the role of primary/secondary control in positive psychological

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THE ROLE OF PRIMARY/SECONDARY CONTROL IN POSITIVE PSYCHOLOGICAL ADJUSTMENT Dr. Luke J. Heeps

B.A./B.Sc. (Australian National University)

B.Sc. Honours (University of Wollongong)

D.Psyc (Clin. Psyc.) (Deakin University)

Submitted in fulfillment of the requirements for the degree of Doctor of Psychology (Clinical) Deakin University October 2000

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THE ROLE OF PRIMARY/SECONDARY CONTROL IN POSITIVE PSYCHOLOGICAL ADJUSTMENT

L. J. Heeps

Abstract

This thesis concerns the relationship between control and positive psychological adjustment. The two-process model of Primary and Secondary Control is a more recent conceptualisation of control that proposes two main strategies by which people may develop a sense of control. Primary control involves the person manipulating environmental circumstances in order to suit their needs and wants, whereas secondary control strategies involve the person manipulating their internal cognitive/affective states in order to reduce the psychological impact of events.

Primacy theory proposes that primary control is functionally more adaptive than secondary control and that secondary control mostly functions to compensate for low primary control. However, some empirical evidence suggests that exercising too much control over the environment may be associated with negative physical and psychological outcomes. Furthermore, cross-cultural evidence suggests that some cultures (particularly Asian cultures) reinforce the benefits associated with secondary control over primary control. In addition, the original authors of the primary/secondary control constructs theoretically suggested the importance of a balance in the ratio of primary to secondary control levels for optimal adaptive

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functioning, rather than the adaptive importance of one control process over the other.

Previous empirical tests of primacy theory have generally produced mixed or inconclusive results. In addition, previous studies testing primacy theory operationalised secondary control in vague, non-descriptive terms that may have equated secondary control with helpless acceptance. Furthermore, studies have only narrowly defined adaptive functioning in terms of negative psychological outcomes (e.g. depression and anxiety), while neglecting the relationship between control and positive expressions of psychological health (e.g. Subjective Quality of Life).

Hence, a new measure of primary and secondary control was developed for this study, the Primary and Secondary Control Scale (PSCS). The PSCS operationalises both primary and secondary control in terms of specific cognitive and behavioural strategies aimed at either control of environmental circumstances (primary control) or control of internal states in order to minimise psychological impacts (secondary control). Factor analyses and reliability analyses of the PSCS items reported in Studies 1 and 2, demonstrate the PSCS as a valid and reliable measure of the primary/secondary control construct.

Studies 1 and 2 also tested hypotheses regarding the primacy of primary control. In particular, it was hypothesised that rather than primary control being more adaptive than secondary control, it is a balance in the levels of primary and secondary control that is important for optimal psychological adjustment. Furthermore, it was predicted that secondary control’s role in adaptive functioning is greater than simply acting to compensate for low primary control. In addition, the relations between primary/secondary control and more comprehensive and positive measures of psychological health were investigated, as opposed to the relationships with negative measures of psychological health as reported in previous studies.

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Results observed in Study 1, then confirmed in Study 2, did not support the primacy of primary control. That is, people that were “control-imbalanced” (high levels on one control process, but low on the other) reported lower levels of positive psychological adjustment compared to people who reported a balance of average or above-average levels of both primary and secondary control (“controlbalanced”). Furthermore, secondary control was found to predict variance in positive adjustment for both high and low groups of primary control, suggesting that secondary control’s role in adaptive functioning is more than simply acting as a back-up strategy for low primary control.

In addition Study 2 aimed to explore the capacity for the personality dimensions of Extraversion and Neuroticism to explain the relationship between primary/secondary control and positive psychological adjustment. Results showed that shared variance between primary/secondary control and positive adjustment was only partially explained by the personality dimensions of Extraversion and Neuroticism. Further analyses conducted showed that personality factors explained the primary control-adjustment link to a greater extent than the secondary control-adjustment link.

The findings are then discussed with reference to the implications they have for understanding adaptive psychological functioning. Hence, it is argued that adaptive psychological functioning involves maintaining higher levels of both primary and secondary control to allow the person to be flexible in their use of approach-avoidant strategies in order to deal with situations with varying levels of objective and subjective controllability associated with them. In contrast, emphasising one control process over the other, it is argued, is associated with vulnerability to the inherent mix of controllable and uncontrollable circumstances that we face in life. Furthermore, secondary control’s role in adaptive functioning, it is argued, is more than simply a back-up strategy for low primary control; it is critical to the effective functioning of primary control behaviour.

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Overall, the present analysis does not support the primacy of primary control in adaptive psychological functioning, but rather the strong functional interdependence of primary and secondary control.

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Acknowledgments

I would like to give greatest thanks to my mother and father. Firstly, to my father, Robin Heeps, whose financial support made the last few years possible. Without his help and belief in what I was trying to achieve for my life I would not have developed the quality of research, clinical and personal skills that will stand me in good stead in later working life. To my mother, Diane Heeps, whose very spirit of wisdom, tolerance and compassion for others inspired and continue to inspire the theory and practice that my thesis and clinical work aspire to.

I would like to dedicate this work to my older brother, Benjamin James Alexander Cottam Heeps, who was killed suddenly and under tragic circumstances last year. His quality of character and respect for those in all-walks of life was truly remarkable. His influence on my development as a person both as a young child and more recently in Melbourne is even more remarkable and defies words. To my brother Simon Heeps, I acknowledge a greater strength and resolve in both of us to have a rich and fulfilling life, and although we may be distant much of the time, our bond of shared struggle in family and wider life I hope will continue into the future.

I also acknowledge two other very important men in my life that also died during the completion of this work. Firstly, Paul Stuckey, whose spirit for adventure and love of natural environments lead us into so many memorable days on the rocks, in the mountains or exploring whatever there might be to explore. I miss you, yet believe me, I am continuing the journey. To Richard Walker-Powell who courageously died last year in a selfless effort, during a United Nations food drop over Kosovo. Rich reminds me about the relationship between belief in oneself, effort and defying the odds. Then to fail

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and get back into life as quickly as possible. I acknowledge this role Rich has had in my life and will continue to. Thank you for reminding me what to do in times of self-doubt.

A special thanks to my supervisor, Professor Bob Cummins, for his professional and respectful attitude toward students. This allowed me the autonomy and respect to pursue a line of research that this work embodies. His willingness to provide direct hands-on effort at finding relevant articles, helping with ethics clearance and achieving a sample allowed me to focus more clearly on the development of new theory and a new measure. In addition, it was due to Bob’s encouragement for much reading and engaging in lengthy discussions of often confusing theory that assisted greatly in the development of the ideas that feature in this work. To my peers and colleagues at Deakin for their emotional and professional support, Roger Brink, Margaret De Judicibus, Monique Garwood, Eoin Killackey, Litza Kiropoulos, Sophie Kurts, Karen Marriage and Fausta Petitio. Also to the administrative staff including, Julie, Betina Gardener, Anne Moirea, and especially Trudy Wallace for her professional and respectful manner in dealing with students needs and the good management of her department functions (e.g. the test libarary). To my friends, both in climbing circles and ‘over the river’ in Fitzroy whose support was akin to the family away from home. Particular thanks to Angus Boyle, Bridget Leo and Geoff Hooker. A heartfelt thank you to Anastasia Konstantelos for her loving friendship, support and cherished visits. Special thanks to Todd Zemeck for his genuine compassion and willingness for lengthy discussions to do with the management of my own health over the last twelve months, thanks Todd. Special thanks to the staff, patrons and friends of the Napier Hotel, especially the publicans Guy and Arty, Peter Hickey and Jody, Glen (G.P.) and Vicky, Pia Emery, Yvette, Katie, Roger, Arnie, old Eric, Mark Collins and Mandy for all extending a normalising, compassionate hand during an unusual time.

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Lastly, to the mountain playgrounds of the Grampians (Gariwerd), Mount Arapiles (Djurite), Victorian Alps and the New Zealand Southern Alps for the wonder, inspiration, enjoyment and understanding that these challenging landscapes instill in me. It is these lands that give my particular journey meaning.

Luke Heeps October, 2000.

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Table of Contents Abstract……………………………………………………………..iv Acknowledgments…………………………………………….……vii Table of Contents…………………………………………………...ix List of Tables…………………………………………………….xiv List of Appendices……………………………………………….xvi CHAPTER 1 – INTRODUCTION TO STUDIES OF PRIMARY AND SECONDARY CONTROL 1.1 General Introduction: An Overview…………………………...1 1.2 Control Concepts and Definitions: A Brief Review…………...2 1.3 Primary and Secondary Control: The Two-Process Model of Control………………………………………………3 1.3.1

Specific Secondary Control Strategies…………………..5

1.3.2

Alternative Conceptions of Primary and Secondary Control………………………………………6

1.3.3

The Expanding Classification of Control Strategies……………………………………….7 Primary Control Strategies……………………………...8

1.3.4 1.4

The Relationship Between Primary/Secondary Control and Psychological Adjustment: The Adaptive Value of Primary Control……………………………………………10

1.4.1

The Adaptive Value of Secondary Control……………..12

1.5 The “Primacy” of Primary Control……………………………14 1.5.1

Empirical Tests of Secondary Control as a Back-Up Strategy For Low Primary Control……………15

1.5.2

Cultural Differences in Preferences for Primary Versus Secondary Control: Is Secondary Control Simply Used as a Back-Up Strategy?……………………17

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1.5.3

Empirical Tests of the Greater Adaptive Value of Primary Control…………………………………….19 The Adaptive Limits to Primary Control……………...21

1.5.4 1.6

The Adaptive Limits to Secondary Control and Primary/Secondary Control Imbalances…………………25

1.7

The Adaptive Value of Maintaining a Balance Between the Levels of Primary and Secondary Control…………...28

1.8

Summary…………………………………………………30

CHAPTER 2 – OPERATIONALLY DEFINING PSYCHOLOGICAL ADJUSTMENT IN CONTROL RESEARCH

2.1 The Negative Affect Bias in Control-Adjustment Research…………………………………………………….32 2.2 Towards a More Positive and More Comprehensive Measure of Psychological Adjustment……………………...34 2.3 Conclusions and Hypotheses for Study 1…………………...36 CHAPTER 3 – STUDY 1: METHOD 3.1 Participants………………………………………………….38 3.2 Materials…………………………………………………….38 3.3 Procedure……………………………………………………41 CHAPTER 4 – RESULTS: STUDY 1

4.1 General Introduction…………………………………………43 4.2 The Factor Structure of the Primary and Secondary Control Scale (PSCS): Initial Analyses………………………………44 4.2.1 Final Solution and Reliability Analyses…………………49

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4.2.2 Possible Interpretations of the Negative Loadings Observed for Factor 2………………………………………50 4.3 Analyses of the Hypotheses to Study 1…………………….54 CHAPTER 5 – DISCUSSION OF STUDY 1 5.1 The “Primacy” of Primary Control…………………………60 5.1.1

Differences With Past Theory and Research: The Importance of Operational Definitions of Primary and Secondary Control in Control-Adjustment Research…………………………..64

5.2 Limitations to Study 1……………………………………...67 CHAPTER 6 – INTRODUCTION TO STUDY 2 6.1 General Introduction……………………………………….69 6.2 A Summary of Previous Theory and Evidence from Study 1: The Importance of Maintaining a Balance in the Levels of Primary and Secondary Control…………..69 6.2.1 Secondary Control’s Adaptive Function is More Than a Compensatory Mechanism For Low primary Control………………………………………………..70 6.2.2

The Relationship Between Primary/Secondary Control and Positive Measures of Psychological Adjustment…………………………………………..70

6.3

Personality, Control and Psychological Adjustment…...71

6.3.1

The Relationship Between Personality and Positive Psychological Adjustment………………………….72

6.3.2

Conceptual Similarities Between Coping and Primary/Secondary Control………………………...75

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6.3.3

Differences Between Coping Measures and the Measurement of Primary/Secondary Control………78

6.3.4

The relationship Between Personality (Extraversion and Neuroticism) and Coping……….80

6.4 Hypotheses for Study 2…………………………………… 81 CHAPTER 7 – STUDY 2: METHOD 7.1 Participants…………………………………………………84 7.2 Materials……………………………………………………84 7.3 Procedure…………………………………………………...87 CHAPTER 8 – RESULTS: STUDY 2 8.1 Data Screening…………………………………………..….89 8.2 Factor Analyses and Reliability Analyses of the Primary and Secondary Control Scale (2nd Version)………………...89 8.3 Replication of Initial Hypotheses: Hypothesis 1 – The Relationship Between Primary/Secondary Control and Positive Adjustment Variables……………………………..92 8.3.1 Hypothesis 2 – The Role of Maintaining a Balance Between Control Processes for Positive Psychological Adjustment…………………………………………….93 8.3.2

Hypothesis 3 – Secondary Control as Simply a Back-Up Strategy for Low Primary Control………....95

8.4 Exploratory Analysis: The Role of Personality in Explaining the Relationship Between Control and Positive Psychological Adjustment…………………....97

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CHAPTER 9 – DISCUSSION OF STUDY 2

9.1 The Measurement of Primary/Secondary Control: The Primary and Secondary Control Scale (PSCS)…………..103 9.2 Primary/Secondary Control and Positive Psychological Adjustment…………………………………….105 9.3 The Primacy of a Balance in the Levels of Primary and Secondary Control for Positive Psychological Adjustment…..107 9.3.1 Possible Explanations for the Primacy of the Primary/Secondary Control Balance in Positive Psychological Adjustment………………………110 9.4 Secondary Control’s Functional Role in Adjustment is Greater Than Simply Compensating For Low Primary Control……………………………………..115 9.4.1 The Function of Secondary Control in Positive Psychological Adjustment………………………117 9.5 The Role of Personality in Explaining the Relationship Between Primary/Secondary Control and Positive Psychological Adjustment…………………………..120 9.6 Further Limitations and New Directions for Research……….123 CHAPTER 10 – CONCLUDING OVERVIEW 10.1 Summary and Conclusion…………………………………..125 10.2 Clinical Implications………………………………………..130 REFERENCES……………………………………………………134

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List of Tables

Table 4.1 Abbreviated Items and Factor Loadings for the PSCS (initial extraction)……………………………………….46 Table 4.2 Primary and Secondary Control Factors and Item Loadings for the PSCS………………………………………50 Table 4.3 Means and Standard Deviations for Factor 1 (Primary Control) and Factor 2 (Secondary Control) for The Total Sample (N = 192), Participants < 45 Years of Age and Participants > 45 years…………………………………………….54 Table 4.4 Summary Table for Multivariate Analysis of Variance Examining Group Differences in Subjective Quality Of Life, Positive Affect and Positive Thinking for the Four Combinations of Primary & Secondary Control……………………………………...56 Table 4.5 Summary Table for Hierarchical Regression Analyses Investigating The Relationship Between Primary/Secondary Control And Subjective Quality of Life for Participants with High Primary Control and Participants with Low Primary Control…………………..58 Table 4.6 Standard Regression Analyses Investigating the Relationship Between Primary/Secondary Control and Measures of Positive Psychological Adjustment………………………59 Table 8.1 Primary and Secondary Control Factors and Item Loadings for the PSCS (2nd Version)……………………………..91

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Table 8.2 Study 2: Standard Regression Analyses and Squared Semi-Partial Correlations (% of Unique Variance Accounted for) Investigating The Relationship Between Primary/Secondary Control and Measures of Positive Psychological Adjustment (Subjective Quality of Life, Positive Affect and Positive Thinking)…………………………………………………92 Table 8.3 Study 2: Summary Table for Multivariate Analysis of Variance Examining Group Differences in Subjective Quality of Life, Positive Affect and Positive Thinking for the Four Combinations of Primary & Secondary Control………………………94 Table 8.4 Study 2: Summary Table for Hierarchical Regression Analyses Investigating the Relationship Between Primary/Secondary Control and Subjective Quality of Life for Participants with High ( N = 94) and Low (N = 75) Primary Control………………….……………………………………………..96 Table 8.5 Study 2: Summary Table for Hierarchical Regression Analyses Predicting Subjective Quality of Life (SQOL) and Positive Thinking with Personality Variables (Neuroticism & Extraversion) and Control Variables (Primary & Secondary Control)……………………………………………………98 Table 8.6 Study 2: Summary Table for Hierarchical Regression Analyses Predicting Positive Affect and Negative Affect with Personality Variables (Neuroticism & Extraversion) and Control Variables (Primary & Secondary Control)………………………………………………………………..99

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Appendices Appendix A1: Information Sheet and Covering Letter Sent to Participants for Study 1

Appendix A2: Information Sheet and Covering Letter Sent to Participants for Study 2

Appendix B1: Questionnaires Used in Study 1 and Brief Notes Describing the Origin of Items for the Primary & Secondary Control Scale (PSCS 1st version) Appendix B2: The 2nd Version of the Primary & Secondary Control Scale (PSCS) and the Extraversion and Neuroticism scales from the NEO FFI Personality Inventory

Appendix C1: Ethics Approval Documents for Study 1

Appendix C2: Ethics Approval Documents for Study 2 Appendix D1: Examiners’ Reviews

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CHAPTER 1 INTRODUCTION TO STUDIES OF PRIMARY AND SECONDARY CONTROL

1.1 General Introduction: An Overview Over the past thirty years extensive psychological theory and research has produced a wide variety of constructs explaining how people may develop a sense of control over the environment and outcomes in life. One recent conceptualisation of control currently under investigation has expanded the control concept to include two-processes of control. Primary control refers to perceptions, beliefs or actions aimed at manipulating the objective conditions of situations. Secondary control refers to perceptions, beliefs or actions aimed at controlling one’s internal reactions to events, in order to reduce their psychological impact. Recent theorising proposed that primary control has greater adaptive value than secondary control, and secondary control is conceived as a back-up strategy when primary control is low. The following analysis of the literature suggests that these theories are oversimplified, and that maintaining a balance between the levels of primary and secondary control is optimally adaptive. Furthermore, it is argued that secondary control may have intrinsic adaptive value for the individual; rather than functioning only as a back-up strategy. In addition, it is argued that psychological adjustment has been narrowly defined in the control literature and that more comprehensive and positive measures of psychological functioning should be used to explore the relationship

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between control processes and psychological adjustment. A more comprehensive and positive method of operationalising adjustment can be achieved by measuring subjective quality of life as well as a mix of cognitive and affective processes such as positive affect and positive thinking.

1.2 Control Concepts and Definitions: A Brief Review

In the late 1950’s and 1960’s researchers began to take an interest in the psychology of personal control. During the 1950’s, the early behaviourist movement removed psychological concepts such as self-control, will and voluntary control of consciousness from psychology’s research agenda, to assist in the development of a new scientific study of human behaviour (Shapiro, Schwartz & Astin, 1996).

However, over the following three decades, a substantial body of literature on control was developed offering a plethora of definitions and conceptions of personal control and control related constructs. It must be noted that the following descriptions are a selection of concepts and in no way represent an inclusive overview of the enormity of psychological constructs that have been related to control (for an overview see Rodin, Schooler & Schaie, 1990).

As examples which demonstrate the breadth of the available constructs, Averill (1973) conceived personal control as comprising three main strategies, or types of control: behavioural control (direct action over the environment), cognitive (the interpretation of events) and decisional (exercising choice amongst goals). Rotter (1966) proposed the locus of control construct which viewed control as a

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generalised belief concerned with whether the person perceived outcomes in life as contingent on their own actions (internal locus of control) or on forces outside of the self (external locus of control). Baron and Rodin (1978) emphasised the difference between perceived control and the persons’ actual, objective ability to control outcomes. Rodin (1990) discussed the underlying theme of control within Bandura's (1977) theory of self-efficacy and outcome expectancies. Peterson and Stunkard (1989) defined control as a person’s belief in their ability to bring about good outcomes and avoid negative outcomes, and Langer, (1975) proposed that control was sometimes a cognitive illusion.

Whilst numerous control-related constructs have been explored, the dominant conceptualisation overall has equated personal control with the person’s actual or perceived ability to influence existing social, physical and behavioural situations (Rothbaum, Weisz & Snyder, 1982; Weisz, Rothbaum & Blackburn, 1984; Ormel & Sanderman, 1989; Evans, Shapiro & Lewis, 1993; Shapiro et al., 1996). That is, the ability to actively influence and shape one’s environment to fit the needs and desires of the individual. According to Weisz, et al. (1984) and Shapiro, et al. (1996) this view of control reflects Western psychology’s culturebound emphasis on the value and importance of changing or controlling situations; rather than controlling the psychological impact of outcomes by controlling self-related processes (e.g. interpretations, attributions etc.).

1.3 Primary and Secondary Control: The Two-Process Model of Control

Rothbaum et al. (1982) broadened the traditional concept of control to include two processes of control, primary control and secondary control. In effect, this

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new construct provided the basis for a less culture-bound conception of personal control that included the notion of controlling the psychological impact of events.

Proponents of the the two-process model (Rothbaum et al., 1982; Weisz et al., 1984; Shapiro, 1987; Weisz, 1990; Rosenberg, 1990; Heckhausen & Schulz, 1995) conceptualise two paths by which a person can develop a sense of control. Primary control describes the traditional view of control in which people develop a sense of personal control by manipulating the objective conditions of the environment to fit their needs and wants (Weisz, 1990). Alternatively, secondary control involves the person accommodating to the objective conditions in order to maximise their fit with the existing environment; thus controlling the psychological impact of objective life outcomes (Weisz et al., 1984).

Weisz et al. (1984) provided a comprehensive description of the two-process model. The general strategy of primary control is to influence “existing realities”. As such, the typical targets for control are “...other people, objects, environmental circumstances, status and behaviour problems”. In contrast, the general strategy of secondary control is to accommodate to the existing reality. In this case, the entities being controlled are typically cognitive, such as “...self’s expectations, wishes, goals, perceptions, attitudes, interpretations and attributions” (p. 956).

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1.3.1 Specific Secondary Control Strategies

Rothbaum et al. (1982) outlined four types or strategies of secondary control and provided details of extensive social-psychological evidence to support each of the types: predictive, illusory, vicarious and interpretive secondary control.

Predictive secondary control involves a process of making attributions for task performance to one's severely limited ability (e.g. “It was too hard for me”). Such attributions may result in the person reducing their expectations for success, thus allowing a degree of prediction over future outcomes (e.g. “I don’t expect to do very well”). Paradoxically this reduction in expectancy affords the individual control over the psychological impact of potentially uncontrollable outcomes by avoiding disappointment (a process complimented by behaviourally withdrawing). According to Rothbaum et al. (1982) disappointment after a course of action is highly aversive since it highlights the person’s complete lack of control. That is, not only have efforts at controlling the situation failed (primary control), but controlling the emotional impact of the failure (secondary control) is also frustrated.

Illusory control involves externalising one’s sense of control to chance factors. Although chance is objectively random, Rothbaum et al. (1982) proposed that people actually attempt to align themselves with chance processes, believing themselves to be “lucky”. Belief that “luck is on my side” allows some people a sense of control over the negative psychological impact (e.g. worry and anxiety) associated with potentially uncontrollable events.

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Vicarious control also involves a process of externalising one’s sense of control, by attributing control to an entity perceived to be more powerful and in control than oneself (e.g. God, nature, a powerful business associate). Thus, the person seeks a sense of control by aligning themselves with, and sharing in the control of another.

Underlying all of the above strategies is the strategy of interpretive control. Interpretive control involves a process of striving to derive meaning and make sense of problematic events; hence, allowing the individual to control the psychological impact of aversive events by having an explanation for problems.

1.3.2 Alternative Conceptions of Primary/Secondary Control

According to Thompson, Nanni and Levine (1994), conceiving secondary control in terms of the above mentioned strategies outlined by Rothbaum et al. (1982) is somewhat problematic since these strategies do not have similar implications for coping (see Mendola, Tennen, Affleck, McCann & Fitzgerald, 1990; Helgeson, 1992; Reed, Taylor & Kemeny, 1993; Carver, Pozo, Harris, Noriega, Scheier, Robinson, Ketcham, Moffat & Clark, 1993).

Rothbaum et al. (1982) believe that it is the adaptive consequences of secondary control that differentiate it from passive helplessness. Thus, secondary control should be operationalised in ways that demonstrate consistent positive relationships with measures of psychological adjustment. Hence, a less problematic way to conceptualise and operationalise secondary control is to emphasise the basic process that characterises secondary control, a process that

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Rothbaum et al. (1982) argue is commonly associated with positive outcomes. That is, acceptance of the objective conditions in one's life.

In addition, Thompson, Cheek & Graham (1988) and Weisz (1990) suggested that primary and secondary control are conceptually related to the concept of problem-focused and emotion-focused coping, respectively. Coyne, Aldwin & Lazarus (1981) defined problem-focused coping as referring to “...efforts to deal with sources of stress, whether by changing one’s own problem maintaining behaviour or by changing environmental conditions”. In contrast, emotionfocused coping was defined as “...coping efforts aimed at reducing emotional distress” (p.440). In comparison with the previous definition of primary and secondary control offered by Weisz et al. (1984), the problem-focused and emotion-focused constructs are almost indistinguishable conceptually. Furthermore, specific secondary control strategies outlined by primary/secondary control theorists (Rothbaum et al., 1982; Heckhausen & Schulz, 1995) have the ultimate function of controlling the psychological impact (particularly the emotional impact) of outcomes in life; as do emotion-focused coping strategies (see Carver, Scheier & Weintraub, 1989). For example, predictive secondary control functions to protect the person from disappointment whilst “positive reinterpretation” (an emotion-focused strategy) serves to reduce emotional distress associated with life events (Carver et al., 1989 p.269).

1.3.3 The Expanding Classification of Secondary Control Strategies

Whether one conceives of secondary control in terms of the specific processes outlined by Rothbaum et al. (1982), more generally in terms of acceptance

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(Thompson et al., 1994) or in terms of the related construct of emotion-focused coping (Weisz, 1990), the concept of controlling the psychological impact of events has led to a growing number of psychological strategies being conceived in terms of secondary control processes.

For instance, Weisz (1990) described the process of selective attention as a secondary control strategy in which the person focuses attention away from a problem so as to reduce the impact of the aversive thoughts and feelings associated with it. Heckhausen and Schulz (1995) described the process of socially comparing oneself with people worse off as a secondary control strategy that helps a person accept poor outcomes. In addition, attributional processes involving attributions for failure to external causes and success to internal causes were construed as a secondary control strategy that allows people to protect and control their level of self-esteem. Furthermore, Cummins (1997a) identified fifteen separate secondary control processes (such as optimistic expectancies and creating worse case scenarios) that allow people to maintain a sense of control over their external and internal environments (self-esteem and subjective well-being).

1.3.4 Primary Control Strategies

According to Rothbaum et al. (1982) and Weisz (1990) the strategies of predictive, illusory, vicarious and interpretive secondary control also have their primary control counterparts. For example, predictive primary control may involve trying to accurately predict, select and execute the strategies that are most likely to alter the environment to fit one's needs and wishes. Illusory primary control may involve attempts to influence chance to allow a better fit with the desires of the person (e.g. spitting on a coin before tossing or “riding a

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lucky streak”). Primary vicarious control may result in a person emulating the behaviour of powerful others in order to influence the environment. Lastly, primary interpretive control involves attempts to make sense of a problem in order to be able to master it, influence it and reduce it's likelihood of recurrence (Weisz, 1990).

The analysis above suggests that both primary control and secondary control can involve similar processes. For example, believing in another's power to control (i.e. vicarious control) can be both a primary and secondary control strategy. According to Weisz (1990), the principle distinction determining whether any particular strategy is of the primary or secondary type must be inferred from the person's overall reason or goal for control; either to change the objective conditions of the environment (primary control), or to accept the objective circumstances and seek to control the psychological impact of those conditions (secondary control).

In summary, according to the two-process model of control, there are two paths a person may pursue to develop a sense of personal control. Primary control is a strategy involving attempts to influence or change objective conditions in the environment. In contrast, secondary control involves accepting the existing environmental conditions as they are, and focusing on controlling internal processes in order to control the psychological impact of outcomes. Primary and secondary control can be conceived in terms of specific strategies, as a general strategy of acceptance, or in terms of problem-focused and emotion focused coping. These various conceptions have allowed for a wide variety of cognitive

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and behavioural strategies to be understood in terms of primary and secondary control processes.

What then are the benefits or costs of seeking a sense of control, whether it be a sense of primary control or secondary control?

1.4 The Relationship Between Primary/Secondary Control and Psychological Adjustment: The Adaptive Value of Primary Control

A substantial body of empirical studies and literature reviews suggest a significant relationship exists between primary control beliefs and levels of psychological distress or adjustment to illness. This research suggests the adaptive value of perceived primary control.

For instance, cancer patients’ levels of anxiety and depression have been found to be significantly negatively correlated with primary control beliefs related to control over physical symptoms (r = -.59), family relationships (r = -.29) and relationships with friends (r = -.41) (Thompson, Sobolew-Shubin, Galbraith, Schwankovsky & Cruzen, 1993). Taylor, Lichtman and Wood (1984) also found, amongst a sample of women with breast cancer, that perceptions of personal control and other's control (e.g. medical staff) over their cancer were significantly related to better adjustment to their illness.

Thompson et al. (1994) found that primary control was significantly negatively correlated with depression amongst a sample of HIV-positive men (r = -.40), even when controlling for the amount of stressful life events associated with

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living with HIV. Furthermore, primary control beliefs remained predictive of less depression within a particularly low-control circumstance (HIV-positive and incarcerated in prison) (Thompson, Collins, Newcomb & Hunt, 1996).

In addition, Weisz (1990) in a review of his own empirical studies, provided evidence for the potential adaptive value of primary control beliefs in children. Control beliefs were operationalised in terms of the child's belief in their competence, contingency and control in solving problems at school and at home. The operationalised focus on control as a method for solving external circumstances lends itself to a primary control classification. Results indicated that perceived competence beliefs accounted for approximately 14 percent (r = -.38) of the variance in a measure of childhood depression. Furthermore, contingency and control beliefs were also found to be significantly correlated with children’s behavioural improvements in response to a six-month course of psychotherapy (r = .48 and r = .41, respectively).

Research on the personality construct of hardiness (Kobasa, 1979) also indicates the adaptive value of perceived primary control. After reviewing research investigating the relationship between health and the individual components of the hardiness construct, Wallston (1989) concluded that perceived control (defined as the ability to influence events) is a major, if not the major component of hardiness that explains the buffering effects of hardiness from physical and emotional ill-health.

Similarly, Peterson and Stunkard (1989) in their review of control and health research cite a large number of studies implicating the link between control

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(defined as the ability to bring about good events and avoid bad events) and physical and psychological health, claiming that the link is now “...well established” to the point that precise mechanisms should be investigated (p.822).

1.4.1 The Adaptive Value of Secondary Control

The previous discussion of secondary control strategies provides a conceptual basis for understanding how secondary control may relate to psychological adjustment. That is, by definition, the strategies aim to reduce or control the psychological impact of objective conditions. Moreover, empirical evidence suggests that secondary control strategies do indeed relate to better psychological adjustment.

Thompson et al. (1993) asked patients with cancer to rate the degree to which they perceived they had control over the symptoms of the disease and control over the negative emotions associated with a cancer diagnosis. Whereas perceptions of control over the objective conditions of the cancer symptoms reflect primary control, the perception of control over the emotional impact of cancer reflects secondary control processes. They found that patients who perceived control over their emotions accounted for 49% of the variance

(r = -.70) in patients emotional adjustment; defined by levels of anxiety and depression. Secondary control strategies reported by the patients included, keeping “faith” and a “positive attitude” (p.301).

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By operationalising secondary control in terms of acceptance over outcomes associated with HIV diagnosis, Thompson et al. (1994) also found that secondary control significantly predicted lower levels of depression.

Carver et al. (1993) used an emotion-focused coping scale that measured secondary control strategies including acceptance of stressful events, turning to religion, positive reframing, and use of humour amongst women diagnosed with early stage breast cancer. Results showed that acceptance, humour and positive reframing all had significant associations with less distress. Furthermore, after controlling for the inter-relationships amongst the various strategies, acceptance and positive reframing remained unique predictors of distress.

Similarly, Carver et al. (1989) found that accepting stressful events was significantly related to optimistic beliefs, whilst positive reinterpretation was associated with optimism, feelings of control, self-esteem, hardiness and less anxiety amongst a sample of undergraduates.

In addition, the tendency to re-interpret a stressful event (impaired fertility) as leading to a strengthening in one's marriage, and attributing the loss to external bio-medical causes, was shown to predict lower levels of psychological distress (Mendola et al., 1990).

Overall, the studies described above would suggest that both primary and secondary control strategies are associated with good psychological adjustment to illness and positive mental health. Nevertheless, recent theoretical proposals and research efforts have made an effort to determine which strategy (primary

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control or secondary control) may play the more important role in adapting to negative outcomes in life.

1.5 The "Primacy" of Primary Control

Heckhausen and Schulz (1995) proposed the functional primacy of primary control over secondary control. In short, they argue that primary control has greater functional importance for the individual than does secondary control. There are two key aspects to this proposition. Firstly, the authors suggest that primary control has greater adaptive value for the organism because it allows the person to control their environment to fit the individual's particular needs; therefore allowing the person to reach their "...full developmental potential" (p.286). Hence, the theory proposes that an individual who manipulates situations to get what they need, will actualise greater positive growth than someone who accommodates to the existing conditions in order to control the psychological impact of events.

Secondly, primacy theory argues that the function of secondary control is to act as a compensatory mechanism to protect the person against actual or anticipated losses in primary control (Heckhausen and Schulz, 1995). According to the theory, when an individual anticipates failure or actually does fail (i.e. anticipates or experiences a loss of primary control), secondary control strategies help the person to re-establish their sense of primary control over the environment. For example, when an employee feels that they have failed, attributing their performance to external factors such as over-work and stress (rather than personal factors such as competence) protects their self-esteem and

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assists them in re-developing a sense of personal efficacy or control over the demands of their job.

1.5.1

Empirical Tests of Secondary Control as Simply a Back-Up Strategy for Low Primary Control

Thompson et al. (1994) conducted a study amongst people living with HIV to test whether secondary control acted as a compensatory (back-up) mechanism for people with low primary control. Hence, they hypothesised that secondary control would be associated with less depression amongst individuals with low perceptions of primary control, but for those with higher perceptions of primary control, secondary control would not be associated with less depression. The researchers claimed that the hypothesis was supported since there was only a "weak" relationship between secondary control and depression amongst those with high primary control (p.543). In contrast, for those with low primary control, secondary control was associated with less depression.

However, due to the lack of thorough statistical reporting it is difficult to assess the exact degree to which the hypothesis was supported. That is, no correlational analysis is reported which shows the relative associations between secondary control and depression amongst high and low primary control subgroups. Instead, the reader is referred to a plot, without scales, plotting secondary control against depression. The absence of scales on the plot and the unreported correlations make it impossible for the reader to judge how “weak” the relationship between secondary control was for those with high perceived primary control. According to primacy theory, if secondary control acts only as

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a back-up strategy then secondary control should be uncorrelated with depression amongst individuals with adequate levels of primary control. However, there is no statistical report of the hypothesised lack of relationship.

Thompson et al. (1996) repeated the hypothesis of secondary control as a backup strategy amongst a group assumed to be characterised by particularly low levels of perceived primary control (prison inmates with HIV). The results showed that secondary control did not predict levels of depression amongst individuals with low, nor high perceptions of primary control. Thus refuting the hypothesis that secondary control acts as a back-up strategy for low primary control. The fact that secondary control did not predict less depression in this study was inconsistent with numerous other studies that have found secondary control to be associated with less depression and distress (Taylor et al., 1984; Carver et al., 1989; Mendola et al., 1990; Carver et al., 1993 & Thompson et al., 1994). The researchers suggested that the sample in the study may have equated acceptance with helplessness, and therefore secondary control did not predict lower levels of depression.

The hypothesis that secondary control acts as a back-up strategy when primary control is low, has received mixed empirical support. Moreover, some research suggests that secondary control may have a greater role for adaptive functioning than simply acting as a back-up strategy. For example, cross-cultural research suggests that while Western culture emphasises the importance of primary control, Eastern culture emphasises the greater importance of secondary control over primary control.

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1.5.2

Cultural Differences in Preferences for Primary Versus Secondary Control: Is Secondary Control Used Only as a Back- Up Strategy ?

Weisz et al. (1984) argue that Western culture encourages and emphasises the value of primary control, whereas Japanese culture prefers the use of secondary control. They cite numerous examples of differences in child-rearing practices, socialisation, work practices, religion, philosophy and psychotherapy which reflect Japanese culture's greater preference for secondary control over primary control. For instance, Western schools of psychotherapy (e.g. behaviour therapy and psychoanalytic therapy) often emphasise the importance of reducing symptoms and changing behaviour problems. In contrast, the Japanese Morita and Naikan schools of psychotherapy emphasise the importance of reducing distress by accepting one's symptoms and developing a sense of meaning to those symptoms through re-interpretation.

Furthermore, Azuma (1984) pointed out numerous popular Japanese aphorisms which view the ability to yield and accept (as opposed to asserting oneself over others and situations) as a sign of self-control, maturity and flexibility. For example, when Japanese children argue, parents may gesture the phrase "...to lose is to win"; meaning that it is more highly valued to yield than assert oneself (p.970).

Although researchers have described Japanese culture as emphasising a greater preference for secondary control (Weisz et al., 1984; Azuma, 1984; Kojima, 1984), the role of yielding and accepting circumstances is not absent from

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Western culture. Rosenberg (1990) cited the Western fable of the fox and the grapes, in which the fox's attempts at primary control (reaching for the grapes) fails, leaving the fox to ameliorate his disappointment by declaring the grapes were sour (secondary control).

In addition, cognitive therapy often teaches clients skills aimed at controlling one’s internal cognitive/affective reactions to situations, rather than changing the situation per se. For example, Burns (1980) gives the example of a mother who berates herself as a “bad mother” (p.73). Rather than developing primary goals for becoming a ‘good mother’ (e.g. by spending more time with the children), cognitive therapy is aimed at teaching her not to interpret her self in terms of dichotomous categories such as good and bad. By learning to perceive her mothering skills more accurately, and manipulating her attentional focus to her positive actions (not just negative ones), the client seeks to control their depressed emotional state rather than the perceived mothering problem.

Furthermore, as discussed previously, Western patients with cancer and HIV have been found to use secondary control strategies such as humour, acceptance, re-interpretation and optimistic beliefs in order to cope (Mendola et al., 1990; Carver et al., 1993; Thompson et al., 1994).

In summary, it has been suggested that certain cultures may actually show a preference for secondary control and that the potential benefits of secondary control are also evident in Western culture. Combined with the previous analysis that indicated mixed empirical support for the back-up hypothesis of secondary control, it is possible that secondary control strategies have intrinsic

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value beyond their potential to compensate for low levels of primary control. That is, although the compensatory role of secondary control as proposed by Heckhausen and Schulz (1995) is intuitively logical and supported by some evidence, the current analysis suggests that secondary control may have functional value in its own right.

In short, conceptualising secondary control as merely a back-up strategy for primary control potentially under-rates the adaptive value of secondary control strategies as proposed by the original authors of the primary/secondary control construct (Rothbaum et al., & Weisz et al., 1984).

1.5.3 Empirical Tests of the Greater Adaptive Value of Primary Control

Thompson et al. (1996) hypothesised that primary control has greater adaptive value than secondary control (acceptance). That is, primary control would be more strongly associated with less psychological distress than secondary control. The researchers claim that this hypothesis was supported because primary control predicted levels of distress when controlling for secondary control. Whereas secondary control did not account for any significant variance in levels of distress when primary control was controlled for.

However, the finding that perceptions of secondary control added no prediction of distress above that offered by primary control is not surprising considering that secondary control was found to be significantly associated with greater psychological distress. Although this association was statistically significant for

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only one of the four data sets (measured at different times), the direction of the correlation between distress and secondary control was always positive. Thus, it remains to be seen whether the “...greater adaptive value” of primary control (Thompson et al., 1996 p.1307) is maintained in a sample that shows secondary control to be helpful in the first place. As the evidence stands now, it can only safely be said that primary control is more adaptive than secondary control when the sample perceives secondary control as unhelpful.

In summary, only two empirical studies have hypothesised and explicitly tested the primacy of primary control theory (Thompson et al., 1994; and Thompson et al., 1996), resulting in mixed support for the potentially superior benefits and greater functional importance of primary control versus secondary control. In addition, difficulties associated with the statistical reporting and samples used in these studies throw some doubt onto the precise degree of support for primacy theory. Regardless of the above analysis, Thompson et al. (1996) concluded that “...there may be no limits to the benefits of primary control” (p. 1316). However, other control research is not so supportive of the “limitless benefits” of primary control.

1.5.4

The Adaptive Limits of Primary Control

As discussed previously, theoretical as well as empirical evidence demonstrate significant associations between primary control and positive psychological adjustment, suggesting the adaptive value of primary control. However, it has also been suggested that primary control may be associated with reduced psychological and physical health.

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In terms of psychological health, Shapiro and Shapiro (1984) discussed a model of intimate relationships in which issues of control are seen as central to the adaptive or non-adaptive functioning of the relationship. According to their model, “assertive control” over situations and people (i.e. primary control) may be positive in that it initially brings the person (and the couple) a sense of effectiveness, achievement and competence (p.97). However, if one partner develops a reliance on primary control over time, this may adversely impact on the quality of the relationship. A partner who relies on primary control may be perceived as over-controlling, domineering and aggressive. Without the knowledge and ability to yield some primary control and to accept another’s views on some issues (secondary control), conflict may result.

Thompson et al. (1988) reviewed a number of control studies that suggested negative effects of perceived control over situations. Their review suggested that there may be many factors that determine whether perceived control will be helpful or harmful to the individual. The relevant factors included: the amount of effort and attention needed to exercise control over a stimulus, whether attempts to exercise control were successful, the preferred coping style of the person and the actual amount of perceived control.

Considering this last factor, research suggests that higher opportunities for primary control can be associated with increased levels of distress. Mills and Krantz (1979) showed that the more opportunities to control the situation offered to patients giving blood, then the greater the level of patient distress. Likewise, Corah and Boffa (1970) found that both a behavioural and decisional mode of

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control independently reduce levels of distress in subjects exposed to experimental threat. When given the opportunity to exercise both modes of control, subjects reported as much discomfort as they did when given no behavioural or decisional control over the threat. It was not clear why more opportunity for primary control was associated with increased stress in these studies. As Averill (1973) commented, whether having control is helpful or harmful in reducing stress depends on the context in which the control response is made. Hence, Mills and Krantz (1979) suggested that people in a blooddoning procedure may have preferred a nurse to take full control. According to the authors, the greater opportunity for control over a stressor may heighten stress in situations in which the person does not want much control.

Other evidence indicates that having a high desire for control or perception of control over one’s environment may be maladaptive when the environment is objectively difficult to control, or does not require such high levels of personal control. Evans et al. (1993) reviewed control research to demonstrate that persons with a high desire for control, high competencies for control and high levels of perceived control, are more vulnerable to stress and depression within low-control environments. According to their review, the increased vulnerability may occur because high-controlling people may be unable to accommodate or accept situations that afford a low degree of control. For example, Collins, Baum and Singer (1983) found that residents involved in the Three-Mile Island power plant disaster showed lower degrees of stress (selfreported, psychophysiological and task performance) when they coped by accommodating to the reality of the situation, compared to those who attempted to instrumentally change the situation through political action and complaints.

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Similarly, when exposed to uncontrollable stimuli, individuals with a high desire for control were found to be significantly more prone to learned helplessness effects than those with a lower desire for control (Burger and Arkin, 1980). Furthermore, perceiving that others have a degree of control over the threat of disease (primary vicarious control) was only helpful when others were actually able to exert control (Helgeson, 1992). When the vicarious control of medical staff was not evident, primary vicarious control predicted poor psycho-social adjustment to cardiovascular illness.

In addition, Strube and Werner (1985) found that Type A persons had such a high need for control over their environment that they had difficulty in relinquishing control of a task to a superior performing partner. By failing to relinquish control to others, the researchers concluded that Type A persons may create high levels of stress by increasing their workload and job involvement, eroding relationships and feeling role-conflict in managerial jobs that require delegation of tasks. Indeed, partial support for these conclusions were provided by Kirmeyer and Biggers (1988) who found that Type A individuals systematically create a more demanding and more stressful work environment for themselves.

Some evidence also suggests that a high desire and perception of primary control may differentiate clinical and non-clinical populations. For instance, Shapiro, Blinder, Hagman and Pituck (1993) found that perceiving too much control over situations and people (over-control) is a factor that discriminated between women with eating disorders and those with healthy eating habits.

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Research also indicates that high levels of perceived primary control may not be advantageous in terms of physical health. Using a structured Type A interview, researchers have found that the behavioural cluster of being verbally competitive, alert and quick to respond was prospectively associated with increased risk for coronary heart disease (Houston, Chesney, Black, Cates & Hecker, 1992). The researchers noted that this communication style is known to reflect a behavioural pattern characterised by a need for social dominance and control. Thus, the authors concluded that a high need for control and social dominance may be a salient behavioural pattern that is predictive of increased risk of heart disease.

Indeed, Seeman (1991) found that high level expectancies for primary control (mastery) were significant independent predictors of the degree of atherosclerosis in people with coronary artery disease. Most importantly, the predictive strength of primary control beliefs on disease process remained unchanged even when controlling for numerous traditional predictors of arterial disease (including smoking, age, sex, hypertension, diabetes, angina, family history and Type A behaviour). The results also indicated a possible threshold to the level of primary control that was adaptive. Higher scores on the mastery scale (above 21) were associated with greater atherosclerosis, whereas the prediction of disease symptomatology was insignificant when using all the primary control raw scores (i.e. both high and low mastery scores).

Whilst the causative role of belief systems could not be determined in Seeman’s (1991) cross-sectional study, the eight year longitudinal design of the Houston et al. (1992) study suggests that a high desire for control and social dominance

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may causatively influence atherosclerosis. In addition, there are numerous psychophysiological paths by which high levels of perceived primary control are suspected to influence coronary risk (e.g. increased levels of blood catecholamines and increased blood pressure; Seeman, 1991).

In summary, the analysis above suggests that primary control (beliefs and actions) may have an adverse impact on psychological and physical health. A common theme amongst most the studies described is that of excesses of primary control beliefs or activity. Thus, to perceive, expect or seek too high levels of primary control may be one important factor in determining whether primary control is associated with positive health, or alternatively, ill-health.

1.6

The Adaptive Limits to Secondary Control and Primary/Secondary Control Imbalances

By definition, secondary control involves leaving existing realities or situations unchanged and alternatively controlling the psychological impact of events (Rothbaum et al., 1982; Weisz et al., 1984). Therefore, to the extent that an individual prefers accepting situations as they are (secondary control), rather than seeking to change situations (primary control), implies a persistent passive interaction with the environment. Burger and Cooper (1979) characterised the person with a low desire for control over situations as “...generally nonassertive, passive, and indecisive” (p.383). Hence, whilst controlling the psychological impact of events may have adaptive value (as previously discussed), research shows that the tendency to accept and leave situations unchanged can also be non-adaptive.

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Anderson, Kiecolt-Glaser and Glaser (1994) proposed a model of adjustment to cancer in which an absence of efforts to control the disease results in poorer psychological and physical adjustment to illness. Their review of the literature indicated the need for patients to assert control over psychological stress and physical disease by exercising regularly, maintaining a nutritious diet and complying closely to the medical regimens for cancer. Patients who did not exercise such controls over the symptoms demonstrated a poorer physical and psychological prognosis.

Optimistic beliefs can also make an individual prone to potentially non-adaptive inactivity. Optimism can be construed as a secondary control strategy in so far as it may engender feelings of self-esteem and reduced stress in the face of adversity (Sheier & Carver, 1992). That is, optimism may assist the person in controlling the psychological impact of real and anticipated threats. Indeed, a sense of optimism about personal risks can be associated with less depression (Alloy & Athrens, 1987). However, as Weinstein (1980) found, optimism also entails people judging themselves to be at much lower risk of experiencing misfortune (e.g. cancer and alcoholism) than others. Thus, to maintain a sense of optimism in the face of objectively risky behaviour (e.g. excessive smoking, gambling and drink driving) may prevent an individual from changing behaviours that could result in negative physical and psychological consequences (Perloff, 1983; Weinstein, 1984; Weinstein, 1989).

Secondary control conceived in terms of acceptance has also been shown to relate to increased psychological distress amongst a sample of HIV-positive men

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in prison (Thompson et al., 1996). The researchers suggested that in circumstances where there is little opportunity for primary control (HIV-positive and incarcerated in gaol), acceptance may be a forced option that feels more like helplessness. As the studies just cited indicate, perhaps the degree to which acceptance co-occurs with leaving problematic situations unchanged (low primary control) may be the determinant of whether acceptance is helpful or harmful. Perhaps the difference between the Thompson et al. (1996) study and other studies that have only found positive benefits associated with acceptance (e.g. Carver et al., 1989; 1993; Thompson at al., 1994), is the combination of acceptance within a low primary control environment.

In summary, as the discussion above indicates, if a reliance on acceptance (secondary control) co-occurs with an absence for making instrumental changes to problematic situations (primary control), then over time the person may be prone to more negative psychological and physical health outcomes.

Overall, the literature suggests that an imbalance in levels of primary and secondary control perceptions or actions may be non-adaptive. As suggested previously, too high levels of primary control are associated with negative physical and mental health outcomes. Likewise, secondary control may be nonadaptive for the individual when it is combined with low levels of primary control.

1.7 The Adaptive Value of Maintaining a Balance Between Levels of Primary and Secondary Control

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The original proponents of the two process model (Rothbaum et al., 1982) conceptualised the adaptiveness of control in terms of a primary/secondary control balance; as opposed to primacy theory (Heckhausen & Schulz, 1995; Thompson et al., 1996) which conceived adaptiveness in terms of a greater degree of primary control. As Rothbaum et al. (1982) state, “the shift from a concern with the optimal degree of control to a concern with the optimal balance between different processes of control is one of the most significant implications of the two-process model” (p. 29). They give the example of a person who relies too much on primary control efforts, persisting at an insoluble task, and becoming prone to persistent disappointment. Alternatively, the person who relies on secondary control may prematurely give-up on a task that they are able to succeed at. Hence, an individual with both primary and secondary control processes available to them would be unlikely to face such dilemmas. As one control process fails, the person can adapt to the demands of the situation by developing the alternative process of control.

In addition, Weisz et al. (1984) point out that Western culture’s emphasis on achieving primary control and Japan’s cultural emphasis towards secondary control are both limited in their adaptive potential. For example, Western models of psychotherapy typically emphasise the importance of symptom reduction, but these models have limited value when the symptoms are not easily controllable through primary efforts (e.g. brain injury and chronic schizophrenia). In contrast, Japanese schools of psychotherapy which emphasise the acceptance of symptoms, may often miss real opportunities to implement change by directly altering the problematic situation. The researchers believe that a balance of both primary and secondary control

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strategies is most adaptive, a balance most easily achieved by an individual with their “...cultural blinders removed” (p. 955).

Whilst the theoretical discussions cited above indicate the adaptive value of a balance of control processes, no empirical study has investigated the adaptive value of a control balance. The paucity of empirical studies investigating the balance hypothesis, is contrasted to the majority of primary/secondary control studies which have argued for the adaptive primacy of primary control over secondary control (Heckhausen & Schulz, 1995; Thompson et al., 1994; Thompson et al., 1996). If Western psychology does emphasise the greater importance of primary control as some suggest (Weisz et al., 1984; Shapiro, 1987; Shapiro et al., 1996), then the idea of an adaptively superior form of control (primacy theory) may be further reflection of Western psychology’s culture-bound emphasis on the importance of primary control.

1.8 Summary

While some have argued for the adaptive primacy of primary control over secondary control, the above analysis suggests that primacy theory may have oversimplified the relationship between primary/secondary control and psychological adjustment. That is, there is limited empirical support for the hypothesis that secondary control functions only as a back-up strategy for low primary control. In addition, researchers have indicated that Japanese culture shows a preference for secondary control over primary control. On the basis of these results, it is argued that secondary control may have intrinsic adaptive

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value in it’s own right and not just function to compensate for low levels of primary control.

Furthermore, the hypothesis that primary control has greater adaptive value than secondary control may also be over-simplified. The literature suggests that primary control can be associated with positive psychological health, but too much primary control is associated with negative physical and psychological health outcomes. In this case, adaptive control is not simply represented by higher levels of one type of control.

Therefore, it is argued that a more accurate account of the relationship between primary/secondary control and psychological health can be achieved by theoretically construing adaptive control in terms of a balance between levels of the two control processes. Whilst a number theoreticians have suggested the adaptive importance of a balance between control processes, empirically the hypothesis has not been explicitly tested. Some research does suggest that an imbalance between levels of primary and secondary control may be nonadaptive. For example, research indicates that secondary control may be nonadaptive for the individual when combined with low levels of primary control. In addition, as stated previously, too high levels of primary control have been associated with poor psychological and physical adjustment. Thus, one of the aims of the present study is to investigate the relationship between a balance of control processes and psychological adjustment.

The whole question of what is adaptive psychological functioning has been narrowly defined in studies investigating the relationship between control and

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adjustment. Many studies have demonstrated the association between control and negative affective states (depression, anxiety and distress). However, no research has investigated the relationship between primary/secondary control processes and more positive and comprehensive measures of psychological adjustment such as subjective quality of life, positive affect, and measures of positive thinking.

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CHAPTER 2

OPERATIONALLY

DEFINING PSYCHOLOGICAL ADJUSTMENT

CONTROL RESEARCH

2.1 The Negative Affect Bias in Control-Adjustment Research

Previous studies investigating the relationship between control and measures of psychological adjustment have narrowly operationalised adjustment in terms of an absence of negative affect. For instance, Mendola et al. (1990) measured global distress from the SCL-90 (Derogatis, 1977); Carver et al. (1993) measured anxiety, depression and anger; Thompson et al. (1993) measured depression and anxiety; and Helgeson (1992) measured depression, anxiety and hostility. Whilst there are a few exceptions (Taylor et al., 1984; Affleck, Tennen, Pfeiffer & Fifield, 1987), the overall tendency in control research has been to operationalise adaptive functioning in terms of negative affect such as depression and anxiety. Amongst studies that explicitly investigated the relationship between primary/secondary control processes and adjustment (Thompson et al., 1994; 1996), adjustment has only been defined in terms of negative affect (depression and anxiety).

Operationally defining adjustment in terms of negative affect can be considered narrow for two reasons. Firstly, adjustment is construed only in terms of affect or emotion, whereas adaptive functioning may involve other psychological processes such as positive thinking, and other domains of human experience such as satisfaction with one’s relationships, material well-being, health, and

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productivity. Indeed, Rothbaum et al. (1982) commented on the difficulty of measuring the adaptive value of control processes. What may be considered adaptive outcomes for one person may be less valuable to another. For example, some people may value high achievement and meeting challenges, which are fostered by primary control, whereas others may value feelings of contentment and safety which are best developed through secondary control.

Secondly, adjustment is construed only in terms of negative affects. However, evidence from the human affect literature suggests that finding a relationship between primary/secondary control and negative affects, does not imply a relationship with measures of positive affect. That is, empirical studies on human affect have demonstrated positive and negative affects are largely independent (Bradburn, 1969; Warr, Barter & Brownbridge, 1983; Burke, Brief, George, Roberson & Webster, 1989; Russell, Weisz & Mendelsohn, 1989; Hutchison and co-workers, 1996; Yik, Russell & Barrett, 1999). Researchers have explained the uncorrelated emotions in terms of different personality factors independently influencing each affect (Costa & McCrae, 1980; Emmons & Diener, 1986). In addition, different sets of demographic and personality variables have been found to independently predict positive and negative affect (Argyle, 1987). Some researchers have even suggested that positive and negative affect may be associated with different physiological systems (Tellegen, 1985). Hence, considering that positive and negative affect may be separate emotional dimensions, a

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more complete understanding of the relationship between primary and secondary control and affect can be obtained by examining both positive and negative dimensions of affect.

2.2 Towards More Positive and More Comprehensive Measures of Psychological Adjustment

Previous research may have demonstrated the relationship between primary/secondary control and negative affect, yet there has been almost no investigation of the relationship between primary/secondary control and positive affect. Affleck et al. (1987) explored the relationship between primary control and positive affect. Although they did not incorporate a measure of secondary control. Taylor et al. (1984) incorporated a measure of well-being in exploring the relationship between primary vicarious control and psychological adjustment. However, the measure of well-being was combined with measures of negative affect to obtain an overall measure of psychological adjustment. As a result, the relationship between well-being per se and psychological adjustment was not evident in the analysis.

One of the aims of the present study is to explore the relationship between primary/secondary control and psychological adjustment defined in terms of positive psychological processes which previous research has mostly neglected. A valid and reliable measure of positive affect, adequate for

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the purposes of the present study, is the Positive Affect sub-scale from the Positive and Negative Affect Scale (PANAS; Watson, Clark & Tellegen, 1988).

A further aim of the present study is to operationalise psychological adjustment in more comprehensive terms than simply measuring peoples’ affective or emotional experience.

One method of comprehensively

operationalising adaptive functioning is to measure quality of life. Quality of life research has identified numerous domains of experience (other than emotional) that people consistently rate as important to their quality of life (Cummins, 1997b). Flanagan (1978) in a large population survey across various regions of the U.S. found five domains that were important for peoples’ quality of life. Physical and material well-being, relationships with others, social and community activities, personal development and recreation. Whilst as many as 173 different domain names have been used in the literature, Cummins (1997b) found that as many as 83% of these names could be grouped under seven quality of life domains: material well-being, health, productivity, intimacy, safety, place in community and emotional well-being. For the purposes of the present study, a useful measure of quality of life is the Comprehensive Quality of Life Scale (Cummins, 1997b) which contains sub-scale measures of all the above mentioned life domains.

In addition, psychological adjustment could be more comprehensively defined by incorporating measures of psychological processes (other than

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emotional) such as cognitive processes, particularly positive thinking. One valid and reliable measure of positive cognition is the Automatic Thoughts Questionnaire- Positive (ATQ-P; Ingram & Wisnicki, 1988). The ATQ-P is a self-report measure assessing individuals’ frequency of positive thoughts. Measuring positive thinking would not only define psychological adjustment in terms of more positive psychological process, but would also provide a more comprehensive definition of psychological adjustment that incorporates measures other than the emotional qualities of human experience.

Hence, the present study also aims to explore the relationship between primary/secondary control and more comprehensive measures of adaptive functioning such as subjective quality of life and positive thinking.

2.3 Conclusions and Hypotheses for Study 1

Both primary control and secondary control have been associated with lower levels of negative psychological adjustment, such as less depression and anxiety. Whilst some theorists argue for the adaptive primacy of primary control over secondary control, the above analysis suggests that primacy theory does not provide an accurate account of the existing literature. In particular, cross-cultural evidence suggests that secondary control may have greater adaptive value than simply acting as a back-up strategy for low primary control. Furthermore, rather than primary control being optimally adaptive, the literature suggests that high levels of

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primary control can be associated with poor mental and physical outcomes, and that secondary control combined with low levels of primary control may also be non-adaptive.

Contrary to primacy theory, the above analysis suggests that maintaining a balance between the levels of primary and secondary control is optimally adaptive, and that secondary control’s functional role is greater than simply compensating for low primary control. Hence, the following hypotheses were proposed for the present study.

Individuals with high levels of primary control combined with low levels of secondary control, and conversely, persons with high levels of secondary control combined with low levels of primary control, demonstrate a control imbalance. Thus, these groups are hypothesised to show significantly lower levels of psychological adjustment (lower subjective quality of life, less positive affect and less positive thinking) than those individuals who demonstrate a relative balance in their levels of primary and secondary control. A control balance group may be operationalised as those persons with average and above-average levels of both primary and secondary control processes.

It is also hypothesised that secondary control will have intrinsic adaptive value, regardless of the levels of primary control. Specifically, secondary control will account for unique variance in subjective quality of life for both high and low sub-groups of primary control.

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In addition, the above analysis indicates that previous research investigating the relationship between primary/secondary control and psychological adjustment has narrowly operationalised adjustment in purely emotional terms, and in terms of only negative affect. Thus, the present study also represents an initial exploration of the relationship between primary/secondary control and more positive and comprehensive measures of psychological adjustment; including Subjective Quality of Life, Positive Affect and Positive Thinking.

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CHAPTER 3 STUDY 1: METHOD

3.1 Participants

The participants in this study were 195 people from the general population. The sample was recruited by two principal methods. The first involved inviting friends and families of the investigator to complete the set of questionnaires, then asking those people to invite their friends and families to participate. This led to the collection of data in both rural and city areas across four states of Australia (VIC, SA, NSW & QLD). The second recruitment strategy made use of an established, university database of research participants who participate in quality of life research conducted by the university. Of the total 380 questionnaires distributed, 195 were returned, representing an adequate response rate of 51.3%. The total sample of 195 consisted of 112 females (57.4%) and 79 males (40.5%). The mean age for the sample was 45 years, with a range of ages from 14-88 years.

Due to the anonymity of those participants that returned a completed questionnaire, no data are available regarding how many participants were recruited from each individual recruitment strategy.

3.2 Materials

The following questionnaires were completed by each participant. Dependent measures of positive adjustment included the subjective satisfaction indices from the Comprehensive Quality of Life Scale (ComQol; 5th edition; Cummins, 1997b), a measure of subjective

43 satisfaction across seven life domains: material well-being, health, productivity, intimacy, safety, community and emotional well-being. Content validity of the scale was demonstrated by Cummins (1996), who found that, of 173 different domain-satisfaction names drawn from the literature, 63% of the names and 83% of the data could be explained by the seven domains used in the Com-Qol. Convergent validity was demonstrated by correlating the satisfaction scores for each of the ComQol domains with alternative scales or questions designed to measure a similar domain (Cummins, 1997b). For example, the ComQol domain of health satisfaction correlated .88 with the question “How do you feel about your health overall? Additionally, a significant correlation of .45 was produced between the physical functioning scale of the Short-Form Health Survey (SF36:PF; Ware & Sherbourne, 1992) and scores for the ComQol Health domain. Scores from the ComQol Intimacy domain correlated .45 with the Miller Intimacy Scale (Miller & Lefcourt, 1982). Overall convergent validity of the subjective satisfaction scale of the ComQol is demonstrated by its significant relation to other measures of distress, such as the Rosenberg Self-Esteem Scale (Rosenberg, 1965) correlated .60 with ComQol satisfaction scores, .48 with Positive Affect and -.43 with Negative Affect as measured by the Positive and Negative Affect Scales (PANAS; Watson, Clark & Tellegen, 1988). Internal-consistency reliability was demonstrated with a Cronbach’s Alpha of .73 for the overall ComQol satisfaction scale and reliabilities between .27 (Safety domain) and .57 (Emotion domain) for individual domains (Cummins, 1997b).

The Positive and Negative Affect Scales (PANAS; Watson, et al., 1988) measure two bi-polar dimensions of mood. Positive Affect represents the degree to which a person is disposed toward experiencing positive, pleasant, and energetic moods. Negative Affect measures the extent to which a person experiences unpleasant arousal or feelings of upset. Convergent validity of the PANAS scales was demonstrated by correlating scores with alternative measures of distress (see Watson et al., 1988). The Positive Affect scale (PA) correlated -.35 and the Negative Affect scale (NA) correlated .56 with the Beck Depression Inventory

44 (Beck, Ward, Mendelson, Mock & Erbaugh, 1961). In addition, scores from the State-Trait Anxiety Scale (Spielberger, Gorusch & Lushene, 1970) significantly correlated .51 with NA and -.35 with PA. Internal consistency of the scale was shown to be .88 for the PA scale and .85 for the NA scale. Test-Retest reliability coefficients, over a time interval of 8 weeks was .68 for the PA scale and .71 for the NA scale.

A measure of positive cognitive functioning was the Automatic Thoughts Questionnaire- Positive (ATQ-P; Ingram & Wisnicki, 1988). This measure of positive thinking asks respondents to indicate the frequency of particular positive thoughts that occurred over the previous week. Each item of the scale has been shown to significantly discriminate depressed persons from non-depressed persons. Factor analysis produced four factors that accounted for 92.6% of the scale variance. These factors were labeled “Positive Daily Functioning”, “Positive Self-Evaluation” and “Others Evaluations of Self” and lastly, “Positive Future Expectations” (p. 900). These factors reflect the opposite construct of Beck’s negative, cognitive triad, which proposed that depressed peoples’ cognitions are dominated by negative thoughts about their self, the world and their future. Hence, ATQ-P factors seem to reflect the reverse process of positive beliefs about the self, world, the future and other’s evaluations. Reliability measures reported for the ATQ-P include adequate Item-Total correlations ranging from .42 to.75 and a Cronbach’s Alpha of .94.

The measure of control was the Primary and Secondary Control Scale (PSCS) that was developed and factor validated as part of this study. Items for the PSCS were developed after an extensive review of control and coping literature with the aim to develop an instrument that measured primary and secondary control in terms of specific, yet comprehensive cognitive and behavioural strategies of control. The operational definitions of primary and secondary control were developed with regard to the theoretical formulations discussed by Rothbaum et al. (1982) and Weisz et al. (1984). Briefly, primary control was defined as strategies that

45 typically attempt to alter the external world of environment (other people, events etc.). In contrast, secondary control strategies typically alter the internal world of the person (their beliefs about problems, and various self-talk strategies that aim to alter some aversive cognitive/affective state). The 21 items of the PSCS used in Study 1 are shown in appendix B1, which contains copies of all the measures used in Study 1, as well as brief notes describing the origin of the items for the PSCS.

Factor analyses on the 21 items of the PSCS are reported in the results to Study 1, in order to empirically validate the two hypothesised factors, primary control and secondary control.

3.3 Procedure

Ethical consent for the study was provided by the Deakin Ethics Committee (see appendix C1). Questionnaires were then distributed to the investigators family and friends whilst asking each participant to nominate friends or family of their own who might want to be involved in the project. A covering information sheet supplied information about the purpose of the project (see appendix A1). Participants were handed the required number of surveys and Reply-Paid envelopes that they believed they could distribute for completion. This was typically between 2-5 surveys per person.

For the existing database sample, a letter inviting the person to participate was sent to their home address, with the information sheet, a survey and Reply-Paid envelope. Appendix A1 contains the information sheet and covering letter sent to the database participants.

All the measures used in the study were converted to 10-point, end-defined Likert scales in order to improve scale sensitivity by providing the participant with a

46 greater range of possible response to each item. In addition, 10-point scales reflect equal psychometric distance between scale points, and hence are believed to make more conceptual sense to research participants than 5 or 7 point scales. In addition, the use of 10-point scales has been shown to have a non-effect on numerous other scales’ reliability and validity coefficients (see Cummins 1998).

CHAPTER 4 RESULTS: STUDY 1

4.1 General Introduction

Numerous analyses were conducted in order to address the various aims and objectives of the study. The first aim was to assess the validity of the Primary and Secondary Control Scale by exploring the factor structure of the scale. The factor structure should confirm at least two factors that differentiate primary and secondary control. In addition, the internal consistency of the scale was also analysed.

Secondly, analyses were conducted in order to test two major hypotheses about the interactive nature of primary and secondary control in psychological health. The first hypothesis predicted that a balance between the levels of primary versus secondary control is more important than simply maintaining high levels of primary control. The second hypothesis proposed that secondary control is not only used as a back-up strategy for low primary control, but also predicts variance in psychological adjustment amongst people with high primary control.

In addition, analyses were conducted in order to explore the relations between primary/secondary control and positive measures of psychological health, as

47 opposed to the relationship between control and negative-distress variables as reported by previous studies.

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4.2 The Factor Structure of the Primary and Secondary Control Scale (PSCS): Initial Analyses

The aim of this analysis was to investigate the factor structure and reliability of the Primary and Secondary Control (PSCS). The PSCS was developed to measure the two-process model of control (primary and secondary control). Since there were no a priori assumptions made about the properties of the instrument, this initial analysis was purely exploratory.

Normality and skewness of each of the 21 items of the scale were assessed through SPSS DESCRIPTIVES. Skewness statistics for the 21 items ranged from –1.254 to .155, with nineteen of the twenty-one PSCS items being negatively skewed, indicating that participants responses were typically toward the upperend of the scale. Cases with partially missing data were omitted from the analysis after an inspection of the raw data suggested random missing data due to a participant accidentally skipping a page amongst the battery of questionnaires. The percentage of missing data in any of the analyses was no more than 2.5% of the total sample. Outlying cases were retained in the analysis as true and valid responses to the items. Responses were submitted to a principal-components analysis using SPSS FACTOR (N = 192). The factorability of the matrix was confirmed through an inspection of the correlation matrix, which showed that all items (except item 14) correlated > .3 with at least one other item in the PSCS correlation matrix. Furthermore, Bartlett’s test of Sphericity statistic was significant (Bartlett’s = .888, p < .001) and the Kaiser-Meyer-Olin measure of sampling adequacy was .89.

The initial extraction yielded 4 factors with eigenvalues > 1. However, inspection of the scree plot suggests that a two-factor solution accounts for the majority of PSCS variance that is explained by the factors (49%). Taking the mid-point on the plot would suggest a three-factor solution that accounts for only 7% more

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variance than the two-factor solution. Nevertheless, all four factors were inspected to gain an overall understanding of the pattern of item loadings, regardless of the final solution to be retained.

An initial inspection of the pattern matrix showed a complex structure with some PSCS items cross-loading between .3 and .55 across more than one factor. The cross-loading items made meaningful interpretation of the factors difficult. In addition, the reliability of any items loading 45 years (N = 93) and < 45 years (N = 93). Separate principal-components analyses were then conducted on both the younger and older portions of the sample.

Results showed a number of significant changes in the factors and their loadings following stratification by age. For the younger portion of the sample (< 45 years) the primary control factor had 3 primary control items (items 12, 16 and 21) and one secondary item loading (item 2). These primary control items previously loaded negatively onto the general secondary control factor extracted in the first analysis. However, when analysing only the younger portion of the sample, the same primary control items (items 12, 16 and 21) now positively load; indicating the presence, not the absence of these primary control strategies in the younger participants responses. In fact, all the negatively loading primary control

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items from the first analysis now loaded positively on factors derived from the older portion of the sample. In behavioural terms, instead of the primary control items reflecting the polar opposite concepts to those stated (e.g. “… do not learn the necessary skills…” or “…I do not invest as much time as I can…” etc.) the positive loadings suggest the item should now read as stated (i.e. “…I learn the necessary skills…” or “I invest as much time as I can…”).

Interestingly, in the analysis of the older portion of the sample (> 45 years), a well-defined primary control factor did not clearly emerge at all. Primary control items tended to load across Factors 3, 4, and 5 along with numerous secondary control items amongst these factors. This complex structure for Factors 3, 4 and 5 shows that no definite primary control factor emerged amongst the older portion of the sample. In addition, the analysis of the older portion of the sample extracted a greater representation of secondary control factors (two secondary control factors) compared to the younger portion of the sample where only one secondary control factor emerged. These findings demonstrate that age can effect the nature of primary control item loadings. That is, by analysing only the younger portion of the sample the direction of primary control item loadings reversed direction from negative to positive. Additionally, the pattern of loadings was also affected by the age of the sample, from a clear primary factor emerging in the younger sample, to no definite primary control factor emerging in the older sample. Furthermore, the analysis of the older group yielded more secondary control factors than either the analysis of the younger group or the sample as a whole. Taken together, these findings may suggest that more elderly participants’ responses reflected a lesser engagement of primary control efforts, but a greater engagement of secondary control strategies when coping with problems. However, although the age of the sample appears to effect the pattern and direction of loadings, other evidence suggests that the older portion of the sample perceived they used as much (on average) primary and secondary control as the younger portion of the sample.

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Table 4.3 shows that by calculating the means for Factor 1 (the general secondary control factor extracted in the first analysis) and Factor 2 (the negatively loaded primary control factor) we find that the younger sample’s mean levels of primary and secondary control differ only marginally from the older sample means. Table 4.3 Means and standard deviations (sd) for Factor 1 (primary control) and Factor 2 (secondary control) for the total sample (N = 192), participants < 45 years of age, and participants > 45 years Total sample

< 45 years

> 45 years

(N = 192)

(N = 93)

(N = 93)

Variable

mean

sd

mean

sd

mean

sd

Factor 1 (Primary)

40.95

10.72

39.89

10.88

43.56

8.44

Factor2 (Secondary)

42.63

8.86

41.58

9.25

42.32

10.61

Therefore, although some evidence suggested that the older group used less primary control than the younger group, the actual mean levels of primary and secondary control are nearly equal. Hence, it appears the negative loadings derived from the initial analysis of the whole sample are better explained by an intrinsic characteristic of secondary control involving a passivity toward changing the environment; rather than the effect of an age bias that is theoretically linked to reduced levels of primary control with increasing age.

4.3 Analyses of the Hypotheses for Study 1

One of the aims of the study was to investigate the importance of the individual maintaining a balance between their primary and secondary control processes. Specifically, it was hypothesised that control-imbalanced groups (i.e. aboveaverage on one control process, but below average on the other) would self-report less Subjective Quality of Life (SQOL), Positive Affect and Positive Thinking compared to individuals who demonstrate a relative balance between their control processes (i.e. average or above-average levels of both primary and secondary control).

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To test this hypothesis an independent variable (Group) was specified by splitting the sample into four groups:

Group 1 (above-average primary control combined with below-average secondary control). Group 2 (below-average primary control combined with above-average secondary control). Group 3 (average and above-average levels of both primary and secondary control). Group 4 (below average levels of both primary and secondary control).

To test the hypothesis a one-way Multivariate Analysis of Variance was performed using SPSS GLM-Multivariate on SPSS for Windows (Version 8.0) on the three dependent variables (SQOL, Positive Affect and Positive Thinking).

The number of cases relative to the number of dependent variables was 7:1 in the cell with the smallest N (N=21), indicating adequate cell-sizes. Normality of the dependent measures was assessed by group via skewness statistics and inspection of histogram plots using SPSS Explore. With the exception of the distribution of SQOL scores for group 1, all other groups for each of the dependent variables were negatively skewed. Skewness statistics for the groups ranged from -.131 to 1.35 indicating that participants scores on measures of positive adjustment were typically toward the upper limits of the distribution of scores. The decision was made not to transform any of the data since Subjective Quality of Life is known to be naturally negatively skewed (Cummins, 1995). Since Positive Affect and Positive Thinking are conceptually and empirically related dimensions to Subjective Quality of Life these distributions are assumed to also naturally skew. Hence, none of the dependent variables were transformed. Furthermore, with large samples (>100 participants), variables displaying moderate levels of skewness can be tolerated (Tabachnick & Fidel, 1996). Univariate and

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multivariate outliers were also retained in the analysis because they represent true observations of participants’ self-reported degree of adaptive functioning. Box’s M was not significant, indicating multivariate homogeneity of variance between groups (18, 27554) = 31.93, p > .01. Wilk’s lambda F(9, 430) = 15.59, p < .001, ß = .20, revealed a significant global difference between the four groups. Groups differed on all the dependent measures of SQOL, Positive Affect and Positive Thinking as shown in Table 4.4.

Table 4.4 Summary table for Multivariate Analysis of Variance examining group differences in Subjective Quality of Life, Positive Affect and Positive Thinking for the four combinations of Primary & Secondary Control Groups 1

2

3

4

(Hi prim-Lo Sec)

(Lo Prim-Hi Sec)

(Hi Prim-Hi Sec)

(Lo Prim-Lo Sec)

Subjective Quality of Life

X 52.50 SD 9.93

X 51.24 SD 6.64

X 58.08 SD 6.97

Positive Affect

X 74.17 SD 11.36

X 70.10 SD 10.30

Positive Thinking

X 192.60 SD 48.07

X 188.14 SD 35.87

Variable

F

p

²

X 43.69 SD 9.97

31.10

.001

.343

X 78.44 SD 8.98

X 59.08 SD 13.30

34.55

.001

.367

X 233.38 SD 39.35

X 155.93 SD 52.16

32.69

.001

.354

Post-hoc Tukey’s analyses revealed that both control-imbalanced groups 1 (HiPrim-LoSec) and group 2 (HiSec-LoPrim) reported significantly less SQOL compared to the group that maintained average or above average levels of both primary and secondary control processes (i.e. the control-balanced group). In terms of Positive Affect, the HiSec-LoPrim group reported significantly less positive emotions compared to the HiSec-HiPrim group. However, the HiPrimLoSec group were not significantly different on positive emotions compared to the control-balanced group. In short, low levels of secondary control skills did not appear to effect Positive Affect. In contrast, persons who reported low levels of primary control (despite having high levels of secondary control) did have less Positive Affect than persons with high levels of both primary and secondary

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control. Hence, primary control appeared to affect Positive Affect, whereas secondary control did not. For Positive Thinking, both control-imbalanced groups 1 (HiPrim-LoSec) and 2 (HiSec-LoPrim) reported significantly less positive thoughts than the controlbalanced group. Interestingly, the HiSec-LoPrim group reported very low levels of positive thoughts that were not significantly different from the control relinquishment group (LoPrim-LoSec). The control relinquishment group was found to have significantly less Subjective Quality of Life, Positive Affect and Positive Thinking compared to all other groups (control-balanced or imbalanced groups).

Regression analyses were also conducted in order to test whether secondary control appeared to act only as a back-up strategy for low primary control. The cases to variables ratio was far in excess of 20:1. Outliers were retained as before, and the assumption of linearity was met. The normal probability plot of standardised residuals demonstrated normal distribution of the residuals.

To test the role of secondary control as simply a back-up strategy for low primary control, a median-split of primary control was taken, creating a low (N = 83) and high (N = 92) primary control group. Table 4.5 shows that, primary control was entered first into a hierarchical regression predicting of SQOL, followed by secondary control for both the low and high primary control groups.

Results showed that within the low primary control group, primary control significantly predicted SQOL accounting for 6.1% of the variance. However, when secondary control was also entered into the prediction of SQOL, primary control ceased to make a significant prediction, with secondary control accounting for 7.3% of the variance in SQOL.

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For the high primary control group, primary control significantly predicted SQOL, accounting for a total 20.4% of the variance. When secondary control was also entered into the regression, it also significantly predicted SQOL, accounting for an additional 3.1% of the variance. The squared semi-partial correlation showed that secondary control accounted for a unique 5.0% of the variance in SQOL, compared to 16.8% variance uniquely accounted for by primary control.

Table 4.5 Summary table for hierarchical regression analyses investigating the relationship between Primary/Secondary control and Subjective Quality of Life for participants with high and low levels of primary control Low primary control (N= 83) Variable Entry 1. Primary Control 2. Primary Control Secondary Control **p
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