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
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
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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 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.
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 (“control-balanced”).
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.
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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.
Overall, the present analysis does not support the primacy of primary control in adaptive psychological
functioning, but rather the strong functional inter-dependence 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 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.
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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
1.3.4 Primary Control Strategies……………………………...8
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
1.5.3 Empirical Tests of the Greater Adaptive Value
of Primary Control…………………………………….19
1.5.4 The Adaptive Limits to Primary Control……………...21
1.6 The Adaptive Limits to Secondary Control and
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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
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
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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
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
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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
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
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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
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,
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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
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
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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
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
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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 over-simplified, 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 culture-
bound 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
new construct provided the basis for a less culture-bound conception of personal
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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).
1.3.1 Specific Secondary Control Strategies
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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.
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
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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
Rothbaum et al. (1982) argue is commonly associated with positive outcomes.
That is, acceptance of the objective conditions in one's life.
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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, emotion-
focused 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
(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.
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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
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
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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
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?
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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
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.
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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
(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
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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).
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
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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
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
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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
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
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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 sub-
groups. 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
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 back-
up 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
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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.
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
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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
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
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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
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
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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
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
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“...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.
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
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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
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 blood-
doning 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
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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 (self-
reported, 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.
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
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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.
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
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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
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
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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 non-
assertive, 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.
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,
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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
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 non-
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adaptive 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
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
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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
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
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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
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 non-
adaptive. For example, research indicates that secondary control may be non-
adaptive 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.
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The whole question of what is adaptive psychological functioning has been
narrowly defined in studies investigating the relationship between control and
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 IN
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 more
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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
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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 (SF-
36: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
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(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
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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
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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.
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In addition, analyses were conducted in order to explore the relations between
primary/secondary control and positive measures of psychological health, as
opposed to the relationship between control and negative-distress variables as
reported by previous studies.
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Chapter 4
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 upper-
end 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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Chapter 4
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 <.4 in a factor-analysis is poor
(Tabachnick & Fidell, 1996). Hence, in order to achieve simple structure, it was
decided to rotate the solution using SPSS OBLIMIN and to omit items that loaded
<.4 from the interpretation of factors. This decision led to a more simple structure
in the factor matrix that greatly improved interpretability and understanding of the
factors.
Table 4.1 shows the results of the initial extraction. Factor 1 accounted for
approximately 33% of the total variance in PSCS scores and is loaded by a variety
of cognitive secondary control strategies. These strategies reflect an attempt to
cognitively and emotionally accommodate to problems through mechanisms such
as downward social comparison (item 7), vicarious control (emotional support;
item 6), interpretive control (finding meaning; item 1), illusory secondary control
(item 4), wisdom of impermanence (item 13), vicarious secondary control
(identification with a successful group; item 10) and reflecting on past
accomplishments (item 9). Hence, Factor 1 may be best described as a general
secondary control factor.
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Chapter 4
Table 4.1 Abbreviated items and factor loadings for the PSCS (initial extraction)
F1 F2 F3 F47. “…remind myself…better off than other people.”
.836
6. “…I can rely on my family or friends for their emotional support.”
.799
1. “…I look for something good.” .763
4. “…Don’t worry.” .744
13. “…remind myself that things will change.”
.705
10. “…think of past success of my family or friends.”
.591
18. “When something gets in the way of a goal, I work out how to remove it.”
-.824
16. “…I am able to work hard to achieve it.”
-.770
21. “…I try learn the skills necessary to do it well.”
-.689
5. “…I look for new ways to reach my goal.”
-.619
12. “…I invest as much time as I can on it.”
-.568
9. “…I keep in mind that I have already accomplished a lot in life”.
.459 -.443
2. “…I do some physical exercise or meditation.”
-.407
19. “…I ask others for help, or advice on what to do about the problem.”
.663
8. “…I make efforts to have it happen.” .621
14. “…I let go of it.” .746
15. “…I think about other aspects of life where I have had more success.”
.521
20. “…I can see it was not my fault.” .522 .411
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Chapter 4
Factor 2 accounts for 9% of the variance and is loaded by mostly primary control
items. Five primary control items and two secondary control items load > .4.
The five primary control items share the conceptual similarity of pro-active
attempts to change, influence or manipulate circumstances in order to get what
one wants. In the popular sense, these control strategies are about “doing
something to attain goals”, or “doing something to solve one’s problems”.
Despite Factor 2 being defined mostly by primary control items, two secondary
control items (Items 9 & 2) also loaded onto Factor 2. An inspection of these
items showed that they both have strong conceptual links to the primary control
concept of influencing situations to bring about desired goals. That is, Item 9 (“…
I keep in mind that I have already accomplished a lot in life”) although in essence
a secondary control strategy to help accommodate (emotionally and cognitively)
to failure situations, the item pre-supposes a lifetime of activity defined by
primary control efforts. Similarly, Item 2 (“…I do some physical exercise or
meditation”) is also a secondary control strategy aimed at accommodating to
situations by controlling the emotional, cognitive and physical reactions to stress
through exercise or meditation. Item 2 is an atypical secondary control item
because its mode of operation is more clearly behavioural, whereas most
secondary control strategies usually operate through manipulating cognitive
mechanisms (e.g. attributions, self-talk, positive and negative expectancies).
Therefore, Item 2 may have loaded on to the primary control factor (Factor2)
because primary control strategies are typically behavioural strategies and Item 2
is the only behavioural secondary control item in the scale.
Factor 3 accounted for 7% of the variance in the initial solution. It is formed by 2
primary control items and one secondary control item that cross-loads with factor
4. Factors with few loadings and only two pure items (i.e. items that load onto
only one factor) make this an unstable factor that should be interpreted with great
caution, if at all (Tabachnick & Fidell, 1996). Nevertheless, the items share the
conceptual similarity of using social environments to exercise control. In the case
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Chapter 4
of the two primary control items (items 8 and 19) the use of the social
environment is through behavioural mechanisms: asking for advice about what to
do (item 8) and organising others to assist in the control effort (item 19). For the
secondary control item (item 20) the use of the social environment is through a
cognitive strategy of construing the social environment in a way that avoids
aversive emotions such as self-blame and guilt.
Factor 4 accounted for approximately 5% of the variance and was loaded by 5
secondary control items. These items all share the common theme in strategy of
managing real or anticipated failure. The precise mechanisms of managing failure
include: goal disengagement (item 14), predictive secondary control
(contemplating negative outcomes; item 17), reflecting on successful aspects of
life (item 15), wisdom of dissatisfaction (item 46) and self-protective attributions
of blame (item 20). Item 20 also loaded onto Factor 3. This may be because the
process of self-protective attributions of blame involve the use of the social
environment (Factor 3) by subjectively construing the social environment. In
addition, self-protective attributions also serve the function of coping with failure
(Factor 4).
Factors 1 and 2 were clearly loaded by a number of purely loading items and
accounted for a total of 42% of scale variance. Hence, they were labeled
Secondary Control and Primary Control, respectively. Factor 3 was an unreliable
factor formed by only 2 purely loading items and was not interpreted. Factor 4
was loaded by four pure items, but only accounted for an additional 5% of the
variance beyond the Primary and Secondary control factors. Furthermore, the
items all shared the common theme of managing real or anticipated failure (a
principle process of secondary control). That is, despite Factor 4 being
statistically separated in the analysis, it is not conceptually different from Factor
1. Hence, it was decided to re-analyse the PSCS by specifying two-factors and
observe if the secondary control items that loaded on to Factor 4 would move
across to the conceptually similar secondary control factor. Thus, providing a
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Chapter 4
clearly interpretable solution with simple structure. The choice of specifying two
factors was based on an inspection of the initial scree plot, as well as theoretical
grounds that the scale was designed to measure two concepts - primary and
secondary control.
4.2.1 Final Solution and Reliability Analysis
Factor loadings for the specified two-factor solution were derived from a
principal-components analysis (N = 192) of the 21 items of the Primary and
Secondary Control Scale (PSCS). The matrix was considered factorable as
indicated by a significant Bartlett’s test of Sphericity statistic (Chi-square =
973.05, p < .001) and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy
was above .8 (KMO = .845). Oblique rotation (SPSS OBLIMIN) of the solution
was conducted to enhance simple structure and interpretability.
Table 4.2 shows the results of the specified 2-factor solution with 13 secondary
control items loading significantly onto the Secondary Control factor (Factor 1),
6 primary control items loaded onto the Primary Control factor (Factor 2) and two
secondary control items (Items 9 & 14) cross-loaded onto the Primary Control
factor. The four secondary control items that loaded onto Factor 4 in the initial
extraction now loaded onto the secondary control factor in the specified two-
factor solution.
The primary control item (Item 2 “I do some physical exercise or meditation”)
failed to load onto either the primary control or secondary control factors and
hence was omitted from further analyses. Overall, the two-factor solution
provides a clearly interpretable solution that approximates simple structure.
The items that loaded onto the secondary and primary control factors in the two-
factor solution were then used to calculate individuals’ levels of primary and
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Chapter 4
secondary control. These scores were then used for evaluating the study’s
hypotheses.
Table 4.2 Primary (Prim) and secondary (Sec) control factors and item loadings for the PSCS (initial extraction)
Item F1 F2
7. Sec .745
13. Sec .73510. Sec .71515. Sec .6813. Sec .67317. Sec .6234. Sec .617
6. Sec .5931. Sec .574
11. Sec .53220. Sec
18. Prim
.448
-.75716. Prim -.703
21. Prim -.685
5. Prim -.652
12. Prim -.5448. Prim -.4939. Sec .528 -42614. Sec .526 .497
Finally, reliability analysis of the PSCS items indicated the items have good
internal consistency as indicated by Cronbach’s Alpha = .90.
4.2.2 Possible Interpretations of the Negative Loadings Observed for
Factor 2
The negatively loaded items that comprise the primary control factor (Factor 2)
suggests that the items should read as the polar opposite concept to what the item
states. Hence, the polar opposite concept of the primary control items of Factor 2
reflect an absence of primary control. That is, “not doing” whatever the strategy
states. For example, item 18 states that “when something gets in the way of a
goal, I work out how to remove it”. However, since none of the items were
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Chapter 4
designed to be reversed scored, the negative loading suggests the item should read
“…not working hard to achieve goals”.
An explanation for the negative loadings of Factor 2 may be provided by
Rothbaum et al. (1982). They believe many learned-helplessness researchers
confuse passive behaviours (e.g. externally attributing outcomes to limited ability
or chance factors, behavioural disengagement etc.) with primary control
relinquishment, but may actually be a form of secondary control that may increase
levels of perceived control.
In their view, “inward behaviours” (being passive, withdrawing from active
problem solving, being submissive to environmental events and making causal
attributions to limited ability, chance or more powerful others; p. 5), rather than
being evidence for the relinquishment of control, may represent a different type of
inward-control that allows for the control of emotional and cognitive reactions to
problems (secondary control).
Perhaps then, the apparent ‘giving-up’, passive behaviour that the negative
loadings suggest (i.e. “not working hard to achieve goals”, “not learning new
skills”, “not removing blocks” etc.) are the reflection of the intrinsic passivity of
secondary control toward changing the environment. That is, behavioural
disengagement. According to Rothbaum et al. (1982) and Heckhausen and Schulz
(1995), the adaptive value of behavioural disengagement is that it avoids what
they argue is one of the most deleterious psychological experiences for a human
being, disappointment. Disappointment is particularly deleterious in that it
represents a failure of both control process options, primary and secondary
control failure. That is, disappointment arises from failing to bring the
environment in line with subjective wishes (primary control failure) as well as
failing to successfully accommodate emotionally to the situation (secondary
control failure). In addition, the adaptive value of behavioural disengagement is
that it is the necessary first step toward coping with primary control failure. If
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Chapter 4
one cannot control the environment to achieve their desired goal, continuing to
try change the situation may incur costs of an escalating perceived sense of loss
of control. This may include all the associated cognitive and emotional reactions
that may stem from such an experience (e.g. loss, frustration, anxious uncertainty,
negative self-talk etc.). Hence, by behaviourally disengaging from the goal, the
person can begin to manage these cognitive-affective reactions. In this way,
behavioural disengagement may be a gateway to secondary control. That is, by
giving-up on trying to change the environment the person can then allocate
greater effort at maintaining control of their self.
Another possible explanation for the negative loadings being investigated is that
they reflect the control processes of a relatively aged sample (mean = 45.77
years). Heckhausen & Schulz (1995) theorised that the prevalence of primary
control reduces with increasing age across the life-span. Hence, perhaps items
loading onto the primary control factor are negatively loaded because the older
sample used in the analysis responded in a way that reflected a relative absence of
primary control efforts. To test this hypothesis, the sample was stratified by age
(median split) into two groups: > 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
items from the first analysis now loaded positively on factors derived from the
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Chapter 4
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.
Table 4.3 shows that by calculating the means for Factor 1 (the general secondary
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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
(N = 192)
< 45 years
(N = 93)
> 45 years
(N = 93)
Variable mean sd mean sd mean sd
Factor 1 (Primary)
Factor2 (Secondary)
40.95
42.63
10.72
8.86
39.89
41.58
10.88
9.25
43.56
42.32
8.44
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. above-
average 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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Chapter 4
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
multivariate outliers were also retained in the analysis because they represent true
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Chapter 4
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
Variable 1
(Hi prim-Lo Sec)
2
(Lo Prim-Hi Sec)
3
(Hi Prim-Hi Sec)
4
(Lo Prim-Lo Sec)F p ²
Subjective Quality of Life
X 52.50SD 9.93
X 51.24SD 6.64
X 58.08SD 6.97
X 43.69SD 9.97
31.10 .001 .343
Positive Affect
X 74.17SD 11.36
X 70.10SD 10.30
X 78.44SD 8.98
X 59.08SD 13.30
34.55 .001 .367
Positive Thinking
X 192.60SD 48.07
X 188.14SD 35.87
X 233.38SD 39.35
X 155.93SD 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 HiPrim-
LoSec 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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Chapter 4
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 control-
balanced 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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Chapter 4
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) High primary control (N = 92)
Variable Entry
ß t Adj. R²(R² Change)
Semi-partial r( r²)
ß t Adj. R²(R² Change)
Semi-partial r( r²)
1.Primary Control
.270 2.52* .061(6.1%)
.270(7.3%)
.461 4.93** .204(20.4%)
.461(21.3%)
2.Primary Control
.112 .954 .106(1.1%)
.404 4.24** .410(16.8%)
Secondary Control
.327 2.786** .134(7.3%)
.297(8.8%)
.207 2.17* .235(3.1%)
.224(5.0%)
**p <.01* p <.05
The study also aimed to conduct an initial exploration of the relationship between
primary/secondary control and positive measures of psychological health (e.g.
Positive Affect, Subjective Quality of Life) rather than measures of negative-
distress (e.g. depression, anxiety etc.).
Standard multiple regressions were used to predict SQOL, Positive Affect and
Positive Thinking from primary and secondary control. Results are shown in
Table 4.6.
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Table 4.6 Standard regression analyses investigating the relationship between Primary/Secondary control and measures of positive psychological adjustment
Primary Control Secondary ControlVariable ß t Semi-
Partial rß t Semi-Partial r
SubjectiveQuality of Life
.398 5.60** .378.
.275 3.87** .272
Positive Affect .474 7.28** .390 .330 4.60** .322
Positive Thinking
.337 5.10** .350 .425 6.44** .427
**p<.001
Primary and secondary control significantly predicted Subjective Quality of Life,
accounting for a total of 35.2% of the variance. Squared semi-partial correlations
showed that primary control accounted for 14.3% of the variance and secondary
control 7.4%.
Primary and secondary control also significantly predicted Positive Affect,
together accounting for a total of 47.1% of the variance. Primary control
accounted for 15.2% of unique variance and secondary control 10.3% unique
variance.
Similarly, Positive Thinking was significantly predicted by primary and
secondary control, accounting for a total 45.4% of the variance. Primary control
uniquely accounted for 12.3% of variance, compared to 18.2% of the variance
explained by secondary control.
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CHAPTER 5
DISCUSSION OF STUDY 1
5.1 The “Primacy” of Primary Control
Previous theory and research investigating the relationship between
primary/secondary control and psychological adjustment suggested that primary
control has functional primacy over secondary control (Heckhausen & Schulz,
1995; Thompson et al., 1994; Thompson et al., 1996; Thompson & co-workers,
1998). However, the present data suggests a more prominent role for secondary
control, in accommodating to problems for psychological health.
Results demonstrated that rather than high levels of primary control being
optimally adaptive, it is important to consider the relative balance or ratio of
primary to secondary control levels. As hypothesised, results showed that
individuals who reported an imbalance between their levels of primary and
secondary control reported less SQOL, less Positive Affect and less Positive
Thinking than individuals who reported average (or above average) levels of both
control processes.
One explanation for the greater reported psychological health of the control-
balanced group compared to unbalanced groups may lie within the comprehensive
nature of the coping skills available to them by maintaining adequate levels of
both primary and secondary control. Without a comprehensive base of coping
skills involving both control processes, the person may be vulnerable to situations
that do not match the preferred control process.
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Hence, those with high levels of primary control combined with low levels of
secondary control are vulnerable to situations that may not be easily controllable
by direct action (e.g. someone resents you). In contrast, those with high levels of
secondary control skills but with low primary control skills are vulnerable to
missing opportunities for directly manipulating situations to fit their needs. Evans
et al. (1993) cited numerous empirical studies that demonstrate the dysfunctional
nature of exercising high levels of control behaviour, motivation or cognitions in
the context of low environmental opportunities for control. However, individuals
who utilize both control process possibilities, have a more comprehensive
repertoire of coping skills allowing them to adapt their coping response to the
objective controllability of the situation.
The present data suggest that simply having average to high levels of primary
control skills is not optimally adaptive, one must also have average to high levels
of secondary control. One possible exception however, is for individuals whose
control imbalance is expressed in terms of high primary control combined with
low secondary control. This group reported significantly less SQOL and positive
thoughts compared to the control-balanced group, but not less Positive Affect.
The explanation for this difference may be less sensitivity of Positive Affect, than
the other positive adjustment variables to variations in secondary control.
Theoretically speaking, Positive Affect may be less sensitive to variations in
secondary control due to the relative stability of the Positive Affect dimension
compared to SQOL and Positive Thinking.
Watson and Clarke (1984) operationalised the PANAS scales to conceptualise
affect as a mood-like personality variable in which individuals were predisposed
toward perceiving events either with a negative bias (Negative Affect) or a
positive bias (Positive Affect). Recent empirical evidence supports the
dispositional quality of Positive and Negative Affect showing the variables are
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closely related to the personality constructs of introversion-extraversion and
neuroticism, and that the personality variables ceased to predict occupational
strain after the PANAS variables were included in the model (Fogarty, Machin,
Sutherland, Lalor & Revitt, 1999).
In contrast to the enduring, trait-like quality of Positive and Negative Affect,
subjective evaluations of quality of life (SQOL) and the frequency of positive
thoughts over the previous week (Positive Thinking) are variables that are less
dispositional in quality as they are unstable constructs that would fluctuate with
the regular changes in circumstances and events. Perhaps Positive Affect was not
effected by secondary control in the MANOVA, whereas SQOL and Positive
Thinking were, because secondary control strategies function at the level of
effecting individuals daily appraisals and evaluations of their life (subjective
states), not at the level of dispositional perceptual biases (subjective traits).
For example, secondary control strategies such as finding meaning in an event or
downward social comparison may result in the reduction of negative cognitive
and affective states, but they might be less effective at changing the person’s
enduring, characteristic way of perceiving the world. Hence, secondary control’s
function in coping may be more to control positive and negative cognitive-
affective states than it is to control enduring trait-like perceptual biases.
In contrast, results showed that persons with low levels of primary control (the
HiSec-LoPrim group) did have less Positive Affect than the control balanced
group, suggesting that variations in primary control did effect the trait Positive
Affect. This result may be evidence of the role of primary control in effecting the
more enduring, less flexible aspects of psychological functioning (i.e.
personality), whereas secondary control may not function at the level of traits.
Nevertheless, the generality of the finding of Positive Affect being less sensitive
to variations in secondary control (compared to the other two positive adjustment
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variables) was tested again in Study 2. In addition, the robustness of the finding
that suggested the importance of a control-balance for optimal psychological
adjustment was also re-tested in Study 2.
Previous theory and research on primary/secondary control also suggests that the
functional role for secondary control was to simply act as a back-up strategy for
individuals or circumstances where primary control was low (Heckhausen &
Schulz, 1995; Thompson et al., 1994). However, the present data show that
secondary control maintains a significant relationship with SQOL, even when the
person perceives primary control opportunities as high.
This suggests that secondary control has intrinsic adaptive value for the individual
regardless of the level of primary control. The intrinsic value of secondary
control for subjective quality of life may simply be that by engaging in secondary
control cognitions or behaviours (e.g. doing something enjoyable to relax, or
telling oneself that one is better off than others), the person perceives a better
quality of life, regardless of the perceived controllability over objective
environmental conditions.
In order to test the robustness of the finding of secondary control’s relationship
with psychological adjustment amongst both people with high and low levels of
primary control, the observed relations were re-tested in Study 2.
Another aim of Study 1 was to explore the relationship between
primary/secondary control and positive adjustment variables, rather than
investigating the relationships with negative-distress variables that have been
explored in previous studies. The data showed that secondary control strategies
also predict Positive Thinking, Positive Affect and Subjective Quality of Life.
Hence, secondary control strategies may not only function to decrease negative
emotionality but may also increase positive cognitions, and subjective perceptions
of quality of life. Although Positive Affect was predicted by secondary control in
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the regression analyses, the results of the MANOVA analysis suggests that
secondary control may have less effect on the trait-like constructs such as Positive
Affect compared to the effect on subjective states such as Subjective Quality of
Life and frequency of Positive Thinking over the past week.
5.1.1 Differences With Past Theory and Research: The Importance of
Operational Definitions of Primary and Secondary Control in Coping
Research
The relative contributions of primary versus secondary control in explaining
unique variance in positive adjustment variables, indicates that the relative
valence of secondary control’s effect on positive psychological adjustment may
be considered less than the effect of primary control.
Hence, previous research that investigated the relationship between the two-
process model and distress variables (Thompson et al., 1994; Thompson et al.,
1996; Thompson & co-workers, 1998) proposed that the greater portion of
variance in distress variables explained by primary versus secondary control
demonstrates the greater functional importance of primary control compared to
secondary.
However, the smaller unique contribution to positive adjustment variables by
secondary control compared to primary control, disguises the importance of
secondary control to psychological health and the adaptive limits to primary
control. That is, primary control may account for more unique variance in
Subjective Quality of Life, but not if the person perceives low levels of primary
control. For individuals with low levels of primary control, primary control did
not predict Subjective Quality of Life at all, only secondary control significantly
predicted quality of life. In other words, secondary control has functional
primacy over primary control for individuals that perceive low levels of primary
control. Furthermore, even for participants with high levels of primary control,
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secondary control was shown to provide an additional prediction of Subjective
Quality of Life beyond the effect of primary control, indicating secondary control
does not only act as a back-up strategy for low primary control. Still further,
participants with high levels of primary control, but correspondingly low levels of
secondary control reported a lower Subjective Quality of Life and significantly
less Positive Thinking compared to participants with high primary control and
high secondary control. Hence, maintaining high levels of primary control is only
functional if the person balances their control repertoire with average to high
levels of secondary control as well.
Whereas Thompson et al., (1996) commented “…there may not be limits to the
benefits of primary control” the current data suggests that the adaptive value of
primary control is indeed limited by the extent to which the person has also
developed their secondary control skills. Likewise, the adaptive value of
secondary control is limited by the extent to which the person has developed their
primary control skills. Excessive levels of primary control with corresponding
low levels of secondary control may be somewhat analogous to the Type A
behaviour pattern involving excessive levels of active control, with a sense of
time pressure and who are predisposed to become aggressive and hostile when
frustrated (Glass, 1977). In contrast, individuals who maintain high levels of
secondary control but correspondingly low levels of primary control may have
limits to their adaptive potential through missed opportunities to manipulate the
environment to fit their needs.
The more prominent functional role found for secondary control in this study
compared to previous research may partly be explained by differences in the
operational definitions of control and psychological adjustment. Thompson et al.
(1994; 1996) operationalised secondary control as the general degree of
“acceptance” of twenty-four different outcomes related to living with HIV
disease. To conceptualise secondary control in vague, non-specific terms as
general acceptance underestimates the variety and comprehensive nature of
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cognitive and behavioural strategies that people use to reduce negative reactions
in anticipating or experiencing failure. By simply asking respondents how much
they accept negative outcomes in their life does not separate acceptance due to
reasons such as control relinquishment versus acceptance due to finding meaning
in the negative event. Furthermore, the non-specific description of secondary
control does not capture any of the positive processes that underlie secondary
control cognitions and behaviours (e.g. finding meaning, pampering oneself,
preparing for the worst etc.). Indeed, Thompson et al. (1996) operationalised
secondary control as general acceptance and found to their surprise that secondary
control related to increased levels of distress; not decreased levels of stress which
has consistently been suggested in other studies (Carver et al., 1989; 1993;
Thompson et al., 1994; 1998). In contrast, by operationalising secondary control
in terms of specific strategies that people use in order to positively accommodate
to problems, a greater functional role for secondary control for psychological
health was demonstrated.
The classification of particular control beliefs or behaviours into either primary or
secondary control has also been an issue of some contention in previous research
(e.g. Heckhausen & Schulz, 1995). Secondary control strategies typically alter
the internal world of the person (their beliefs about their problems, and various
self-talk strategies that aim to alter some negative cognitive/affective state). In
contrast primary control strategies typically aim to alter the external world (other
people, events etc.). In real terms however, all primary control strategies may
result in internal changes, just as secondary control strategies are believed to
result in renewed motivation to engage the environment in order to tackle
problems (Heckhausen & Schulz, 1995). Hence, primary and secondary control
are best discriminated by the most salient goal of the control strategy. Some
control/coping strategies are more clearly attempts to alter internal cognitions or
behavioural attempts at reducing negative affects (e.g. through exercise or doing
something pleasant for oneself), without engaging in direct manipulation of the
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external world; whereas others are more clearly attempts to alter external
environmental processes.
5.2 Limitations to Study 1
One important limitation of the study is that the investigation of optimally
adaptive combinations of primary and secondary control does not refer to what is
optimally adaptive for a specific problem or at a specific time within the temporal
sequence of coping with a problem. Intuitively speaking, the optimally adaptive
responses for some problems may require different ratios of primary versus
secondary control behaviour, at different times. For instance, being physically
attacked may at first require a high degree of primary control response to ensure
safety, with little or no secondary control response. Later in time however,
secondary control responses may be important to assist the person to cope with
their limited primary control over the levels of poverty and violence in their
neighbourhood. Similarly, the diagnosis of a congenital disease with little known
treatment may require a high level of secondary control to limit negative
emotional reactivity, with little or no primary control response. Later however,
primary control responses may be important for managing the physical effects of
the illness. The present study conceptualised the balance between control
processes in terms of a balance in the individuals ‘coping repertoire’, not what is
adaptive for specific situations. Hence, the present data suggests that an
individual’s repertoire of coping skills would best reflect a relative balance of
average or above-average levels of both primary and secondary control.
A second limitation of the study is intrinsic to the non-experimental design used
for the study. The importance of maintaining a balance in levels of both control
processes assumes that the positive correlation between control and health
variables is underlied by causal processes. Whilst the cross-sectional nature of
the design does not infer underlying causality, most of the previous research on
the adaptive value of control did use experimental manipulations, suggesting that
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control perceptions and behaviour causally effected various positive and negative
psychological outcomes (see Averill, 1973 for a review; Miller, 1979; Mills &
Krantz, 1979; Thompson, 1981). This is not to say that distress and positive
affects would not effect perceptions of control; intuitively speaking, feeling
depressed may lead a person to perceptions of reduced control over their self and
environment. Overall however, it is likely that the relationship between perceived
control and psychological health is bi-directional. Furthermore, from the clinical
perspective, it is less useful for psychological research to determine which
temporally occurs first, emotion or perception. Considering that psychological
interventions rely on manipulation of perceptions, coping research is best aimed at
understanding the role of perceptions in determining various psychological
outcomes. Interventions that aim directly at the manipulation of emotion with
little attention to perceptual processes would infer a more biological/medical
approach than a psychological one.
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CHAPTER 6
INTRODUCTION TO STUDY 2
6.1 General Introduction
The aims of the second study were twofold. First, the hypotheses tested in
the first study were investigated with a second sample in order to see if the
findings could be replicated. Second, a new hypothesis was tested to
determine whether the relationship between control and adjustment could
be explained by the personality dimensions of extraversion and
neuroticism.
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
Previous theory and research into the adaptive potential of primary and
secondary control suggested that primary control has functional primacy
over secondary control (Heckhausen & Schulz, 1993; Heckhausen &
Schulz, 1995; Thompson et al., 1994; Thompson et al., 1996). That is,
primary control is proposed to be intrinsically more adaptive, to be the
control strategy for which people have an underlying preference, and that
secondary control functions in a subsidiary capacity to primary control by
compensating for anticipated or real losses in primary control (failure).
However, data from Study 1 challenges the notion that primary control is
more adaptive than secondary control, suggesting that secondary control
may play a crucial role in maintaining optimal levels of positive
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psychological adjustment. It was found that participants who reported a
control-imbalance between their levels of primary and secondary control
(i.e. average or above-average levels on one
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control process but not the other) reported significantly lower positive
adjustment (Subjective Quality of Life and less Positive Thinking)
compared to people who reported a control balance (average or above-
average levels of both primary and secondary control). These results
suggest that individuals’ ratio of primary versus secondary control skills is
important to adaptive psychological functioning, rather than simply high
levels of primary control. Study 2 re-tested this hypothesis in order to
determine the robustness of the findings from Study 1.
6.2.1 Secondary Control’s Adaptive Function is More than a Compensatory
Mechanism for Low Primary Control
Results from Study 1 also found that the role of secondary control was
more than simply acting as a compensatory mechanism for low primary
control. For participants with low primary control, primary control failed to
predict psychological adjustment, whereas secondary control did. This
suggests secondary control may function as a compensatory control strategy
for people with low levels of primary control. However, for participants
with high levels of primary control, secondary control also explained
significant variance in psychological adjustment. This suggests that
secondary control’s functional role is more than simply compensatory. The
robustness of the finding that secondary control explained variance in
psychological adjustment for both groups of high and low primary control
was re-tested in Study 2.
6.2.2 The Relationship Between Primary/Secondary Control and Positive
Measures of Psychological Adjustment
Study 1 also provided data on the relationship between primary and
secondary control and measures of positive psychological adjustment, as
opposed to measures of negative adjustment or distress. Study 2 aims to re-
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test the robustness of the observed relations between primary/secondary
control and measures of positive psychological adjustment.
Regression analyses from Study 1 showed that primary and secondary
control explained significant amounts of variance in all three positive
adjustment variables (Subjective Quality of Life, Positive Affect and
Positive Thinking). However, whilst secondary control significantly
predicted Positive Affect, independent of primary control, a split based on
secondary control did not distinguish between levels of Positive Affect,
even though it did distinguish between levels of the other two positive
adjustment variables. Particularly, participants who reported low levels of
secondary control, and high levels of primary control, reported as much
Positive Affect as participants with high levels of both primary and
secondary control. This was not the case for the other positive adjustment
variables (Subjective Quality of Life and Positive Thinking) in which
groups with low levels of secondary control reported lower Subjective
Quality of Life and less Positive Thinking. The explanation for this
difference may be less sensitivity of Positive Affect than the other two
positive adjustment variables, to variations in secondary control. This
result will also be re-tested in the second study.
6.3 Personality, Control and Psychological Adjustment
The major aim of Study 2 was to address the issue of the relationship
between primary/secondary control, personality and positive psychological
adjustment. Previous research has not addressed this question. However,
data from both the subjective well-being literature and prior research in the
conceptually related area of coping suggests that the personality dimensions
of extraversion and neuroticism might have a role in explaining the
relationship between primary/secondary control and positive psychological
adjustment.
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The following discussion highlights the role of personality in positive
psychological adjustment. Conceptual linkages between the constructs of
coping and control are then discussed, whilst pointing out important
differences in the operational definitions between the control measure used
in this study and past measures of coping (the Ways of Coping models).
That is, the similarities between the constructs of coping and
primary/secondary control provide a firm rationale to expect that control
should also relate to the personality dimensions of extraversion and
neuroticism. However, the similarity between the constructs of coping and
control are more conceptual than operational, suggesting that coping
measures and the primary/secondary control scales used in this study are
not interchangeable. Next, evidence regarding the relationship between
coping and personality is discussed, which suggests that the conceptually
related constructs of primary/secondary control may also be related to
personality.
In short, the following discussion highlights the role of personality factors
in positive psychological adjustment. It is suggested that
primary/secondary control may relate to the personality factors of
extraversion and neuroticism (just as coping strategies are known to relate
to extraversion and neuroticism). Hence, Study 2 aims to extend the results
achieved from Study 1 by testing the capacity of the personality dimensions
of extraversion and neuroticism to explain the link between
primary/secondary control and positive psychological adjustment.
6.3.1 The Relationship Between Personality and Positive Psychological
Adjustment
Personality refers to aspects of thinking, feeling and behaving that are
relatively stable over time and throughout various situations. For instance,
a person may describe themselves as “generally quiet and shy”, referring to
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psychological characteristics that are relatively unchanged as the person
moves between different situations and over time (Carlson, 1987). This
should be contrasted with aspects of behaviour that might be more closely
linked to situational cues rather than stable ways of typically thinking,
feeling and behaving.
Typically, personality theorists have studied personality from the trait-
approach, as opposed to early attempts to describe individual differences in
terms of personality types (e.g. see Carlson for an extended discussion on
“type” conceptions of personality). Traits are dimensions of common
psychological characteristics amongst people by which individuals are
believed to differ, not in quality of behaviour but quantity (Carlson, 1987).
A common approach of trait-theorists work over the last half-century (see
Cattell, 1946; John, Angleitner & Ostendorf, 1988) was the exploration of
thousands of various linguistic terms in English and other languages that
appear to describe particular characteristics of feeling, thinking and
behaviour that are common to peoples description of other people. Using
this lexical approach to identify traits, Costa and McCrae developed (see
John, 1990) one of the more recent and most comprehensive descriptions of
the structure of personality and the measurement of such, in their
instrument the NEO Personality Inventory-Revised (Costa & McCrae,
1992). Their “Big Five” conception of personality refers to a set of five
empirically derived, super-ordinate factors, or “Domains”, which are each
comprised of various inter-correlated “Facets” (traits)(p. 14). The five
factors, or domains of behaviour include Neuroticism, Extraversion,
Openness (to experience), Agreeableness and Conscientiousness.
Of particular interest to Study 2 are the domains of Extraversion and
Neuroticism which previous research has demonstrated are consistently
observed to correlate with a range of psychological indicators of positive
psychological adjustment (Costa & McCrae, 1980; Emmons & Diener,
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1986; Argyle, Martin & Crossland, 1989; Heady & Wearing, 1989; Argyle
& Lu, 1990; Pavot, Diner & Fujita, 1990; Hoffman, Levy-Shiff & Milinski,
1996; Fogarty, Machin, Albion, Sutherland Lalor, Revitt, 1999).
Extraversion is conceived as one of the five personality domains which
represents various component aspects, or “facets” of behaviour including,
Gregariousness, Assertiveness, Activity, Excitement-Seeking and Positive
Emotions (such as optimistic beliefs; Costa & McCrae, 1992).
Extraversion is a construct involving tendencies toward being sociable and
preferring large groups. Extraverts also tend toward being assertive, active
and talkative. By contrast introverts tend toward feeling less sociable
(preferring to be alone), are independent and even-paced (Costa & McCrae,
1992).
Neuroticism describes a person who tends to experience frequent negative
emotions or distress, such as fear, sadness, guilt, embarrassment and anger.
Neuroticism is also linked to experiencing irrational ideas, to be less
controlling of their impulses, and to cope more poorly with stress.
Researchers have not only established the relationship between
extraversion, neuroticism and subjective well-being, but have also sought to
explain the precise mechanisms that account for the observed relationships.
For instance, Emmons and Diener (1986) found that the specific component
of extraverted behaviour that correlated with positive affect was the
sociability component of extraversion. Thus, the greater happiness of
extraverts could be explained by extraverts’ greater participation in social
activities. In contrast, the impulsivity component of extraversion was
uncorrelated with either positive or negative affect. In addition to being
more sociable than introverts, extraverts tend to be more warm in social
interaction, showing a greater tendency toward approaching people in a
friendly and affectionate manner (Costa & McCrae, 1984). Hence, perhaps
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the greater happiness of extraverts can also be explained by not just more
frequent social contact, but also more positive interaction. Furthermore,
Argyle and Lu (1990) found that extraverts tend to withdraw less from
social activities (e.g. at parties) compared to introverts, and that
withdrawing from social activities was negatively correlated with
subjective well-being. Thus, the authors argued that the greater happiness
of extraverts may be explained by their greater participation in social
activities, their more warm approach to social interactions and their
tendency to withdraw less.
The reduced levels of subjective well-being for people with a tendency
toward neuroticism is more clearly explicable in terms of the finding that
all six facets of Neuroticism as measured by the NEO PI-R (Costa &
McCrae, 1992) have been found to be significantly, negatively correlated
with subjective well-being (Costa & McCrae, 1984).
Whilst extraversion and neuroticism have been theoretically and
empirically linked to better and poorer adjustment respectively, the
relationship between these personality factors and primary/secondary
control is unknown. However, the construct of coping has been linked to
extraversion and neuroticism, which maintains numerous conceptual
similarities to the primary/secondary control constructs, thus suggesting
that control may also be related to extraversion and neuroticism.
6.3.2 Conceptual Similarities Between Coping and Primary/Secondary
Control
Coping may be defined as “…the person’s constantly changing cognitive
and behavioural efforts to manage specific external and/or internal demands
that are appraised as taxing or exceeding the person’s resources” (Folkman,
Lazarus, Dunkel-Schetter, DeLongis & Gruen, 1986, p.993).
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Likewise, primary and secondary control are strategies or responses toward
the management of external or internal demands, either through the
manipulation of external circumstances (primary control) or internal
conditions in order to accommodate to problems (secondary control). In
addition, the conceptual overlap between the primary/secondary control
constructs and coping is further apparent in terms of the problem and
emotion focused coping constructs of the Ways of Coping scales (Folkman
and Lazarus 1980; 1985). The Ways of Coping scales represent the most
pervasively used measures of self-reported coping in coping research since
the early 1980s (Schwarzer & Schwarzer, 1996). The Ways of Coping
scale distinguishes between problem and emotion focused coping which
maintain strong functional similarities to the primary and secondary control
constructs, respectively.
That is, problem focused coping functions to “…alter the troubled person-
environment relationship through problem solving, decision making or
direct action” (Folkman, 1984; p. 844-845). Similarly, primary control
involves altering the person-environment fit by making direct attempts to
change objective conditions in the environment to fit one’s own needs and
wants (Rothbaum et al., 1982; Weisz, 1990).
Just as primary control is conceptually similar to problem focused coping,
secondary control is functionally similar to emotion focused coping. That
is, emotion focused coping functions to regulate emotions and distress
(Folkman, 1984), whilst secondary control involves attempts to
accommodate to the objective conditions of the environment in order to
control aversive psychological impacts (Rothbaum et al., 1982; Weisz,
1990). In essence, secondary control also functions to regulate emotions or
distress, just as emotion focused coping is proposed to do.
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Not only are similarities apparent between primary/secondary control and
the problem/emotion focused constructs, but similarities are also evident in
terms of Folkman’s concept of coping appraisals. That is, Folkman et al.
(1986, p.993) described coping as a process, involving “primary appraisal”
in which the person cognitively determines what is at stake to lose (or gain)
from a stimulus. “Secondary appraisal” involves the person assessing what
coping options are available to them, or possible. Followed by the person’s
actual problem focused or emotion focused coping response, or specific
cognitive/behavioural strategy aimed at managing a stressor. Folkman
(1984) herself, commented on the strong degree of functional overlap
between the coping processes of appraisal, coping (actual strategies), and
primary and secondary control beliefs. In her view, primary/secondary
control beliefs can function at the level of primary appraisal (evaluating
what is to lose or gain by a stimulus), secondary appraisal (evaluating
coping resources and options) and can function as an actual coping strategy.
For example, a person has a disagreement with their supervisor at work
who becomes angry with them, yet the person forms the belief that “…the
supervisor will respect the fact that I stood up for myself”. Such a
cognition both functions at the level of primary appraisal, evaluating
potential consequences for disagreeing with the supervisor as potentially
positive, and functions as a secondary control strategy, regulating
potentially negative feelings that might arise after an argument with the
supervisor. Furthermore, primary and secondary control beliefs can also
function in a secondary appraisal capacity. In the current example, the
person’s analysis of their upsetting the supervisor may lead them to think
“…I’ll be really polite and friendly with my boss from now on”. This
cognition acts as a secondary appraisal of the resources the person may
have to manage the situation. In this case the person has appraised a
personal characteristic (i.e. being amiable) as an option to manage any
potential conflict arising with the supervisor. Yet the belief also has a
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primary control function of aiming to manipulate external conditions (the
supervisor) in order to maintain favourable workplace relationships.
Hence, whilst much conceptual overlap exists between the concepts of
appraisal, problem/emotion focused coping and primary and secondary
control, important differences exist in the operational definitions of
problem/emotion focused coping and primary/secondary control. These
differences suggest that the problem focused and emotion focused coping
scales, although conceptually similar in terms of function, are not
interchangeable with the primary/secondary control measure used in this
study.
6.3.3 Differences Between Coping Measures and the Measurement of
Primary/Secondary Control
The Ways Of Coping (WOC) scale, and it’s contemporary version (the
Ways of Coping Questionnaire; Folkman & Lazarus, 1988) measure
problem focused and emotion focused coping by asking respondents to
think of a specific stressful encounter. However, as Gallahger (1996)
suggests, one effect of asking respondents to think about a specific stressful
situation is that a person’s reported coping response may be constrained by
the situational characteristics of the stressor. For instance, the potential
consequences of the stressful situation may effect the person’s choice of
coping strategies. Gallagher presents the example of an “avoidant surgeon”
whose coping response may vary widely depending on whether the
situation is a patient in dire need of a surgical operation, or the surgeon
having a disagreement with a colleague at a cocktail party (p. 423). Hence,
asking respondents to think of a specific stressful situation may mask some
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participant’s usual or typical coping responses. That is, the participant may
not report some of their most commonly used coping strategies due to their
chosen situation not requiring those strategies.
Beyond the potential masking of a respondent’s common coping strategies,
recent factor analytic studies have called into question the proposed factor
structure of the Ways of Coping Questionnaire and hence, it’s construct
validity. Folkman and Lazarus (1985) factor analysed ratings on a revised
version of the Ways of Coping Checklist (subsequently referred to as the
Ways of Coping Questionnaire; Folkman & Lazarus, 1988) finding an
eight-factor solution which they proposed measured eight distinct types of
coping strategies (e.g. Confrontive Coping, Distancing, Seeking Social
Support etc.). However, other studies have consistently failed to replicate
the proposed eight-factor structure, finding a variety of factors that do not
correspond with the number, or structure of factors that the instrument is
supposed to measure (Vitaliano, Russo, Carr, Maiuro & Becker, 1985;
Parker and Endler, 1992; Parker, Endler & Bagby, 1993; Bouchard,
Sabourin, Lussier, Wright & Richer, 1997; Edwards & O’Neill, 1998).
Parker et al. (1993) concluded that the failure of the WCQ to show a
replicable factor structure in different samples confronting a homogeneous
stressor seriously challenges the construct validity of the instrument. So
much so that they recommend that any data collected using the WCQ
should be factor analysed first, in order to derive scales that may be relevant
and valid for that particular sample.
In contrast, the Primary and Secondary Control Scale (PSCS) does not
instruct respondents to think of a specific stressful encounter. The PSCS
contains a number of control strategies (items) categorised on
theoretical/conceptual grounds as either primary or secondary control.
Items were selected in order to represent the diversity of possible ways in
which people may attempt to solve problems or reach goals either by
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changing conditions to suit their needs or to accommodate to problems.
This conceptual diversity of control strategies was achieved by selecting
strategies which differed in terms of their mode of operation (i.e. both
cognitive and behavioural strategies were selected), as well as selecting
strategies from both ends of the approach-avoidance continuum.
Respondents are instructed to read and evaluate on a Likert-scale rating,
“…to what extent the following statements apply to you” “…when facing a
tough problem or trying to reach a difficult goal”. That is, participants are
asked the degree to which they perceive the particular control strategy is
characteristic of themselves when coping, or trying to control their goals
and problems situations. Hence, the instrument allows respondents to
report the variety or diversity of possible control strategies that they either
could or generally do use, not what they did use in a specific situation.
Thus, the PSCS measures the person’s ‘control-repertoire’, defined as the
potential diversity of cognitive and behavioural strategies that the person
could draw upon when facing difficulties.
Overall, despite some functional similarities between the constructs of
problem/emotion focused coping (and appraisal) and primary/secondary
control, important differences exist in the operational definitions of coping
and control. Hence control was measured, for the purposes of this study,
using the newly developed Primary and Secondary Control Scale. In
addition, the widely used measures of problem and emotion focused coping
moreover, have recently been criticised as potentially invalid.
6.3.4 The Relationship Between Personality (Extraversion and Neuroticism)
and Coping
Evidence suggests that personality factors not only relate to measures of
positive psychological adjustment but are also significantly related to
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measures of coping (Rim, 1987; Carver et al., 1989; Vollrath, Torgesen &
Alnaes, 1995; Gallagher, 1996; Gomez, Holmberg, Bounds, Fullarton &
Gomez, 1999). This suggests that certain personality characteristics may be
linked to coping (or control), which also influence the quality of
psychological outcomes.
For example, the relationship between personality and coping was
demonstrated by Rim (1987) who factor analysed coping data from two
different conceptualisations of coping (Lazurus and Plutchik). These two
conceptualisations represent two divergent approaches to the study of
coping. The Plutchik model highlights people’s coping in terms of a small
set of specified strategies (e.g. suppression) aimed to deal with a small set
of basic human emotions (e.g. fear, sadness). In contrast, Lazarus’ model
proposes coping as a problem-solving effort that draws upon a much wider
range of possible cognitive and behavioural strategies, selected largely on
the basis of situational determinants of the stressor. Analysis of the two
theoretically divergent data sets showed that the personality dimensions of
extraversion and neuroticism were significantly associated with a variety of
specific coping factors derived from both theoretical conceptualisations of
coping, including: minimization, suppression, self-blame and focusing on
the positive.
In addition, Gomez and co-workers (1999) found significant relationships
between extraversion and approach-coping strategies (including cognitive
and behavioural styles of coping), whereas avoidance coping styles were
predicted by neuroticism. Gallagher (1996) also demonstrated relationships
between extraversion/neuroticism and coping, finding that introverts coping
style was characterised by seriousness and an avoidance of social support,
whereas extraverts’ coping was not characterised by seriousness.
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Overall, personality variables have been shown to relate to coping and to
measures of positive adjustment (such as subjective well-being). As
discussed previously, the measure of control used in Studies 1 and 2
operationalises primary and secondary control constructs in terms of what
the person generally does, or generally could do, as opposed to what they
did do in a specific situation (as measured by the Ways of Coping models).
This measurement of the person’s stable or typical ways of control is more
closely associated with the trait-approaches to the measurement of coping
(see Carver et al., 1989) which also study coping in terms of the
individual’s typical ways of responding to stress. Considering this more
dispositional character of the Primary and Secondary Control Scale, it may
be expected that primary/secondary control are significantly associated with
personality factors (extraversion and neuroticism), just as personality has
been shown to influence the conceptually similar construct of coping.
6.4 Hypotheses for Study 2
Hypotheses 1-3 are replications of the hypotheses tested in Study 1, in order
to assess the robustness of the results observed in the first study. In
addition, an exploratory analysis addresses the issue of the relationships
amongst primary/secondary control, personality variables and positive
psychological adjustment. Particularly, the exploratory analysis aims to test
the capacity of extraversion and neuroticism to explain the relationship
between primary/secondary control and positive psychological adjustment.
Hypotheses 1: That primary and secondary control will significantly predict
measures of positive psychological adjustment (Subjective Quality of Life,
Positive Affect and Positive Thinking).
Hypothesis 2: That participants who report having a control-imbalance
(average or above levels on one control process, but not the other) will
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report significantly lower levels of positive psychological adjustment (less
Subjective Quality of Life, Positive Affect and Positive Thinking) than
participants who maintain average or above average levels of both primary
and secondary control.
Hypothesis 3: Previous theory and research in primary/secondary control
suggests that secondary control only has a functional role for people with
low levels of primary control. However, results from Study 1 found a role
for secondary control within sub-samples of both high and low levels of
primary control. Hence, the robustness of the result of secondary control’s
greater functional role amongst people with high primary control was tested
a second time.
Thus, it is predicted that secondary control will explain significant amounts
of variance in Subjective Quality of Life for sub-samples of both high and
low primary control.
Exploratory Analysis: As discussed previously, evidence suggests that the
personality dimensions of extraversion and neuroticism are related to
positive psychological adjustment. These personality factors have been
related to the construct of coping, but not to primary/secondary control.
However, primary/secondary control maintains conceptual similarities to
the coping constructs of problem/emotion focused coping and appraisal,
providing rationale to expect that primary/secondary control may also relate
to the personality factors of extraversion and neuroticism.
Considering the previously discussed relationships between personality and
positive adjustment, as well as the suggested link between personality and
primary/secondary control, it is proposed that the personality variables of
extraversion and neuroticism will explain significant amounts of shared
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variance between primary/secondary control and positive psychological
adjustment.
Hence, personality factors will be entered first into a series of hierarchical
regressions predicting positive psychological adjustment. Next, primary
control and secondary control will also be included into the prediction of
adjustment, in order to assess the unique contributions of primary control
and secondary control to explaining variance in the positive adjustment
variables.
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CHAPTER 7
STUDY 2: METHOD
7.1 Participants
The participants were 173 people from the general population. The majority of
the sample (95%) was recruited using an already established database of people
who are part of a register of research participants in quality of life studies
conducted by the university. In addition, approximately 5% of the sample were
friends or family of the investigator who were recruited in the manner described
for Study 1. Of the total 350 questionnaires distributed, 173 were returned,
representing a response rate of 49.4 %. Of the total 173, 115 participants were
female (66.5%). The mean age for the total sample was 48.39 years with ages
ranging from 15-90 years.
7.2 Materials
The questionnaires used for Study 2 were identical to those used in Study 1,
except for minor revisions made to the Primary and Secondary Control Scale, and
the addition of the personality scales of Extraversion and Neuroticism from the
NEO-Five Factor Inventory (NEO-FFI). All other scales, including the subjective
indices from the Comprehensive Quality of Life Scale (5th edition; Cummins,
1997), the Positive and Negative Affect Scales (PANAS; Watson, Clarke &
Tellegen, 1988) and the Automatic Thoughts Questionnaire- Positive (ATQ-P;
Ingram & Wisnicki, 1988), remained unchanged in format from Study 1. Thus,
readers are referred to the psychometric data described in the Method to Study 1
for validity and reliability data for these instruments.
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The changes made to the Primary and Secondary Control Scale (PSCS) included 3
new items, minor revisions of wording to all the secondary control items, and
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revisions to the order of appearance of items. A full copy of the 2nd version of the
Primary and Secondary Control Scale used in Study 2 is contained in appendix
B2, as well as a copy of the Extraversion and Neuroticism scales from the NEO
FFI Personality Inventory (Costa & McCrae, 1992).
Whilst all the primary control items remained unchanged, three new secondary
control items were added in order to increase the conceptual diversity of
secondary control strategies that the PSCS presents to respondents. This diversity
is central to the instruments intended purpose to measure the person’s control
repertoire, or the potential strategies that a person could or would draw upon when
facing difficult problems. The three new secondary control items added to the 2nd
version of the PSCS are:
Item 22 “When something bad happens that I cannot change: I ignore it by
thinking about other things” (Conscious use of distraction).
Item 23 “When something bad happens that I cannot change: I realise I didn’t
need to control it anyway” (Reducing control motivation).
Item 24 “When something bad happens that I cannot change: I relax and don’t
think about it” (Suppression).
In addition, revisions were made to the wording of all the secondary control items
in the first version of the PSCS used in Study 1. Hence, all secondary control
items for the 2nd version of the PSCS were preceded by the words “When
something bad happens that I cannot change…” in order to further the theoretical
integrity of the instrument by highlighting the inherent passivity of secondary
control strategies toward manipulating problem situations. Thus, the preceding
words direct the participant toward thinking about control strategies that might
apply to them when facing problems that are not easily amenable to primary
control manipulations of the objective conditions of the problem.
Furthermore, minor revisions were made to the wording of some of the actual
secondary control strategies, in order to further simplify the language, expression,
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and overall readability of each item. For example, Item 1 from the first version of
the PSCS, “When faced with a difficult problem, I look for something good or
positive in what is happening”, was revised to “When something bad happens that
I cannot change: I can see that something good will come of it”. In addition,
Item10 from the first version, “When struggling with a problem I think of the past
successes of my family or friends”, was changed to, “When something bad
happens that I cannot change: I remember the success of my family or friends”.
In addition to the above mentioned changes of the PSCS, the order of appearance
of items was refined so that in the 2nd version of the scale all primary control
items were listed first, followed by the secondary control items. This improved
the overall organisation of the instrument so that items were grouped together on
the basis of them sharing similar theoretical functions. Hence, primary control
items were grouped together, as were the secondary control items.
Considering the changes made to the PSCS, the factorial validity of the 2nd
version of the instrument was re-analysed, to ensure the instrument maintained the
two-factor simple structure that was accepted in Study 1. The results are
presented later.
In order to conduct the exploratory analysis into the relations between personality,
primary/secondary control and positive psychological adjustment, the
Extraversion and Neuroticism scales from the NEO Five Factor Inventory (NEO
FFI) were added to the measures for Study 2. The NEO FFI is a short form
version of the NEO Personality Inventory- Revised (NEO PI-R Costa & McCrae,
1992).
Costa & McCrae selected NEO FFI items from the highest loading items from
five principal-components extracted from a factor analysis of 180 items from the
NEO PI. Items were then substituted in order to diversify item content or in cases
where items cross-loaded onto more than one factor. Costa & McCrae (1992)
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provide extensive data that show correlations between the NEO FFI scales and a
measure of the five-factor model based on self-reported adjective ratings, as well
as correlations between the NEO FFI scales with observer ratings (spouse and
peers) using the NEO PI-R scales. Correlations with convergent measures (e.g.
spouse and peer ratings) were all significant and moderate in magnitude.
Specifically, the correlation between the Extraversion scale of the NEO FFI and
the adjective ratings was .60. Spousal ratings correlated .64 with FFI
Extraversion and .39 with peer ratings. For the Neuroticism scale from the NEO
FFI, convergent correlations were: .62 with the adjective measure of
Neuroticism, .52 with the spouse ratings, and .36 with the peer ratings. Divergent
validity was assessed by correlating NEO FFI Extraversion and Neuroticism
scales with the Openness, Agreeableness and Conscientiousness scales from the
adjective-ratings measure. None of the divergent correlations exceeded .20.
Reliability of the NEO FFI scales (internal consistency) was assessed by
calculating coefficient alphas. Alphas for the Neuroticism and Extraversion
scales, respectively, were .86 and .77, indicating adequate levels of internal
consistency.
7.3 Procedure
The Deakin Ethics Committee provided ethical consent for Study 2 (see appendix
C2). A questionnaire package was then sent to participants registered with the
university’s database of volunteers to be involved in quality of life research
conducted by the university. The package included, a covering letter and
information sheet, information regarding the aims of the project, introducing the
principle investigator and an invitation to participate in the study, as well as
ethical information concerned with informed consent and confidentiality of the
returned data. The package also contained a copy of the questionnaire battery
containing all the scales mentioned previously. Participants were told in the
information sheet that their consent to participate in the project would be
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registered by simply responding to the questionnaire and sending it back to the
investigator in Reply-Paid envelopes provided by the university. Participants
were instructed to complete the questionnaire in their own time, and that the
questionnaire takes approximately 25 minutes to complete. Appendix A2
contains the covering letter and information sheet sent to participants.
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CHAPTER 8
RESULTS: STUDY 2
8.1 Data Screening
Data for the second study were checked for missing data, out-of-range values, as
well as exploring the frequency distributions for each of the variables in the study.
All dependent measures were observed to have generally mildly skewed
distributions, For example, skewness statistics for SQOL items ranged from
(smallest to largest) 1.18 to –1.29. Only one item (PANAS item 13), was severely
skewed (Skew = 4.47). This measured participant’s feeling “…ashamed” and the
large positive skew reflects the sample’s limited experience of this emotion.
Overall, data were not transformed because the distributions are known to be
naturally skewed in the population, and the magnitude of the skewness for each
item (except item 13) was typically small.
8.2 Factor Analysis and Reliability Analysis of the Primary & Secondary
Control Scale (2nd version)
As mentioned previously, revisions were made to the format and wording of the
secondary control items of the Primary and Secondary Control Scale (PSCS) used
in Study 1. Hence, the 2 nd version of the PSCS was factor analysed in order to
check that the overall factorial validity of the instrument observed in Study 1 (2
factors: “Primary Control” and “Secondary Control”) was not altered
significantly. In addition, the internal consistency reliability of the revised items
and the reliability of the overall scale were re-analysed.
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The factor procedure used was similar to the procedure used for Study 1,
except that in this procedure two factors were specified a priori, rather than the
exploratory analyses conducted in Study 1. The rationale to specifying two
factors was to test the stability of the factor structure observed in Study 1.
A Principle-Components Analysis was conducted (N = 170), including
oblique rotation of the solution (SPSS OBLIMIN) in order to aid interpretation
of the factors by achieving simple-structure. Table 8.1 shows that Factor 1 is
loaded purely by all the items that measure primary control, Factor 2 is loaded
by purely secondary control items, and 2 items that are theoretically classed as
secondary control strategies, failed to load onto either factor.
The two items that failed to load on either of the two factors (Items 9 & 12)
correlated significantly with only a few of the other 24 items on the scale.
This could be explained by the fact that these are the only secondary control
items that are behavioural in their mode of operation. That is, Item 9 is to do
with doing exercise in order to control the psychological impact of a negative
event. Item 12 is about using social supports by telling someone about the
problem. All other secondary control items on the PSCS are cognitive in their
mode of operation and involve a self generated effort to think in a way that
changes the person’s perception of the aversive aspects of a problem (e.g.
telling oneself that something good will come from difficult situations).
Because Items 9 and 12 failed to load onto either factor they were omitted
from any further analyses conducted in
Study 2.
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Table 8.1 Primary (Prim) and secondary (Sec) control factors and item
loadings for the PSCS (2 nd version)
Item F1 F2
19. Sec .707
18. Sec .68123. Sec .68015. Sec .67822. Sec .66020. Sec .65217. Sec .642
14. Sec .56821. Sec .548
24. Sec .54716. Sec .54210. Sec .496
13. Sec .433
11. Sec .422
8. Sec .4114. Prim -.910
3. Prim -.835
5. Prim -.790
7. Prim -.7252. Prim -.719
1. Prim -.683
6. Prim -.637
12. Sec9. Sec
The reliability analysis showed item-total correlations for the majority of items
were adequate (above .5). Item-total correlations ranged from relatively poor
(.26; Item 24) to relatively high .69 (Item 14).
The internal-consistency (Chronbach’s Alpha) for the primary control scale,
secondary control scale and the overall scale were high. That is, alpha = .89
for the 17 secondary control items, .87 for the 7 primary control items.
8.3 Replication of Initial Hypotheses
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Hypothesis 1: The Relationship Between Primary/Secondary Control and
Positive Adjustment Variables
The results from Study 1 demonstrated significant relationships between
primary and secondary control and measures of positive psychological
adjustment. In order to further investigate this in Study 2, a series of standard
multiple regressions was used to predict the dependent variables SQOL, PA
and Positive Thinking with the control variables primary and secondary
control (entered simultaneously). The results are presented below in Table
8.2.
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)
Primary Control Secondary ControlVariable ß t Semi-Partial r
(r²)ß t Semi-Partial r
(r²)
SubjectiveQuality of Life
.352 4.88** .313**(9.8%)
.306 4.25** .273**(7.5%)
Positive Affect .535 8.09** .478**(22.8%)
.194 2.93* .173*(3.0%)
Positive Thinking
.411 6.12** .367**(13.5%)
.333 4.96** .298**(8.9%)
**p<.001*p<.01
This table shows that the control variables were significant independent
predictors of variance in SQOL, Positive Affect (PA) and Positive Thinking.
Table 8.2 also shows the squared semi-partial correlations (expressed as % of
unique variance accounted for) between primary/secondary control and the
positive adjustment variables. Hence, both Studies 1 and 2 provide empirical
evidence of the significant relationships between primary and secondary
control and positive adjustment variables.
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Of particular interest however, was the somewhat counter-intuitive result of
the relationship between control variables and Negative Affect (NA).
Although Studies 1 and 2 aimed to explore the relationship between
primary/secondary control and measures of positive psychological adjustment,
analyses were also conducted with a measure of negative adjustment
(Negative Affect), for the purpose of completeness of reporting. It was found
that while primary control predicted significant amounts of variance in NA,
secondary control did not predict NA. Subsequent inspection of the
correlation matrix confirmed that whilst a small, negative correlation was
found between primary control and NA (r = -.18, p <.05), secondary control
failed to predict NA (r = -.09, p > .05).
8.3.1 Hypothesis 2: The Role of Maintaining a Balance in Control
Processes for Positive Adjustment
To re-test the finding that a control-imbalance is related to reduced levels of
positive psychological adjustment, the control balance groups were separated
by a Cluster Analysis (SPSS K-MEANS CLUSTER) of the variables Primary
and Secondary Control. This method was favoured from the method used to
create groups in the previous study (via mean splits) for it provides a more
natural separation between groups by clustering on the basis of qualities of the
actual data. That is, participants were clustered on the basis of the
combination of their actual primary and secondary control scores, so that four
clusters were formed from the combinations of high and low levels of primary
and secondary control. These four clusters were labeled as control-
imbalanced (HiPrim-LoSec and HiSec-LoPrim), control-balanced (HiPrim-
HiSec) and a relinquished-control group (LoPrim-LoSec). The groups were
then treated as an independent variable in a one-way MANOVA with SQOL,
PA and Positive Thinking as the dependent variables. This procedure was
performed using SPSS GLM-Multivariate for Windows (Version 9.0). The
number of cases in the smallest cell (N = 20) was much greater than the
number of dependent variables, indicating adequate cell sizes. Box’s M was
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not significant (p > .001), indicating multivariate homogeneity of variance
between groups.
Wilk’s Lambda F(9, 492) = 6.147, p < .001, ² = .11, revealed a significant
global difference between the four control groups on the combination of
dependent variables. Table 8.3 shows the means and standard deviations for
each group and the significance levels. Significant differences were found
between the groups on all the dependent variables. Post-Hoc analyses were
then conducted in order to see which groups differed, on which variables.
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
Groups
Variable 1
(Hi Prim-Hi Sec)
2
(Hi Prim-Lo Sec)
3
(Lo Prim-Hi Sec)
4
(Lo Prim-Lo Sec)F p ²
Subjective Quality of Life
X 58.85SD 6.04
X 50.38SD 9.89
X 55.33SD 6.34
X 43.40SD 12.75
14.90 .001 .214
Positive Affect
X 81.78SD 10.74
X 66.99SD 13.07
X 73.63SD 10.14
X 60.45SD 17.15
14.64 .001 .211
Positive Thinking
X 228.81SD 39.85
X 188.73SD 46.02
X 214.17SD 34.39
X 157.85SD 50.83
14.29 .001 .207
As had been found in Study 1, Tukey’s analyses revealed that the control-
imbalanced group (HiPrim-LoSec) reported a lower SQOL, less Positive
Affect and less Positive Thinking than the sample with higher levels of both
primary and secondary control (HiPrim-HiSec). However, the other control-
imbalanced group (LoPrim-HiSec) did not differ from the HiPrim-HiSec
group on any of the dependent variables. This is in contrast to the results from
Study 1 where it was found that the LoPrim-HiSec group did report
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significantly less Subjective Quality of Life, less Positive Affect and less
Positive Thinking than the control-balanced group (HiPrim-HiSec). Further
differences from the results from Study 1 were observed for the effects on
Positive Affect. In Study 1, the control-imbalanced group HiPrim-LoSec
reported equivalent levels of Positive Affect compared to the HiPrim-HiSec
group. In Study 2, it was found that this group reported significantly less
Positive Affect, as was predicted, than the HiPrim-HiSec group, but the other
control-imbalanced group LoPrim-HiSec reported equivalent levels of Positive
Affect as the HiPrim-HiSec group.
8.3.2 Hypothesis 3: Secondary Control as Simply a Back-Up Strategy
for Low Primary Control?
Study 1 found that secondary control did not just act as a back-up control
strategy for people with low levels of primary control. In short, secondary
control predicted significant amounts of variance in Subjective Quality of Life
for both high and low groups of primary control. Study 2 re-tested the ‘back-
up’ or compensatory role hypothesis for secondary control in an identical
method to Study 1, which was similar to the method used by Thompson et al.
(1994) to argue that secondary control only functions as a compensatory
mechanism.
First, a mean split of the sample into high (N = 94) and low primary control
groups (N = 75) was conducted. Hierarchical regression was then used to
predict SQOL, entering primary control first, followed by secondary control.
Table 8.4 shows that within the low primary control group, primary control
significantly predicted variance in SQOL. Secondary control was then entered
into the equation and significantly explained more unique variance in SQOL,
beyond that of primary control. However, in contrast to Study 1, when
secondary control was included in the regression, primary control continued to
significantly predict SQOL within the low primary control group. This
suggests that even for a group with below average levels of primary control,
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both primary and secondary control may contribute to Subjective Quality of
Life.
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 levels of
primary control (N = 75)
Low primary control (N= 75) High primary control (N = 94)
Variable Entry
ß t Adj. R²(% R² Change)
Semi-partial r( r²)
ß t Adj. R²(% R² Change)
Semi-partial r( r²)
1.Primary Control
.384 3.56** .136(13.6%**)
.384**(14.7%)
.193 1.89 .027(2.7%)
.193(3.7%)
2.Primary Control
.280 2.53* .262*(6.9%)
.112 1.12 .109 (.01%)
Secondary Control
.294 2.65* .202(20.2%*)
.275*(7.6%)
.331 3.30** .121(12.1%**)
.321**(10.3%)
**p <.01* p <.05
A similar analysis conducted with the high primary control group showed that
primary control failed to significantly predict SQOL (see Table 8.4). When
secondary control was added to the prediction, it significantly predicted
SQOL. The semi-partial correlation between secondary control and SQOL,
representing the unique relationship between secondary control and SQOL,
was also significant (r = .321, p < .01).
These results are similar to the results in Study 1, in that even for a group of
participants with high levels of primary control, secondary control maintains a
significant prediction of SQOL. The results differ from Study 1 in that, for the
high primary control group, primary control did not significantly predict
SQOL at all; whereas in Study 1 primary control continued to significantly
predict SQOL, even after the entry of secondary control.
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8.4 Exploratory Analysis: The Role of Personality in Explaining the
Relationship Between Control and Positive Psychological Adjustment
The unique aspect of Study 2 was the proposal that the relationship between
control variables and positive adjustment might be explained by the influence
of personality variables. That is, some people may perceive more primary and
secondary control over their environment and self due to the influence of
stable characteristic ways of thinking and behaving and consequently enjoying
greater levels of positive psychological adjustment. Hence, a series of
hierarchical regressions were conducted predicting positive psychological
adjustment. These entered the personality variables first, followed by primary
and secondary control.
Table 8.5 reports the results for SQOL and Positive Thinking and Table 8.6
the regressions for Positive Affect and Negative Affect.
Both Neuroticism and Extraversion made significant, independent predictions
of SQOL, Positive Thinking and PA scores. However, Neuroticism was the
only personality variable to significantly predict NA. Squared semi-partial
correlations (r²) between personality variables and SQOL, Positive Thinking
and PA showed that Neuroticism accounted for unique variance in SQOL,
independent of Extraversion, as well as smaller portions of unique variance in
Positive Thinking and PA. Extraversion accounted for unique variance in
SQOL scores, Positive Thinking and in PA.
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 [PRIMCON] & Secondary control [SECCON])
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SQOL Positive Thinking
Variable Entry
ß t Adj. R²(%R² Change)
Semi-partial r( r²)
ß t Adj. R²(%R² Change)
Semi-partial r( r²)
1.NEUROT.-. -.387 -5.85** -.379**
(14.4%)-.221 -3.40* -.22*
(4.8%)
EXTRAV .331 5.01** .305(30.5%**)
.324**(10.5%)
.492 7.57** .33(33.0%**)
.48**(23.0%)
2. NEUROT -.332 -5.39** -.317**
(10.0%)-.156 -2.66* -.148*
(2.2%)
EXTRAV .168 2.50* .147*(2.2%)
.303 4.74** .264**(7.0%)
PRIMCON .204 2.84* .167*(2.8%)
.257 3.77** .210**(4.4%)
SECCON .269 4.13** .425(12.0%**)
.243**(5.9%)
.282 4.60** .484(15.9%**)
.257**(6.6%)
**p <.001* p <.05
When the control variables (primary and secondary control) were entered,
both primary and secondary control made significant predictions of SQOL
scores, PA and Positive Thinking, independent of the variance already
accounted for by the personality variables. The change in proportions of
variance in the positive adjustment variables after the inclusion of primary and
secondary control (Adjusted R-Square) were all significant. The control
variables explained a further 12.0% of variance in SQOL scores, an additional
10.7% of the variance in PA and 15.9% additional variance in Positive
Thinking, beyond the variance accounted for by the personality variables. The
addition of primary and secondary control into the prediction of Negative
Affect however, failed to explain any further variance in NA that was not
already explained by Neuroticism. After all variables (control variables and
personality variables) were entered into the prediction, squared semi-partial
correlations showed that all the independent variables (Extraversion,
Neuroticism, primary and secondary control) each significantly accounted for
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unique variance in all the positive adjustment variables (Subjective Quality of
Life, Positive Affect and Positive Thinking).
Table 8.6 Study 2: Summary table for hierarchical regression analyses
predicting Positive Affect & Negative Affect with personality variables
(NEUROTICISM & EXTRAVERSION) and control variables (Primary
[PRIMCON] & Secondary control [SECCON])
Positive Affect Negative Affect
Variable Entry
ß t Adj. R²(%R² Change)
Semi-partial r( r²)
ß t Adj. R²(%R² Change)
Semi-partial r( r²)
1.NEUROT -.25
1-4.17** -.245**
(6.0%).644 10.59** .628**
(39.4%)
EXTRAV .554 9.20** .423(42.3%**)
.541**(29.3%)
-.015 -.244 .412 (41.2%**)
-.014
2.NEUROT -.18
0-3.22* -.171*
(2.9%).644 10.261** .613**
(37.6%)
EXTRAV .381 6.26** .332**(11.0%)
-.013 -.185 -.011
PRIMCON .314 4.83** .256**(6.6%)
.010 .120 .007
SECCON .137 2.35* .530(10.7%*)
.125*(1.6%) -.021 -.319
.405(0.0%) -.019
**p <.001* p <.05
In short, these results demonstrate that primary and secondary control
continued to predict significant portions of variance in positive adjustment
variables, beyond variance in adjustment that was already accounted for by the
effect of Extraversion and Neuroticism.
A further analysis was conducted in order to determine the extent Extraversion
and Neuroticism explained shared variance between primary/secondary
control and positive adjustment variables. Squared semi-partial correlations
conducted as part of Hypothesis 1 (Study 2) demonstrated the magnitude of
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relations between primary control (independent of secondary control) and each
of the positive adjustment variables (see Table 8.2). However, after the
inclusion of Extraversion and Neuroticism into the prediction of positive
adjustment, primary control explained much less variance in positive
adjustment (see Tables 8.5 and 8.6). The magnitude of the reductions in
variance in adjustment accounted for by primary control, after the inclusion of
the personality variables, across the three positive adjustment variables was
typically large. That is, the variance accounted for in each of the positive
adjustment variables by primary control alone, was reduced by approximately
65-70% after the inclusion of Extraversion and Neuroticism. For example,
primary control alone predicted 9.8% of variance in Subjective Quality of Life
(independent of secondary control). When Extraversion and Neuroticism were
also included into the prediction of SQOL, the percentage of variance
accounted for in SQOL by primary control was reduced to only 2.8% (see
Table 8.5).
However, the reductions in percentage of variance in positive adjustment
accounted for by secondary control, after the inclusion of Extraversion and
Neuroticism, were somewhat less than with primary control. For example, the
variance in Subjective Quality of Life accounted for by secondary control
alone, was 7.5% (see Table 8.2). However, when Extraversion and
Neuroticism were also included into a prediction of SQOL, the variance in
SQOL accounted for by secondary control was reduced by only 21%,
substantially less than the reduction in adjustment variance explained by
primary control after the inclusion of Extraversion and Neuroticism. The
reduction in Positive Affect variance explained by secondary control, after the
inclusion of Extraversion and Neuroticism was 47%, compared to the 71%
reduction in variance explained by primary control after the inclusion of
personality. For Positive Thinking, the reduction in variance explained by
secondary control was approximately 23%. Compared to the 67% reduction in
Positive Thinking variance explained by primary control after the inclusion of
Extraversion and Neuroticism.
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The capacity for Extraversion and Neuroticism to differentially effect the
magnitude of observed relations between primary control and positive
adjustment, and secondary control and positive adjustment, is explained by the
correlations between primary/secondary control and Extraversion and
Neuroticism. Correlational analyses (Pearson bivariate correlations)
demonstrate a moderate positive correlation between primary control and
Extraversion (r = .463, p < .01) and a smaller, but significant negative
correlation with Neuroticism (r = -.287,
p < .01), such that primary control is associated with increased levels of
Extraversion and reduced levels Neuroticism. Correlations between secondary
control and personality variables are lower, such that secondary control is also
associated with higher levels of Extraversion, but is not significantly
correlated with Neuroticism (r = -.108, p > .05) .
Overall, the results from Study 2 can be summarised as follows. Primary and
secondary control each explained significant amounts of unique variance in
positive psychological adjustment variables (Subjective Quality of Life,
Positive Affect and Positive Thinking). The results for negative adjustment
(Negative Affect) showed that only primary control significantly predicted
Negative Affect.
It was found that, as predicted, people who reported an imbalance in their
levels of primary and secondary control (particularly high levels of Primary
Control but low levels of Secondary Control) reported a lower Subjective
Quality of Life, less Positive Affect and less Positive Thinking, than
participants who reported relatively higher levels of both primary and
secondary control.
However, contrary to predictions, no significant differences in levels of
adjustment were found between the other control-imbalanced group (LoPrim-
HiSec) and the control-balanced group.
It was also found that secondary control predicted Subjective Quality of Life
amongst people with both high and low perceptions for primary control, thus
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demonstrating that secondary control does not function only as a back-up
control strategy for people with low perceptions for primary control.
Finally, both primary and secondary control continued to explain significant
amounts of unique variance in positive adjustment, beyond the variance in
adjustment explained by the effect of the personality factors of Extraversion
and Neuroticism. Furthermore, the extent to which personality explained
control-adjustment variance is shown by the magnitude of reductions in
adjustment variance explained by primary/secondary control, after variance
attributed to Extraversion and Neuroticism was accounted for. Results
showed that the inclusion of personality variables into the prediction of
positive adjustment reduced the primary control-adjustment variance to a
greater degree than the variance shared between secondary control and
adjustment. This may be explained by the stronger correlations observed
between personality variables and primary control, compared to the magnitude
of relations observed between personality variables and secondary control.
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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)
One of the aims of Study 2 was to factor analyse the PSCS, following changes
made to the format and wording of secondary control items. It was found that
the changes made to the instrument did not alter the two-factor simple
structure observed in Study 1, such that primary control items loaded
significantly onto one factor and secondary control items loaded significantly
onto the other factor. Furthermore, reliability analyses conducted in Study 2
demonstrated that the items on the scale show adequate item-total correlations
and good internal consistency of both the primary control sub-scale and the
secondary control sub-scale.
The development of a new measure of primary and secondary control with
conceptually diverse control strategies was seen as necessary in order to
redress potential measurement biases in other studies investigating the
adaptive value of primary/secondary control (Thompson et al., 1994;
Thompson et al., 1996). These studies operationalised secondary control as
“acceptance” over numerous negative outcomes associated with HIV
diagnosis amongst prison inmates. It is believed that operationalising
secondary control in such vague, non-descriptive terms as general acceptance
of negative outcomes fails to capture the conceptual diversity and complexity
of methods by which people seek to control internal psychological states.
Furthermore, operationalising secondary control as general acceptance of
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negative outcomes is conceptually equivalent to helpless-acceptance while
disregarding the specific cognitive/behavioural processes that people may use
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in order to derive meaning, explanation and possible benefits associated with
facing uncontrollable events (e.g. “I’ll be stronger for it”).
In short, these definitions of primary control as equivalent to changing negative
outcomes, and secondary control as a vague acceptance without reflection on
explanation, meaning or potential benefits associated with uncontrollable events
were overly simplistic. For example, Thompson et al. (1996) operationalised
primary control as the person’s rating as to “How much control do you feel you
have over…” (followed by a list of 23 relevant aspects of prison life). While
secondary control was measured by asking, “How much do you feel O.K. about...
(the 23 aspects of prison life) …because you just accept it and don’t try to change
it”.
Hence, it is believed that operational definitions such as these have led to an
inherent bias in measures of control that may have artificially magnified the
benefits associated with primary control, whilst minimising the adaptive role of
secondary control processes.
The consistent findings of a two-factor structure with primary control items
loading one factor and secondary control items the other factor across the two
studies, provide good evidence that the PSCS is a valid measure of the
primary/secondary control construct. Furthermore, reliability analyses of the
PSCS across the two samples demonstrate that the PSCS items show adequate
item-total correlations and the primary and secondary control scales of the PSCS
show high internal consistency.
The instrument was developed in accordance with the theoretical formulations of
primary/secondary control proposed by Rothbaum et al. (1982) and Weisz et al.
(1984). Particular reference was made to operationalising a diverse range of
possible secondary control strategies based on the predictive, vicarious, illusory
and interpretive secondary control strategies discussed by Rothbaum et al. (1982)
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and Weisz et al. (1984). In addition, a review of coping literature was made to
identify additional secondary control strategies that people use in order to
minimise the psychological impact of events, while remaining passive toward
changing the environment. Furthermore, a range of conceptually diverse primary
control strategies were selected from the Optimisation in Primary/Secondary
Control scales (OPS Scales) developed by Heckhausen et al. (1998).
Hence, the PSCS is a new measure of control that aimed to operationalise a
greater diversity of control strategies that measured specific cognitive/behavioral
mechanisms of primary and secondary control that incorporate notions of
meaning, explanation, or benefits associated with implementing the particular
control strategy. Furthermore, factor-analyses and reliability-analyses
demonstrate that the PSCS provides a valid and reliable measure of primary and
secondary control.
9.2 Primary/Secondary Control and Positive Psychological
Adjustment
The positive semi-partial correlations between primary/secondary control and
psychological adjustment show that increasing levels of both primary and
secondary control were associated with increasing levels of positive psychological
adjustment. Considering that Study 1 also found positive semi-partial correlations
between primary/secondary control and the three positive adjustment variables,
the observed positive relationships between primary/secondary control and
positive psychological adjustment are considered reasonably robust.
Previous empirical investigations of the relationship between primary and
secondary control and psychological adjustment had only used measures of
negative psychological adjustment (e.g. level of depression). These studies
showed that control was typically associated with decreased levels of negative
affect (Thompson et al., 1993; Thompson et al., 1994; Thompson et al., 1996;
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Thompson & co-workers, 1998). Hence, the present data furthers the potential
role for primary and secondary control processes in psychological adjustment by
demonstrating that both control processes (including relatively passive strategies
of secondary control) are related to increased levels of positive psychological
processes.
Primary control may be intuitively linked to positive psychological adjustment in
that primary control strategies involve the individual making direct, active
attempts to change problem situations, other people and events, to meet the
developmental needs and wants of the person (see Heckhausen & Schulz, 1995).
However, secondary control theoretically involves strategies that are inherently
passive (i.e. they do not involve active manipulation of the environment) and were
therefore typically viewed by researchers and clinicians as relinquished control
(Rothbaum et al., 1982). For instance, the relative passivity of secondary control
is evident in strategies such as, ‘thinking bad might happen’ (predictive secondary
control), using denial, or doing something pleasurable to forget about the
problem. These strategies may reflect a passivity toward making changes to the
external, or environmental aspects of the problem situation; however, this hides
the extent to which secondary control strategies involve direct, active attempts to
manage internal, cognitive and affective states. Hence, the present data provide
empirical support for Rothbaum et al. (1982) who proposed that passive coping
behaviours that do not involve direct manipulation of external problem situations
(e.g. denial or ‘thinking bad might happen’) actually do reflect a
positive/protective attempt to control internal states. Rather than being indicative
of relinquished control, as suggested by learned helplessness research (Rothbaum
et al., 1982).
While significant relationships were observed between control and positive
psychological adjustment, the cross-sectional nature of the design of Studies 1 and
2 cannot be regarded as evidence of a causative role between control strategies
and positive psychological adjustment. However, as discussed in Study 1, much
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of the original work on the adaptive value of control did use experimental
manipulations. These studies typically involved manipulating people’s
perceptions of control over a stimulus in order to bring about measurable changes
in the person’s reported degree of distress (see Averill, 1973 for a review; Miller,
1979; Mills & Krantz, 1979; Thompson, 1981). These experiments typically
manipulated the person’s perception for primary controllability over a relatively
minor stressor (e.g. a blood-donoring procedure), but did not manipulate
secondary control. However, evidence of experimental manipulations of
secondary control are evident within the extensive experimental work
investigating outcomes associated with cognitive therapy (see Teasdale, 1985 for
a review). Hence, for the purposes of further discussion it is assumed that the
relationship between primary/secondary control and positive psychological
adjustment is causative.
Although not an explicit aim of the current study, the observed relationships
between primary/secondary control and Negative Affect were far weaker than the
relationship between primary/secondary control and measures of positive
adjustment. That is, results showed that secondary control failed to significantly
predict Negative Affect. Whilst primary control statistically related to NA, the
magnitude of the relationship was relatively small. Since no a priori assumptions
were made regarding the relationship between control and Negative Affect or
negative psychological adjustment, any interpretation of this result should be
examined with caution. Nevertheless, such a result is somewhat consistent with
Thompson et al. (1996) study that reported a non-significant relationship between
secondary control and distress in two out of three regression procedures (Time 2
and a longitudinal regression). However, inconsistent with the current data is
Thompson et al. (1994) finding of a small, yet significant negative relationship
between secondary control and distress.
9.3 The Primacy of a Balance in the Levels of Primary and
Secondary Control for Positive Psychological Adjustment
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Previous theory and research in primary and secondary control has made various
claims about the functional nature of primary and secondary control. Particularly,
that primary control maintains functional primacy over secondary control
(Heckhausen & Schulz, 1993; Thompson et al., 1994; Heckhausen & Schulz,
1995; Thompson et al., 1996; Thompson & co-workers, 1998; Heckhausen &
Schulz, 1999). In this view, primary control has primacy in terms of having
greater adaptive value than secondary control, and being the preferred control
strategy. Furthermore, secondary control’s functional role is theoretically
construed as secondary to primary control in that secondary control was purported
to chiefly function as a compensatory control strategy for people who perceived
low levels of primary control. Hence, according to primacy theory, as an
individual confronts loss or failure in their environment (loss of primary control)
secondary control primarily serves to protect motivation and emotional resources
(e.g. self-esteem) in order to support further efforts at primary control
(Heckhausen & Schulz, 1995; 1999). This compensatory, or ‘sidekick’ nature of
secondary control as proposed by primacy theorists, recently led to the metaphoric
description of secondary control as primary control’s “…confederate”
(Heckhausen & Schulz, 1999 p.606).
However, data from Study 2 demonstrated that rather than primary control being
functionally more adaptive than secondary control, it is the balance or ratio of
levels between primary and secondary control which predicts higher levels of
positive psychological adjustment. Hence, it was shown that the adaptive value of
primary control is limited to the extent that secondary control skills are also
developed. That is, individuals with relatively high levels of primary control, but
low levels of secondary control reported a lower Subjective Quality of Life, less
Positive Affect and less Positive Thinking compared to individuals with relatively
high (average or above) levels of both primary and secondary control.
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These data replicate (in part) the results observed from Study 1 which found that
the control-imbalanced group (high primary control, combined with low
secondary control) reported a significantly lower Subjective Quality of Life and
less Positive Thinking than the control-balanced group (high levels of both
primary and secondary control). The main difference in the results between
Studies 1 and 2 is that in the first sample, the HiPrim-LoSec group were found to
have reduced levels of Subjective Quality of Life and Positive Thinking,
compared to the control-balanced group, but not less Positive Affect. Considering
the only differences between the two groups was the level of secondary control, it
was suggested that secondary control may not function at the level of more stable,
affect-based psychological structures such as Positive Affect, instead operating
more at the level of less stable evaluations of cognitive/affective states such as
one’s subjective quality of life and the frequency of positive thinking over the
past week. However, the initial finding of the HiPrim-LoSec group reporting
equivalent levels of Positive Affect was not replicated in the data from Study 2.
Instead, as was predicted, the control-imbalanced group HiPrim-LoSec reported
significantly less Positive Affect than the control-balanced group (HiPrim-HiSec).
Hence, the explanation that secondary control may not function at the level of
stable traits such as Positive Affect was not supported in the data from Study 2.
Overall, results from both studies demonstrate that secondary control’s
relationship with Positive Affect is relatively strong. That is, secondary control
predicted significant amounts of variance in Positive Affect. However, when
comparing the Positive Affect levels of groups that are high or low in secondary
control, the data suggest a less strong relationship between secondary control and
Positive Affect. This was indicated by the inconsistent finding of Positive Affect
differences between high and low secondary control groups over the two different
samples.
In short, the control-imbalance of high primary control, combined with low
secondary control, was found within both studies to have reductive effects on
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Subjective Quality of Life and Positive Thinking. However, only data from Study
2 supports the hypothesised reductive role of the control-imbalance (HiPrim-
LoSec) on Positive Affect levels. Hence, any suggestion that secondary control
does not operate at the level of stable traits like Positive Affect, but does function
to influence cognitive/ affective states (like Subjective Quality of Life) could be
described as tenuous, at best.
Data from Study 1 also showed that the adaptive value of secondary control was
limited to the extent that primary control skills were developed. That is, people
who reported low levels of primary control, combined with high levels of
secondary control reported a lower Subjective Quality of Life, less Positive Affect
and less Positive Thinking, compared to people with average (or above) levels on
both control processes. However, the results for the control-imbalanced group
(LoPrim-HiSec), in Study 2 did not confirm this result.
The consistent lack of a statistically significant finding across the three dependent
variables for this group alone in Study 2, suggested that something about the
LoPrim-HiSec group itself may explain why the findings were not replicated.
Indeed, closer inspection of the mean levels of primary and secondary control for
the LoPrim-HiSec group showed that the LoPrim-HiSec group in Study 2 actually
had slightly above-average levels of primary control. Apparently the Cluster
Analysis led to the creation of a group that was low in primary control when
compared with other clusters formed in the analysis, but was actually reporting
above-average levels of primary control compared to the whole sample. In short,
the “low primary control” aspect of the LoPrim-HiSec group was in effect,
actually slightly above-average. Considering the positive, significant semi-partial
correlations observed between primary control and the positive adjustment
variables, it is possible that the average levels of primary control reported by this
group may explain the statistically equivalent levels of positive adjustment to the
control-balanced group.
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9.3.1 Possible Explanations for the Primacy of the Primary/Secondary
Control Balance in Positive Psychological Adjustment
The greater positive psychological adjustment of individuals who maintain
a balance in levels of both primary and secondary control processes may be
partly explained by the comprehensive nature of their coping skills. That
is, individuals with high levels of both primary and secondary control have
an expanded coping repertoire that can respond to a variety of problems
that may have quite varying degrees of objective and subjective
controllability associated with them. Hence, individuals with average or
higher levels of both primary and secondary control skills have the dual
abilities to approach problems by manipulating the environmental
conditions to meet their needs, as well as the ability to be able to control
their concomitant emotional reactions to problems.
This working knowledge of both primary and secondary control processes
can be viewed as allowing for the optimal mix of approach-avoidance
coping in order to manage stressors that come with varying degrees of
objective controllability and associated feelings of self-efficacy. Within
the coping literature, both approach and avoidant coping strategies have
theoretically been suggested to have a protective role in coping with stress.
Yet the adaptive value of approach coping strategies has typically been
suggested as more helpful than avoidant strategies (see Roth & Cohen,
1986 for a review).
In contrast, Gomez et al. (1999) provided empirical evidence of the benefits
associated with avoidant coping. Particularly, they found that avoidance
coping was positively correlated with approach coping styles. Hence, the
researchers proposed that the adaptive role for avoidance coping may be
that it tends to be associated with approach coping. The tendency for
approach and avoidance coping to be associated with each other allows
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people to use a mix of both approach and avoidance coping strategies,
resulting in a flexible approach to conflicts, problems and attaining goals.
This view is consistent with the data from Study 1 that showed optimal
levels of Subjective Quality of Life, Positive Thinking and to a lesser extent
Positive Affect were observed for participants who reported a control
repertoire involving both primary and secondary control. That is, primary
control can be conceptualised as an “approach” coping style in which
problems are dealt with by directly approaching and manipulating external
problem circumstances. In contrast, secondary control strategies typically
involve an inherent avoidance of the environmental aspects of the problem,
instead focusing more on attempting to control the internal reactions to the
problems. Consequently, people who develop a coping repertoire involving
both primary and secondary skills will be able to generate the most
advantageous mix of approach and avoidance strategies resulting in a
flexible approach to coping that can deal with the inherent changes and
various degrees of objective controllability over the environment.
In contrast, people who tend to rely on, favour, or are knowledgable of mostly
primary control may be vulnerable to having little or no coping response in
situations with objectively limited controllability associated with them. Indeed,
Evans et al. (1993) described numerous empirical studies that demonstrated the
problems associated with exercising high levels of primary control behaviour,
motivation or cognitions in the context of low environmental opportunities for
control. For instance, people who tried to cope with the Three Mile Island power
plant accident by exercising high levels of direct, active control (e.g. political
action, rallies, complaining) were found to have greater levels of physiological
and task-performance stress than people who attempted to manage their emotional
reactions by focusing on other things in their lives (i.e. secondary control; Collins,
Baum & Singer, 1983).
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Furthermore, problem situations that are not easily amenable to primary control
may require some coping response in which the cognitive, affective and
behavioural reactions to problems are managed in order to insure that the
cognitive and emotional conditions are adequate for effective decision-making
and problem-solving. As Folkman (1984) claimed, “theoretically, the
effectiveness of problem-focused coping efforts [conceptually similar to primary
control, as discussed previously] depends largely on the success of emotion-
focused efforts. Otherwise heightened emotions will interfere with the cognitive
activity necessary for problem-focused coping” (p. 845). Roth and Cohen (1986)
agree, suggesting the theoretical importance of withholding a primary control
response in coping. By withholding an approach-coping response (instead
focusing on preventing feelings of being overwhelmed) the person provides
themselves with adequate time to assimilate information about the stressor and to
mobilise resources in order to better plan for changing their environment.
In addition, as mentioned previously, the control imbalance of high primary
control, low secondary control, appears analogous to the excessive levels of active
control in workplace practices and relationships associated with the Type A
behaviour pattern described by Glass (1977). Moreover, the Type A behaviour
pattern has also been associated with increased potential for frustration, sensing
time pressure and becoming aggressive (i.e. suggestive of low secondary control).
Hence, the Type A behaviour pattern and the associated consequences are
congruent with the current data. That is, people who maintain excessively high
levels of active (primary control) over circumstances, people and events,
combined with a reduced ability to manage their emotions following failure or
frustration (i.e. low secondary control), report a lower Subjective Quality of Life,
less Positive Affect and less Positive Thinking, compared to people who have the
capacity for both active control and managing negative emotions.
Just as people who emphasise their levels of primary control over secondary
control are vulnerable to contexts of objective low controllability, people that
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favour secondary control strategies over primary control are vulnerable to missing
opportunities for controlling problems in a way that meets the individual’s
particular developmental needs and wants (Heckhausen & Schulz, 1995; 1999).
That is, a person who emphasises their need for secondary control typically
accommodates to problems by controlling their aversive cognitive/affective
reactions to those problems. However, by emphasising needs for emotional
control (without also looking for primary control opportunities), over time, the
person is increasingly vulnerable to missing objective opportunities to control the
environmental circumstances, people and events that fit their desired course in life
and to meet their particular developmental goals.
In summary, previous theory and research in primary and secondary control
suggests that primary control has functional primacy over secondary control.
However, the data from Studies 1 and 2 suggest that high levels of primary
control (when combined with low levels of secondary control) were associated
with reduced levels of positive psychological adjustment. Similarly, high levels
of secondary control (combined with low levels of primary control) were also
associated with reduced levels of positive adjustment in Study 1. However, this
result was not supported in Study 2. The lack of statistically significant
differences between adjustment levels of the LoPrim-HiSec group and the
control-balanced group in Study 2 was explained in terms of methodological
problems associated with the creation of the clusters that were used in order to test
the balance hypotheses.
In short, as hypothesised, people who report a control-imbalance (high on one
control process, but low on the other) tended to report themselves to experience
less positive psychological adjustment than people who maintain higher levels of
both primary and secondary control. Hence, rather than one control process being
described as having functional “primacy” over the other, the current data suggests
that maintaining a control-balance, or relatively high levels of both primary and
secondary control has functional “primacy” in positive adjustment.
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These results support Gould’s (1999) recent critique of Heckhausen and Schulz’s
(1995) life-span theory of human development as culturally biased for proposing
the functional primacy of one type of control (primary) over the other
(secondary). According to Gould (1999), Shapiro et al. (1996) and Weisz et al.
(1984), an examination of control in Asia reveals cultural prescriptions that
highlight the functional importance of secondary control over primary control.
Heckhausen and Schulz (1999) replied to Gould’s critique with a critique of
methodological issues within the studies that suggested the greater prescription of
secondary control in Asian cultures.
Although Studies 1 and 2 did not investigate cultural differences in the use of
control, the present data do not support any theoretical description of one type of
control being functionally more adaptive than the other, even in a Western
population. The data from both studies show that the benefits associated with one
control process is dependent on the balanced development of the other control
process in the person’s control repertoire. That is, rather than secondary control
being conceived as primary control’s “confederate” (Heckhausen & Schulz, 1999,
p. 606), the relationship between the two control processes may best be described
as one of strong interdependent support, or co-dependence. That is, maintaining
a preference for one control process over the other is subject to problems as
described previously. However, by maintaining a balance of relatively higher
levels of both primary and secondary control, the shortfalls associated with one
control process is minimised by the function of the other control process. For
example, the person who emphasises primary control only, may be prone to
failure through distracting emotional states that interfere with the effective choice
and use of primary control strategies, whereas if the person emphasises secondary
control, they are prone to failure due to an inherent passivity toward manipulating
the environment. However, by developing an awareness of both control
processes the person can reduce the negative effects associated with each control
process. That is, the rational exercise of manipulating the environment to get
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what we want may be assisted by maintaining a relatively even
cognitive/emotional keel. On the other hand, maintaining an even emotional keel
needs to be supported by behaviour aimed at manipulating the environment to
achieve the individual’s needs and wants.
Overall, the present data support the notion of primary control and secondary
control as two interdependent processes which functionally support each other in
order to provide a flexible approach toward meeting goals and solving problems
based on control of both self and environment.
9.4 Secondary Control’s Functional Role in Adjustment is Greater
than Simply Compensating for Low Primary Control
Results from Study 1 showed that, amongst participants with reported low levels
of primary control, secondary control continued to significantly predict SQOL
after primary control was entered into the prediction. Indeed, with secondary
control in the equation, primary control ceased to predict SQOL for participants
with low primary control. This suggested that secondary control might play an
important back-up role for people with low levels of primary control. However,
even amongst participants with high levels of primary control, secondary control
continued to predict significant amounts of SQOL variance. This suggested that
secondary control did not just act as a compensatory strategy for people with low
levels of primary control, but that secondary control had an intrinsic relationship
with SQOL, regardless of whether primary control is high or low.
As predicted, Study 2 also provided evidence of secondary control having a
greater functional role in psychological adjustment than acting only as a
compensatory mechanism for people with reported low primary control. The data
supported the findings from Study 1 by demonstrating that even for a group with
reported higher levels of primary control, secondary control continued to
significantly predict variance in Subjective Quality of Life. That is, even with
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average or above levels of primary control, secondary control still predicted
10.3% unique variance in SQOL. Most unexpected was the finding that primary
control failed to predict SQOL at all, amongst the high primary control group.
Data from Study 1 showed that 20.4% of SQOL variance was explained by
primary control amongst the high primary control group, whereas this figure was
reduced to 1% in Study 2. Hence, for participants with high primary control in
Study 2, it is actually secondary control that contributed to explaining variance in
SQOL, not primary control. One possible reason for the reduced role of primary
control (and the increased role of secondary control) amongst the high primary
control group, may be due to the differences in the levels of secondary control
observed between samples 1 and 2.
In the first sample, the mean level of secondary control for the high primary
control group was 83.73. For the second sample the mean levels of secondary
control for the high primary control group was 109.09. Considering the positive
relationships between all three measures of positive psychological adjustment and
secondary control (such that people with higher levels of secondary control were
associated with increasingly high levels of positive psychological adjustment),
secondary control may function as a protective factor. This protective value of
secondary control may have resulted in the high primary control group mostly
relying on secondary control skills in dealing with problems and meeting goals,
rather than relying on primary control. Put another way, the high primary control
group in sample 2 may have reported much higher levels of secondary control that
served to reduce their reliance on primary control skills. Hence, primary control
in sample 2 was found to be unimportant to a group with high levels of primary
control.
Ironically, such a result is suggestive that secondary control’s functional role in
adjustment is more useful to people with high levels of primary control, rather
than people with low primary control, as previous theorists have suggested
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(Heckhausen & Schulz, 1995; Heckhausen, Schulz & Wrosch 1998; Heckhausen
& Schulz, 1999).
9.4.1 The Function of Secondary Control in Positive Psychological
Adjustment
Previous theory in primary and secondary control suggested that the function of
secondary control is to simply act as a compensatory mechanism (back-up) to
maintain motivational resources (e.g. hope and self-esteem) in the face of losses,
or failure in primary control (Heckhausen & Schulz, 1995; Heckhausen et al.,
1998; Heckhausen & Schulz, 1999). Another function of secondary control,
according to the life-span theory of human development (Heckhausen & Schulz,
1995), is “selective secondary control” which comprises of volitional self-
management strategies aimed at enhancing commitment to goals, as well as
minimising distractions and competing goals (Heckhausen et al., 1998, p. 7).
The data from Study 1 supported Heckhausen & Schulz’s (1995; 1999) functional
description of secondary control as a compensatory control mechanism for low
primary control participants. The data from Study 2 did not confirm the
compensatory role of secondary control. That is, results from Study 2 showed
that primary control significantly predicted positive adjustment amongst people
with low primary control, which somewhat challenges the notion that people with
low primary control need a compensatory control strategy.
Instead, results from Studies 1 and 2 demonstrated secondary control’s role
extends both to people with high and low levels of primary control; not just low
primary control participants as primacy theorists suggest.
Hence, the hypothesis regarding secondary control being more than a back-up
strategy for low primary control was supported in both samples, and is therefore
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considered robust. What then might be the functional nature of this greater role of
secondary control?
Heckhausen et al. (1998) more recently expanded their theoretical proposition of
the role of secondary control, proposing the importance of secondary control in
enhancing a person’s commitment to primary control goals. That is, according to
their life-span model of human development (Heckhausen & Schulz, 1993; 1995)
the developmental potential for an individual is determined (in part) by their
ability to choose one option amongst the multiple courses of actions that may be
available to the person, then generating a volitional commitment to the chosen
goal. In their view, this is the role of “selective secondary control” strategies
which allow the person to maintain volitional commitment to the person’s chosen
goals, whilst reducing the commitment to competing possible courses of action (p.
7). Such strategies may take the form of cognitively enhancing commitment to a
goal by reminding oneself of the benefits of finally achieving the goal, or
avoiding distractions that may interfere with the goal (Heckhausen et al. 1998).
While this selective function of secondary control represents a theoretical
expansion of it’s role in adaptive functioning beyond a compensatory function,
the measure of primary/secondary control used in Studies 1 and 2 did not
incorporate items that operationalise the Heckhausen et al. (1998) concept of
“selective secondary control”. Hence, the additional variance in positive
adjustment accounted for by secondary control amongst people with high levels
of primary control in Studies 1 and 2, cannot be explained by this proposal.
The secondary control items used in Studies 1 and 2, highlighted the role of
secondary control in controlling the psychological impact of events. Hence, the
explanation for secondary control’s role in positive adjustment, for people with
high levels of primary control (as opposed to the compensatory benefits that may
be associated for people with low primary control) is more likely to do with this
cognitive/emotional management aspect of secondary control.
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As mentioned previously, the management of emotions (secondary control) may
be of central importance to the psychological processes (e.g. decision-making and
problem solving) that are part of pro-active attempts at controlling the
environment (i.e. primary control; Folkman, 1984; Roth & Cohen, 1986). Hence,
the variance in positive adjustment accounted for by secondary control amongst
people with high levels of primary control may be explained by the importance of
managing emotions during primary control striving.
For example, a worker’s ability to do their tasks (primary control) may be
impeded by them ruminating on the unresolved argument they had with their
partner before work. Furthermore, a reduced ability to control emotions in one
context (family) may begin to effect other people from other contexts (e.g.
colleagues at work), thus hindering others performance as well as their own. In
addition, when faced with more difficult challenges, secondary control strategies
may also allow for greater tolerance of aversive environmental conditions,
allowing the person more time and analysis of the problem situation and it’s
potential solutions. In contrast, a person who faces a stressful challenge without
adequate understanding of how to control their cognitive/emotional reactivity to
events may be prone to reducing their reactivity by making a more immediate
primary control response to the environment. This more immediate primary
control response may reduce the person’s level of discomfort, but it may not
provide adequate time to incorporate all the necessary information in order to
fully understand the problem and decide on the most adaptive solution, amongst a
possible range of solutions.
In summary, data from both Studies 1 and 2 suggest that the role of secondary
control in positive psychological adjustment is more than simply acting to
compensate for low levels of primary control. Most importantly, secondary
control predicted significant amounts of variance in positive adjustment for
people with high levels of primary control. Previous theory suggests that the
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nature of this greater functional role for secondary control may be the importance
of managing cognitive/affective reactivity to events in order to allow for the most
adaptive primary control response. Future research designs could test this
proposition more precisely, by investigating the personal/interpersonal outcomes
following people’s primary control responses, amongst sub-samples of people
with both high and low levels of secondary control. Such a research design could
be used to determine whether higher levels of secondary control do, indeed, relate
to better intrapersonal, inter-personal or objective outcomes following a primary
control response.
9.5 The Role of Personality in Explaining the Relationship Between
Primary/Secondary Control and Positive Psychological Adjustment
The exploratory analysis designed for Study 2 proposed that the relationship
between primary/secondary control and positive psychological adjustment might
be explained by the personality dimensions of Extraversion and Neuroticism.
Hence, a series of hierarchical regressions was conducted in which Extraversion
and Neuroticism were entered first into the prediction of each of the positive
adjustment variables (Subjective Quality of Life, Positive Affect and Positive
Thinking). Next, primary/secondary control were entered into the prediction of
positive adjustment, in order to assess primary/secondary control’s capacity to
predict variance in positive adjustment, after variance in positive adjustment that
could be attributed to personality was already accounted for.
It was found that primary/secondary control continued to predict significant
portions of variance in all three positive adjustment variables (Subjective Quality
of Life, Positive Affect and Positive Thinking) beyond the variance accounted for
by the personality factors. The capacity of both primary and secondary control to
continue to predict significant portions of variance in adjustment demonstrates
that significant portions of shared variance between primary/secondary control
and all three measures of positive adjustment cannot be attributed to the effect of
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the personality dispositions of Neuroticism or Extraversion. Therefore, the role
of personality in explaining the relationship between primary/secondary control
and positive psychological adjustment is limited.
While Extraversion and Neuroticism could not entirely account for the adaptive
value of primary/secondary control, results showed the extent to which
personality did explain shared variance between primary control and adjustment,
and secondary control and adjustment. Hence, the smaller reductions in
proportions of variance in adjustment accounted for by secondary compared to
primary control, after the inclusion of personality variables, suggests that
secondary control’s relationship to positive adjustment is less determined by the
personality factors than the relationship between primary control and positive
adjustment. This suggests a greater influence for personality in explaining the
adaptive value of primary control, compared to secondary control.
These results provide initial data to help identify the mechanisms that explain why
primary and secondary control are associated with positive psychological
adjustment. That is, results from the exploratory analysis in Study 2 suggest that
part of the explanation of why control is associated with higher levels of positive
adjustment is due to the influence of the personality factors of Extraversion and
Neuroticism. Furthermore, these personality factors explain more of the primary
control-adjustment link, than they do the secondary control-adjustment link.
Thus, suggesting that whilst approximately 65-75% of the primary control-
adjustment link was explained by personality, leaving approximately 35% of the
variance yet to be explained, much higher portions of variance in the secondary
control-adjustment link remain unexplained.
Hence, future research could be aimed at determining what other factors might
explain additional portions of control-adjustment variance. Other potential
constructs that might explain additional portions of shared variance may include
other personality variables, objective measures of social/economic conditions, or
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any other construct that can be theoretically, or intuitively linked to both
primary/secondary control and to psychological adjustment. Nevertheless, data
from Study 2 suggests that the positive outcomes enjoyed by people with higher
levels of primary/secondary control cannot be fully explained by the influence of
personality characteristics such as Extraversion or Neuroticism.
The results for negative adjustment however, showed that the relationship
between primary/secondary control and Negative Affect was explained by the
effect of the personality dimension of Neuroticism. It was found that that both
primary control and secondary control failed to predict variance in Negative
Affect, after variance attributed to Neuroticism was accounted for. Extraversion
failed to predict Negative Affect at the first step of the regression. Hence, in
psychological terms, the tendency for people with low levels of
primary/secondary control to experience relatively higher levels of Negative
Affect, may be explained by the influence of a personality disposition that
predisposes the person toward frequent negative feelings (Neuroticism).
This result can be contrasted with the results for the positive adjustment variables
(Subjective Quality of Life, Positive Affect and Positive Thinking) which
continued to be significantly related to primary/secondary control, after variance
attributed to Neuroticism and Extraversion was accounted for. That is, results
from Study 2 show different patterns of relationship between primary/secondary
control, personality and positive adjustment, versus the pattern of relations
observed between control, personality and negative adjustment. This different
pattern of relations between variables measuring positive versus negative
adjustment may be a valid indication that the relations between primary/secondary
control and positive adjustment are not reciprocal to measures of negative
psychological functioning. Hence, in order to develop a more comprehensive
understanding of the adaptive value of primary/secondary control, future research
would best select measures that operationalise both positive and negative
expressions of psychological health.
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Further investigation of the pattern of relations amongst personality, control and
both positive and negative measures of adjustment would assist in determining
whether the different pattern of relations observed between positive and negative
measures are robust. Such research could have important clinical implications in
that attempts to clinically train people in primary and secondary control (e.g.
Weisz, Thurber, Sweeney, Proffitt & LeGagnoux, 1997) may lead to differential
benefits between effecting positive outcomes (e.g. improving Subjective Quality
of Life) versus reducing negative outcomes (e.g. reducing level of depression).
9.6 Further Limitations and New Directions for Research
The implications of the present data suggest the adaptive value associated with a
balance in the levels of control processes, as opposed to preferring one control
process over the other. However, a central assumption within Studies 1 and 2 is
that having higher levels of Subjective Quality of Life, Positive Affect and
Positive Thinking is actually more adaptive, or indicative of better psychological
adjustment. An important qualification is to recognise that the highest levels of
these positive cognitive/affective states does not necessarily imply highest levels
of psychological adjustment or psychological health.
For example, the highest levels of the positive feeling states may be seen in
clinical disorders involving manic or hypomanic episodes (see Kaplan & Sadock,
1998 for an extended description of mania/hypomania). Hence, excessively high
levels of positive cognitive/affective states may actually impede the person’s
ability to adapt to their environment.
Hence, another potential direction for future research could be to study the
adaptive value of primary/secondary control and incorporating more objective
measures of social, emotional or occupational functioning and checking them
against more objective measures of functioning (e.g. the Objective Quality of Life
Scale; Cummins 1997b). By incorporating both subjective and more objective
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measures of psychological functioning within the one study, future research could
empirically confirm that the subjective reporting of higher levels of positive
cognitive/affective states actually corresponds with better objective social,
emotional and occupational functioning. Together, the suggested additions to
future research conducted with the primary/secondary control construct may assist
in the development and understanding of psychological processes that may
improve people’s ability to control any subjective condition (e.g. psychological
disorders, happiness or discontent) or objective conditions in their life (e.g.
housing, work environments or aspects of physical health).
In summary, the present data suggest that future attempts to enhance peoples’
preference for primary and secondary control would best achieve healthy
outcomes by encouraging a comprehensive repertoire of control strategies
involving both control mechanisms. That is, the current analysis demonstrated
that developing a preference for one control process over the other is associated
with reduced levels of positive psychological adjustment. Furthermore, the
present data suggest that the function of secondary control may be more than
simply compensating for low primary control. That is, secondary control may be
of critical importance to the effective functioning of primary control.
Furthermore, it was found that the relationship between control and positive
psychological adjustment may be partly explained by the personality dimensions
of Extraversion and Neuroticism.
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CHAPTER 10
CONCLUDING OVERVIEW
10.1 Summary and Conclusion
The aim of this thesis was to test a number of theoretical propositions regarding
the adaptive value of control. Previous theory within the primary/secondary
control framework suggested the primacy of primary control. This theory
proposes that primary control is intrinsically more adaptive than secondary
control, and secondary control is conceived as simply acting as a back-up strategy
for when primary control is low.
However, previous theoretical and empirical evidence reviewed suggests that
rather than primary control being inherently more adaptive than secondary
control, high levels of primary control have been shown to be associated with
various negative mental and physical outcomes. Furthermore, some cross-cultural
evidence suggests that Western cultures show a cultural bias, in which the
benefits associated with primary control are emphasised, whereas Asian cultures
emphasise the adaptive value of secondary control over primary control. In
addition, contrasting with primacy theory, is the theoretical proposal by the
original authors of the two-process model, suggesting the importance of a balance
between the two-processes of control for optimal adjustment (Rothbaum et al.,
1982; Weisz et al., 1984).
Empirical research aimed at testing the functional primacy of primary control has
been limited and the results generally mixed or inconclusive. Furthermore,
previous attempts to operationalise primary and secondary control were vague and
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non-descriptive and therefore may have equated secondary control with helpless
acceptance. In addition, previous studies in primary and secondary control had
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measured only a limited set of constructs pertaining to negative psychological outcomes (i.e. depression and anxiety). Hence, relations between primary/secondary control and more positive and comprehensive indicators of psychological functioning (e.g. Subjective Quality of Life and Positive Affect) remained relatively unexplored.
Therefore, Study 1 involved the development of a new measure of primary and
secondary control, the Primary & Secondary Control Scale (PSCS). The PSCS
operationalises primary and secondary control by specifying precise
cognitive/behavioural mechanisms by which people may seek control over the
external environment (primary control) or control over their internal reactions to
events in order to minimise their impact (secondary control). In particular,
secondary control items were selected with reference to the predictive, vicarious,
illusory and interpretive types of secondary control discussed by the original
proponents of the primary/secondary control construct (Rothbaum et al., & Weisz
et al., 1984). In addition, literature from the coping area was scanned for
additional secondary control mechanisms by which people may minimise the
impact of events.
Factor-analyses of the PSCS conducted in Studies 1 and 2 demonstrated the
factorial validity of the scale, showing a two-factor simple structure in which
primary control items load onto one factor and secondary control items onto the
other factor. Furthermore, reliability analyses showed that the PSCS items
demonstrate adequate item-total correlations and good internal consistency to the
primary control and secondary control sub-scales.
Hypotheses were then developed for Study 1 in order to test primacy theory using
the newly developed Primary and Secondary Control Scale. Hence, it was
hypothesised that people who show a preference for one control process over the
other (“control-imbalanced”) would report lower levels of positive psychological
adjustment compared to people who maintained average or above-average levels
of both primary and secondary control (“control-balanced”). Furthermore, it was
hypothesised that secondary control’s role in adaptive functioning is greater than
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simply acting to compensate for low levels of primary control. Thus, secondary
control was predicted to explain significant amounts of variance in positive
adjustment, for people both high and low in terms of primary control. Study 1
also explored the relations between primary/secondary control and positive
measures of psychological adjustment, as opposed to measures of negative
psychological processes as reported in previous studies.
Results from Study 1 showed that as predicted, people with a control-imbalance
(average or above-average levels on one control process, but below average on
the other) reported lower levels of positive psychological adjustment, compared to
people with average or above levels of both primary and secondary control. It
was also found that secondary control was related to positive psychological
adjustment for both sub-groups of high and low primary control, suggesting that
secondary control has a greater role in adaptive functioning than had been
suggested by previous theory. In addition, results from Study 1 provided
evidence of significant relations between primary/secondary control and positive
measures of psychological adjustment.
A major aim of Study 2 was to conduct an exploratory analysis to determine the
capacity of the personality dimensions of Extraversion and Neuroticism to explain
the relationship between control and positive adjustment. In addition, this study
aimed to re-test the hypotheses from Study 1 in order to assess the robustness of
the observed findings.
Results generally supported those observed in Study 1, such that the control-
imbalanced group (high primary control, combined with low secondary control
[HiPrim-LoSec]) was found to have reduced levels of positive psychological
adjustment. The other control-imbalanced group (LoPrim-HiSec) did not show
reduced levels of positive adjustment as observed in Study 1. However, this
result was explained in terms of methodological problems associated with the
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creation of the cluster-group such that the LoPrim-HiSec group actually had
average levels of primary control.
In regards to the hypothesis regarding secondary control as having a greater
functional role than simply compensating for people with low primary control,
results in Study 2 supported those observed in Study 1. Results from both studies
show that secondary control explained variance in positive adjustment amongst
both high and low primary control sub-groups, confirming secondary control’s
role in positive adjustment as more than just acting to compensate for low primary
control.
The consistency of the findings across both studies does not support the primacy
of primary control. That is, optimally adaptive functioning was reported amongst
people who have a repertoire of control strategies involving relatively higher
levels of both primary and secondary control strategies. This makes evolutionary
sense in that the inherent shortfalls associated with each of the control processes
can be minimised by the operation of the other. This allows the person to adapt to
the variety of situations in life, which have varying levels of objective
controllability associated with them, by selecting the optimally adaptive mix of
approach-avoidance strategies. Hence, situations that are less amenable to
primary control (e.g. Multiple Sclerosis) could be met with a range of secondary
control strategies for minimising the psychological impact of the event. Whereas
situations with greater levels of objective controllability (e.g. a broken arm), may
be met with a range of primary control strategies that change the existing problem
situation by engaging the environment (e.g. going to Emergency).
In contrast, the person who shows a preference for one control process over the
other (as primacy theory suggests), appears to experience a reduced Subjective
Quality of Life, less positive thoughts and to a lesser extent, reduced levels of
positive feelings, compared to people who use both control processes (i.e. control-
balanced).
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Hence, it is suggested that people who emphasise their use of primary control
while tending to neglect secondary control, are at risk of experiencing strong
cognitive/affective states that may interfere with cognitive processes (e.g.
attention, concentration, problem solving and decision making) that are important
psychological resources for the optimal operation of primary control strategies.
For example, a worker with few secondary control strategies who performs poorly
at an important meeting may become distracted by their feelings of self-doubt and
disappointment over the perceived failure, leading them to concentrate less on the
day’s tasks at hand. Thus, secondary control strategies may minimise
psychological impacts of primary control failure, thereby reducing distraction
from subjective feelings of discontent (e.g. worry) or positive feelings (e.g.
romantic love). In short, the use of secondary control strategies allows the person
to maintain the necessary level of cognitive resources (attention, concentration
etc.) that permit full focus on primary control strategies and goals.
This function of secondary control is more to do with ensuring that the process of
primary control striving is optimally supported by good levels of cognitive skills,
thereby ensuring that the person develops and decides on the most advantageous
courses of solution and action considering the inherent limitations of the
environment. This “quality-assurance” function of secondary control is
conceptualised as additional to the back-up function of secondary control
proposed by Heckhausen and Schulz (1995), which is more concerned with re-
motivating the person’s primary control striving after failure or losses in primary
control.
On the other hand, people who emphasise their use of secondary control over
primary control run the risk of missing opportunities to achieve developmental
needs and wants. In the extreme case, very low levels of primary control could
result in failure to meet basic requirements for survival (e.g. food, shelter,
income).
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Study 2 also explored the capacity of personality factors of Extraversion and
Neuroticism to explain the control-adjustment relationship. Results showed that
both primary and secondary control continued to predict significant variance in
positive adjustment after variance attributed to Extraversion and Neuroticism had
been removed. This shows that the shared variance between primary/secondary
control and positive adjustment was only partially explained by the personality
dimensions of Extraversion and Neuroticism. Further analyses also demonstrated
that Extraversion and Neuroticism explained the primary control-adjustment link
to a greater extent than the secondary control-adjustment link. It was found that
this result was consistent across all three of the positive adjustment variables,
Subjective Quality of Life, Positive Affect and Positive Thinking.
10.2 Clinical Implications
The clinical implications of the present results are wide reaching across all models
of counselling and psychotherapy. That is, the findings concerning the role of a
balance in levels of both primary control and secondary control, suggest that,
regardless of the model of change that a clinician works with, optimal levels of
adjustment may best be achieved with a focus on the dual goals of improving the
person’s ability to manage their emotions (e.g. whether via insight or newly learnt
strategies for change), as well as encouraging pro-active attempts to achieve the
person’s desired needs and wants by engaging the environment. This is not to say
that every counselling relationship, or every problem would profit from a mix of
primary and secondary control interventions, because some problems necessitate a
greater level of one control process over the other due to differences in the
objective controllability associated with different problems and goals. However,
the results do suggest that clinicians and clients could benefit from a general
analysis of the person’s control repertoire over the course of the counselling
relationship and across all the assessed problem areas, in order to provide both
client and therapist with a road map to possible interventions.
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138
In summary, the primary/secondary control dichotomy represents a super-ordinate
construct for human change by providing a simple framework to understand the
two main ways by which people may achieve goals and solve problems. The
dichotomy is super-ordinate because all models of counselling and psychotherapy
can be conceptualised as attempting to improve the cognitive, affective and
behavioural functioning of the person by manipulating either the internal
functioning of the person’s beliefs and attitudes (e.g. psychoanalysis: secondary
control focus), the way the person engages their environment (e.g. solution-
focused therapy: primary control focus) or a combination of both (e.g. cognitive-
behavioural therapy: a combination of environmental and internal manipulation).
Hence, regardless of the client and clinician’s chosen framework for change, the
findings on the importance of the primary/secondary control-balance helps both
parties navigate through all the possible courses of intervention, suggesting to
clinicians to be cognisant of the importance of both types of control in people's
lives. Without paying attention to both control processes as potential sources for
intervention the present results suggest that clients may not achieve the optimal
benefit from their counselling because they remain vulnerable to the shortfalls
associated with the underdeveloped control process.
Another important clinical implication of the present results concerns clinicians’
interpretations of commonly experienced client behaviours in counselling
relationships. As Rothbaum et al. (1982) argue, learned helplessness research
(Seligman, 1975) had falsely interpreted behaviours involving a passive attitude
toward the environment, or withdrawing from attempts to control environmental
stressors, as indicative of relinquished control. In their view, certain behaviours
that reflect a passive attitude toward the environment and characterised at times
by psychological or behavioural withdrawal do not reflect a reduced desire or
attempt for control (giving-up), but a secondary attempt to minimise the
psychological impact of potentially debilitating and threatening situations. In
particular, the researchers argue that a lot of secondary control behaviour is aimed
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at minimising a particularly debilitating aspect of failure – disappointment.
Disappointment is particularly debilitating, in their view, because it represents a
loss of both primary control (to get what one wanted) as well as a loss of
secondary control (ability to control the emotional impact of the failure). Hence,
secondary control behaviours function to reduce chances of disappointment by
showing the person that there is some meaning, or benefit to be achieved from
failure experiences, thus preventing the person from disappointment.
The results from Studies 1 and 2 show that secondary control behaviours
characterised by passivity toward the environment or withdrawal (e.g. “I know
something bad will happen”, an example of predictive secondary control) are
linked to positive psychological outcomes such as a higher Subjective Quality of
Life, Positive Affect and Positive Thinking. Hence, evidence suggests that
behaviours such as the predictive, illusory, interpretive and vicarious types of
secondary control described by Rothbaum et al. (1982) and Weisz et al. (1984)
are indeed positive psychological processes concerned with attempting to control
the psychological impact of events rather than being indicative of relinquished
control.
For clinicians in practice, behaviours that reflect an inherent passivity toward the
environment are commonly interpreted as further signs of clients’ depressed
motivation and thus a symptom to be discouraged either by direct verbal
challenge or via behavioural experiment. However, considering the potential
benefits associated with such secondary control behaviours, the present results
suggest that clinicians, at the very least, should interpret apparent signs of the
client “giving-up”, or choosing less pro-active mechanisms for control as possible
attempts by the person to control the psychological impact of the failure. Less
pro-active secondary control behaviours such as those described by
Rothbaum et al. (1982) may well be unacceptable to those clinicians focused on
achieving direct, measurable changes in client behaviour, however, these same
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140
behaviours may represent self-protective attempts by clients to manage
psychological impacts such as disappointment. These less pro-active attempts for
control make sense for many clients considering the reduced emotional, financial
and educational resources that many clients’ perceive after facing chronic
stressors.
In conclusion, the results from this thesis suggest a much greater role for
secondary control beliefs and behaviour in adaptive psychological functioning.
This suggests to research psychologists and clinicians alike, the importance of
controlling both the internal self as well as controlling the external environment
for optimal positive psychological adjustment.
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Appendix A1
Information Sheet and Covering Letter Sent to participants for Study 1
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