, is limited by a notable difference between the mean score for neuroticism reported for the comparison sample in this