University of Groningen Psychosocial outcomes in diabetes ...9 Diabetes is a serious chronic disease that has evolved into a major public health issue. Treatment of diabetes consists

University of Groningen

Psychosocial outcomes in diabetesSchokker, Marike Christina

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Psychosocial outcomes in diabetes: the interplay of intra- and interpersonal factors

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Colofon

Cover, lay-out and print: Ridderprint Offsetdrukkerij B.V.Cover image: Sculpture ‘Samenwerking in vertrouwen’ by Gerri GrijsenISBN: 978 94 6070 021 7

The study was conducted within the Research Institute SHARE of the Groningen Graduate School for Medical Sciences (University Medical Center Groningen, University of Groningen) and under the auspices of the Research Institute for Psychology & Health.

The printing of this thesis was financially supported by the Research Institute SHARE, the faculty of Medical Sciences (UMCG), the University of Groningen and the Dutch Diabetes Research Foundation.

© 2010, Marike Schokker


RIJKSUNIVERSITEIT GRONINGEN

Psychosocial outcomes in diabetes: the interplay of intra- and interpersonal factors

Proefschrift

ter verkrijging van het doctoraat in de Medische Wetenschappen

aan de Rijksuniversiteit Groningen op gezag van de

Rector Magnificus, dr. F. Zwarts,in het openbaar te verdedigen op

woensdag 29 september 2010om 14.45 uur

door

Maria Christina Schokker

geboren op 19 februari 1981te Drachten


Promotores Prof. dr. M. Hagedoorn Prof. dr. T.P. Links Prof. dr. R. Sanderman Prof. dr. B.H.R. Wolffenbuttel

Copromotor Dr. J.C. Keers

Beoordelingscommissie Prof. dr. A. Dijkstra Prof. dr. D.T.D. de Ridder Prof. dr. F.J. Snoek


Contents Chapter 1 Introduction 7

Chapter 2 The association between regulatory focus and distress in patients 29 with diabetes: the moderating role of partner support BritishJournalofHealthPsychology,2010,15,63-78Chapter 3 The role of overprotection by the partner in coping with diabetes: a moderated mediation model Psychology&Health,2010Feb18,e-pubaheadofprintChapter 4 Support behavior and relationship satisfaction in couples dealing 73 with diabetes: main and moderating effects JournalofFamilyPsychology,acceptedforpublicationChapter 5 The impact of social comparison information on motivation in 93 patients with diabetes as a function of regulatory focus and self-efficacy HealthPsychology,2010,29,438-445Chapter 6 General discussion 113Summary 137 Samenvatting 145 Dankwoord / Acknowledgements 153 SHARE and previous dissertations 159

51



Chapter 1

Introduction



Introduction

9

Diabetes is a serious chronic disease that has evolved into a major public health issue. Treatment of diabetes consists of a combination of diet, exercise, and medication (tablets and/or insulin injections), which is necessary to keep blood glucose levels within a normal range (for more details on diabetes, see Box 1.1). The required self-care behaviors are viewed as burdensome by many patients (Weijman et al., 2005; Woodcock & Kinmonth, 2001). Moreover, a substantial number of patients express a fear of developing diabetes complications (Woodcock & Kinmonth, 2001). As diabetes may have a large impact on one’s life, and can be a burden to patients, it may come as no surprise that adults with diabetes were found to have elevated levels of depressive symptoms compared to adults from the general population (e.g., Pouwer et al., 2003; for meta-analyses see Ali, Stone, Peters, Davies, & Khunti, 2006; Anderson, Freedland, Clouse, & Lustman, 2001). However, a large number of patients do not report elevated levels of depressive symptoms, which may indicate that patients differ in the way they appraise their disease. This will be illustrated by examples of two patients, who will be referred to as John and Mary.

When John received the diagnosis of diabetes he had quite some difficulties accepting this chronic illness. He is quite anxious that he will develop complications in the future, and every day he is occupied with trying to avoid either too low or too high blood sugar levels. Mary was just like John devastated when she received the diagnosis of diabetes. Soon however, she became determined to deal with the diabetes in a positive manner, and to try to maintain good health. Mary engages in adequate self-care behaviors to balance her blood sugar levels, without focusing on her diabetes too much. One can readily see that the way John deals with his diabetes is more likely to evoke high levels of distress than the way Mary is dealing with the diabetes. Paragraph 1.1 will discuss how certain individual characteristics of patients may determine the way patients cope with the disease and the levels of (diabetes-related) distress they experience.

Besides individual characteristics of patients, the support behavior of the partner may greatly influence patients’ levels of distress. A patient whose partner provides support by showing interest in how the patient is coping with the disease is less likely to feel distressed than a patient whose partner is too much involved, for example by constantly reminding the patient to check his or her blood sugar levels. The influence of partner’s support behaviors on patients’ psychosocial outcomes will be discussed in paragraph 1.2.

Earlier it was described how a patient like John, with his negative outlook, may be at risk of experiencing high levels of distress. If John has a partner who supports him in a positive way, and stimulates John to focus on the things he is still able to do, then this may compensate for John’s less adequate coping behavior, and his distress levels may decrease. In contrast, if John’s partner expresses worries by constantly telling John what to do, then John’s own worries may aggravate, thereby further increasing his levels of distress. This combined impact of patients’ individual characteristics and support behavior


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of the partner on patients’ levels of distress will be described in paragraph 1.3.Diabetes may not only be burdensome for patients themselves, but may also negatively

affect the partner of the patient. For example, the partner may feel that the diabetes has a limiting influence on some of the activities they enjoy doing together. Furthermore, just like the patient, the partner may worry whether the patient will develop complications. It is therefore important that not only the partner will provide adequate support to the patient, but it is perhaps of equal importance that the patient adequately supports the partner, for example by actively involving the partner in the self-care regimen the patient needs to adhere to. Paragraph 1.4 will therefore explain the support behaviors of couples dealing with diabetes, so of both patients and partners, and it will be explained how these behaviors may impact relationship functioning in these couples.

A great part of this thesis focuses on the influence the partner may have on patients’ psychosocial outcomes. However, there are other persons in the patient’s social environment besides the partner that may exert an influence on how the patient deals with the disease. Patients may encounter fellow patients who are doing either better or worse than themselves in terms of self-management who may motivate patients to perform just as well or to avoid performing just as inadequately. Paragraph 1.5 will describe how fellow patients may motivate patients with diabetes to manage their disease.

To summarize, the present thesis addresses psychosocial outcomes in patients with diabetes and their partners, by taking both an intrapersonal and an interpersonal perspective. The overall framework of this thesis and the corresponding paragraphs and chapters is presented below.

1.1 Intrapersonal factors: regulatory focus

The burden of self-management and the prospect of complications may increase psychosocial problems in patients with diabetes. Psychosocial problems may also be increased in patients who for example have made the transition from oral medication to insulin injections (Delahanty et al., 2007; Katon et al., 2004; Pouwer et al., 2003), and in patients who already have developed diabetes complications (Katon et al., 2004; Peyrot & Rubin, 1997; Polonsky et al., 1995; Pouwer et al., 2003; Trief, Grant, Elbert, & Weinstock, 1998; Vileikyte et al., 2005). Although disease-related variables may influence psychosocial outcomes, patients’ individual characteristics such as coping strategies and personality traits may be of equal or even greater importance (e.g., Paddison, Alpass, & Stephens, 2008; Pibernik-Okanovic, Begic, Peros, Szabo, & Metelko, 2008; Rose et al., 1998). Previous studies have suggested that psychosocial outcomes in patients may be positively affected by patient’s characteristics such as high levels of self-efficacy (Eiser,

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Introduction

11

Figure 1.1 Frameworkofthethesis

Note. The role of gender will be explored throughout the chapters

Riazi, Eiser, Hammersley, & Tooke, 2001; Senecal, Nouwen, & White, 2000; Van Der Ven et al., 2003), having optimistic beliefs (Fournier, De Ridder, & Bensing, 2002), and having an active coping style (Rose, Fliege, Hildebrandt, Schirop, & Klapp, 2002).

A characteristic that has been mostly overlooked thus far in the context of a chronic illness, but which may be very relevant for psychosocial adaptation is called regulatory focus (Higgins, 1998; Higgins, 1997; Lockwood, Jordan, & Kunda, 2002). It is a characteristic that may influence the way patients appraise their disease outcomes and that may determine which strategies and behaviors patients engage in to manage their disease. According to regulatory focus theory there are two distinct self-regulatory systems: self-regulation with a promotion focus and self-regulation with a prevention focus. Individuals with a strong promotion focus are striving to achieve an ideal self and are oriented towards obtaining positive outcomes. Individuals with a strong prevention focus are striving to achieve an ought self, that is, how they think they should be as a person, and these individuals are oriented towards avoiding negative outcomes. Since regulatory focus determines how individuals appraise their environment, and the type of goals they pursue, it can be viewed as a basic individual characteristic.

Regulatory focus is believed to be a stable trait-like characteristic that develops early on in childhood during interactions with caretakers (Higgins & Silberman, 1998). Empirical support is provided by studies that found regulatory focus to be related to

Figure 1.1 Framework of the thesis

Note. The role of gender will be explored throughout the chapters

Patient’s and

partner’s relational

outcomes

Patient’s

psychological

outcomes

Intrapersonal

factors

Interpersonal

factors

×

§ 1.3 & 1.5,

chapters 2,

3, & 5 § 1.2, chapters

2 & 3

§ 1.1, chapters

2 & 5

§ 1.4, chapter 4

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parenting styles (Keller, 2008; Manian, Papadakis, Strauman, & Essex, 2006). For example, individuals’ prevention focus was associated with perceiving parents’ behavior during childhood as critical and punitive, while individuals’ promotion focus was associated with perceiving parents’ behavior as responsive and encouraging (Keller, 2008). It may seem that persons either have a strong promotion focus or a strong prevention focus. However, it is also possible that promotion and prevention focus are both strongly or both weakly developed. The theoretical notion that all combinations of promotion and prevention focus are possible is supported by the weak or non-significant correlations that previous studies found between these two self-regulatory orientations (e.g., Coolsen, 2004; Keller & Bless, 2006; Keller, 2008; Lockwood et al., 2002; Oyserman, Uskul, Yoder, Nesse, & Williams, 2007; Sullivan, Worth, Baldwin, & Rothman, 2006).

Previous research on regulatory focus has mainly been conducted within the field of experimental social or applied health psychology. The majority of these studies examined the regulatory fit hypothesis (e.g., Higgins, 2000; Keller & Bless, 2006; Mann, Sherman, & Updegraff, 2004; Shah, Higgins, & Friedman, 1998; Spiegel, Grant-Pillow, & Higgins, 2004), which states that individuals’ performance and motivation is enhanced when a task or message is framed in terms that are congruent with individuals’ regulatory focus. For example, it was demonstrated that students with a relatively strong promotion focus performed better on a task when it was framed in terms that were congruent with their promotion focus (e.g., ‘there are no point deductions for wrong answers’ and ‘try and solve as many items as possible’). In contrast, students with a relatively strong prevention focus performed better on a task when it was framed in terms that fitted their prevention focus (‘one point will be deducted for every wrong answer’ and ‘try and avoid errors’; Keller & Bless, 2006). It can be concluded from these studies that there is no a priori advantage of either promotion or prevention focus on motivation and performance. Instead, it is the fit between a person’s regulatory focus and the situational context that determines whether motivation and performance is enhanced.

Only little is known about regulatory focus in relation to psychological outcomes such as distress. Whereas both promotion and prevention focus may have beneficial effects on outcomes such as motivation and performance, depending on the fit of one’s focus with the situation at hand, it can be expected that this will not hold with regard to outcomes such as well-being and distress. Based on literature on approach and avoidance goals (cf. promotion and prevention focus) it can be expected that unlike promotion focus, prevention focus will lead to a range of maladaptive perceptual, attentional, and mental control processes (for an overview of research on approach and avoidance goals, see Elliot & Friedman, 2007). Individuals with a strong prevention focus can be expected to have a heightened sensitivity to negative information (Higgins & Tykocinski, 1992). Furthermore, they may be biased towards negative information, a so-called ‘hypothesis test’ for the presence of negative information (Wegner, 1994). For example, if your prevention goal

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Introduction

13

is to ‘avoid high blood sugar levels’, it is likely that you are constantly occupied whether high blood sugar levels are present at that moment. Together, these processes may lead to an increase of negative feelings, and heighten one’s level of distress. In line with this reasoning, there are a few studies of samples of healthy individuals suggesting that overall, a strong promotion focus is more adaptive in terms of psychological outcomes than a weak promotion focus (Coolsen, 2004; Miller & Markman, 2007), while a weak prevention focus is more adaptive than a strong prevention focus (Coolsen, 2004; Eiser, Eiser, & Greco, 2004; Miller & Markman, 2007). Furthermore, one study of women with breast cancer showed that although overall, distress levels were not related to promotion focus, they were positively related to prevention focus (Frieswijk & Hagedoorn, 2009).

To date, it is unknown how a basic characteristic like regulatory focus is associated with distress in adults dealing with a chronic illness such as diabetes. Diabetes is an illness that requires an intensive self-management regimen, in which patients’ self-regulatory orientations (i.e., promotion and prevention focus) may prove to be highly salient. Although a long-term goal for patients with diabetes may be to try to prevent the development of complications, which is a prevention goal, they may also formulate the goal of trying to stay or become healthy, which is a promotion goal. These different regulatory goals may prove to have different associations with patients’ level of distress. In chapter 2 of this thesis, these associations in patients will be examined.

1.2 Interpersonal factors: support behavior of the partner

In addition to patient characteristics, interactions with the family and in particular those with the partner may be associated with patients’ psychosocial outcomes (e.g., Fisher et al., 2004; Hagedoorn et al., 2006; Wearden, Tarrier, & Davies, 2000). There are several explanations for the important role of the partner. First of all, most of the self-management behavior takes place within the family or home (see also Fisher et al., 2000). Secondly, the support provided by patient’s intimate partner may not be compensated for by other sources of support (Coyne & DeLongis, 1986).

In research on social or spousal support, often a distinction is made between different types of support such as emotional and instrumental support (House, 1981). However, these types of support can be provided in different ways. For example, emotional support can be provided by openly discussing patients’ feelings about the illness, by letting the patient believe everything is fine, or by asking how the patient feels every time he or she exerts himself or herself. Instrumental support can be provided by bringing the patient his or her insulin pen after consulting with the patient, or the partner may bring the patient’s pen without discussing this with the patient beforehand. This thesis examines three different ways of providing support: Active engagement, Protective Buffering,

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14

and Overprotection (ABO; Buunk, Berkhuysen, Sanderman, & Nieuwland, 1996). Active engagement means that the partner asks how the patient feels, and this support behavior is further characterized by using constructive problem-solving methods, like openly discussing the illness with the patient. Protective buffering is characterized by hiding your concerns from the patient, and trying to prevent the patient from thinking about the illness. Finally, overprotection involves providing unnecessary help, and giving excessive praise for accomplishments. Although previous studies have not been entirely consistent (Buunk et al., 1996; Coyne & Smith, 1994; Coyne & Smith, 1991; De Ridder, Schreurs, & Kuijer, 2005; Hagedoorn et al., 2000; Hinnen, Hagedoorn, Ranchor, & Sanderman, 2007; Joekes, Maes, & Warrens, 2007; Kuijer et al., 2000; Langer, Brown, & Syrjala, 2009; Manne et al., 2007), in general, active engagement can be viewed as adequate support behavior that is associated with positive psychosocial outcomes in patients, whereas protective buffering and overprotection can be perceived as less adequate support behaviors which seem to have negative effects on patients’ psychosocial outcomes.

Most studies that used the Active engagement, Protective Buffering, and Overprotection (ABO) questionnaire concern patients with heart disease or cancer (e.g., Berkhuysen, Nieuwland, Buunk, Sanderman, & Rispens, 1999; Buunk et al., 1996; Coyne & Smith, 1991; 1994; Hagedoorn et al., 2000; Hinnen et al., 2007; Joekes, Van Elderen, & Schreurs, 2007; Kuijer et al., 2000; with the exception of De Ridder et al., 2005; Hagedoorn et al., 2006). This thesis examines the role of active engagement, protective buffering, and overprotection in the context of diabetes, a disease that is partly controllable by the patient.

Chapter 3 specifically focuses on overprotection by the partner, and examines how this behavior is associated with distress in patients. Overprotection is a behavior that may especially occur within the context of diabetes. Patients with this disease need to engage in several self-care behaviors and partners of patients may worry whether the patient is capable of doing so. Consequently, partners may overprotect their partners by expressing these worries to patients and by taking over several activities from the patient. Partners’ overprotective behavior is probably well-intended but is expected to have a negative impact on patients’ level of diabetes-related distress. Besides examining the association between overprotection by the partner and patient’s diabetes-related distress, the aim of chapter 3 is to gain insight in the underlying mechanism in this association.

Previous research has identified coping behavior as a mediator in the association between support and distress (e.g., Holahan, Moos, Holahan, & Brennan, 1997; Karlsen, Idsoe, Hanestad, Murberg, & Bru, 2004; Manne & Zautra, 1989; Manne, Ostroff, Winkel, Grana, & Fox, 2005; for an overview see Schreurs & De Ridder, 1997). Based on social learning theory it can be predicted that self-efficacy determines whether an individual adopts adaptive coping behaviors (Bandura, 1977; Bandura, 1982). Several studies supported this prediction by demonstrating that self-efficacy can indeed be viewed as a coping resource (Jensen, Turner, & Romano, 1991; Schwarzer, Boehmer, Luszczynska,

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Introduction

15

Mohamed, & Knoll, 2005; Terry, 1994). Therefore, in chapter 3 of this thesis, self-efficacy is proposed as an important mediator in the association between overprotection and distress.

1.3 Combined impact of intra- and interpersonal factors

Although patients’ individual characteristics as well as partner support may separately affect patients’ level of distress, it is also conceivable that they conjointly affect distress levels. However, this possibility has received little attention thus far. A few studies of other chronic diseases did point out that low levels of positive support or high levels of negative support in combination with a vulnerable coping style or personality trait may lead to negative psychosocial outcomes (e.g., Danoff-Burg, Revenson, Trudeau, & Paget, 2004; Devine, Parker, Fouladi, & Cohen, 2003; Jacobsen et al., 2002). Especially within the context of diabetes, the interplay between inter- and intrapersonal factors is an unexplored area.

In chapter 2, the combined effect of regulatory focus and partner support will be examined. More specifically, it will be investigated whether patients with either a weak promotion focus or a strong prevention focus report high levels of distress, especially when they receive low levels of positive support (i.e., active engagement) or high levels of negative support (i.e., protective buffering and overprotection).

In chapter 3 it is proposed that patients whose partners are relatively overprotective will experience more diabetes-related distress through diabetes-specific self-efficacy. This indirect link between overprotection and diabetes-related distress is expected to apply most strongly to patients with poor glycemic control. Overprotection may transfer the message to the patient that the partner has little confidence in the patient’s abilities. When patients have poor glycemic control this may lead them to believe that the partner is right in having little confidence in their abilities with regard to diabetes management, thus increasing patients’ levels of distress to a higher extent. In contrast, if patients have good glycemic control, this may point out to patients that they are capable of managing their disease. In this case, overprotective behaviors from their partner will have a less strong impact on their levels of distress.Furthermore, the indirect link between overprotection and diabetes-related distress is expected to apply more strongly to female than to male patients, since some studies have shown that women are more strongly influenced by partner behavior and characteristics than are men (e.g., Acitelli & Antonucci, 1994; Hagedoorn et al., 2000; Hagedoorn et al., 2001; Mcrae & Brody, 1989). The role of gender will also be explored in the other chapters concerning partner support.

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1.4 Interpersonal factors: support behavior of both patients and partners

A chronic illness such as diabetes will not only affect the patient, but also the partner of the patient, and their intimate relationship (for overviews see Berg & Upchurch, 2007; Burman & Margolin, 1992; Thompson & Pitts, 1992). In order to maintain a satisfactory relationship patients and partners need to engage in certain support behaviors or relationship-focused coping strategies, that is, ways to cope with the illness and each others’ emotional responses. To date, an increasing number of studies have demonstrated significant associations between partner or family support behavior and patients’ psychosocial outcomes (e.g., Chesla et al., 2003; Fisher et al., 2000; Fisher et al., 2004; Hagedoorn et al., 2006; Trief et al., 2003; Trief, Ploutz-Snyder, Britton, & Weinstock, 2004). However, less is known about whether patients’ support behaviors are associated with partners’ psychosocial outcomes such as relationship satisfaction. Chapter 4 fills this gap by examining received support behaviors and how these behaviors are associated with relationship satisfaction in both patients and partners. More specifically, this chapter focuses on patients’ and partners’ received active engagement and protective buffering, since these behaviors can be enacted by both patients and partners. That is, both patients and partners may for example express interest in how the other is coping with the illness (active engagement), or may try to distract the other from thinking about the illness (protective buffering). To conclude, the first aim of chapter 4 will be to examine associations between support behaviors (i.e., received active engagement and protective buffering) and relationship satisfaction in both patients and partners. Moreover, this will be done by using a dyadic data analytic approach (Kenny, Kashy, & Cook, 2006). A strength of this approach is that it takes into account the interdependence between patients and partners.

A second aim of chapter 4 is to examine the interactive effects of received active engagement and protective buffering on patients’ and partners’ relationship satisfaction. It is possible that a person receives both active engagement and protective buffering to a certain extent throughout a period of time. At one moment, a person may show active engagement, while at another moment the same person may show protective buffering. Another possibility is that a person shows active engagement with regard to some illness aspects, and protective buffering with regard to other aspects.

Negative support behaviors of the partner, such as protective buffering, may be interpreted as less negative if at other times or with respect to other issues, the partner acts supportively (cf. Hagedoorn et al., 2009). For example, imagine that John, a person with diabetes comes home from work, rather upset because he had an important meeting today, but his blood sugar levels were too low and he had trouble keeping focus. John’s partner reacts rather indifferently when he tells her about his day, as she believes that there

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Introduction

17

are worse things that could happen. John is not pleased with this reaction. However, John may be less offended by his partner’s reaction when his partner showed more interest the other day when the two of them talked openly about his diabetes. In this case, John may believe that his partner’s reaction of today has to do with the fact that she had a rough day herself for example. If however John believes that his partner’s reaction is typical of how she normally reacts, than he interprets her behavior more negatively which may lead John to evaluate his whole relationship negatively. Indeed, it has been shown that negative interpretations of certain support behaviors are associated with less relationship satisfaction (e.g., Fincham & Bradbury, 1992). It is therefore expected that the protective buffering one receives will have a less negative effect on relationship satisfaction, when at the same time one receives high instead of low levels of active engagement.

A number of previous studies found support for an interactive effect of positive and negative support on psychological outcomes (Kleiboer et al., 2007; Manne et al., 2003; Revenson, Schiaffino, Majerovitz, & Gibofsky, 1991; Sherman, 2003). These studies focused on the patient as the person of interest and not on the partner (with the exception of Kleiboer et al., 2007). Our study will be the first to test the interactive effects of positive and negative support (i.e., active engagement and protective buffering) on relationship satisfaction in both patients with diabetes and their partners, using a dyadic data analytic approach.

1.5 Influence of fellow patients

The current thesis focuses on the influence of the intimate partner on patients, but will also examine the influence fellow patients may exert on patients. Persons with diabetes may know of other patients in their family or work environment, or they encounter other patients when visiting the hospital for their check-up. Furthermore, patients may read or hear about other patients with diabetes in magazines, newspapers, on television programs, or on the internet. In chapter 5, the aim is to examine the impact of such a fellow patient on patients’ motivation to manage the disease.

The process of comparing oneself with others is referred to as social comparison (Festinger, 1954), and was originally thought to be driven by a desire for self-evaluation, that is, the motivation to establish that one’s opinions are correct, and to correctly estimate one’s capabilities. Later on, research acknowledged that people may engage in social comparisons for various other reasons, for example to feel better about oneself (Tennen, McKee, & Affleck, 2000; Wills, 1981) or to improve oneself (Aspinwall, 1997; Collins, 2000). It is argued (Wills, 1981) that individuals who encounter situations that produce a decrease in their well-being will compare downward in order to repair their well-being. Seeing others

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who are doing worse, for example in terms of disease outcomes, may lead individuals to feel better about themselves and their own outcomes. It has been demonstrated that downward comparisons are quite prevalent in patients with a chronic illness (Gorawara-Bhat, Huang, & Chin, 2008; Wood, Taylor, & Lichtman, 1985; for a review see Tennen et al., 2000). Several studies have shown that downward comparisons are indeed positively associated with patients’ well-being and adjustment (e.g., Helgeson & Taylor, 1993; Van der Zee et al., 1996; for a review see Tennen et al., 2000). However, downward comparison targets may also represent a feared future (Markus & Nurius, 1986) and as such evoke distress in patients (e.g., Ybema & Buunk, 1995).

Individuals may compare themselves with better-off others (upward comparison) when they have an interest in improving themselves (e.g., Taylor & Lobel, 1989). This notion has been supported by studies that found that students who compared themselves with other students who were doing better than themselves in school or college, showed enhanced performance at a later time point in terms of higher grades (Blanton, Buunk, Gibbons, & Kuyper, 1999; Gibbons, Blanton, Gerrard, Buunk, & Eggleston, 2000; Huguet, Dumas, Monteil, & Genestoux, 2001). Another study showed that students were most motivated to work on their career when they were confronted with a recent graduate who was successful instead of unsuccessful in the job market (Buunk, Peiro, & Griffioen, 2007).

The majority of the studies on the influence of (upward) social comparisons on motivation have been conducted in the context of academic performance. In contrast, although several studies of patients with a chronic illness investigated the impact of social comparisons on affect and well-being, less is known about the impact on patients’ motivation to manage the disease. This is an important research question, especially in a sample of patients with diabetes, since a number of aspects of this illness are controllable with adequate self-care behaviors. Motivated patients are more likely to carry out such behaviors (e.g., Courneya & Friedenreich, 1999) and motivation is therefore a relevant outcome. The impact of social comparison information (upward and downward) on patients’ motivation to work on their diabetes regulation will be investigated in chapter 5.

Furthermore, the role of patients’ regulatory focus will be examined. As described earlier, chapter 2 will address the combined impact of regulatory focus and partner support on patients’ level of distress. In chapter 5, the combined impact of regulatory focus and social comparison information on patients’ motivation will be investigated. More specifically, the regulatory fit hypothesis that was mentioned previously will be tested. This hypothesis states that a task or message that is framed in terms that are congruent with one’s regulatory focus, is most likely to enhance motivation and performance (for an overview see Higgins, 2000). In a similar manner, it can be expected that social comparison information that fits one’s regulatory focus will most likely boost one’s motivation. In fact, this has already been demonstrated in studies of students and healthy older individuals showing that both upward and downward comparison information may

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motivate individuals, e.g. to study harder, depending on individuals’ regulatory focus (e.g., Lockwood, Marshall, & Sadler, 2005; Lockwood et al., 2002; for an overview see Lockwood & Pinkus, 2008). It was found that promotion-focused individuals are motivated by upward social comparison information, while prevention-focused individuals are motivated by downward social comparison information. These findings demonstrate that under some circumstances, downward social comparisons can have a motivating effect, as much as upward social comparisons.

However, it is not yet known whether a fit between social comparison information and regulatory focus will lead to enhanced motivation in individuals dealing with a chronic disease, such as patients with diabetes. This is the first aim that will be addressed in chapter 5. Another aim of chapter 5 is to examine whether the interactive effect of social comparison information will be further qualified by patient’s self-efficacy. Previous studies have identified the positive role of control and attainability (Aspinwall, 1997; Lockwood & Kunda, 1997; Major, Testa, & Blysma, 1991) when examining the effects of social comparison information. Individuals, who encounter other individuals doing either better or worse than them, will show more persistence and motivation to obtain a similar positive future, or avoid a similar negative future, when they have confidence in their own abilities to do so. In chapter 5 it is therefore proposed that patients will be motivated by social comparison targets that match with their regulatory focus, and that this will apply even more strongly for patients who feel self-efficacious in managing their diabetes.

OverviewTo conclude, the different chapters focus on intrapersonal and interpersonal factors when studying psychosocial outcomes in diabetes. The outline of the thesis can be summarized as follows:Chapter 2 addresses both intra- and interpersonal factors by examining whether the association between regulatory focus (intrapersonal) and general distress in patients is moderated by partner support (interpersonal).Chapter 3 addresses both intra- and interpersonal factors by examining the indirect link between overprotection by the partner (interpersonal) and diabetes-related distress in patients and by examining whether this indirect link is moderated by intrapersonal factors, that is, gender and glycemic control.Chapter 4 specifically focuses on interpersonal factors by examining the interactive effects of active engagement and protective buffering on relationship satisfaction in both patients and partners.Chapter 5 focuses on both intra- and interpersonal factors by investigating whether the impact of social comparison information (interpersonal) on patient’s motivation depends on regulatory focus and self-efficacy (intrapersonal).

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Diabetes is a chronic disease affecting 220 million people worldwide (WHO, 2009) with a rising prevalence. As for the Netherlands, data from The National Institute for Public Health and the Environment (RIVM) indicate the number of known cases with diabetes in the Netherlands around 740.000 (RIVM, 2009). Furthermore, it is estimated that there are around 250.000 people with diabetes who have not yet been diagnosed as such. These numbers add up to a total of 1 million people with diabetes in the Netherlands. Diabetes does not only negatively affect the patient, but may also carry societal costs. In 2003, the costs associated with diabetes health care in the Netherlands were estimated around 735 million euro. Furthermore, the lower work force participation and the higher percentage of disability of people with diabetes compared to healthy people may lead to additional costs (RIVM, 2007).

There are two main types of diabetes: type 1 and type 2. Both types reflect an endocrine disorder that occurs when the pancreas does not produce insulin anymore (type 1) or alternatively, when a disturbed secretion and / or decreased sensitivity is present, and the body does not respond adequately to the insulin it produces (type 2). Insulin is a hormone that enables cells to absorb glucose in order to turn it into energy needed to function. In both type 1 and type 2 diabetes, glucose is not (adequately) converted into energy, leading to elevated blood glucose levels (hyperglycemia). Type 1 diabetes is usually contracted at an early age, in childhood or adolescence.Although it is not fully understood what causes type 1 diabetes, it is believed to be of immunological origin. Type 2 is much more prevalent than type 1 diabetes (around 90% of all diabetes patients have type 2 diabetes), and is usually contracted later on in adulthood, although due to lifestyle, the number of patients that develop type 2 diabetes at an earlier age is growing. Type 2 diabetes is often caused by a combination of hereditary factors, obesity and a lack of exercise. It has a more gradual onset than type 1 diabetes, and therefore, type 2 diabetes may remain undiagnosed for years.

In both type 1 and type 2 diabetes, the treatment goal is to keep blood glucose levels within a normal range. The percentage of glycosylated hemoglobin, HbA1c, is used as a measure of glycemic control and reflects the average blood glucose levels of the preceding 6 to 8 weeks. The aim for diabetes patients is to obtain HbA1c values that resemble the values of healthy people as closely as possible (reference values for healthy people: 4-6%). Prolonged elevated blood glucose levels increase patients’ risk of developing microvascular and macrovascular complications (Diabetes Control and Complications Trial Research Group, 1993; Lawson, Gerstein, Tsui, & Zinman, 1999; UK Prospective Diabetes Study Group, 1998; 2000). Microvascular complications include retinopathy (eye disease, which may eventually lead to blindness), nephropathy (kidney disease) and neuropathy (nerve disease, which in the long term can lead to amputation of extremities). Macrovascular

Box 1.1 Diabetesanditstreatment

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complications include cardiovascular disease and stroke.To prevent these complications patients with diabetes need to keep their blood glucose

levels within a normal range by performing several self-care behaviors. Patients need to follow a daily routine of taking medication, injecting insulin, self-testing blood glucose levels multiple times per day, and adhering to a specific diet and exercise. The difficulty is that patients cannot take a vacation from their diabetes; they need to perform these self-care behaviors every day. Another complicating factor is that patients need to keep a balance in these behaviors, since they may work in opposite directions. For example, activity and insulin will lower blood glucose levels, whereas certain foods and stress may elevate blood glucose levels. Patients need to find out for themselves how much activity

is needed, and which foods they can take, in response to the insulin dosage they injected.

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Chapter 2

The association between regulatory focus and distress in patients with a chronic disease:

the moderating role of partner support

Marike C. Schokker , Thera P. Links, Marie Louise Luttik, Mariët Hagedoorn

British Journal of Health Psychology, 2010, 15, 63-78

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2.1 Introduction

A chronic illness can have quite an impact on a person’s life. Many chronic illnesses require permanent life-style changes and self-management, for which the patient needs knowledge, skills, and discipline. Considering their difficult task, it is not surprising that a substantial minority of the patients develops psychosocial problems (for reviews, see Anderson, Freedland, Clouse, & Lustman, 2001; MacMahon & Lip, 2002; Schmier, Chan, & Leidy, 1998).

However, a large number of patients do not report elevated levels of distress, which raises the question what factors may protect patients from the experience of distress. Several studies demonstrated the importance of considering individual characteristics and coping skills of patients as influential factors (e.g., Bedi & Brown, 2005; Hesselink et al., 2004; Rose, Fliege, Hildebrandt, Schirop, & Klapp, 2002; Shnek, Irvine, Stewart, & Abbey, 2001; Skaff, Mulan, Fisher, & Chesla, 2003; Van Jaarsveld, Ranchor, Sanderman, Ormel, & Kempen, 2005).

In this study, we are interested in regulatory focus (Higgins, 1997, 1998; Lockwood, Jordan, & Kunda, 2002) as an individual characteristic that might predispose patients to experience either low or high levels of distress. Regulatory focus consists of two self-regulatory systems: self-regulation with a promotion focus and self-regulation with a prevention focus. A promotion focus refers to the extent to which one is focused on obtaining positive outcomes, whereas a prevention focus refers to the extent to which one is focused on avoiding negative outcomes. A person’s regulatory focus is considered to be a stable individual difference variable which develops during interactions with caregivers in childhood. This notion is supported by studies that showed a relation between parenting styles and regulatory focus (Keller, 2008; Manian, Papadakis, Strauman, & Essex, 2006). Furthermore, persons can have either a strong promotion focus or a strong prevention focus, but it is also possible that a person has both a strong (or weak) prevention and promotion focus. This is also illustrated by the weak or nonsignificant associations that have been found between promotion and prevention focus in previous studies (Coolsen, 2004; Keller, 2006; Keller & Bless, 2006; Lockwood et al., 2002; Miller & Markman, 2007; Oyserman, Uskul, Yoder, Nesse, & Williams, 2007; Sullivan, Worth, Baldwin, & Rothman, 2006).

Some studies have put forward that overall, a strong promotion focus might be more adaptive than a weak promotion focus, while a weak prevention focus might be more adaptive than a strong prevention focus (Eiser, Eiser, & Greco, 2004; Miller & Markman, 2007). In a sample of students, a prevention focus was positively related to depressive symptoms (r = .56), whereas a promotion focus and depressive symptoms were negatively related (r = -.50; Miller & Markman, 2007). Another study of students found that a relatively

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strong prevention focus was associated with more depression, anxiety, and neuroticism, and less self-esteem, whereas a relatively strong promotion focus was associated with, for example, more self-esteem, agreeableness, and openness (Coolsen, 2004). Parents of survivors of childhood cancer who expressed a stronger prevention focus during an interview, reported less well-being than parents who expressed a weaker prevention focus (Eiser et al., 2004).

A related concept to regulatory focus is that of approach and avoidance goals. An approach goal is formulated in terms of trying to reach or achieve a positive outcome (cf. promotion focus) whereas an avoidance goal is formulated in terms of avoiding or preventing something (cf. prevention focus). A number of studies within this line of research deal with the question to what extent approach and avoidance goals are associated with well-being (for a review, see Elliot & Friedman, 2007). Within these studies people are asked to formulate their goals in their own words, after which each goal is coded by the researcher as either avoidance, or an approach goal. Numerous studies have demonstrated that a high proportion of avoidance goals relative to approach goals is associated with multiple negative consequences, like more physical symptoms (Elliot & Sheldon, 1998), lower perceived competence and autonomy (Elliot & Sheldon, 1998), and lower subjective well-being (Elliot & Church, 2002; Elliot & Sheldon, 1997; Elliot, Sheldon, & Church, 1997).

To conclude, research on regulatory focus and research on approach and avoidance goals suggests that persons with a relatively weak promotion focus and persons with a relatively strong prevention focus are more prone to experiencing negative psychological outcomes.

Regulatory focus has been mainly examined in student samples. However, it is not yet known how regulatory focus is related to psychological outcomes in older adults with a chronic disease. In our study, we selected patients with diabetes, asthma, or heart disease. These are all three chronic diseases in which the patient can exert control over the course of the disease by engaging in several self-management behaviors (see also Kuijer & De Ridder, 2003; Schreurs, Colland, Kuijer, De Ridder, & Van Elderen, 2003). In persons with a chronic disease imposing certain limitations and self-management tasks, it may be especially beneficial to focus on the positive outcomes that can be achieved, whereas a rather weak orientation towards positive outcomes will probably be maladaptive. Therefore, we expect that patients with a relatively weak promotion focus experience more distress than patients with a relatively strong promotion focus. Also, we expect that a relatively strong prevention focus is associated with more distress than a relatively weak prevention focus. Although the long-term goal within the context of chronic illness is often communicated to patients in terms of preventing the development of complications, we believe patients’ well-being is enhanced when they reframe this goal in terms of being

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and staying fit and healthy. Put differently, patients will feel less distressed when they are less preoccupied with possible negative outcomes in the future (a weak prevention focus), and instead, are more focused on positive outcomes (a strong promotion focus).

Although a person’s regulatory focus is considered to be a trait-like characteristic, one’s current focus can also be situationally induced, for example by letting individuals describe personal experiences relevant either to achieving a positive or a negative outcome (Higgins, Roney, Crowe, & Hymes, 1994; Lockwood et al., 2002). Similarly, we posit that certain supportive behaviors of significant others may create either a promotion- or prevention-focused environment, directing patients to use either promotion- or prevention-focused strategies. Previous studies on chronic diseases demonstrating associations between support from the family and coping behaviors by the patient support this notion. For example, supportive behaviors that can be viewed as promotion-oriented, such as promoting self-care behaviors or stimulating a positive appraisal, were associated with adaptive coping behaviors, such as actively dealing with the disease by seeking information (cf. promotion-focused strategies). On the other hand, unsupportive behaviors that can be viewed as prevention-oriented, such as criticism or avoidance, were associated with maladaptive coping behaviors, such as avoiding thinking about the disease (cf. prevention-focused strategies; Holahan, Moos, Holahan, & Brennan 1997; Karlsen, Idsoe, Hanestad, Murberg, & Bru, 2004; Kvam & Lyons, 1991; Manne & Zautra, 1989; for a review, see Schreurs & De Ridder, 1997). We argue that the promotion-focused environment a partner’s supportive behavior is thought to create, may buffer patients with a weak promotion focus and/or a strong prevention focus against high distress. The prevention-focused environment that might be created by unsupportive behavior, may aggravate distress in patients with a weak promotion focus and/or a strong prevention focus.

ThreeStylesofSpousalSupportIn this study, we assessed three support behaviors, namely, active engagement, protective buffering, and overprotection (Coyne, Ellard, & Smith, 1990; Coyne & Smith, 1991, 1994; Hagedoorn et al., 2000). Active engagement is a support behavior in which the partner uses constructive problem-solving methods, like involving the patient in discussions, inquiring how the patient feels and asking about the help and information needed. As this definition implies, active engagement is a support behavior in which the partner makes use of promotion-oriented support strategies. Protective buffering means hiding one’s concerns, denying one’s worries, concealing discouraging information, preventing the patient from thinking about the illness, and yielding in order to avoid disagreement. Overprotection means that the partner underestimates the patient’s capabilities, resulting in unnecessary help, excessive praise for accomplishments, or attempts to restrict activities.

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These latter-two support behaviors are more prevention-oriented in that partners who adopt these styles are focused on keeping the patient from being harmed.

Based on our theoretical outline, we derived the following hypotheses:

1. Patients’ promotion focus will be negatively associated with distress. 2. Patients’ prevention focus will be positively associated with distress.3. Moreover, these associations will especially apply to patients who perceive their

partner to be low in active engagement, to patients who perceive their partner to be high in protective buffering, and to patients who perceive their partner as highly overprotective. The highest levels of distress are expected in those patients with a weak promotion focus and/or a strong prevention focus combined with either low levels of active engagement, and/or high levels of protective buffering and overprotection.

2.2 Method

ParticipantsandProcedureThe data used to test our hypotheses are part of a large national survey. Within this survey nine local district council offices from different areas in the Netherlands were asked for a random sample of addresses of 500-1000 persons of 55 years of age or older who were not living at the same address. In total 5500 individuals were invited to participate in the study. They received a questionnaire accompanied by an information letter by mail. Individuals who were willing to participate could return their completed questionnaire in a pre-stamped envelope. Anonymity and confidentially was guaranteed. After three weeks a reminder letter was sent to everyone. In total, a number of 2497 respondents (45.4%) completed the questionnaire.

For the purposes of this study, we only used the data of respondents with an intimate partner and who reported having diabetes, asthma, or heart disease when presented a list with several health problems. There were 477 respondents (19.10%) with an intimate partner and who indicated having either one of the three chronic illnesses. This final subsample consisted of 356 men and 111 women, and 10 respondents for whom sex is unknown. The majority of the respondents (72.5%) reported having one or more other comorbidities besides diabetes, asthma, or heart disease, which may not be surprising because of the older age of the sample. The mean age was 67.76 years (SD = 7.87 years) and the mean duration of respondents’ relationship was 40.19 years (SD = 11.39 years). The majority of the respondents (87.8%) were married.

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MeasuresRegulatory focus. Regulatory focus was assessed with the Regulatory Focus

Questionnaire developed by Lockwood et al. (2002); Dutch translation by Van Stekelenburg and Klandermans (2003). It has been demonstrated that this questionnaire is related to the Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) scales by Carver & White (1994), which measures approach and avoidance (Summerville & Roese, 2008). The Regulatory Focus Questionnaire consists of two subscales designed to measure promotion and prevention focus. Both subscales contain nine items and each item was rated on a seven-point scale ranging from 1 (totallydisagree) to 7 (totallyagree). A few adjustments were made, since some of the items of the original questionnaire focused on the academic domain, and therefore were not relevant to our sample. For example, in the items in which the original questionnaire referred to academic goals and ambitions, we removed the word ‘academic’. Examples of promotion items are “I frequently imagine how I will achieve my hopes and aspirations”, and “In general, I am focused on achieving positive outcomes in my life” (M = 4.15, SD = 1.32, Cronbach’s α= .85). Examples of prevention items are “I am anxious that I will fall short of my responsibilities and obligations”, and “I often imagine myself experiencing bad things that I fear might happen to me” (M = 3.79, SD = 1.24, Cronbach’s α = .78).

Ways of giving support. We used a questionnaire developed by Buunk, Berkhuysen, Sanderman, and Nieuwland (1996) to assess three ways of partner support; active engagement, protective buffering, and overprotection. Respondents were asked to rate to what extent their partner adopted each support style in reaction to their illness. All items were measured on a five-point scale ranging from 1 (never) to 5 (veryoften). Buunk et al. (1996) reported adequate internal consistencies and test-retest reliabilities for the subscales regarding perceptions of patients who had suffered a myocardial infarction as well as their partners. Also, studies of persons coping with cancer found satisfactory internal consistencies (Hagedoorn et al., 2000; Hinnen, Hagedoorn, Sanderman, & Ranchor, 2007; Kuijer et al., 2000). The subscale for active engagement consisted of five items. Examples are “My partner asks me how I feel”, and “When something bothers me, my partner tries to discuss the problem” (M = 3.90, SD = .78, Cronbach’s α = .88). The original subscale for protective buffering consisted of eight items. Examples are “My partner tries to hide his or her worries about me”, and “My partner gives in when I make an issue of something”. However, because the internal consistency was relatively low (Cronbach’s α = .61), three items were deleted, which increased the internal consistency (Cronbach’s α = .72, M = 2.39, SD = .74). Six items measured overprotection. Examples are “My partner treats me like a baby”, and “When it comes down to it, my partner seems to think that I don’t know what’s right for me” (M = 2.34, SD = .74, Cronbach’s α = .75).

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Distress.Psychological distress was assessed with the 12-item version of the General Health Questionnaire (GHQ; Goldberg & Hillier, 1979; Werneke, Goldberg, Yalcin, & Ustun, 2000). The 12 items were summed into a total score, with a higher score indicating more psychological distress (M = 10.28, SD = 4.95, Cronbach’s α= .88). An example item is “Lately, did you feel unhappy and low spirited/down?” (0 = notatall, 3 = muchmorethanusual).

2.3 Results

DescriptivesTable 2.1 presents the correlations and means for the variables under study. Age was weakly positively associated with overprotection, and promotion and prevention focus. The three support styles were only weakly to moderately intercorrelated. Furthermore, overprotection showed a weak positive association with distress, whereas active engagement and distress showed a weak negative association. The associations between the support styles and the two regulatory foci were weak at most. The correlations between regulatory focus and distress were not entirely in line with our first two hypotheses. There was no significant association between promotion focus and distress and prevention focus was only weakly positively associated with distress. Further, the positive correlation between promotion and prevention focus was stronger than was expected in view of previous studies (Coolsen, 2004; Keller, 2006; Keller & Bless, 2006; Lockwood et al., 2002; Miller & Markman, 2007; Oyserman et al., 2007; Sullivan et al., 2006).

Table 2.1 Means,StandardDeviations,andIntercorrelationsfortheVariablesunderStudy

Variable 2 3 4 5 6 7 8 9 M SD

1. Age .61** .13** .07 .05 .28** .15* .23** .05 67.76 7.87

2. Relationship duration in years

.03 .07 .05 .15** .05 .10* -.04 40.19 11.39

3. Comorbidities .08 .03 .01 .00 .17** .24** 2.42 1.31

4. Active engagement -.45** .13** .10* -.02 -.17** 3.90 0.78

5. Protective buffering .19** .08 .17** .20** 2.39 0.74

6. Overprotection .17** .25** .16** 2.34 0.74

7. Promotion focus .57** -.07 4.15 1.32

8. Prevention focus .18** 3.79 1.24

9. GHQ 10.28 4.95

Note. N varies as a result of missing values.*p < .05, **p < .01.

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We also tested whether gender and type of illness were associated with the variables under study. The only significant differences for gender were found on the three support styles. Men reported that their partner used more active engagement than women did (M = 3.98, SD = .75 vs. M = 3.64, SD = .83), t = 3.84, p < .001. Men also perceived their partner as more overprotective than women (M = 2.44, SD = .71 vs. M = 1.95, SD = .69), t = 6.31, p < .001. Women reported that their partner engaged more in protective buffering than men (M = 2.33, SD = .72 vs. M = 2.56, SD = .79), t = -2.92, p < .01. The only significant difference for type of illness was found on promotion focus F(3,473) = 3.56, p = .03. Post hoc tests indicated that patients with heart disease reported a significantly stronger promotion focus than patients with asthma (M = 4.30, SD = 1.30 vs. M = 3.88, SD = 1.27), p = .02.

TestingmoderatingeffectsTo test whether partner support (i.e., active engagement, protective buffering and overprotection) moderated the association between the patient’s regulatory focus and distress in patients, we conducted several hierarchical regression analyses. Number of comorbidities was associated with distress and was therefore included as a covariate in the analyses.

In consecutive steps, main effects (regulatory focus, either prevention or promotion focus, and support style, either active engagement, protective buffering, or overprotection) and interaction effects were examined. We avoided multicollinearity between the predictors and the interaction terms by computing the multiplicative functions as the products of the ‘centered’ scores on the component variables (Aiken & West, 1991). Distress was entered as the dependent variable. We calculated and plotted the regression slopes for patients high (+ 1 SD) and low (- 1 SD) on partner support, separately (Aiken & West, 1991).

Results of the regression analyses are depicted separately for promotion (Table 2.2) and prevention focus (Table 2.3). All the interactions between promotion focus and the three ways of support contributed significantly to psychological distress. These interaction effects were in line with hypothesis 3. Figure 2.1 depicts the results for promotion focus and active engagement. A promotion focus was negatively associated with psychological distress in patients. This effect was significant in patients who reported their partner showed relatively little active engagement (B = -0.73, p < .01), but not in patients who reported that their partner adopted this support style relatively often (B = 0.31, p = .17). Additional tests showed that, when promotion focus was weak, distress was significantly higher in patients who reported low levels of active engagement than patients who reported high levels of active engagement (B = -1.87, p < .001). In contrast, no significant difference between the two groups was observed in patients with a strong promotion focus (B = -0.11, p = .79).

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Figure 2.2 presents the results for promotion focus and protective buffering. A promotion focus was negatively associated with psychological distress, but only in those patients who perceived their partner adopted the style of protective buffering relatively often (B = -0.83, p < .001)¹. For patients who perceived their partner adopted this style seldom, the association was not significant (B = 0.18, p = .42). Further, the results showed that, when promotion focus was weak, distress was significantly higher in patients who reported high levels of protective buffering than patients who reported low levels of protective buffering (B = 2.21, p < .001). In contrast, no significant difference between the two groups was observed in patients with a strong promotion focus (B = 0.41, p = .30). Figure 2.3 presents the significant interaction of promotion focus and overprotection. Again as expected, a promotion focus was negatively associated with more psychological distress, but only in patients who perceived their partner as relatively overprotective (B = -0.75, p < .01). For patients who perceived their partner as less overprotective, this effect was not significant (B = -0.03, p = .91). Additional tests showed that, when promotion focus was weak, distress was significantly higher in patients who reported high levels of overprotection than patients who reported low levels of overprotection (B = 1.85, p < .001). In contrast, no significant difference between the two groups was observed in patients with a strong promotion focus (B = 0.54, p = .19).

For prevention focus we did find a main effect, but we did not find moderating effects of partner support, with the exception of overprotection (see Figure 2.4 for the depiction of this interaction effect). However, the shape of the interaction was different as expected. In contrast to hypothesis 3, a stronger prevention focus was associated with more distress in patients who perceived to be relatively little overprotected by their partner (B = 0.75, p < .01), but not in patients who perceived their partner as relatively overprotective (B = 0.10, p = .70). From Figure 2.4 it can be seen that patients who reported relatively low overprotection by their partner and who also reported a relatively weak prevention focus were relatively better off.

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Table 2.2 ResultsoftheRegressionofPsychologicalDistressonSupportBehaviorandPromotionFocus

Psychological distressB SE ∆ R² ∆ F p

Active engagement analysis

Step 1 .06 28.71 <.001

Number comorbidities 0.91** 0.16

Step 2 .04 9.85 <.001

Promotion focus (Prom) -0.21 0.16

Active engagement (AE) -0.99** 0.28

Step 3 .02 10.99 <.01

Prom × AE 0.66** 0.20

Protective buffering analysis

Step 1 .06 28.34 <.001


Step 2 .04 11.45 <.001

Prom -0.33* 0.16

Protective buffering (PB) 1.31** 0.29

Step 3 .02 10.89 <.01

Prom × PB -0.68** 0.21

Overprotection analysis

Step 1 .06 28.01 <.001


Step 2 .04 9.04 <.001

Prom -0.39* 0.17

Overprotection (O) 1.20** 0.30

Step 3 .01 5.57 .02

Prom × O -0.50* 0.21

Note. N varies as a result of missing values.*p < .05; **p < .01.

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Table 2.3 ResultsoftheRegressionofPsychologicalDistressonSupportBehaviorandPreventionFocus

Psychological distressB SE ∆ R² ∆ F p

Active engagement analysis

Step 1 .06 28.71 <.001


Step 2 .05 13.96 <.001

Prevention focus (Prev) 0.54** 0.18

Active engagement (AE) -1.16** 0.28

Step 3 .00 0.04 .84

Prev × AE -0.04 0.22

Protective buffering analysis

Step 1 .06 28.34 <.001


Step 2 .05 12.67 <.001

Prev 0.43* 0.18

Protective buffering (PB) 1.16** 0.30

Step 3 .00 0.27 .60

Prev × PB -0.12 0.23

Overprotection analysis

Step 1 0.06 28.01 <.001


Step 2 0.04 9.48 <.001

Prev 0.43* 0.19

Overprotection (O) 0.95** 0.31

Step 3 0.01 4.13 .04

Prev × O -0.45* 0.22

Note. N varies as a result of missing values.*p < .05; **p < .01.

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Figure 2.1Theinteractiveeffectofpromotionfocusandactiveengagementonpsychologicaldistress

Figure 2.2 Theinteractiveeffectofpromotionfocusandprotectivebufferingonpsychologicaldistress

Figure 2.1 The interactive effect of promotion focus and active engagement on psychological distress

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Figure 2.2 The interactive effect of promotion focus and protective buffering on psychological distress

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Figure 2.3Theinteractiveeffectofpromotionfocusandoverprotectiononpsychologicaldistress

Figure 2.4Theinteractiveeffectofpreventionfocusandoverprotectiononpsychologicaldistress

Figure 2.3 The interactive effect of promotion focus and overprotection on psychological distress

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Figure 2.4 The interactive effect of prevention focus and overprotection on psychological distress

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2.4 Discussion

Although the concept of regulatory focus has been extensively studied in student samples, this study is the first to investigate regulatory focus in a sample of older adults with a chronic disease requiring self-management behavior. In contrast with the study by Miller and Markman (2007), our study showed that promotion focus was not related to distress, and that prevention focus was only weakly related to distress. However, our results are in line with a recent study among women with breast cancer in which there was also no main effect of promotion focus on distress (Frieswijk & Hagedoorn, 2009).

Differences in findings may have to do with different types of samples (older age versus younger age, patient versus student). The weak positive correlation between prevention focus and distress, for example, might be explained by the older age of our sample. With increasing age, people may experience several losses, such as functional decline (Hebert, 1997) and a reduced capacity of working memory (Dobbs & Rule, 1989). Further, as shown in Table 2.1, the occurrence of a chronic illness and comorbidities become more prevalent with advancing age. This increasing salience of losses might lead older persons to become more focused on avoiding (further) losses, which would explain the correlation between age and prevention focus in our sample. In addition, under the circumstances of experiencing losses, a stronger prevention orientation would probably be less maladaptive then under the circumstances of being young and healthy. Although our sample of older adults scored lower on both prevention and promotion focus compared to the student samples in previous studies (all ts > 2.33, all ps < .05; Keller, 2008; Lockwood et al., 2002; Miller & Markman, 2007; Oyserman et al., 2007; Sullivan et al., 2006), the discrepancy between prevention and promotion was smaller compared to these student samples (all ts > 2.64, all ps < .01). Further, other studies did find that older adults reported a stronger goal orientation toward loss prevention (Ebner, Freund, & Baltes, 2006; Heckhausen, 1997). In addition, an orientation toward loss prevention was related to less well-being in younger adults, but no such negative association existed for older adults (Ebner et al., 2006).

The fact that our study on regulatory focus comprised a different type of sample might also explain the different associations between promotion and prevention focus that we found compared to other studies (Coolsen, 2004; Keller, 2006; Keller & Bless, 2006; Lockwood et al., 2002; Miller & Markman, 2007; Oyserman et al., 2007; Sullivan et al., 2006). While these other studies revealed rather weak correlations between the promotion and prevention subscales, (ranging from .05 to .27), our study showed a much stronger association between promotion and prevention focus (r = .57, p < .001), indicating that stronger prevention scores are associated with stronger promotion scores. The chronic diseases that were present in our sample, that is diabetes, asthma and heart disease,

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require both promotion-focused and prevention-focused goals. Patients need to engage in short-term goals such as taking the right medication, keeping a healthy diet, exercising sufficiently, which indicates a need for a strong promotion focus. On the other hand, some of the long-term goals in the illness context are often communicated in prevention-focused terms, such as the prevention of complications. This means that patients (may feel the) need to focus on both positive outcomes as well as negative outcomes, which might explain the positive association between promotion and prevention focus. Another explanation for the rather strong association between promotion and prevention focus could be that our sample (older adults with a chronic illness) viewed the two subscales of prevention and promotion focus as one scale measuring goal-orientedness (see also Fellner, Holler, Kirchler, & Schabmann, 2007). Put differently, respondents in our sample may have looked upon prevention and promotion focus as two sides of the same coin.

Our hypothesis, that partner support would moderate the negative association between promotion focus and distress was confirmed. Although we could not detect a main effect of promotion focus on distress, our findings show that there is a negative association between promotion focus and distress in those patients who report to receive low levels of active engagement, and high levels of protective buffering and overprotection. The results are in line with the idea that promotion-oriented support (active engagement) encourages patients with a relatively weaker promotion focus to adopt promotion-oriented strategies and cognitions, leading to less distress. In contrast, behaviors like protective buffering and overprotection might induce a prevention-focused environment, which prevents patients with a relatively weak promotion focus further from adopting a more promotion-oriented mind set, thereby leading to more distress in these patients. To put it in other words, the results indicate that vulnerable patients, in terms of a relatively weak promotion focus, may benefit more, in terms of lower levels of distress, from supportive, promotion-oriented behaviors, whereas they may be harmed more by less supportive, prevention-oriented behaviors by the partner (cf. Hagedoorn et al., 2000).

Our results complement prior studies pointing out that social support might buffer or increase the negative impact of a vulnerable coping style or personality trait. For example, in patients with rheumatoid arthritis, it was found that unmitigated communion, an extreme focus on others to the exclusion of the self, was associated with distress, but only in those patients who reported high social constraints (Danoff-Burg, Revenson, Trudeau, & Paget, 2004). In cancer patients, high avoidance coping or behaviors in combination with low levels of social support predicted the highest levels of distress (Devine, Parker, Fouladi, & Cohen, 2003; Jacobsen et al., 2002).

Although we did find a main effect of prevention focus, in that a prevention focus was associated with more distress, this main effect was not moderated by partner support, except for overprotection. It was expected that a combination of a strong prevention focus

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and a perception of high partner overprotectiveness would be problematic in terms of relatively high levels of distress. However, Figure 2.4 shows that either a strong prevention focus or high overprotectiveness is a sufficient prerequisite for experiencing relatively high levels of distress. Patients with a relatively weak prevention focus, who reported low levels of overprotectiveness, were found to show the lowest levels of distress. The fact that we could not find a moderating effect of active engagement and protective buffering suggests that unlike a lack of promotion focus, a relatively strong prevention focus cannot be compensated for by adequate partner support nor can its association with high distress be aggravated by inadequate partner support. It supports the idea that having a weak promotion focus is not the same as having a strong prevention focus. Future research may investigate under which circumstances a prevention focus is associated with distress.

The present study has a number of limitations that needs to be taken into account when interpreting the results. One limitation concerns our sample. We selected those respondents who reported having either diabetes, asthma, or heart disease when presented with a list of several health problems. However, we do not know for example the duration of their disease, or how well they were able to manage their disease, which might have an effect on regulatory focus and on partner support. Future studies should take into account such disease parameters.

A second limitation concerns our rather low response rate. Although this is what can be expected among elderly populations (Kaldenberg, Koenig, & Becker, 1994), we cannot exclude the possibility that any differences between responders and non-responders could have biased our results.

A third limitation is the cross-sectional design of our study which precludes us from drawing conclusions about causality. For example, there was a positive correlation between prevention focus and overprotection. This might indicate that a prevention focus in patients evokes overprotective behaviors from partners or that overprotection by partners leads to an adoption of a prevention focus in patients. However, it could also indicate that a prevention focus is associated with a negative outlook, and that this causes patients with a prevention focus to interpret partner behaviors negatively. Some studies provide preliminary evidence for this explanation. For example, one study showed that avoidance goals (cf. prevention focus) were associated with a more pessimistic evaluation of another person described in an essay (Strachman & Gable, 2006). It might therefore be interesting to include other measures of partner support, such as partners’ own perceptions of the support they provide, or observational measures.

Importantly, the third variable explanation is not very plausible with respect to the interaction effects, but we cannot conclude that a relatively weak promotion focus increases distress in patients who report to receive less active engagement, or more protective buffering or overprotection. Experimental studies are needed that establish

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whether the manipulation of partner support styles that encourage either a promotion- or prevention-focused environment would lead to lower or higher levels of distress, especially in patients lacking a promotion focus.

More research is needed to draw final conclusions, but we can tentatively say that it appears that patients are psychologically better off when partner support stimulates a promotion focus in patients. Finally, our results do not necessarily have to represent a process only applicable to older persons with a chronic disease requiring self-management. It is quite possible that similar processes also apply to other stressful contexts besides having a chronic disease. Therefore, we would like to encourage future studies employing different samples to test the generalizability of our findings suggesting that supportive partner behavior weakens the negative link between promotion focus and distress in chronic diseases requiring self-management behaviors, while unsupportive partner behavior strengthens this link.

Footnotes

¹We also performed regression analyses with the original scale of protective buffering thatconsisted of eight items. The interaction effect between promotion focus and protectivebuffering remained significant, while the interaction effect between prevention focus andprotectivebufferingremainednonsignificant.

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Chapter 3

The role of overprotection by the partner in coping with diabetes: a moderated mediation model

Marike C. Schokker , Thera P. Links, Jelte Bouma, Joost C. Keers, Robbert Sanderman, Bruce H.R. Wolff enbuttel, Mariët Hagedoorn

Psychology and Health, 2010 Feb 18, e-pub ahead of print

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3.1 Introduction

Diabetes is a chronic illness that requires a demanding and unending self-care regimen of taking medication, engaging in physical exercise, and maintaining a healthy diet to obtain a good glycemic control. A good glycemic control is needed to lower the risk of developing microvascular complications (neuropathy, retinopathy or nephropathy) and macrovascular complications (Diabetes Control and Complications Trial Research Group, 1993; Lawson, Gerstein, Tsui, & Zinman, 1999; UK Prospective Diabetes Study Group, 1998; 2000). The burden of adhering to the self-care regimen and the threat or actual onset of complications may lead patients to experience diabetes-related distress (Gonder-Frederick, Cox, & Ritterband, 2002; Jacobson, 1996; Polonsky et al., 1995; Rubin & Peyrot, 2001; Welch, Jacobson, & Polonsky, 1997). Besides the influence of disease-related variables and patient characteristics, a growing body of research has demonstrated the influential role of the partner and the family on patients’ level of distress (Fisher et al., 2004; Hagedoorn et al., 2006; Karlsen, Idsoe, Hanestad, Murberg, & Bru, 2004; Trief, Wade, Britton, & Weinstock, 2002; Trief, Grant, Elbert, & Weinstock, 1998; Wearden, Tarrier, & Davies, 2000).

Of specific interest is the role of overprotection by the partner, which can be viewed as unhelpful behavior. Overprotecting the patient means that the partner underestimates the patient’s capabilities, resulting in unnecessary help, excessive praise for accomplishments, or attempts to restrict activities. Previous studies concerning other chronic diseases have shown that overprotection by the partner was associated with higher levels of distress in patients (Buunk, Berkhuysen, Sanderman, & Nieuwland, 1996; Joekes, Van Elderen, & Schreurs, 2007; Kuijer et al., 2000). Further, diabetes patients participating in a diabetes education program showed a larger decrease in distress over time if, at the start of the program, patients perceived their partner to be less overprotective (Hagedoorn et al., 2006). However, these previous studies have not yet identified underlying mechanisms in the association between overprotection and distress, nor conditions under which the associations may be stronger or weaker. This study will address this gap by examining whether diabetes-specific self-efficacy mediates the association between overprotection and distress and whether this mediation depends on glycemic control and gender.

We argue that overprotective behavior by the partner may convey the message to the patient that the partner has little confidence in the patient’s abilities to deal with the diabetes effectively. For example, the partner may try to prevent the patient from eating a piece of pie because the partner doubts whether the patient will be able to keep his or her glycemic control within a normal range in this situation. Such a lack of partner confidence may cause a decrease in patients’ diabetes-specific self-efficacy, that is, the confidence that patients have in their own ability to manage the diabetes. Studies concerning other

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chronic diseases have supported this line of reasoning by showing that overprotection was indeed negatively associated with feelings of self-efficacy with respect to a number of disease management behaviors (Berkhuysen, Nieuwland, Buunk, Sanderman, & Rispens, 1999; Buunk et al., 1996; Coyne & Smith, 1994). In turn, we expected lower levels of self-efficacy to increase levels of distress. This self-efficacy–distress linkage has been abundantly demonstrated in prior research (Eiser, Riazi, Eiser, Hammersley, & Tooke, 2001; Kanbara et al., 2008; Rose, Fliege, Hildebrandt, Schirop, & Klapp, 2002; Senecal, Nouwen, & White, 2000; Van Der Ven et al., 2003). In sum, overprotection was expected to be associated with diabetes-related distress through diabetes-specific self-efficacy.

Further, we propose a moderated mediation model in which the indirect link between overprotection and diabetes-related distress will apply more strongly for patients with worse glycemic control. There are several ways in which an indirect link may be dependent upon a moderator. For example, glycemic control may moderate the association between overprotection, the predictor, and diabetes-specific self-efficacy, the mediator. When glycemic control is poor, overprotection by the partner may be even more strongly associated with self-efficacy than when glycemic control is good. Overprotection conveys little confidence of the partner in the patient’s abilities. A poor glycemic control may point out to the patient that the partner is right in having little confidence, thus decreasing patient’s self-efficacy to a higher extent.

Another possibility is that glycemic control moderates the association between diabetes-specific self-efficacy, the mediator, and diabetes-related distress, the outcome. This means that overprotection will be associated with less diabetes-specific self-efficacy, and these lower levels of self-efficacy may be more detrimental in patients with a poor glycemic control. A poor glycemic control indicates that patients need to take certain actions to improve their control. Patients with high self-efficacy will be more persistent in the face of obstacles (Bandura, 1977; 1982; 2004), such as a poor glycemic control, and will feel confident that they are able to make improvements. As a consequence, patients who feel self-efficacious are less inclined to feel distressed when confronted with a poor glycemic control. In contrast, patients with low self-efficacy are more likely to feel distressed when confronted with a poor glycemic control because they feel less capable of performing the necessary actions for improvement.

It was also expected that gender may moderate the mediation model. Women have been found to attach more value to relationship-oriented aspects than do men (Cross & Madson, 1997; Strough, Berg, & Sansone, 1996; Thoits, 1992). As a consequence, relationship-oriented aspects, such as support from others, may have a stronger impact on women’s than on men’s level of distress. Although some studies of associations between support and distress did not find gender differences (e.g., Sherman, 2003; Vinokur, Price, & Caplan, 1996), the studies that did were consistent in demonstrating that women are

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indeed more strongly influenced by partner behavior and characteristics than are men (e.g., Acitelli & Antonucci, 1994; Hagedoorn et al., 2000; Hagedoorn et al., 2001; Horwitz, McLaughlin, & White, 1998; Mcrae & Brody, 1989). This leads to the formulation of a second moderated mediation model in which the indirect link between overprotection and distress through diabetes-specific self-efficacy will apply more strongly for female than for male patients. More specifically, it can be expected that the association between overprotection and self-efficacy is stronger for women. However, it is also conceivable that the association between self-efficacy and diabetes-related distress is stronger for women. There is evidence suggesting that women and men have different attitudes towards their diabetes. Female patients were more likely than male patients to perceive the diabetes as serious and they also reported a higher impact of the diabetes on daily life than did male patients (Mosnier-Pudar et al., 2009). Furthermore, female patients defined themselves more in terms of their diabetes than male patients did (Helgeson & Novak, 2007). Because female patients seem to perceive their diabetes as more serious and intruding than male patients, female patients may become more distressed than male patients when feeling little self-efficacious in dealing with the disease.

Previous research on the impact of partner support has mainly utilized patients’ own perceptions of support provided by the partner. A drawback of assessing only patients’ perceptions is that these perceptions may be confounded with patients’ level of distress (Story & Bradbury, 2004). That is, patients who experience high levels of distress may interpret their partner’s behavior as overprotective. Therefore, to test the associations, we incorporated both patient and partner ratings of overprotection, in separate analyses. In sum, we formulated the following hypotheses (see also Figure 3.1):

1. The link between overprotection and diabetes-related distress will be mediated by diabetes-specific self-efficacy.

2. The indirect link, that is, the mediation effect, will be larger for those patients who show relatively poor glycemic control, because:

a. Glycemic control moderates the overprotection-self-efficacy linkageb. Glycemic control moderates the self-efficacy-distress linkage

3. The indirect link will be larger for female than for male patients, because:a. Gender moderates the overprotection-self-efficacy linkageb. Gender moderates the self-efficacy-distress linkage

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Figure 3.1 Theproposedmoderatedmediationmodels

3.2 Method

ParticipantsandProcedureThe research was carried out in accordance with the guidelines of the Medical Ethical Committee of the University Medical Center Groningen. Patients were considered eligible when they satisfied the following inclusion criteria: age 18-70 years, no severe comorbidity such as a clinical depression or a psychiatric disorder, not pregnant, and Dutch speaking. Approximately 690 eligible, consecutive patients with type 1 and 2 diabetes requiring insulin were approached by their physician during a check-up visit to complete a short screening questionnaire¹. This short questionnaire was filled out and returned by 507 patients. Of these patients, 419 (82.6%) indicated to have an intimate partner. For the purposes of this study, we were interested in the larger questionnaire that was sent to both patients and their partners after patients had filled out the short questionnaire. However, some couples accidentally did not receive this larger questionnaire and of the 413 couples that were sent the questionnaire, 223 couples (54%) completed it². Eight couples were excluded afterwards (reasons: receiving help filling out the questionnaire, missing data on one of the variables, not providing consent to collect measures for glycemic control from their medical charts), which means the final subsample consisted of 215 couples. Hundred and sixteen (54%) of the patients were men. The mean diabetes duration was 15.6 years (SD = 11.4). The mean age of the patients was 53.7 years (SD = 11.3) and the mean age of the partners was 53.8 years (SD = 11.7). The mean duration of respondents’ relationship was 28.1 years (SD = 12.9). The majority of the respondents (88.8 %) were married, 7.4 % reported living together with a partner, and 3.7 % reported having a partner, but not living together. We checked whether there were differences between responders and non-responders. For example, HbA1c and diabetes-related distress were known for non-

Figure 3.1 The proposed moderated mediation models

Gender: 1 = male patients, 2 = female patients

Overprotection (patient or partner

perception)

Diabetes-specific Self-efficacy

Diabetes-related Distress

Glycemic control / Gender


- -

+ +

Figure 3.1 The proposed moderated mediation models

Gender: 1 = male patients, 2 = female patients

Overprotection (patient or partner

perception)

Diabetes-specific Self-efficacy

Diabetes-related Distress



- -

+ +

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responders since this was measured in the short screening questionnaire. It appeared that patients who dropped out after the short questionnaire had higher HbA1c compared to those patients who did not drop out (M = 7.00, SD = 0.88 vs. M = 7.21, SD = 0.98, t(341) = -1.97, p = .04), but drop-outs had lower diabetes-related distress levels compared to patients who did not drop out (M = 15.22, SD = 15.34 vs. M = 18.89, SD = 16.37, t(349) = -2.10, p = .04).

MeasuresOverprotectionbythepartner.We used a subscale of the Active Engagement, Protective

Buffering, and Overprotection (ABO) questionnaire (Buunk et al., 1996) based on work by Coyne and colleagues on relationship-focused coping (Coyne & Smith, 1994; Coyne, Ellard, & Smith, 1990) to assess overprotection by the partner. The overprotection subscale has acceptable test-retest reliability and good construct validity (Buunk et al., 1996). Patients were asked to rate to what extent their partner adopted this support style in reaction to their illness. A parallel measure assessed the partners’ perception of their own overprotective behavior. The scale consists of six items measured on a five-point scale ranging from 1 (never) to 5 (veryoften). Examples of the patient subscale are “My partner treats me like a baby” and “When it comes down to it, my partner seems to think that I don’t know what’s right for me”. All items were averaged into a single score where higher scores indicate more overprotection (patients: α = .70; partners:α = 69).

Diabetes-specificself-efficacy.The Confidence in Diabetes Self-care (CIDS) scale (Van der Ven et al., 2003) was used to assess the patient’s perceived self-efficacy specific to diabetes self-care tasks. The CIDS was found to have good validity and high internal consistency in Dutch diabetes patients (Van der Ven et al., 2003). All 20 items were measured on a five-point scale ranging from 1 (no,IamsureIcannot) to 5 (yes,IamsureIcan). Examples are “….check my blood glucose at least two times a day” and “…treat a high blood glucose correctly”. Scores were summed and transformed to a 0-100 scale, with higher scores representing higher diabetes-specific self-efficacy (α = .89).

Diabetes-related distress. Diabetes-related distress was assessed with the Problem Areas in Diabetes scale (PAID; Polonsky et al., 1995; Snoek, Pouwer, Welch, & Polonsky, 2000). Patients were asked to what extent they experienced problems with each of the 20 items. The items were measured on a five-point scale ranging from 0 (notaproblem) to 4 (aseriousproblem). Item examples are “Feeling overwhelmed by your diabetes regimen” and “Worrying about the future and the possibility of serious complications”. The items were transformed into a scale ranging from 0-100, with a higher score indicating more diabetes-related distress (α= .95).

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Glycemiccontrol.Glycemic control was determined by measuring glycated hemoglobin levels (HbA1c), which reflects the average blood glucose over the preceding three months (Biorad HPLC, Munich: 4.3 – 6.1%). HbA1c values were obtained from the medical charts at the time of the study (M=0.05 months,SD=0.22 months). Higher numbers reflect a poorer glycemic control. HbA1c values above 8.0 % is defined as poor glycemic control (American Diabetes Association, 2002).

StatisticalanalysesFirstly, demographic and disease-related variables were tested for inclusion as control variables. Secondly, mediation and moderated mediation analyses were performed to test the hypotheses.

Testsofsimplemediation. To test the significance of the indirect effect of overprotection on distress through self-efficacy, we ran a macro developed by Preacher and Hayes (2004), which facilitates the implementation of a bootstrapping method. Bootstrapping has the advantage that it does not impose distributional assumptions, since the assumption that the indirect effect is normally distributed is often violated (e.g., Shrout & Bolger, 2002). Bootstrapping is a procedure in which a number of samples (e.g. 5000) is taken from the original data by random sampling with replacement. The indirect effect in each of these bootstrap samples is computed. The macro provides bootstrapped confidence intervals (CIs) around these indirect effects.

Tests of moderated mediation. We used another SPSS macro provided by Preacher, Rucker and Hayes (2007) to test whether the strength of the hypothesized indirect (mediation) effect is conditional on the value of the moderator, also known as a conditional indirect effect, or moderated mediation. The output of this macro provides the significance of conditional indirect effects at different values of the moderator variable (HbA1c in Hypothesis 2 and gender in Hypothesis 3). The macro further facilitates the implementation of a bootstrapping method.

3.3 Results

DescriptivesTable 3.1 presents means, standard deviations and correlations for the variables under study. Overall, diabetes-related distress was weakly positively associated with overprotection as perceived by the partner, but not with overprotection as perceived by the patient. Overprotection (both partner and patient perception) was associated with less diabetes-specific self-efficacy. Paired t tests showed that patients and partners did not differ in their perception of overprotection, t(214) = -0.42, p = .68 (not presented in Table

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3.1). The correlation, however, between partner and patient perception of overprotection was only 0.39. Diabetes-specific self-efficacy was negatively associated with diabetes-related distress and HbA1c. Diabetes-related distress was moderately associated with higher HbA1c levels. Mean HbA1c value was 7.3 % with a standard deviation of 1.03. Twenty one % had relatively poor glycemic control as indicated by HbA1c values ≥ 8.0% (not in Table 3.1). Age, number of comorbidities, relationship duration, number of hypoglycemia, and diabetes duration were associated with either the mediator or the outcome variable and were therefore entered as covariates in the subsequent analyses.

Table 3.1 IntercorrelationsfortheVariablesunderStudy

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Age .08 -.27** .75** .19** .19** -.16* .22** .08 .14* .06 -.19** -.21**

2. Sex -.13 .15* .17* .01 .13 .28** -.08 -.28** -.02 .01 .10

3. Educationª -.21** -.07 .02 .12 -.10 -.18* -.07 .12 -.14* .02

4. Rel. dur.ª .18* .19* -.04 .10 -.03 -.01 .11 -.12 -.20**

5. Diab.dur.ª .29** .14* .18* -.00 -.04 .15* .09 -.01

6. Diab. compl.

-.03 .17* .06 .15* -.03 -.04 .10

7. Nr. hypo’s -.03 -.21** -.27** .17* -.12 .11

8. Comorb. .18** .03 -.04 -.08 .20**

9. OP partn .39** -.28** .04 .19**

10. OP pat -.21** .06 .12

11. SE -.17* -.45**

12. HbA1c .27**

13. PAID

Mean 53.65 - 1.57 28.08 15.57 0.26 2.45 1.46 1.85 1.83 84.02 7.27 18.31

SD 11.34 - 0.74 12.91 11.36 0.55 1.19 1.33 0.53 0.55 12.64 1.03 16.72

Note. ªFor these variables, N varies as a result of missing values.*p < .05; **p < .01.Sex: 1 = male patients, 2 = female patients; Education: 1 = lower educated, 2 = middle educated, 3 = higher educated; Rel. dur. = relationship duration in years; Diab.dur. = diabetes duration in years; Diab.compl. = number of diabetes complications (retinopathy, neuropathy, nephropathy); Nr. hypo’s = number of hypoglycaemia in the preceding month; Comorb. = number of comorbidities; OP partn = Overprotection as perceived by the partner; OP pat = Overprotection as perceived by the patient; SE = Diabetes-specific self-efficacy; PAID = Problem Areas in Diabetes / diabetes-related distress.

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TestingsimplemediationWe first ran the simple mediation macro for overprotection as perceived by the partner. The bootstrapping procedure yielded an estimate of the indirect effect of 3.48, with a 95% confidence interval ranging from 1.65 to 6.11. Because this interval does not contain zero, the indirect effect (i.e., mediation effect) is significant at α = .05. This analysis was repeated for overprotection as perceived by the patient. The bootstrapping procedure yielded an estimate of the indirect effect of 2.47, with a 95% confidence interval ranging from 0.48 to 4.94. Altogether, these results provide support for Hypothesis 1, in that overprotection (both patient and partner perception) was associated with diabetes-related distress through diabetes-specific self-efficacy.

TestingmoderatedmediationHypothesis 2 and 3 state that the indirect effect of overprotection will be stronger for patients with worse glycemic control, reflected in higher HbA1c levels, and that it will be stronger for female than for male patients. The results for overprotection as perceived by the partner are presented in Table 3.2 - 3.4. The results for overprotection as perceived by the patient were similar to the results for overprotection as perceived by the partner. For reasons of brevity, we do not show the tables and results for overprotection as perceived by the patient, however, these tables are available from the authors upon request. We first tested Hypothesis 2a and 3a, that is, the moderated mediation model in which the path between the predictor and the mediator is moderated (see Table 3.2). In the first step, the mediator variable is regressed on the independent variable, and the interaction between the independent variable and the moderator. As can be seen, the interaction term with HbA1c and the interaction term with Gender were both nonsignificant. Therefore, Hypotheses 2a and 3a were not supported.

Table 3.2 Regression Results for Conditional Indirect Effect, with Overprotection as perceived by thePartner, and HbA1c and Gender as a Moderator of the Association between the Predictor and theMediator

MediatorVariable(Self-efficacy)Model(Step1) HbA1c analysis Gender analysis

Predictor B SE t p B SE t p

Constant 89.05 22.39 3.98 <.001 89.44 10.08 8.88 < .001

OP 1.94 11.20 0.17 .86 -5.60 4.76 -1.18 .24

MOD 0.15 3.00 0.05 .96 -1.42 6.24 -0.23 .82

OP × MOD -1.06 1.50 -0.71 .48 -0.45 3.25 -0.14 .89

Note. The analyses are controlled for age, number of comorbidities, relationship duration, number of hypoglycaemia, and diabetes duration. OP = overprotection; MOD = moderator (HbA1c or Gender).

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Second, we tested Hypotheses 2b and 3b, that is, the moderated mediation model in which the path between the mediator and the outcome is moderated (see Table 3.3 and 3.4). Our findings did support these hypotheses. The first two steps represent conventional regression analyses. In the first step, the mediator variable (diabetes-specific self-efficacy) is regressed on the independent variable (overprotection). As can be seen, overprotection significantly predicted diabetes-specific self-efficacy. In the second step, a multiple regression is conducted that predicts the dependent variable (diabetes-related distress) from the mediator, the moderator (HbA1c), the independent variable, and the interaction between the moderator and the mediator. As shown in Table 3.3, the interaction between Self-efficacy (the mediator) and HbA1c (the moderator) was significant.

In the third step, the conditional indirect effect of overprotection is tested at three values of the moderator variable: the mean, one standard deviation below the mean, and one standard deviation above the mean. The results show that the conditional indirect effect was significant at all three of these values, but the indirect effect was larger for higher values of HbA1c.

Whereas the test in the third step assumes normality of sampling distribution, the test conducted in the fourth step verifies the results of the third step with bootstrapping (5000 bootstrap samples). Setting the moderator at one standard deviation below the mean yielded a bootstrap 95% bias corrected and accelerated confidence interval of 0.70 – 4.99 (not listed in Table 3.4). Because this interval does not contain zero, the conditional indirect effect at one SD below the mean is significantly different from 0 at α = .05. Repeating this procedure for the moderator at the mean and one standard deviation above the mean yielded 95% bias corrected and accelerated confidence intervals of 1.49 – 5.36 and 1.89 – 7.67, respectively. Altogether, bootstrapping corroborated the results of the normal-theory tests.

Hypothesis 3b states that the indirect effect of overprotection will be stronger for female patients. The first step in Table 3.4 shows that overprotection significantly predicted diabetes-specific self-efficacy. The second step yielded a significant interaction between Self-efficacy (the mediator) and Gender (the moderator). In the third step, the conditional indirect effect of overprotection is tested for males and females separately. The indirect effect of overprotection as perceived by the partner was significant for both female and male patients, but stronger for female patients. In the fourth step, the results are verified with bootstrapping. The indirect effect of overprotection as perceived by the partner yielded a bootstrap corrected and accelerated confidence interval of 0.86 – 4.43 for male patients, and 2.18 – 9.55 for female patients (not listed in Table 3.4). These results supported the results of the normal-theory tests.

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Table 3.3 Regression Results for Conditional Indirect Effect, with Overprotection as perceived by thePartner,andHbA1casaModeratoroftheAssociationbetweentheMediatorandtheOutcome

MediatorVariable(Self-efficacy)Model(Step1)

Predictor B SE t p

Constant 87.41 5.86 14.91 <.001

OP -6.02 1.62 -3.71 <.001

DependentVariable(Distress)Model(Step2)

Predictor B SE z p

Constant -62.85 45.67 -1.38 .17

OP 2.00 1.88 1.06 .29

Self-efficacy 0.65 0.53 1.22 .23

HbA1c 16.64 5.97 2.79 .01

Self-efficacy × HbA1c -0.16 0.07 -2.24 .03

ConditionalEffectsassumingNormalDistribution(Step3)

HbA1c Indirecteffect SE z p

6.2379 (-1 SD) 2.13 1.00 2.13 .03

7.2693 (Mean) 3.13 0.97 3.24 < .01

8.3007 (+1 SD) 4.12 1.40 2.95 < .01

ConditionalEffectswithBootstrapMethod(Step4)

HbA1c Indirecteffect SE z p

6.2379 (-1 SD) 2.14 1.02 2.10 .04

7.2693 (Mean) 3.13 0.97 3.22 < .01

8.3007 (+1 SD) 4.09 1.41 2.90 < .01

Note. The analyses are controlled for age, number of comorbidities, relationship duration, number of hypoglycemia, and diabetes duration. OP = overprotection.

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Table 3.4 Regression Results for Conditional Indirect Effect, with Overprotection as perceived by thePartnerasthePredictor,andGenderastheModeratoroftheAssociationbetweentheMediatorandtheOutcome

MediatorVariable(Self-efficacy)Model(Step1)

Predictor B SE t p

Constant 87.41 5.86 14.91 <.001

Overprotection -6.02 1.62 -3.71 <.001

DependentVariable(Distress)Model(Step2)

Predictor B SE t p

Constant 4.64 22.07 0.21 .83

OP 2.29 1.92 1.19 .24

Self-efficacy 0.13 0.24 0.54 .59

Gender 41.45 12.96 3.20 < .01

Self-efficacy × Gender -0.48 0.15 -3.14 < .01

ConditionalEffectsassumingNormalDistribution(Step3)

Gender Indirecteffect SE z p

Male 2.14 0.88 2.45 .01

Female 5.04 1.82 2.77 < .01

ConditionalEffectsWithBootstrapMethod(Step4)

Gender Indirecteffect SE z p

Male 2.16 0.89 2.44 .02

Female 5.08 1.82 2.80 .01

Note. The analyses are controlled for age, number of comorbidities, relationship duration, number of hypoglycaemia, and diabetes duration. OP = overprotection.

3.4 Discussion

The current study examined when and how overprotection of the patient, as perceived by both patient and partner, is associated with diabetes-related distress. The results showed rather weak bivariate correlations between overprotection and distress (see also De Ridder, Schreurs, & Kuijer, 2005). Nonetheless, the simple mediation analyses did show that these weak associations were mediated by diabetes-specific self-efficacy. Overprotection by the partner was associated with less diabetes-specific self-efficacy of the patient, which in turn was associated with more diabetes-related distress. Furthermore,

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the results of the moderated mediation analyses showed that under some conditions, the indirect associations were stronger. We established that the indirect association between overprotection and diabetes-related distress through diabetes-specific self-efficacy was moderated by glycemic control and by gender, thereby supporting Hypotheses 2b and 3b. The findings are consistent with our reasoning that overprotection by the partner undermines diabetes-specific self-efficacy, and that these lower levels of self-efficacy lead to higher levels of diabetes-related distress, especially when glycemic control is poor and when the patient is female.

Our results complement and extend the results of previous studies in several ways. Previous studies have also identified a mediating effect of self-efficacy in the association between partner or family behavior and distress, for example in students (Saltzman & Holahan, 2002), in women undergoing an abortion (Major et al., 1990), in adults who underwent a knee surgery (Khan et al., 2009), and in women in midlife (Martire, Stephens, & Townsend, 1998). These studies specifically found associations between positive support and psychological outcomes, thereby demonstrating the enabling hypothesis (Benight & Bandura, 2004; Schwarzer & Knoll, 2007). The enabling hypothesis states that positive support enables feelings of self-efficacy that in turn foster beneficial psychological outcomes. In contrast, our study specifically focused on the disabling effect of overprotection, which is unhelpful support behavior, on feelings of self-efficacy, which in turn would increase feelings of distress (see also Manne et al., 2003; Manne & Glassman, 2000).

Another way in which our study extends prior research is by demonstrating that the mediation effect of self-efficacy is conditional on other variables, thereby indicating the need to consider not only how, but also when associations occur. As mentioned in the introduction, there are several ways in which the magnitude of an indirect effect may be dependent upon a moderator. For example, the association between the predictor and the mediator may be moderated, but also the association between the mediator and the outcome may be moderated. In our theoretical rationale outlined in the text, we explained how both possibilities might be plausible. The findings showed that Hypotheses 2a and 3a, in which HbA1c and gender moderate the path between overprotection (predictor) and self-efficacy (mediator; Model 2 in the moderated mediation macro of Preacher, Rucker, and Hayes (2007)) was not supported. We did find support for Hypotheses 2b and 3b, in which HbA1c and gender moderate the path between self-efficacy (mediator) and diabetes-related distress (Model 3 in the moderated mediation macro). Thus our results are in line with the idea that patients who feel less self-efficacious will experience more diabetes-related distress when confronted with a poor glycemic control because these patients do not feel capable to perform the actions that are needed in this situation. Patients who do feel self-efficacious will not be as easily defeated when confronted with

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a poor glycemic control and will therefore be at a lower risk for developing diabetes-related distress. This argumentation is in accordance with a preponderance of evidence showing that (illusions of ) control and a belief in personal efficacy help people to cope effectively with negative events and setbacks (Alloy & Clements, 1992; Henselmans, Sanderman, Baas, Smink, & Ranchor, 2009; for reviews see Bandura, 1982; Taylor & Armor, 1996; Taylor & Brown, 1988). Furthermore, the moderating role of glycemic control is in line with previous studies that showed that negative support behavior in combination with more serious disease symptoms or vulnerable personality trait-like characteristics were most detrimental for patients’ well-being (Danoff-Burg, Revenson, Trudeau, & Paget, 2004; Hagedoorn et al., 2000; Schokker, Links, Luttik, & Hagedoorn, 2010).

The moderating effect of gender that was found is consistent with the hypothesis that diabetes-specific self-efficacy is more strongly associated with distress in female than in male patients, because of the higher salience of diabetes to women compared to men (e.g., Helgeson & Novak, 2007; Mosnier-Pudar et al., 2009). Our findings are not necessarily inconsistent with previous studies showing that women are more strongly influenced by partner behavior and characteristics than are men (e.g., Acitelli & Antonucci, 1994; Hagedoorn et al., 2000; Hagedoorn et al., 2001; Horwitz et al., 1998; Mcrae & Brody, 1989). It might be that if these studies had included self-efficacy as a mediator, that these studies also would have demonstrated that gender specifically moderated the path between self-efficacy and distress, and not the path between overprotection and diabetes-specific self-efficacy.

A strength of the current study is that we used both patient and partner ratings of overprotection. The incorporation of both patient and partner ratings provides the opportunity to reach a fuller understanding of patients’ level of distress (see also Berg & Upchurch, 2007). The fact that the results based on the partner ratings were significant indicates that it is not common method variance that triggered the associations.

There were also some limitations in the current study that one has to bear in mind when drawing conclusions. First, differences between responders and non-responders could have biased our results. Non-responders had higher HbA1c, but lower diabetes-related distress levels compared to responders. Although differences in mean scores on study variables do not necessarily mean that associations between variables are different for different groups, we should be cautious to generalize the results to the general population of diabetes patients. Second, this was a cross-sectional study, therefore we cannot make causal inferences. For example, it is assumed in this study that overprotection leads to more distress in patients, but the reverse order, that high levels of distress evoke more overprotective behaviors by the partner is also possible. Further, in our study, we conceptualized glycemic control as a moderator, but it can also be viewed as an outcome or predictor of self-efficacy.

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The mediation effect that was found especially in patients with poor glycemic control and female patients indicates that reducing partners’ overprotective behavior may increase patients’ diabetes-specific self-efficacy. Nevertheless, there are several alternative methods to increase patients’ self-efficacy. For example, interventions that focused on patient education, patient empowerment, self-monitoring of physical activity, cognitive behavioral group training or social learning variables have demonstrated beneficial effects on patients’ self-efficacy (Glasgow, Toobert, Hampson, & Strycker, 2002; Gleeson-Kreig, 2006; Howorka et al., 2000; Piette, Weinberger, & Mcphee, 2000; Van der Ven et al., 2005). The question is, however, to what extent these interventions will be successful for those patients who are being overprotected by their partner. For example, a previous study of persons with diabetes demonstrated that patients with more overprotective partners benefited less from a diabetes education program aimed to increase feelings of control than patients with less overprotective partners (Hagedoorn et al., 2006). This implies that beneficial effects of interventions might be counteracted by an overprotective partner. It has been found that psychosocial interventions that included partners had a beneficial effect on adults with a chronic illness (Kuijer, Buunk, De Jong, Ybema, & Sanderman, 2004; for a review see Martire, Lustig, Schulz, Miller, & Helgeson, 2004). It is very well possible that interventions specifically focusing on reducing overprotection by the partner, or the perception of this by the patient, may be especially effective in improving patient outcomes (see also Hagedoorn et al., 2006). Future research is necessary to establish causal chains by intervening on overprotection and examining whether this indeed leads to higher levels of self-efficacy and lower levels of distress. Although we have to be cautious in interpreting the results, it seems that partner overprotection may have negative consequences on patients’ level of diabetes-specific diabetes-related distress through diabetes-specific self-efficacy, especially in patients who are worse off in terms of poor glycemic control and in female patients. The results highlight the importance of paying attention to both how and when associations between negative partner behavior and patient distress may occur.

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Footnotes

¹Thepurposeoftheshortquestionnairewastoidentifypatientswithhighlevelsofdiabetes-relateddistress.Thesepatientswereofferedareferraltoadiabeteseducationprogram.Beforepatients were offered this referral they (and their partners) received a larger questionnairecontaining the measurement instruments relevant for this study. Also patients with lowerlevelsofdiabetes-relateddistressontheshortquestionnairereceivedthelargerquestionnaireshortlyafterwards.

²Thetotalresponseratecanonlybeestimated,because183patientsofthe690patientsdidnotfilloutthefirstscreeningquestionnaire,anditisunknownhowmanyofthese183patientshadapartner.Assumingthatabout80%hadapartner,thisnumberwouldbe146.Thenthetotal number of patients with a partner would be 559 (146 + 413). The total response ratewouldthenbe40%(223outof559).

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UK Prospective Diabetes Study Group (2000). Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BritishMedicalJournal,321, 405-412.

Van Der Ven, N. C., Weinger, K., Yi, J., Pouwer, F., Ader, H., Van Der Ploeg, H. M. et al. (2003). The confidence in diabetes self-care scale: psychometric properties of a new measure of diabetes-specific self-efficacy in Dutch and US patients with type 1 diabetes. DiabetesCare,26, 713-718.

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Van der Ven, N. C. W., Hogenelst, M. H. E., Tromp-Wever, A. M. E., Twisk, J. W. R., Van Der Ploeg, H. M., Heine, R. J. et al. (2005). Short-term effects of cognitive behavioural group training (CBGT) in adult Type 1 diabetes patients in prolonged poor glycaemic control. A randomized controlled trial. DiabeticMedicine,22, 1619-1623.

Vinokur, A. D., Price, R. H., & Caplan, R. D. (1996). Hard times and hurtful partners: How financial strain affects depression and relationship satisfaction of unemployed persons and their spouses. JournalofPersonalityandSocialPsychology,71, 166-179.

Wearden, A. J., Tarrier, N., & Davies, R. (2000). Partners’ expressed emotion and the control and management of type 1 diabetes in adults. JournalofPsychosomaticResearch,49, 125-130.

Welch, G. W., Jacobson, A. M., & Polonsky, W. H. (1997). The Problem Areas in Diabetes Scale. An evaluation of its clinical utility. DiabetesCare,20, 760-766.

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Chapter 4

Support behavior and relationship satisfaction in couples

dealing with diabetes: main and moderating eff ects

Marike C. Schokker, Ilse Stuive, Jelte Bouma, Joost C. Keers, Thera P. Links, Bruce H.R. Wolff enbuttel, Robbert Sanderman, Mariët Hagedoorn

Journal of Family Psychology, accepted for publication

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4.1 Introduction

A chronic illness such as diabetes can have a considerable impact on patients since they are confronted with major life-style changes and the prospect of possible future complications. Furthermore, the disease may also profoundly impact those who are close to the patient, most notably the partner, and their intimate relationship (for overviews see Berg & Upchurch, 2007; Burman & Margolin, 1992). The vulnerability-stress-adaptation model of marriage (Karney & Bradbury, 1995) proposes that stressors encountered by couples may affect adaptive processes such as the behaviors couple members exchange, which in turn may affect relationship satisfaction. Nowadays, it is increasingly recognized that a chronic illness can be perceived as a stressor shared by patients and partners, urging for the adoption of relationship-focused coping strategies, that is, ways to cope with the illness and each others’ emotional responses (for overviews see Berg & Upchurch, 2007; Bodenmann, 1997).

An increasing number of studies have demonstrated the important role the family and the partner may have on diabetes patients’ psychosocial outcomes (e.g., Chesla et al., 2003; Fisher et al., 2004; Hagedoorn et al., 2006; Trief et al., 2006; Wearden, Tarrier, & Davies, 2000). There are also a number of studies that have examined psychosocial outcomes in partners of diabetes patients (e.g., Fisher, Chesla, Skaff, Mullan, & Kanter, 2002; Gonder-Frederick, Cox, Kovatchev, Julian, & Clarke, 1997; Stahl, Berger, Schaechinger, & Cox, 1998; Wearden, Ward, Barrowclough, & Tarrier, 2006) but these studies have not examined whether partners’ psychosocial outcomes could be predicted by patients’ behaviors towards the partner. Therefore, the aim of the current study is to examine how patients’ and partners’ support behaviors may help both patients and their partners to maintain their relationship satisfaction in the face of diabetes.

Coyne and Smith (1991) have distinguished two types of relationship-focused coping, which we will refer to as ways of providing support, namely active engagement and protective buffering. Active engagement consists of support behaviors, including openly discussing the illness with the other, asking how the other is feeling, and engaging in joint problem solving strategies. Protective buffering refers to support behaviors such as hiding one’s concerns for the other, pretending everything is fine and avoiding conflict. Both active engagement and protective buffering refer to support behaviors that are aimed at dealing with a chronic illness, in this case diabetes.

It has been suggested that when couple members communicate openly with each other and express their personal feelings, they perceive each other as responsive and understanding, which in turn enhances couples’ intimacy and relationship satisfaction (Laurenceau, Barrett, & Pietromonaco, 1998; Reis & Shaver, 1988). This implies that a support behavior such as active engagement, which includes open communication,

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will be positively associated with relationship satisfaction. Indeed, previous studies of patients with cancer or heart disease have demonstrated positive associations between partners’ active engagement and patients’ relationship satisfaction (Buunk, Berkhuysen, Sanderman, & Nieuwland, 1996; Hagedoorn et al., 2000; Hinnen, Hagedoorn, Ranchor, & Sanderman, 2008; Kuijer et al., 2000). Although the use of protective buffering may be well-intended, this strategy is expected to have a negative impact on relationship satisfaction, since it includes withholding feelings and concerns instead of sharing them. Consistent with this notion, some studies have shown that partners’ protective buffering was negatively associated with cancer patients’ relationship satisfaction (Hagedoorn et al., 2000; Hinnen et al., 2008; Langer, Rudd, & Syrjala, 2007; Langer, Brown, & Syrjala, 2009), although other studies have not found significant associations (Buunk et al., 1996; Kuijer et al., 2000). This study examines protective buffering displayed by the partner as perceived by the recipient, which may especially be detrimental. That is, when you are aware that your partner is trying to hide his or her worries from you, this may have more negative effects on your relationship satisfaction than when your partner is effectively hiding his or her worries so you do not recognize the buffering of your partner.

Active engagement and protective buffering are support behaviors that can be enacted by both patients and partners; however, most studies have focused on partners’ support behaviors and patients’ psychological outcomes such as relationship satisfaction. One of the few studies that focused on patients’ perception of their own active engagement and protective buffering and partners’ relationship satisfaction reported nonsignificant correlations (Coyne & Smith, 1994). Another study, however, did find partners’ relationship satisfaction to be negatively associated with both patients’ perception of their own buffering as well as partners’ perception of received buffering (Langer et al., 2009).

In the present study, we will examine associations between support behaviors (i.e., active engagement and protective buffering enacted by the significant other as perceived by the recipient) and relationship satisfaction in both patients and partners, using a dyadic data analytic approach that takes into account the nonindependence between patients and partners (Kenny, Kashy, & Cook, 2006).

Relationship Satisfaction as a Function of the Interactive Effect of Active Engagement andProtectiveBufferingReceiving active engagement does not preclude that one also receives protective buffering. For example, it is possible that at a certain moment, a person shows active engagement by asking how the other is feeling, while at another moment, the same person shows protective buffering by avoiding talking about the illness and pretending everything is fine. It is also possible that a person adopts active engagement with regard to some aspects of the illness, and protective buffering with regard to other aspects.

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This notion is supported by previous studies showing that although receiving higher levels of active engagement was associated with receiving lower levels of protective buffering, correlations were only weak to moderate (e.g., De Ridder, Schreurs, & Kuijer, 2005; Hagedoorn et al., 2000; Hinnen et al., 2008; Schokker, Links, Luttik, & Hagedoorn, 2010). Thus, active engagement and protective buffering can co-occur, and it would be interesting to examine not only the main effects but also the interactive effects of these support behaviors on relationship satisfaction.

The current study addresses this unexplored question. We argue that receiving inadequate support such as protective buffering may be less harmful, if at the same time, individuals receive high levels of active engagement. Active engagement, which is considered to be a more adequate support behavior, may counteract the negative effect of buffering. Particularly in the absence of active engagement, protective buffering may be more strongly associated with relatively low levels of relationship satisfaction.

The underlying rationale is that different attributions about stability (e.g., my partner hardly ever acts like this vs. my partner always acts like this) and intentions (e.g., my partner tries to protect me from further burden or my partner is indifferent to what happens to me) may be made for protective buffering, depending on the levels of received active engagement. These different attributions in turn can be expected to be differently associated with relationship satisfaction (for overviews see Bradbury & Fincham, 1990; Bradbury, Fincham, & Beach, 2000). For example, it has been found that perceiving negative partner behavior as stable and intentional was negatively associated with relationship satisfaction (Fincham & Bradbury, 1992).

Less adequate support behavior such as protective buffering may be perceived as less negatively intended when at the same time, one receives high levels of active engagement. The other person’s buffering can be perceived as an attempt not to add more distress. Therefore, received buffering may not be associated with less relationship satisfaction, since it is not viewed as negative behavior under these circumstances. In contrast, received buffering may be perceived as negatively intended when at the same time, one receives low levels of active engagement. In this situation, one may believe that the other person pretends everything is fine because he or she does not care at all. Received buffering is then viewed as negative behavior and is likely to have negative effects on relationship satisfaction.

The hypothesis that detrimental effects of inadequate support on psychological outcomes may be buffered by adequate support from friends, family or the partner has been previously investigated and supported, but mainly in patients (Kleiboer et al., 2007; Manne et al., 2003; Revenson, Schiaffino, Majerovitz, & Gibofsky, 1991; Sherman, 2003) and not in partners (with the exception of Kleiboer et al., 2007). It was found that negative support from friends and family was positively associated with distress in patients with

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rheumatoid arthritis, but only in those patients who also reported receiving little positive support from friends and family (Revenson et al., 1991). Distress levels were highest in patients who reported both high levels of negative support and low levels of positive support. Only few studies focused specifically on partner support, showing inconsistent results. A study of cancer patients did not find support for an interactive effect of positive and negative partner support on distress (Manne, Taylor, Dougherty, & Kemeny, 1997). A study of patients with multiple sclerosis and their partners did find the expected interactive effects, in that the positive association between received negative behavior and negative mood was attenuated when levels of received positive behavior were high (Kleiboer et al., 2007). Moreover, these latter results applied to both patients and their partners.

In our study we will focus on both patients and partners when examining the joint effects of positive and negative support. More specifically, we will examine the interactive effect of received active engagement and protective buffering and we are interested in relationship satisfaction as the outcome measure.

The hypotheses can be summarized as follows:1. Received active engagement will be positively associated with relationship

satisfaction in both patients and partners2. Received protective buffering will be negatively associated with relationship

satisfaction in both patients and partners3. Received protective buffering will be negatively associated with relationship

satisfaction in both patients and partners, especially if levels of received active engagement are relatively low

4.2 Method

ParticipantsandProcedurePatients with type 1 and 2 diabetes requiring insulin from two outpatient clinics were invited to participate in a longitudinal study, as well as their partners (for a more detailed description of the procedure see Schokker et al., 2010). The aim of this study was to investigate adaptation to diabetes in both patients and partners. Overall, 223 of the 413 couples that were sent the baseline (T1) questionnaire completed it. Two of these couples were excluded afterwards because they had indicated receiving help filling out the questionnaire, and 16 were excluded because patients in these couples were referred to a diabetes education program. This means the final sample at T1 consisted of 205 couples. After couples had filled out the T1 questionnaire they were sent three more questionnaires (T2 – T4); approximately three to four months separated the administration of the first three questionnaires (M = 0.32 years, SD = 0.10 for T1 – T2; M = 0.31 years, SD = 0.02 for

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T2 – T3), and five to six months separated the third and fourth questionnaire (M = 0.40 years, SD = 0.03). The T2 questionnaire was filled out by 154 couples, and the T3 and T4 questionnaire was filled out by respectively 142 and 129 couples.

MeasuresSupportbehaviors.We used a questionnaire developed by Buunk et al. (1996) to assess

two ways to support the ill or healthy partner, namely active engagement and protective buffering. Both patients and partners were asked to rate to what extent the other adopted each specific strategy in reaction to the illness. All items were measured on a five-point scale ranging from 1 (never) to 5 (very often). Previous studies have reported adequate internal consistencies and test-retest reliabilities have been found for the subscales (Buunk et al., 1996; Hagedoorn et al., 2000; Hinnen, Hagedoorn, Sanderman, & Ranchor, 2007; Kuijer et al., 2000). Five items were averaged into the active engagement scale. Examples are “My partner asks me how I feel” and “When something bothers me, my partner tries to discuss the problem” (Cronbach’s α = 0.87 and 0.85, for patients and partners respectively). Six items were averaged into the protective buffering scale. Examples are “My partner tries to hide his or her worries about me” and “My partner tries to act as if nothing is the matter” (Cronbach’sα = 0.70 and0.80, for patients and partners respectively).

Relationshipsatisfaction.We used the Dutch version of the marital quality subscale of the Maudsley Marital Questionnaire (MMQ) to assess relationship satisfaction in patients and their partners (Arrindell, Boelens, & Lambert, 1983). The subscale consists of 10 items measured on a nine-point scale. The items were averaged into one index, with higher scores indicating higher relationship satisfaction. Item examples are “Are you satisfied about the leisure time you spend with your partner” and “How often do you think about getting a divorce?” (Cronbach’s α = 0.91 for both the patient and partner version).

StatisticalTestingoftheHypothesesusingDyadicDataAnalyticApproachesScores of patients and their partners cannot be regarded as independent from each other (Kenny et al., 2006). First, individuals within a couple are more likely to be similar on a wide range of variables (such as age and socioeconomic status) than randomly paired couples owing to processes of assortative mating. Second, individuals within a couple are nonindependent because characteristics of one individual may affect characteristics of the other. Standard statistical methods such as analysis of variance and multiple regressions are less suitable for analyzing nonindependent data, because these methods are based on the independence assumption. A drawback of ignoring nonindependence is that it may result in bias in significance testing (Kenny et al., 2006). We have used data analytic approaches detailed by Kenny et al. (2006) that take into account the nonindependence between two individuals, the so-called dyads.

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We used MLwiN software (Rasbash, Charlton, Browne, & Healy, 2009) to perform the analyses. With this software, we can adequately analyze our data, which consists of two levels, namely dyads at level 2, and individuals (i.e., patients and partners) nested within a dyad at level 1. All variables were measured at level 1 (predictor and outcome measures). Level 2 (dyads) was specified to take into account the dependence between patient and partner. Following the model presented by Laurenceau and Bolger (2005), patient and partner effects were estimated in the same model. Dummy variables were used to nest patient and partner data within each couple.

All data were grand-mean centered prior to applying the files to MlwiN and two dummy coded variables were created, one for patients (1=patient, 0=partner) and one for partners (1=partner, 0=patient) (Laurenceau & Bolger, 2005). Following the two-intercept approach suggested by Kenny et al. (2006), each level 1 predictor variable was multiplied by the dummy coded variables to create two separate predictor variables; one for patients and one for partners. At level 1, the general intercept was removed and replaced with the dummy coded variables ‘patients’ and ‘partners’ (Kenny et al., 2006).

The model can be specified in the following function: Yij = β0j(Patient) + β0j(Partner) + β2(Patient Active Engagement)j + β2(Partner Active Engagement)j + β3(Patient Protective Buffering)j + β3(Partner Protective Buffering)j + β4(Patient Active Engagement × Protective Buffering)j + β4(Partner Active Engagement × Protective Buffering)j + eij, where Yij is the relationship satisfaction of a member of couple j. The dummy variables were used to estimate the within-person effects for patients and partners in the same model taking into account the nonindependence of patient and partner data.

The constructs of interest in this study were assessed four times over a period of time in both patients and partners. Patients in our study had been diagnosed with diabetes a long time ago, and patients and partners were in long-term relationships. Thus, it is plausible that patients and partners had developed rather stable routines of dealing with the disease and each other. As a consequence, the constructs in our study were not expected to change over time. To test this assumption a data file was created in which the four time points were nested within persons. Multilevel analyses were then performed, separately for patients and partners, where Time (assessment points 1, 2, 3 and 4) was used as a predictor for active engagement, protective buffering, or relationship satisfaction. A nonsignificant slope for this fixed effect of Time indicates that on average there is no change over time on the three variables studied, but this does not exclude the presence of variation in individual slopes. Therefore, not only the fixed effect of Time but also the variation of its slope was tested. If both tests show no significant effects, longitudinal analyses are not appropriate as there is no variance to explain on the Time level. However, our longitudinal dataset is suitable for testing the robustness of the hypotheses, by analyzing the assessment points separately. Although these findings cannot be considered

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independent replications, these repeated analyses will show whether or not the findings are sensitive to (selective) drop-out.

4.3 Results

DescriptivesAt T1, 112 were couples with a male patient and 93 were couples with a female patient. Most couples were married (89.8%). Being married was not required because in the Netherlands, many couples form long-lasting relationships without being married. The mean length of the relationship was 28.7 years (SD = 12.9). Patients and partners had a mean age of 54.0 (SD = 11.2) and 54.1 years (SD = 11.7), respectively. Of the patients, 61.8% had received lower education, 23.1% had received intermediate education, and 15.1% had received higher education. For the partners, this was respectively 57.1%, 25.8%, and 17.2%. On a list of chronic conditions (Ormel et al., 1998), the majority of the patients reported at least one comorbidity (73.7%) and the majority of the partners (62.9%) also indicated a chronic condition. In both patients and partners, high blood pressure was the most frequently mentioned health condition (31.2% patients, 19% partners). Arthrosis was also frequently mentioned (18.0% patients, 17.1% partners). Mean diabetes duration was 15.7 years (SD = 11.8) and mean HbA1c level around T1 was 7.2% (SD = 0.99; normal values 4-6%, target value < 7%), which can be viewed as acceptable. We checked whether the scores on these descriptives differed between couples who completed all four assessments and those who dropped out. It appeared that significantly higher HbA1c levels were observed in patients from couples who had dropped out than in patients from couples who did not drop out (M = 7.5%, SD = 0.94 vs. M = 7.1%, SD = 0.99, t(200) = -2.77, p < .01). We checked whether there were differences between patients’ and partners’ perceptions of received active engagement and protective buffering, and of relationship satisfaction. Patients reported higher levels of received active engagement than did partners (M = 3.79, SD = 0.74 vs. M = 3.51, SD = 0.78), t(200) = 4.62, p < .001. Patients reported lower levels of received protective buffering than did partners (M = 2.20, SD = 0.65 vs. M = 2.41, SD = 0.75) t(200) = -3.69, p < .001. Patients’ and partners’ perception of relationship satisfaction did not differ (M = 6.81, SD = 1.08 vs. M = 6.70, SD = 1.14), t(200) = 1.36, p = .17. We compared our scores to those of a reference group of Dutch adults (Schroevers, Ranchor, & Sanderman, 2006). This study reported sum scores and coded relationship satisfaction in a way that higher scores indicate lower relationship satisfaction (first assessment: M = 13.17, SD = 12.37). After recoding relationship satisfaction in our sample (patients: M = 11.90, SD = 10.84, partners: M = 12.97, SD = 11.04) to match those of the reference group, it appeared that our scores were comparable (patients: t(301) = 0.92, p> .15 partners: t(302) = 0.15, p > .25).

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Table 4.1 presents the T1 correlations for the variables under study (a comparable pattern of associations was found at the other assessment points). As can be seen, relationship satisfaction of both patients and partners was positively associated with received active engagement, and negatively associated with received protective buffering. To examine whether patient and partner scores were indeed nonindependent we calculated the correlation between T1 patient and partner relationship satisfaction, which was .50, p < .001 (see Table 4.1). However, if there are more variables that can be used to distinguish couple members, it is advised to control for these other distinguishing variables (Kenny et al., 2006). Besides patient and partner status, couple members in our study can be distinguished by gender. The correlations between the patient and partner variables remained significant, after controlling for gender (.55, .38, and .31 for relationship satisfaction, active engagement, and protective buffering respectively, all p’s < .001). This nonindependence indicates the necessity of using the dyadic data analysis approach.

Table 4.1 T1CorrelationsfortheVariablesunderStudy

Variable 2 3 4 5 6 7 8 9 10 11

1. Relationship duration .17* .03 .19* -.11 -.09 .22** .02 -.15* .26** .02

2. Diabetes duration .17* -.02 .10 .06 .09 .09 .10 -.05 .11

3. Comorbidities patient .31** -.07 -.02 .21** -.10 .02 .13 -.03

4. Comorbidities partner -.12 .00 .05 -.06 -.09 .15* -.24**

5. HbA1c .01 .02 -.02 -.10 -.07 -.12

6. AE patient -.41** .63** .36** -.21** .32**

7. PB patient -.35** -.21** .29** -.15*

8. MMQ patient .31** -.20** .50**

9. AE partner -.29** .60**

10. PB partner -.41**

11. MMQ partner

Note. N varies as a result of missing values. *p < .05; **p < .01. AE = active engagement as perceived by the recipient; PB = protective buffering as perceived by the recipient; MMQ = relationship satisfaction.

PreliminaryAnalysesTo test the assumption that the variables in our study are stable over time, the slopes and variances for the predictor Time were studied for the variables active engagement, protective buffering and relationship satisfaction. In all the analyses, the regression weights and variances for Time were nonsignificant for both patients and partners (relationship satisfaction analysis: B = -0.03, p = .48, Var(B) = 0.02, p = 0.75) for patients, and B = -0.06, p

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= .13, Var(B) = 0.04, p = 0.64) for partners; active engagement analysis: B = -0.02, p = .49, Var(B) = 0.01, p = 0.72 for patients, and B = -0.01, p = .73, Var(B) = 0.01, p = 0.76 for partners; protective buffering analysis: B = -0.02, p = .53, Var(B) < 0.01, p = 0.94 for patients, and B = -0.04, p = .15, Var(B) = 0.03, p = 0.30 for partners). Thus, the assumption that the variables under study are stable appears to be supported. This precludes the necessity to perform longitudinal analyses. Instead, we performed separate analyses for all four assessments to test whether the model estimates are similar after drop-out.

TestingtheHypothesesTable 4.2 shows that the results are more or less the same at each assessment. As can be seen, received active engagement was positively associated with relationship satisfaction, in both patients and partners. Received protective buffering was negatively associated with relationship satisfaction, in both patients and partners. Our first two hypotheses were thus supported. Table 4.2 further shows that the interactive effects of received active engagement and protective buffering were significant for both patients and partners. We calculated and plotted the regression slopes for patients and partners at two levels of received active engagement: high (+ 1 SD) and low (- 1 SD). The interaction figures indicated the same pattern at each assessment point, therefore, we only present the figures for T1. Figure 4.1 depicts the results for patients. Received protective buffering was negatively associated with relationship satisfaction, but only in patients who reported relatively low levels of received active engagement (B = -0.43, p = .001). The association was not significant in patients who reported relatively high levels of received active engagement (B = -0.01, p = .97). Similar findings were observed for partners (see Figure 4.2). The association between received protective buffering and relationship satisfaction was significant in partners who reported low levels of received active engagement (B = -0.56, p < .001), but not in partners who reported receiving relatively high levels of active engagement (B = 0.04, p = .73). These significant interactive effects are in line with our third hypothesis. We checked whether the interactive effects were qualified by gender, since this was a second distinguishing variable in our study, besides patient and partner status. These results were not significant.

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Table 4.2 Hierarchical Linear Model: Associations between Support Behavior and RelationshipSatisfaction

PatientRelationshipSatisfaction PartnerRelationshipSatisfaction

Analysis Effect B SE d t p B SE d t p

T1 AE 0.82 0.08 1.37 9.80 <.001 0.75 0.08 1.39 9.92 <.001

PB -0.22 0.10 0.32 2.31 .02 -0.26 0.08 0.44 3.12 <.01

AE × PB 0.29 0.11 0.37 2.65 <.01 0.38 0.08 0.70 5.04 <.001

T2 AE 0.75 0.10 1.23 7.64 <.001 0.81 0.11 1.22 7.58 <.001PB -0.54 0.11 0.77 4.79 <.001 -0.27 0.11 0.38 2.36 .02

AE × PB 0.44 0.12 0.59 3.67 <.001 0.40 0.14 0.46 2.87 <.01

T3 AE 0.75 0.11 1.19 7.08 <.001 0.88 0.11 1.30 7.73 <.001PB -0.26 0.11 0.41 2.46 .01 -0.30 0.11 0.45 2.65 <.01

AE × PB 0.34 0.13 0.43 2.65 .01 0.54 0.15 0.62 3.72 <.001

T4 AE 0.90 0.11 1.45 8.24 <.01 0.85 0.14 1.09 6.17 <.001PB -0.41 0.12 0.61 3.46 <.001 -0.43 0.14 0.57 3.21 .001

AE × PB 0.37 0.14 0.45 2.58 <.01 0.63 0.18 0.62 3.55 <.001

Note. AE = active engagement as perceived by the recipient; PB = protective buffering as perceived by the recipient; Effect size d for each twas computed with the following equation: d = 2t/√N,in which N is the number of dyad. We examined correlations between demographic variables and the dependent variables to see whether we needed to include covariates. These correlations differed somewhat across the different assessments (T1 – T4), however, if these variables (gender, comorbidities, HbA1c) were included in the analyses, the interactive effects remained significant.

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Figure 4.1 The interactiveeffectofreceivedprotectivebufferingandactiveengagementonpatient’srelationshipsatisfaction

Figure 4.2 Theinteractiveeffectofreceivedprotectivebufferingandactiveengagementonpartner’srelationshipsatisfaction

Figure 4.1 The interactive effect of received protective buffering and active engagement on patient’s relationship

satisfaction

5

6

7

8

-1 SD +1 SD

Protective buffering

Pa

tie

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ship

sa

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Low active

engagement, B = -

0.43, p = .001

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0.01, p = .97

Figure 4.2 The interactive effect of received protective buffering and active engagement on partner’s relationship

satisfaction

5

6

7

8

-1 SD +1 SD

Protective buffering

Pa

rtn

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s re

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0.56, p < .001

High active

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0.04, p = .73

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4.4 Discussion

To the best of our knowledge, this is the first study that examined associations between support behaviors and relationship satisfaction within couples dealing with diabetes. As expected, relationship satisfaction was positively associated with received active engagement and negatively with received protective buffering, in both patients and partners. The fact that significant associations were found for partners as well, is in line with the reasoning that a chronic illness such as diabetes has an impact on both the patient and the partner and that they both may benefit from or be harmed by certain support behaviors.

Furthermore, our third hypothesis that active engagement would moderate the negative association between protective buffering and relationship satisfaction was supported. We observed this association, but only when levels of received active engagement were relatively low. This interactive effect was found in both patients and partners. The results are consistent with previous studies indicating that positive support may suppress the detrimental effects of receiving negative support (e.g., Kleiboer et al., 2007; Manne et al., 2003; Revenson et al., 1991). As far as we know, our study is the first to test the interactive effect of positive and negative support in both persons with diabetes and their partners. Our study specifically focused on couples dealing with a chronic illness and our measures of support behavior were embedded in the context of a chronic illness. The findings revealed that the hypothesized support processes are relevant in the context of diabetes. This does not mean however that such processes play a role exclusively in couples who are dealing with illness. In fact our rationale was based on theory of marital attributions examined in marital interaction research (Bradbury & Fincham, 1990). Furthermore, our results are consistent with a study among newly-wed couples showing that an individual experienced lower levels of relationship satisfaction when the individual’s spouse displayed both high levels of negative communication skills, and low levels of positive affect during a session in which couples discussed marital difficulties (Johnson et al., 2005). Thus, the processes described in our study may be found not only in couples dealing with a chronic illness, but also in couples confronted with other daily stressors and in couples in long-term relationships.

As previously mentioned, a possible explanation for the interactive effects is that more benign attributions are made for protective buffering when at the same time, levels of active engagement are high instead of low. These more benign attributions in turn may mitigate the negative impact on relationship satisfaction (for overviews see Bradbury & Fincham, 1990; Bradbury et al., 2000). Related to this, it is likely that protective buffering is more easily forgiven when levels of active engagement are high as people are then more inclined to make more benign attributions to this behavior. This line of reasoning is

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supported by studies that found that positive attributions were associated with forgiving one’s partner for certain behaviors (Fincham, Paleari, & Regalia, 2002). The ability to forgive one’s partner in turn, has been shown to be positively associated with relationship satisfaction (Paleari, Regalia, & Fincham, 2005; for an overview see Fincham, Hall, & Beach, 2006). Finally, our findings and argumentation are supported by a study of couples dealing with colorectal cancer (Hagedoorn et al., submitted) that showed that inadequate support (i.e., low levels of active engagement and high levels of protective buffering) was associated with less relationship satisfaction especially when the significant other had not been very supportive in the past. Future research could employ observational studies in which naturally-occurring behavior of couples during a discussion about the illness is coded as supportive or unsupportive. Afterwards individuals could be asked to interpret each other’s behavior. Such research may provide an answer to the question whether one indeed interprets the protective buffering (e.g., changing the topic, minimizing a concern) as less negatively intended when levels of active engagement are high.

The focus on both patients and partners is a clear strength of our study. Moreover, we used a dyadic approach in analyzing the results, thereby taking into account the nonindependence between patients and partners. Another strength is our rather large sample size. Finally, we had a longitudinal data set. This dataset was not suitable for predicting change over time, as indicated by the non-significant effects of time on relationship satisfaction and active engagement and protective buffering. This was not very surprising, as the majority of the patients in our study had been diagnosed with diabetes many years ago, and because patients and their partners often reported a long relationship duration. As a consequence, we cannot draw any conclusions about causality. Nonetheless, our longitudinal dataset did allow us to see whether the model estimates were similar after drop out. Results showed that the findings were robust despite the fact that patients with worse glycemic control were more inclined to drop out. Future longitudinal studies focusing on couples in which the patient has been recently diagnosed with diabetes are more likely to have predictive value. These couples still need to adjust to the illness and may not yet have established routines in their coping behaviors. So in this context a longitudinal study may shed more light on causality. In our study, it was assumed that active engagement leads to more relationship satisfaction, whereas protective buffering leads to a decreased relationship satisfaction. However, it is also conceivable that low levels of relationship satisfaction urge one to adopt low levels of active engagement and high levels of protective buffering.

A limitation that should be considered when interpreting the results concerns the response rate. Only couples of whom both the patient and the partner were willing to participate were included. It is possible that our sample was biased towards high-functioning couples. Another limitation is that we used patients’ and partners’ self-reports

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of received support and relationship satisfaction, which may lead to common method variance. This has also been referred to as the ‘glop’ problem which entails that correlations are higher when variables are measured with self-report data from a single reporter (e.g., Gottman, 1998).

Our findings may have clinical implications, for example, for the way interventions for couples dealing with a chronic illness should be constructed. Instead of teaching patients and partners to adopt high levels of active engagement and low levels of protective buffering, interventions may be most efficient and effective when they particularly focus on teaching positive strategies. After all, our results may imply that protective buffering is less influential when levels of active engagement are relatively high. Previous intervention studies for couples dealing with cancer have shown that relationship satisfaction may improve in both patients and their partners (Baucom et al., 2009; Kuijer, Buunk, De Jong, Ybema, & Sanderman, 2004). The intervention programs in these studies focused on the types of supportive behaviors patients and partners need from each other. Although more research is needed, our results indicate that it is necessary to examine positive and negative support simultaneously if one wants to obtain a full understanding of support and dyadic coping processes.

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Chapter 5

The impact of social comparison information on motivation in patients with diabetes as a function of regulatory focus

and self-effi cacy

Marike C. Schokker, Joost C. Keers, Jelte Bouma, Thera P. Links, Robbert Sanderman, Bruce H.R. Wolff enbuttel, Mariët Hagedoorn

Health Psychology, 2010, 29, 438-445

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5.1 Introduction

Patients with diabetes need to adhere to a range of self-care behaviors in order to reduce the risk of developing serious disease complications (Diabetes Control and Complications Trial Research Group, 1993; Lawson, Gerstein, Tsui, & Zinman, 1999; UK Prospective Diabetes Study Group, 1998; 2000). Therefore, it is important that patients are motivated to carry out self-care behaviors, despite the potentially burdensome nature of these behaviors. Motivated patients are more likely to show desirable behavior changes. For example, individuals with low levels of motivation are less likely to engage in exercise than individuals with high levels of motivation (e.g., Courneya & Friedenreich, 1999). In the current study, we will use insights from the social comparison theory to explain individuals’ motivation to manage their diabetes.

Social comparison consists of upward and downward comparisons. Upward comparison refers to comparing oneself with others who are doing better, whereas downward comparison refers to comparing oneself with others who are doing worse. Traditionally, it has been proposed that upward comparisons inspire and motivate individuals (Taylor & Lobel, 1989), for example, in the context of dealing with a chronic illness. Upward comparison targets may provide individuals with useful information for self-improvement (e.g., Blanton, Buunk, Gibbons, & Kuyper, 1999; Buunk, Peiro, & Griffioen, 2007; Lockwood & Kunda, 1997). Research in the context of academic performance and health, however, suggests that not only upward, but also downward comparison information may motivate and inspire individuals. This research has identified regulatory focus as an individual characteristic that may determine whether upward and downward social comparison information is inspiring (Lockwood, Chasteen, & Wong, 2005a; Lockwood, Marshall, & Sadler, 2005b; Lockwood, Sadler, Fyman, & Tuck, 2004; Lockwood, Jordan, & Kunda, 2002; for an overview, see Lockwood & Pinkus, 2008).

Regulatory focus (Higgins, 1997; 1998; Lockwood et al., 2002) consists of two self-regulatory systems: self-regulation with a promotion focus and self-regulation with a prevention focus. A promotion focus refers to the extent to which one is focused on obtaining positive outcomes, whereas a prevention focus refers to the extent to which one is focused on avoiding negative outcomes. Studies have found that promotion-focused individuals are inspired by upward social comparison information, while prevention-focused individuals are inspired by downward social comparison information (e.g., Lockwood et al., 2005b; Lockwood et al., 2002; for an overview, see Lockwood & Pinkus, 2008). These studies suggest that individuals will be most motivated to study or improve their health when the social comparisons match their regulatory focus. Specifically, upward comparison targets may activate an ideal possible future self (Markus & Nurius, 1986) and therefore function as a positive role model. Promotion-focused individuals

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who are oriented to obtain positive outcomes will be motivated by such positive role models, especially if these highlight not only positive outcomes, but also strategies to obtain these outcomes. On the contrary, a downward comparison target may activate a feared possible future self (Markus & Nurius, 1986) and therefore function as a negative role model. Prevention-focused individuals who are oriented towards avoiding negative outcomes will be motivated by such negative role models, especially if these highlight not only negative outcomes, but also strategies to avoid these outcomes.

A first aim of the current study was to examine whether the findings highlighted above can be generalized to a clinical sample of patients with diabetes. In most of the studies by Lockwood and colleagues, student samples were used to test the hypotheses; only one study included elderly individuals (Lockwood et al., 2005a). Furthermore, this older sample consisted of community-dwelling individuals who rated their own health positively. To the best of our knowledge, the question of whether the impact of social comparison information depends on regulatory focus has never been investigated in a clinical sample. This is surprising for two reasons. Firstly, while a lack of motivation to engage in certain (health) behaviors may have serious consequences for healthy individuals, the risk is even higher for individuals with a chronic illness such as diabetes. Compared to healthy individuals, people with diabetes have an increased risk of developing cardiovascular diseases and other comorbidities; therefore, a lack of motivation may have more detrimental effects on these individuals. Secondly, it has been documented that during interviews, patients spontaneously compared themselves to other patients (Gorawara-Bhat, Huan, & Chin, 2008; Wood, Taylor, & Lichtman, 1985) which implies that social comparisons are central to patients’ experiences. Due to these observations, we deemed it important to examine the impact of social comparison information and regulatory focus in a clinical sample of individuals with diabetes. In line with the findings of Lockwood and colleagues, we formulated the following hypotheses:

1. A promotion focus will be positively associated with motivation to manage the diabetes, but only in patients presented with a positive role model.

2. A prevention focus will be positively associated with motivation to manage the diabetes, but only in patients presented with a negative role model.

A second aim was to extend these hypotheses by investigating patients’ self-efficacy as a second moderator. We postulate that our hypotheses will apply more strongly to patients who have high levels of self-efficacy. Previous research has identified perceived control as an important variable that may determine the impact of role models (for overviews, see Aspinwall, 1997; Wood & Van der Zee, 1997). It was found that individuals who were exposed to positive role models showed less persistence on a task when they felt they

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had little control over their ability to obtain positive outcomes (Testa & Major, 1990). Similarly, it can be expected that individuals exposed to negative role models will show less persistence and motivation when they have little control over their ability to avert negative outcomes. We propose that promotion-focused patients will be even more motivated by positive role models if they experience high levels of self-efficacy related to managing their diabetes. Patients who feel capable of managing their disease will feel that they are able to obtain a similar future represented by the positive role model. Likewise, prevention-focused patients will be even more motivated by negative role models if they experience high levels of self-efficacy related to managing their diabetes. These patients will feel capable of avoiding a similar future represented by the negative role model (for a similar line of reasoning, see Lockwood, 2002). This moderating effect of self-efficacy has not yet been investigated in the context of role models and regulatory focus. We formulated two additional hypotheses:

3. A promotion focus will be positively associated with motivation to manage the diabetes, but only in patients presented with a positive role model. This will apply more strongly to patients who feel self-efficacious about managing their diabetes.

4. A prevention focus will be positively associated with motivation to manage the diabetes, but only in patients presented with a negative role model. This will apply more strongly to patients who feel self-efficacious about managing their diabetes.

5.2 Method

ParticipantsandProcedureData consist of the third assessment from a longitudinal study investigating adaptation to diabetes (Schokker et al., 2010). Approximately 690 eligible patients with type 1 and 2 diabetes requiring insulin were approached to complete a short screening questionnaire. Patients with high levels of distress were offered a referral to a diabetes self-management intervention which has been described earlier (Keers et al., 2004). Inclusion criteria were: age 18-70 years, no severe comorbidity such as a clinical depression or a psychiatric disorder, not pregnant, and Dutch speaking. After patients had filled out the short questionnaire they were sent four larger questionnaires (T1 – T4); approximately three to four months separated the administration of the first three questionnaires, and approximately five to six months separated the third and fourth questionnaire. Eight of the 507 patients that filled out the initial short questionnaire did not receive follow-up questionnaires due to logistic problems. Of the 499 patients who did receive the T1 questionnaire, we excluded 33 patients, because they accepted a referral to participate in the intervention

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program. Of the 466 patients who received the T1 questionnaire and were included in the present study, 234 patients (50.2%) filled out the T3 questionnaire, which assessed several additional constructs (e.g., general distress and partner support).

ManipulationofsocialcomparisonWe made use of an experimental manipulation, namely, one version of the T3 questionnaire contained a description of a positive role model (upward social comparison information), whereas the other version contained a description of a negative role model (downward social comparison information). Patients were randomly assigned to one of these versions. They were instructed to carefully read a fragment from an interview with a person with diabetes and to answer questions about the interview afterwards. The interview was printed realistically as a ripped-out section from a newspaper article. Both role model conditions did not state gender and age to make sure all participants could identify with the role models. The positive role model interview read as follows:

“…my doctor. When I was told I had diabetes, I was very frightened. Controlling my diabetes did not go very well in the initial period, but I’m doing much better nowadays. I have succeeded in adjusting my life to the diabetes. Every day I cycle to my work, and I exercise twice a week, which has a beneficial effect on my blood sugar levels. My diet is also properly adjusted to the diabetes. I eat much healthier and I have lowered my fat consumption. I eat many more vegetables and fruit now. In the beginning I found it difficult to take into account that I had to inject insulin, but now I am used to it. I think I handle my diabetes very well, especially because I know a lot about diabetes and because I engage in healthy behaviors. My blood sugar levels have been quite stable and low for years now, and I still don’t suffer from any complications. According to my doctor, I should be able to maintain good health if I keep up the good work”.

The negative role model interview was as closely mirrored as possible to the positive role model interview, and read as follows:

“… my doctor. When I was told I had diabetes, I was very frightened. Controlling my diabetes did not go very well in the initial period, and it is still not going well. I have not succeeded in adjusting my life to the diabetes. I intended to cycle to my work every day, and I should exercise twice a week, because this would have a beneficial effect on my blood sugar levels. However, I have not put these intentions into practice yet. My diet is also not properly adjusted to the diabetes. I love snack food and I am not so crazy about vegetables and fruit. I still find it difficult to take into account that I need to inject insulin; I can’t get used to it. I don’t think I handle my diabetes well, because of my insufficient knowledge of diabetes, and because I engage in unhealthy behaviors. My blood sugar levels have been too high for years now, and I am beginning to develop some complications. According to my doctor, there is a very high chance that my health will deteriorate if I do not change my life style”.

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MeasuresRegulatory focus. The T3 questionnaire included a measure of regulatory focus

(Lockwood et al., 2002), Dutch translation by Van Stekelenburg and Klandermans (2003), which consists of two subscales measuring promotion and prevention focus. Both subscales contain nine items and each item response ranges from 0 (totallydisagree) to 7 (totallyagree). A few adjustments were made, as some of the items from the original questionnaire focused on an academic domain and were therefore not relevant to our sample. More specifically, for the items in which the original questionnaire referred to academic goals and ambitions, we removed the word ‘academic’. Examples of promotion items include “I frequently imagine how I will achieve my hopes and aspirations”, and “In general, I am focused on achieving positive outcomes in my life” (M = 3.83, SD = 1.32, Cronbach’s α = .87). Examples of prevention items include “I am anxious that I will fall short of my responsibilities and obligations”, and “I often imagine myself experiencing bad things that I fear might happen to me” (M = 3.20, SD = 1.28, Cronbach’s α = .82). The promotion and prevention focus subscale were positively correlated (r = .54, p < .001), indicating that a stronger promotion focus is associated with a stronger prevention focus (for a similar finding, see Schokker, Links, Luttik, & Hagedoorn, 2010).

Self-efficacyinDiabetesManagement.We used a subscale of the Diabetes Empowerment Scale (Anderson, Funnell, Fitzgerald, & Marrero, 2000), which measures self-efficacy in diabetes management. The subscale we used specifically refers to the patients’ self-efficacy in managing their diabetes by setting and achieving diabetes-specific goals. The subscale consists of 10 items and each item response ranges from 1 (totallyagree) to 5 (totallydisagree). We recoded the items in such a way that a higher score indicates a higher level of self-efficacy. Examples of items include “In general, I believe I can reach my diabetes goals once I make up my mind”, and “In general, I believe that I am able to decide which way of overcoming barriers to my diabetes goals works best for me” (M = 3.72, SD = 0.59, Cronbach’s α = .94).

MotivationtoWorkonDiabetesRegulation. After patients had read the bogus interview, they were asked, “To what extent does the interview motivate you to work on your diabetes regulation?” Patients rated this item on a five-point scale ranging from 1 (theinterviewdoesnotmotivatemeatall) to 5 (Iamverymuchmotivatedbytheinterview), M = 2.44, SD = 1.16.

Manipulation Check. Finally, patients completed a manipulation check item in which they rated their own diabetes management relative to that of the target. Ratings were made on a five-point scale ranging from 1 (myowndiabetesmanagementis much worse) to 5 (my own diabetes management is much better), M = 3.59, SD = 1.18.

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5.3 Results

DescriptivesThe questionnaire containing the upward comparison information was filled out by 113 patients and the questionnaire containing the downward comparison information was completed by 121 patients. Overall, 50.9% were men. The average age of the participants was 54.5 years (SD = 11.60) and the average diabetes duration was 16.7 years (SD = 11.60). Mean HbA1c value, which reflects patients’ glycemic control, was 7.2 (SD = 0.92; normal values 4-6%, target value < 7%). The majority of the patients were married (71.8%), 6.4% were living together with a partner, 2.1% reported having a partner, but not living together, 19.6% did not have a partner. There were no significant differences between patients in the upward and the downward condition on any of the descriptive variables.

We also examined whether promotion and prevention focus, in addition to self-efficacy in diabetes management were related to any of the descriptive variables. There was a weak positive association between promotion focus and self-efficacy (r = .14, p = .04), and a weak negative association between promotion focus and age (r = -.14, p = .03). Additionally, there was a weak negative association between self-efficacy and HbA1c level (r = -.13, p = .05). No other significant associations were found.

ManipulationCheckTo see whether our manipulation was successful, we examined the mean ratings on the manipulation check item. A score of 3 on the manipulation check item indicates that patients perceive their own diabetes management as equally good. The results showed that mean ratings in both conditions were significantly different from 3, t(112) = -2.76, p < .01 and t(120) = 18.93, p < .001, for the positive and negative role model condition respectively. These results indicate that patients felt inferior to the positive role model and superior to the negative role model.

In addition, we examined whether the positive role model was perceived as doing better, and the negative role model as doing worse by patients with different levels of promotion and prevention focus, as well as different levels of self-efficacy in diabetes management. We performed a hierarchical regression analysis using direction of social comparison (the positive role model coded as +1 and the negative role model as -1), promotion and prevention focus, and self-efficacy as predictors of the manipulation check. To avoid multicollinearity between the predictors and the interaction terms, we centered the scores on the continuous predictors (Aiken & West, 1991). In subsequent steps, we entered into the regression equation the main effects (step 1), all two-way interactions (step 2), and the three-way interactions between direction of social comparison, regulatory focus (either promotion or prevention focus), and self-efficacy (step 3). In general, patients perceived

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their own diabetes management as relatively worse in comparison to the positive role model than in comparison to the negative role model (M = 2.76, SD = 0.92 vs. M = 4.36, SD = 0.80, respectively, B = -.81, p < .001). There were also main effects of promotion focus (B = .11, p = .05) and prevention focus (B = -.13, p = .02). These main effects indicated that with stronger levels of promotion focus, one’s own diabetes management was perceived as better, whereas with stronger levels of prevention focus, one’s own diabetes management was perceived as worse. The main effect of self-efficacy was not significant (B = .20, p = .06). All two-way interactions and the three-way interactions were not significant (all p’s > .06). This suggests that regardless of the level of promotion and prevention focus and self-efficacy in diabetes management, patients perceived the positive role model as doing better and the negative role model as doing worse in comparison to themselves.

TestingtheHypothesesHierarchical regression analyses were performed to examine the effects of direction of social comparison (positive versus negative role model); regulatory focus (promotion and prevention focus); self-efficacy in diabetes management; and the interactions on motivation to work on diabetes regulation.¹

The results (see Table 5.1) revealed a main effect of prevention focus, namely that a stronger prevention focus was associated with more motivation. No main effects of direction of social comparison, promotion focus, or self-efficacy were found. As expected, there was a significant two-way interaction between promotion focus and direction of social comparison. To probe this two-way interaction we calculated and plotted the regression slopes for patients confronted with the positive and the negative role model, at the average level of prevention focus (see Figure 5.1). A promotion focus was associated with more motivation in patients confronted with the positive role model (B = 0.27, p = .01), but not in patients confronted with the negative role model (B= -0.04, p = .63). The three-way interaction among direction of social comparison, promotion focus, and self-efficacy was not significant.

The hypothesized interaction between prevention focus and direction of social comparison was also significant. A prevention focus was associated with more motivation in patients confronted with the negative role model (B = 0.38, p < .001), but not in patients confronted with the positive role model (B = -0.12, p = .22). This two-way interaction was qualified by a three-way interaction. We further explored this three-way interaction by investigating the two-way interactive effect of direction of social comparison and prevention focus on the motivation of patients with relatively low self-efficacy and of patients with relatively high self-efficacy, separately (+1 SD for high and -1 SD for low self-efficacy). Among patients with relatively low self-efficacy, the two-way interaction between direction of social comparison and prevention focus was not significant (B = -.10, p = .29).

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Table 5.1 ResultsoftheRegressionofMotivationtoworkondiabetesregulationonDirectionofSocialComparison,RegulatoryFocus,andSelf-efficacyinDiabetesManagement

Motivation

B SE ∆ R² ∆ F p

Step 1 0.06 3.77 < .01

Direction of social comparisona -0.04 0.08 .63

Promotion Focus (Prom) 0.10 0.07 .18

Prevention focus (Prev) 0.14 0.07 .05

Self-efficacy in diabetes management (SE) 0.01 0.14 .97

Step 2 0.06 2.64 .02

Prev × Prom < 0.01 0.04 .95

Prev × SE < 0.01 0.11 .96

Prom × SE -0.11 0.10 .28

Direction × SE -0.16 0.14 .24

Direction × Prom 0.14 0.07 .04

Direction × Prev -0.24 0.07 < .01

Step 3 0.03 3.38 .04

Direction × Prom × SE -0.02 0.10 .87

Direction × Prev × SE -0.24 0.11 .02

Note. aDirection of social comparison: -1 = negative role model, +1 = positive role model

Furthermore, the slopes for the negative and positive role model were both nonsignificant (B = .24, p = .09, and B = .03, p = .82, respectively, see Figure 5.2A). As predicted, among patients with relatively high self-efficacy, there was a significant two-way interaction between direction of social comparison and prevention focus (B = -.38, p < .001). In these patients with relatively high self-efficacy, prevention focus was positively associated with motivation when patients had read the negative role model (B = .52, p < .001), but not when patients had read the positive role model (B = -.24, p = .06; see Figure 5.2B).

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Figure 5.1 Theinteractiveeffectofdirectionofsocialcomparisonandpromotionfocusonmotivation,atanaveragelevelofpreventionfocus

Figure 5.2A Theinteractiveeffectofdirectionofsocialcomparisonandpreventionfocusonmotivation,ofpatientswitharelativelylowself-efficacyindiabetesmanagement,atanaveragelevelofpromotionfocus

Figure 5.1 The interactive effect of direction of social comparison and promotion focus on motivation, at an average

level of prevention focus

1

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Figure 5.2A The interactive effect of direction of social comparison and prevention focus on motivation, of patients with

a relatively low self-efficacy in diabetes management, at an average level of promotion focus

Low self-efficacy

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Figure 5.2B Theinteractiveeffectofdirectionofsocialcomparisonandpreventionfocusonmotivation,ofpatientswitharelativelyhighself-efficacyindiabetesmanagement,atanaveragelevelofpromotionfocus

5.4 Discussion

In this clinical sample of patients with diabetes, motivation to manage the disease is an important outcome. Patients who are motivated are more likely to carry out self-care activities which may eventually prevent or postpone disease complications. Our first two hypotheses are consistent with these findings. Patients with a relatively strong promotion focus were motivated by the positive role model, which highlighted strategies to obtain positive outcomes. Conversely, patients with a relatively strong prevention focus were motivated by the negative role model, which highlighted strategies to avoid negative outcomes.

Our third hypothesis was not confirmed; the interaction between promotion focus and direction of social comparison was not qualified by self-efficacy. A possible explanation may be that overall, patients with a strong promotion focus had high levels of self-efficacy, and that a ceiling effect occurred. This explanation does not hold however, since self-efficacy and promotion focus were not significantly correlated (r = .08, p = .21; self-efficacy and prevention focus were only weakly correlated: r = .13, p = .04). The fact that self-efficacy did not moderate the findings with regard to promotion focus appears to suggest that having a strong promotion focus is sufficient in order to boost patients’ motivation when they encounter a positive role model.

Figure 5.2B The interactive effect of direction of social comparison and prevention focus on motivation, of patients with

a relatively high self-efficacy in diabetes management, at an average level of promotion focus

High self-efficacy

1

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The results did confirm our fourth hypothesis. Prevention focus was positively associated with motivation in patients who were confronted with the negative role model, but only when these patients had relatively high levels of self-efficacy in managing diabetes by setting and achieving diabetes-specific goals.

Our results contribute to the existing literature in two important ways. Firstly, our results indicate that previous findings regarding regulatory focus and social comparison in healthy populations (e.g., Lockwood et al., 2002), can be generalized to a clinical sample. Managing a chronic illness such as diabetes may help patients maintain good health and prevent or postpone complications. Thus, it is highly important that patients are motivated to engage in healthy behaviors and avoid unhealthy ones. Our findings demonstrate that motivation may be enhanced when patients are confronted with role models that are congruent with patients’ regulatory focus.

Secondly, our findings contribute to the existing literature on regulatory focus and social comparison by showing that self-efficacy qualified the interaction between prevention focus and direction of social comparison. In a study that demonstrated that students were most motivated by a negative role model when they felt vulnerable to the fate of this role model, it was speculated that perceived control (cf. self-efficacy) may also be important in determining whether negative role models boost one’s motivation (Lockwood, 2002). As far as we know, our study is the first to test the hypothesis that regulatory focus will moderate the effects of role models only when feelings of self-efficacy are high. Our findings are in line with the reasoning that only patients with a strong prevention focus who believe they can avoid the feared self represented by the negative role model will be motivated by this model. Patients who have a strong prevention focus but who do not believe they can avoid this feared self, will not be motivated by the negative role model.

The results of the manipulation check item showed that the positive role model was indeed viewed as upward, and the negative role model as downward. This is not a self-evident result because individuals tend to perceive positive role models as similar to themselves, rather than superior (Collins, 2000). However, additional analyses showed that the manipulation of the negative role model was stronger than the manipulation of the positive role model. Ratings on the manipulation check item were farther from the neutral midpoint of the scale (the point at which patients perceived their own diabetes management as equally good) for the negative role model than for the positive role model (t(232) = 10.09, p < .001). This may indicate that the interaction effect of promotion focus and the positive role model would be even more pronounced with a stronger manipulation of the positive role model.

The description of the role models contained information on behaviors the targets engaged in, as well as outcomes they experienced. Perhaps the same results would be

Figure 5.2B The interactive effect of direction of social comparison and prevention focus on motivation, of patients with

a relatively high self-efficacy in diabetes management, at an average level of promotion focus

High self-efficacy

1

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model, B = 0.52, p <

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obtained if the role models contained information on only the outcomes. However, a previous study among teachers (Van Yperen, Brenninkmeijer, & Buunk, 2006) demonstrated that role models may increase intention to work harder, but only when the success of the positive role model is explained in terms of high effort, and the failure of the negative role model in terms of low effort. It is therefore also plausible that in our study, information on behaviors that explain how to achieve or avoid the outcomes experienced by the role models was necessary in order to boost motivation.

The interview fragments in the current study were as closely mirrored as possible to enhance the consistency between the two conditions, which can be considered as a strength. However, as a consequence the negative role model largely referred to the absence of health-promoting behaviors rather than the presence of unhealthy behaviors (except for the snacking behavior). Prevention messages (i.e., a negative role model description) may thus be framed in different ways and future studies could more closely examine whether these different ways of framing have different effects on motivation.

Future studies should also focus on how role models can be adopted in clinical practice. For example, during intervention programs, patients could be provided with examples of role models that fit their regulatory orientations. Additionally, examples of role models could be provided during regular consultations with physicians. It would be interesting to examine whether the recurrent implementation of role models in practice could lead to enhanced motivation and actual behavior change in the long run. Related to this, future research could take into account different types of behavioral change. For individuals who are considering additive (promotion-focused) behaviors, such as eating more healthy foods, positive role models may be more stimulating. On the other hand, when individuals are considering subtractive (prevention-focused) behaviors, such as quitting smoking, negative role models may be more stimulating (Lockwood et al., 2004). Likewise, patients with diabetes may contemplate additive or subtractive behaviors (e.g. eating vegetables versus avoiding eating fatty snacks), which may determine whether positive or negative role models are most effective.

A limitation of this study is that motivation was measured with only one item. However, we chose a more global measurement of motivation, since the salience of specific self-management behaviors that need to be carried out can differ from patient to patient. Furthermore, it should be noted that several studies showed that single-item measures can function well in comparison to multiple-item scales (e.g., Robins, Hendin, & Trzesniewski, 2001; Wanous, Reichers, & Hudy, 1997). A second limitation is that we do not know whether patients did indeed engage in social comparison. It could be argued that the effects of the positive and negative role model were not as much due to the direction of social comparison but rather to the positive or negative tone of the story (for a similar line of reasoning, see Buunk & Ybema, 2003). Similar results may be obtained when

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patients are confronted with merely positive or negative information, without referring to social comparison targets. Indeed, several studies of individuals without chronic illnesses have demonstrated similar effects of merely positive and negative information on intentions and behaviors. Individuals who were presented with information (positive or negative) that fit their regulatory focus (promotion or prevention focus) reported a stronger engagement in behaviors and showed enhanced performance (e.g., Latimer et al., 2008; Mann, Sherman, & Updegraff, 2004; Plessner, Unkelbach, Memmert, Baltes, & Kolb, 2009). It is common practice to present information to patients that purely focuses on positive and negative consequences of (not) adhering to self-management activities (e.g. ‘exercising regularly may improve glycemic control’). It would be interesting to see whether information referring to another patient with diabetes (e.g. ‘Because John is exercising regularly, his glycemic control has improved’) would have a greater impact on motivation and behavior than information that does not refer to another patient. It could be argued that social comparison information may prove to be especially effective when trying to motivate patients. A previous study of patients with diabetes demonstrated that the majority did make social comparisons and that these patients were more likely to perform self-management behaviors than patients who did not engage in social comparison (Gorawara-Bhat et al., 2008). Nevertheless, individuals may differ in their tendency to make social comparisons (e.g., Gibbons & Buunk, 1999), and it is plausible that the provision of purely positive or negative information is more beneficial for individuals with a low social comparison orientation.

Although several factors need to be taken into account for future research, the current results suggest that individual differences in regulatory focus influence the motivating impact of positive and negative role models in patients with diabetes. Furthermore, prevention-focused patients may be most motivated when confronted with negative role models, but only when their level of self-efficacy is relatively high. Overall, it appears that when trying to motivate patients, a ‘one size fits all’ approach is not sufficient.

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Footnote

¹We also ran an analysis in which we included the three-way interaction of promotionfocus, prevention focus, and goal self-efficacy, the three-way interaction of promotionfocus, prevention focus, and direction of social comparison, and the four-way interactionofpromotionfocus,preventionfocus,goalself-efficacy,anddirectionofsocialcomparison.Becausebothinteractionswerenotsignificantandbecausetheywerenotofmaininterestinourstudy,weexcludedtheseinteractionsinourfinalanalysis.

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Van Yperen, N. W., Brenninkmeijer, V., & Buunk, A. R. (2006). People’s responses to upward and downward social comparisons: The role of the individual’s effort-performance expectancy. BritishJournalofSocialPsychology,45, 519-533.

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General discussion

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This thesis examined whether psychosocial outcomes in patients with diabetes (and their partners) could be explained by the interplay of intrapersonal factors (e.g., regulatory focus and self-efficacy) and interpersonal factors (i.e., partner support and social comparison information). Four overall conclusions can be drawn from the results of this thesis. A first conclusion is that patients who receive inadequate support from their partner perceive more (diabetes-related) distress, especially when patients possess individual characteristics that make them vulnerable to experience distress, such as a weak promotion focus or a poor glycemic control. A second conclusion is that the negative effects of protective buffering on relationship satisfaction may be compensated for by high levels of active engagement, in both patients and partners. A third conclusion is that we did not find consistent gender differences with regard to associations between support behavior and psychosocial outcomes. Finally, a fourth conclusion is that social comparison information is most likely to boost patients’ motivation when this information is congruent with patients’ regulatory focus. Patients who are oriented towards obtaining positive outcomes are most motivated by information on a fellow patient with a very good diabetes self-management. In contrast, patients who are oriented towards avoiding negative outcomes are most motivated by information on a fellow patient doing poorly in terms of diabetes management. For each conclusion, the most important findings will be discussed, theoretical and clinical implications will be addressed, and directions for future research will be described.

CONCLUSION 1 “Patients with vulnerable individual characteristics and patients with poor disease outcomes may be at risk of experiencing high levels of distress, especially when their partner provides inadequate support”

MaineffectsofregulatoryfocusandpartnersupportWe proposed regulatory focus as an individual characteristic that might be important for psychosocial outcomes in patients with a chronic illness such as diabetes. Regulatory focus is a characteristic that determines to what extent individuals are occupied with obtaining positive outcomes (promotion focus) and to what extent they are occupied with avoiding negative outcomes (prevention focus). An orientation towards avoiding negative outcomes implies that one is constantly on the lookout whether these negative outcomes are present (Wegner, 1994) and a strong prevention focus may therefore evoke high levels of distress. A promotion focus on the other hand, was expected to be associated with less distress. To the best of our knowledge, our study is the first that examined associations between regulatory focus and distress in a sample of patients with a chronic illness requiring self-management behaviors. In chapter 2, we showed that promotion focus was not related to distress, and that there was a weak positive association between prevention

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Discussion

focus and distress¹. These findings for promotion focus are not entirely in line with a study of students that demonstrated a moderate negative association between promotion focus and distress (Miller & Markman, 2007), but they are in line with a study of breast cancer patients that also reported a nonsignificant association (Frieswijk & Hagedoorn, 2009). Although no causal conclusions can be drawn, the results suggest that overall, a promotion focus does not alleviate levels of distress, but having a strong prevention focus might be detrimental in terms of higher levels of (diabetes-related) distress.

We further proposed support behavior of the intimate partner as an important factor with regard to patients’ psychosocial outcomes. Only a limited number of previous studies have examined associations between partner support and diabetes patients’ psychosocial outcomes. Partners are involved in many of the self-care behaviors the patient needs to perform (Fisher et al., 2000). Furthermore, the support that is provided by the patient’s partner may not be easily compensated for by other sources of support (Coyne & DeLongis, 1986). It is thus important to study support by the partner and its association with patient’s psychological outcomes. In chapter 2, we found a weak negative association between active engagement and general distress, indicating that patients experience less distress when they feel that their partner is actively involving them in discussions, and showing interest in their well-being than when their partner shows less of these behaviors. Protective buffering and overprotection both showed weak positive associations with general distress. These findings suggest that as partners deny their worries and pretend everything is fine, patients experience higher levels of distress. Also, patients may experience higher levels of distress when their partner is overprotecting them, for example by telling the patient what to eat and when to monitor blood sugar levels. Furthermore, in chapter 3 we specifically focused on overprotection, and although partner’s overprotective behavior as perceived by the patient was not significantly associated with diabetes-related distress, we did find that partner’s overprotective behavior, as perceived by the partner, was weakly positively associated with diabetes-related distress. Thus, if a partner overprotects the patient and worries whether the patient is able to engage in the necessary behaviors, this may increase patient’s own worries and emotional problems concerning the diabetes. The previously mentioned associations are in line with previous studies that used the Active Engagement, Protective Buffering, and Overprotection (ABO) questionnaire and support the notion that active engagement can be considered as an adequate support style, whereas protective buffering and overprotection seem to be less adequate support styles².

In conclusion, we did find several main effects of regulatory focus (an intrapersonal factor) and partner support (an interpersonal factor) on patients’ levels of distress, but these main effects were not very strong. This raises the question whether the combination of these intra- and interpersonal factors is of greater importance than the separate effects

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when explaining patients’ level of distress. In the next section I will discuss the combined impact of intra- and interpersonal factors, that is, the moderating effects we found.

ModeratingeffectsIn chapter 2 we investigated whether the association between regulatory focus (i.e. promotion and prevention focus) and distress was moderated by partner support. It was shown that although overall, having a weak promotion focus does not seem to be problematic, it may increase patient’s distress if at the same time the patient receives either low levels of positive support (active engagement) or high levels of negative support (protective buffering and overprotection). Put differently, the findings indicate that patients with a relatively weak promotion focus may benefit more from adequate partner support behaviors that stimulate promotion-oriented strategies and cognitions in patients. At the same time, these patients may be harmed more by inadequate partner support behaviors that induce a prevention-oriented mind set in patients.

In chapter 3, we examined whether the indirect link between overprotection by the partner and diabetes-related distress through diabetes-specific self-efficacy was moderated by patients’ level of glycemic control. It was found that this link was strongest when levels of glycemic control were high instead of low. Patients with relatively poor glycemic control and whose partners were relatively overprotective reported the highest levels of diabetes-related distress.

As briefly mentioned in the previous section, in chapter 3 we found that overprotection was associated with diabetes-related distress through diabetes-specific self-efficacy, that is, the confidence patients have in their ability to manage the disease. Thus, we not only identified a moderator effect of glycemic control in this association, but also a mediator effect of self-efficacy (see also Figure 3.1 in chapter 3). Although overprotection by the partner and the possible impact on patients’ psychosocial outcomes has been studied previously, no study has yet examined through which underlying mechanism overprotection may exert its’ negative effects. It has been previously shown that partners may overprotect the patient because they have little confidence in the patient’s ability to adequately deal with the disease (Kuijer et al., 2000). Our findings suggest that overprotective behavior, although perhaps well-intended, indeed confers the message to the patient that the partner has little confidence in the patient’s abilities. As a consequence, patients themselves experience less confidence in their own ability to manage the disease, which in turn leads to more diabetes-related distress.

In sum, the results of chapter 2 and 3 show that inadequate partner support and vulnerability in terms of individual or disease characteristics are only weakly (to moderately) associated with distress. Importantly, the findings are in line with the notion that especially the combination of these factors is harmful.

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TheoreticalandclinicalimplicationsThe findings in chapter 2 and 3 are in line with the stress-buffering and stress-exacerbation hypotheses. The stress-buffering hypothesis (Cohen & Wills, 1985) entails that high levels of positive support buffer the negative impact of a stressor on psychosocial outcomes. The stress-exacerbation hypothesis (Rook, 1998) entails that high levels of negative support exacerbate the negative impact of a stressor on psychosocial outcomes. Several studies found support for these hypotheses. For example, the association between job stress and distress was only present when levels of positive social support were low, thus demonstrating a buffering effect of support (Larocco, House, & French, 1980). Support for a stress-exacerbation effect was found in a study that indicated that negative support may exacerbate the negative effect of life events on psychological outcomes (Ingersoll-Dayton, Morgan, & Antonucci, 1997). Another study showed that the association between caregiving demand and distress was stronger when negative support was high (Rauktis, Koeske, & Tereshko, 1995). A final example is a study of breast cancer patients (Koopman, Hermanson, Diamond, Angell, & Spiegel, 1998) that demonstrated a positive association between life stress and mood disturbance, but only when levels of negative support were high. Furthermore, life stress was positively associated with mood disturbance, only when patients reported having just a few persons in their social network instead of many. This study thus demonstrated both a buffering and an exacerbating effect of support or network ties.

Studies demonstrating a stress-buffering or stress-exacerbating effect often focus on how support may buffer or exacerbate the effects of stressors, such as life events, or job stress. A number of studies suggested that the buffering effect of positive support and the exacerbating effect of negative support may also occur with regard to vulnerable traits (Danoff-Burg, Revenson, Trudeau, & Paget, 2004; Devine, Parker, Fouladi, & Cohen, 2003; Jacobsen et al., 2002) and our findings are in line with these studies. The findings in chapter 2 indicated that the negative association between promotion focus and distress is buffered by high levels of engagement, and exacerbated by high levels of protective buffering or overprotection. Furthermore, in chapter 3, results were indicative of an exacerbating effect of overprotection. We demonstrated that the indirect link between overprotection and diabetes-related distress was stronger in patients with poor glycemic control. Patients with poor glycemic control and highly overprotective partners appeared to be worst off in terms of high levels of distress.

The findings of chapter 2 and 3 may have important clinical implications. When trying to lower patients’ (diabetes-related) distress, interventions could either target intrapersonal factors (i.e., regulatory focus and self-efficacy) or interpersonal factors (i.e., partner support). To date, most intervention studies that were successful in improving psychosocial outcomes included some form of cognitive behavioral therapy (for reviews see Ismail, Winkley, & Rabe-Hesketh, 2004; Steed, Cooke, & Newman, 2003).The

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successfulness of these interventions might be enhanced if they would also target the cognitions attached to a strong prevention focus or a weak promotion focus. For example, patients may be challenged to reformulate some of their diabetes management goals. Patients who are focused on avoiding diabetes complications may adopt a somewhat different focus, by trying to keep their blood glucose levels within a normal range, and trying to maintain in good health.

At first sight it may seem difficult to influence regulatory focus, since it is considered to be a stable trait-like characteristic. However, studies have shown that a promotion or prevention focus can also be situationally induced, for example through a word-categorization task that includes words related either to promotion or to prevention (Lockwood, Jordan, & Kunda, 2002) or by letting individuals describe personal experiences that are related to promotion or prevention focus (Higgins, Roney, Crowe, & Hymes, 1994). It is not yet known whether these inducements of either prevention or promotion focus will have a long-lasting impact. On the other hand, the assumption that regulatory focus is a stable trait-like individual characteristic has also not yet been investigated.

In our study, patients’ and partners’ regulatory focus was assessed four times over a period of more than a year. Based on the correlations and mean scores that we found for promotion and prevention focus over time³, we conclude that regulatory focus does show a moderate stability over time. However, the correlations are not extremely high, which indicates that one’s regulatory focus may also be somewhat malleable.

Correlations of diabetes-specific self-efficacy over time appeared to be somewhat higher (.76 - .82) than those of regulatory focus. Even though self-efficacy appears to be rather stable, perhaps even more stable than regulatory focus, interventions targeting patient education, patient empowerment, self-monitoring of physical activity, cognitive behavioral group training or social learning variables did appear to be successful at enhancing patients’ self-efficacy (Glasgow, Toobert, Hampson, & Strycker, 2002; Gleeson-Kreig, 2006; Howorka et al., 2000; Piette, Weinberger, & Mcphee, 2000; Van Der Ven et al., 2005). However, it can be questioned whether those interventions are equally successful when patients have overprotective partners. Results of a previous study indicated that the beneficial effects of interventions may be decreased in this case, by showing that a diabetes education program enhanced feelings of control but to a lesser extent in patients with relatively overprotective partners (Hagedoorn et al., 2006). It may therefore be necessary to target supportive behavior of the partner as well. Interventions that not only included patients, but partners as well were found to have a positive impact on patients’ psychosocial outcomes (Kuijer, Buunk, De Jong, Ybema, & Sanderman, 2004; Martire, Schulz, Keefe, Rudy, & Starz, 2007). Based on our findings, it may be expected that interventions targeting patients’ characteristics and coping behavior, as well as partners’ support behavior will be most effective.

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FutureresearchBefore the findings are implemented in interventions, more research is necessary to establish causal chains between the variables. That is, experimental and intervention studies are needed to confirm whether altering patients’ regulatory focus and self-efficacy, or partners’ supportive behaviors will lead to lower or higher levels of distress.

An underlying assumption in chapter 2 was that a support behavior such as active engagement will encourage patients to adopt a stronger promotion-oriented mind set while support behaviors such as protective buffering and overprotection will urge patients to adopt a stronger prevention-oriented mind set and/or a weaker promotion-oriented mind set. Although our findings supported our line of reasoning, this assumption was not actually tested. Future studies might look into the question whether these support behaviors can alter patients’ regulatory focus in the long run.

Another recommendation for future research is assessing possible mediators in the moderate association between prevention focus and distress. It can be expected that patients with a strong prevention focus have a tendency to avoid certain behaviors and situations, and as such adopt avoidant coping strategies. For example, a patient with a strong prevention focus may be occupied with avoiding hypoglycemia (too low blood sugar levels) and he or she may avoid engaging in very intensive exercise, as this may cause a serious decrease in blood sugar levels. These avoidant coping strategies in turn can be expected to be related to more distress and lower well-being (e.g., Felton, Revenson, & Hinrichsen, 1984; Jacobsen et al., 2002; Macrodimitris & Endler, 2001; Manne, Ostroff, Winkel, Grana, & Fox, 2005).

Finally, it is not known whether the findings of chapter 2 and 3 are only applicable to patients dealing with a chronic illness requiring self-management behaviors, or whether the findings would also apply to patients with other chronic diseases, or to individuals dealing with other stressful situations.

CONCLUSION 2 “The negative effects of protective buffering on relationship satisfaction may be compensated for by high levels of active engagement, in both patients and partners”

MaineffectsA chronic illness such as diabetes may not only affect patients, but partners of patients as well. Consequently, it can be expected that not only the partner will try to support the patient, but also that the patient will support the partner, for example by trying to discuss the partner’s feelings about the disease. Both patients and partners may show active engagement towards the other, that is, openly discussing feelings that the disease may

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evoke and thinking of constructive problem-solving methods to deal with the disease. Similarly, both patients and partners may show protective buffering, that is, hiding their feelings concerning the disease and pretending everything is fine. Since both patients and partners may be affected by the disease, and both patients and partners may be supported by the other, we examined how received active engagement and protective buffering are associated with relationship satisfaction in patients as well as in partners. For both, it was shown that relationship satisfaction was positively associated with received active engagement, and negatively associated with received protective buffering. These results are in line with the reasoning that couples who adopt active engagement as a support style perceive each other as responsive and understanding, which in turn promotes relationship satisfaction (Laurenceau, Barrett, & Pietromonaco, 1998; Reis & Shaver, 1988). Couples who adopt protective buffering experience less relationship satisfaction since this support style consists of withholding concerns and feelings instead of sharing them.

ModeratingeffectsIn chapter 4, we showed that patients and their partners experienced the lowest levels of relationship satisfaction when they reported to receive both low levels of positive support (i.e., active engagement) as well as high levels of negative support (i.e., protective buffering). An underlying explanation for these results is that the receipt of both support behaviors are not interpreted independent of each other, but rather, that these behaviors are interpreted in light of each other. In general, protective buffering may be interpreted as negative support behavior, and may consequently have a negative impact on relationship satisfaction. Thus, individuals (either the patient or the partner) who feel that the other is hiding his or her worries, and is pretending everything is fine, may experience their relationship as less satisfactory. However, if individuals also feel that at other times, their partner shows active engagement by being responsive, and by engaging in open discussions about the illness, they may interpret the protective buffering as less negative behavior. For example, they may think that the other is just having a bad day and that is why he or she is reacting indifferently. These more benign (or less negative) interpretations are in turn expected to mitigate the negative association between protective buffering and relationship satisfaction (for reviews see Bradbury & Fincham, 1990; Bradbury, Fincham, & Beach, 2000). Previous studies have further shown that more positive attributions to and interpretations of certain behaviors were associated with forgiving the other for engaging in these behaviors (Fincham, Paleari, & Regalia, 2002). If you think for example, that the other engages in protective buffering because he or she had a bad day, you are probably more likely to forgive him or her for this behavior than when you think the other adopts this support style because he or she truly is indifferent about you. In turn, forgiving one’s partner has been found to be positively associated with relationship satisfaction (Fincham, 2000; Paleari, Regalia, & Fincham, 2005; for an overview see Fincham, Hall, & Beach, 2006).

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TheoreticalandclinicalimplicationsThe findings of chapter 4 are in line with previous studies that found support for the hypothesis that adequate support may buffer the negative impact of inadequate support on psychosocial outcomes (e.g., Kleiboer et al., 2007; Manne et al., 2003; Revenson, Schiaffino, Majerovitz, & Gibofsky, 1991). Our results further underline the importance of considering both patients and partners when studying support behavior. The majority of previous studies focused on the patient, and not on the partner. However, a chronic illness can be perceived as a stressor shared by both patients and partners (Berg & Upchurch, 2007; Bodenmann, 1997). Partners may therefore benefit from positive support and be harmed by negative support, just like patients. This notion is supported in this thesis by the fact that the associations between supportive behavior and relationship satisfaction, as well as the interactive effects, were found in both patients and partners.

Interventions aimed at enhancing relationship satisfaction in couples dealing with diabetes are probably most effective when they target supportive behaviors enacted by both patients and their partners. These interventions seem promising, which is supported by research that showed that interventions that included both patients with a chronic illness (e.g., cardiovascular disease, cancer) and their partners had a beneficial impact on patients’ psychosocial outcomes (for a meta-analysis see Martire, Lustig, Schulz, Miller, & Helgeson, 2004). Moreover, intervention studies for cancer patients and their partners, targeting relationship aspects, showed that relationship satisfaction improved not only in patients, but in partners as well (Baucom et al., 2009; Kuijer et al., 2004). The intervention programs in these studies focused on what both partners need from each other in terms of supportive behavior, and couples were given homework assignments in which they had to practice specific supportive behaviors. To the best of our knowledge, no intervention studies for diabetes have been published that targeted psychosocial outcomes in both patients and their partners. Such interventions may prove to be as useful in couples dealing with diabetes as they have been in couples dealing with other chronic illnesses.

FutureresearchWe argued that active engagement and protective buffering may co-occur. Future studies could examine how these behaviors actually co-occur in practice. For example, do active engagement and protective buffering interchange within a certain period of time? Or does a person consistently adopt active engagement with regard to some aspects of the illness and protective buffering with regard to other aspects of the illness?

Our explanation for the interactive effects was that protective buffering is interpreted less negatively, and is more easily forgiven when at the same time levels of active engagement are high instead of low. However, this assumption needs to be confirmed in future studies. Diary and observational studies may be suitable to test such questions and will provide better insight into these support processes than self-report studies.

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CONCLUSION 3 “There are no consistent gender differences with regard to associations between support behavior and psychosocial outcomes”

Throughout this thesis we explored the role of gender. Previous studies have shown that women seem to attach more value to relationship-oriented aspects than men do (Cross & Madson, 1997; Strough, Berg, & Sansone, 1996; Thoits, 1992). As a consequence, relationship-oriented aspects, such as support from one’s partner, may have a stronger impact on women’s than on men’s psychosocial outcomes. In chapter 3 it was indeed shown that the indirect link between overprotection by the partner and diabetes-related distress was stronger for female than for male patients. It was further shown that the moderating effect of gender was specifically found in the association between diabetes-specific self-efficacy (the mediator) and diabetes-related distress. This finding can be explained by previous research suggesting that female patients perceive their diabetes as more serious and intruding upon their life than male patients (Helgeson & Novak, 2007; Mosnier-Pudar et al., 2009). Consequently, if female patients do not feel self-efficacious in dealing with a disease that is such a central aspect of their self, they will feel more distressed about their disease than male patients, for whom the disease is less central to their self. It is possible that for male patients it is more important in terms of well-being to feel self-efficacious in other domains of their life. More research is needed to unravel the role of gender in perceptions of and attitudes towards diabetes.

We also examined whether gender would qualify the findings of the other chapters that included support behavior as an independent variable. The interactive effects of regulatory focus and partner support in chapter 2 were not further qualified by gender, nor were the interactive effects of active engagement and protective buffering in chapter 4. Apparently, the finding that the combination of vulnerability in terms of individual or disease characteristics and inadequate partner support is associated with the highest levels of distress applies to both male and female patients. Also the finding that adequate support may buffer the negative effect of inadequate support on relationship satisfaction seems to apply to both male and female individuals (both patients and partners). The main effects in chapter 2 and 4 of support behavior were also not consistently moderated by gender.

Altogether, the results show that the role of gender with regard to supportive behavior and psychological outcomes is not clear. Previous research also showed inconsistent results. That is, some studies did find support for the notion that women are more strongly influenced by partner support than men are (e.g., Acitelli & Antonucci, 1994; Hagedoorn et al., 2000; Hagedoorn et al., 2001; Horwitz, McLaughlin, & White, 1998; Mcrae & Brody, 1989), whereas other studies did not show gender differences (e.g., Sherman, 2003; Vinokur, Price, & Caplan, 1996). It seems that more research is necessary examining when and why support behavior will have a stronger impact on women than on men.

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CONCLUSION 4 “Social comparison will boost patients’ motivation to manage their disease when this information is congruent with patients’ self-regulatory focus”

MaineffectsofsocialcomparisoninformationandregulatoryfocusThe results of chapter 2-4 demonstrated that the partner may have an important impact on the patient. Other persons in the social environment of the patient, such as fellow patients, may also affect the patient. In chapter 5 we focused on comparisons patients make with fellow patients, and on the impact of these comparisons on patients’ motivation to manage the disease. Comparing oneself with others is referred to as social comparison (Festinger, 1954), and research on the effects of social comparisons within the context of health and illness is flourishing (e.g., Aspinwall, 1997; Bennenbroek, Buunk, Van der Zee, & Grol, 2002; Buunk, Zurriaga, Gonzalez, Terol, & Roig, 2006; Buunk et al., 2009). Most of this research focuses on the impact of social comparison information on outcomes such as affect and well-being. Less is known about the effects on patients’ motivation. Especially for patients with diabetes, this is an important question. These patients can largely control a number of aspects of their disease by performing the proper self-care behaviors, and therefore patients need to be motivated to do so.

In chapter 5, we examined the impact of social comparison information (i.e., upward vs. downward targets) on patients’ motivation to manage the disease, and whether regulatory focus and self-efficacy as individual characteristics determine which type of social comparison information is most likely to boost motivation. Before discussing the interactive effects of social comparison information, regulatory focus and self-efficacy, I will summarize the main effects.

Social comparison information (i.e., upward or downward) was not significantly associated with patients’ motivation to manage the disease. Thus, upward comparison information did not lead to increased motivation compared to downward comparison information. We also examined whether regulatory focus (i.e., promotion and prevention focus) and self-efficacy were related to motivation to manage the disease. There was only a weak main effect of prevention focus such that patients with a stronger prevention focus reported a higher motivation to work on their own diabetes regulation after reading the interview fragment containing social comparison information.

The fact that the direction of social comparison was not associated with patients’ motivation may indicate that there are individual characteristics that determine whether upward or downward social comparison information is most likely to increase one’s motivation.

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ModeratingeffectsIn chapter 5, regulatory focus and self-efficacy were put forward as important characteristics that may influence how patients interpret social comparison information. As expected, patients with a strong promotion focus were most motivated to work on their own diabetes regulation when they had read the description of the upward target, that is, a fellow patient doing better than themselves in terms of diabetes management. Patients with a strong prevention focus were most motivated when they had read the description of the downward target. The underlying process for the interactive effect of regulatory focus and social comparison information may be that patients with a strong promotion focus are more attuned to information that highlights positive outcomes and strategies, which may guide them to achieve their ideal possible self. The increased attention to this type of information may lead to increased motivation. Patients with a strong prevention focus on the other hand are more attuned to and therefore more motivated by information that highlights negative outcomes and strategies, which guides them to avoid their feared possible self.

The interactive effect of social comparison information and prevention focus was further qualified by self-efficacy, such that patients with a strong prevention focus were more motivated than patients with a weak prevention focus, but only when they had read the description of the downward target and when they felt highly self-efficacious with regards to setting and achieving their diabetes goals. In other words, patients who are focused on negative outcomes, but believe that they can reach their diabetes goals, are especially motivated to work on diabetes management after reading about a fellow patient who shows poor management.

TheoreticalandclinicalimplicationsOur study is one of the first, if not the only, to examine the effects of social comparison information on motivation to work on their diabetes regulation in patients with diabetes. The findings stress the importance of considering individual differences in regulatory focus and self-efficacy when examining the impact of social comparison information. Depending on these individual differences, social comparison information may be interpreted in different ways and have different effects on motivation. Our findings were supportive of the regulatory fit hypothesis (Higgins, 2000) which states that a task or message should be framed in terms that are congruent with one’s regulatory focus in order to enhance motivation and performance. Similar to the findings of Lockwood and colleagues (e.g., Lockwood, Marshall, & Sadler, 2005; Lockwood et al., 2002), our findings show that also socialcomparison information may be most effective when it is framed in terms that fit one’s focus. Furthermore, our study demonstrated that the findings can be generalized to a sample of patients with diabetes.

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We extended the regulatory fit hypothesis by showing that the interactive effects of social comparison information and prevention focus were further qualified by self-efficacy in diabetes management. Our findings showed that patients who are focused on negative outcomes were motivated to work on their diabetes management after reading about a fellow patient who showed poor management, but only if they believed that they can reach their diabetes goals. This may seem contradictory with a previous study that found that motivation was boosted only in students who perceived themselves vulnerable to the fate of the negative role model (Lockwood, 2002). However, also students who perceived themselves as vulnerable still scored relatively high on perceived control. Apparently, on the one hand, one needs to feel susceptible to the negative outcomes experienced by the negative role model in order to become motivated. But at the same time, one needs to feel self-efficacious in avoiding these negative outcomes.

Our study focused on how the influence of social comparison information may be dependent on individual differences in self-efficacy and regulatory focus. Previous research on social comparison also demonstrated a great interest in individual difference variables. Some researchers have put forward that both upward and downward comparison information may have positive and negative effects on well-being, depending on whether individuals contrast or identify themselves with this information (Buunk & Ybema, 1997). Contrasting yourself with others who are doing better and identifying yourself with others who are doing worse have been indicated as negative interpretations of social comparison information, whereas identifying yourself with others who are doing better and contrasting yourself with others who are doing worse have been put forward as positive interpretations (Van der Zee, Buunk, Sanderman, Botke, & Van den Bergh, 2000). Furthermore, it has been demonstrated that individual differences in neuroticism for example may account for whether social comparison information is interpreted negatively or not (Van Oudenhoven-van der Zee, Buunk, Sanderman, Botke, & Van den Bergh, 1999).

It is plausible that prevention focus, like neuroticism, is associated with a negative interpretation of social comparison information, which may lead to negative emotions, such as anxiety and fear. These negative emotions however, might in turn activate and motivate individuals. That is, if you see a fellow patient doing worse than yourself, you may fear that a similar future lies ahead of you. This fear in turn may stimulate you to engage in behaviors that are needed to avoid such a future.

The results of our study not only have theoretical but clinical implications as well. Interventions aimed at improving motivation and self-care behaviors may sort positive effects if they would present patients with social comparison information, that is, descriptions of fellow patients doing either worse or better than themselves. Role models could perhaps also be implemented in regular care. For example during consultations, physicians could use examples of (fictitious) fellow patients. The recurrent use of role

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models during interventions or in daily practice may lead to enhanced motivation and actual behavioral change in the long run. Based on our results, presenting patients with social comparison information must be done carefully, taking into account individual differences in self-efficacy and regulatory focus. Furthermore, in group interventions, social comparisons are most likely automatically made by patients since members of the group may function as upward or downward targets to each other (cf. Taylor et al., 2007). Patients may be taught to actively compare themselves with those patients who are most likely to enhance their motivation. FutureresearchMore research is needed that will examine the underlying explanation of our findings. It was argued that individuals are more attuned to social comparison information that matches their regulatory focus, and that this increased attention in turn will lead to increased motivation. When individuals are more attuned to certain information they can be expected to better process and remember this information then when they are less attuned to it. Some support for this line of reasoning has been found by a previous study demonstrating that promotion-focused individuals were more likely to recall information relating to the achievement of success by another person (i.e., positive outcomes), whereas prevention-focused individuals were more likely to recall information relating to the avoidance of failure by another person (i.e., negative outcomes) (Higgins & Tykocinski, 1992). However, this study used a different measure of regulatory focus than we did, and effects on motivation were not assessed.

Reconcilingchapter3and5In light of this previous discussion, the results of chapter 2 and 5 that may seem contradictory at first sight (i.e., prevention focus in chapter 2 was associated with negative outcomes, while in chapter 5 it was found to have positive effects in some circumstances) can be more easily reconciled. If one considers the fact that these two chapters refer to different patient outcomes; distress in chapter 2, and motivation in chapter 5, the results are logical. Patients with a strong prevention focus are more likely to be attuned to negative information in their environment. Even though this focus on negativity may lead to more distress, at the same time, it may lead to more motivation when patients encounter (social comparison) information that fits their negativity bias.

Having a strong promotion focus may also lead to enhanced motivation in some circumstances, and unlike prevention focus, promotion focus is not positively associated with distress. Moreover, a strong promotion focus may compensate for low levels of positive support or high levels of negative support. Thus, it can be argued that overall, it is more beneficial to have a strong promotion focus than it is to have a strong prevention

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focus. A question that arises is whether a person’s regulatory focus can be changed in the long run. As discussed earlier, previous studies did show that a person’s regulatory focus can be situationally induced. It is not yet known whether these inducements of either prevention or promotion focus will have a long-lasting impact, although the correlations and means presented earlier do seem to indicate that regulatory focus seems to be stable only to a certain extent.

Future studies should not only assess the effects of social comparison information on patients’ motivation, but should also examine whether social comparison information will lead to actual behavior change in the long run. Both promotion-focused and prevention-focused patients may engage more strongly in self-care behaviors after having been confronted with social comparison information. However, the type of behaviors may be different for promotion-focused and prevention-focused patients. A previous study found support for the notion that a strong promotion focus is related to additive behaviors and that a strong prevention focus is related to subtractive behaviors (Lockwood, Sadler, Fyman, & Tuck, 2004). For example, patients who formulate the prevention-focused goal “to avoid an unhealthy weight” may be inclined to engage in subtractive behaviors, such as cutting back on fat and reducing calorie intake. Patients who have adopted the promotion-focused goal of “achieving a healthy weight” may be inclined to engage in additive behaviors, such as increasing their exercise level, and eating more fruit and vegetables. It would be interesting to examine whether the additive behaviors associated with promotion focus and the subtractive behaviors associated with prevention focus are both equally effective in terms of achieving or maintaining a good self-management, or whether one type of behavior is superior over the other.

Strengths and limitations of the study

The research described in this thesis has several strengths. We have a rather large sample size, and our study is one of the few that included both patients and their partners. Most studies purely focus on patients and their outcomes. Partners of patients are less often included in diabetes studies, and the studies that did focus on partners did not examine how patient’s behavior may affect the partner.

The fact that our research considered the interplay between intra- and interpersonal factors is also relatively unique within the context of diabetes. Many studies focus on either intrapersonal or interpersonal factors, or they focus on the separate effects of these factors. Our findings show that these intra- and interpersonal factors do not operate in isolation, but rather that they interact and influence each other.

In chapter 5, we used an experimental design within questionnaire research. That

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is, patients were randomly assigned to one of the two versions of the questionnaire containing social comparison information. Future studies could make use of experimental designs more often, especially since these designs can provide a good model of testing which components may be useful in interventions. Finally, a clear strength in our research is the utilization of sophisticated methods to analyze the data; in chapter 3 we used a technique that allowed us to test moderated mediation, and in chapter 4 a dyadic data analytic approach was used, which takes into account the nonindependence between patient and partner data.

Nevertheless, there were also some limitations attached to our study. One limitation is that it is not certain whether our sample was representative of all insulin-dependent patients with diabetes. The majority of the patients in our sample did not experience severe diabetes-related distress4. Another study of Dutch diabetes outpatients found a mean score of 23.2 with an SD of 19.5 (Klis, Vingerhoets, De Wit, Zandbelt, & Snoek, 2008; Zandbelt, De Wit, Lubach, Breas, & Snoek, 2007) which is significantly higher than our mean score of 18.2 at T0 (t = 3.72, p< .001). Furthermore, the percentage of patients with seriously elevated levels of diabetes-related distress was also higher than in our study (19.6% vs. 10.9%). The fact that our sample seems to experience less severe diabetes-related distress could be due to the rather strict inclusion criteria we handled (e.g., no serious complications such as polyneuropathy, age between 18 and 70, etc.).

A second limitation is that although we did have a longitudinal data set, it was not very suitable for predicting changes over time. The patients included in our study had been diagnosed with diabetes several years ago, and most patients had long-term relationships with their partner. As indicated by the correlations and mean scores, patients’ and partners’ relationship-focused coping strategies had stabilized to some extent (see chapter 4). Furthermore, patients may have developed rather stable routines of dealing with the diabetes. This is supported by the rather high correlations between the four assessment points on self-care activities (.75 - .80), on diabetes-related distress (.71 - .88), and on diabetes-specific self-efficacy (.76 - .82). Future longitudinal studies may have more predictive value and shed more light on causality if they for example include couples in which the patient has been recently diagnosed, or if they include patients who have only recently been involved in a relationship with an intimate partner.

A final limitation is that all of our results are based on self-report measures, and future studies should include observational measures as well. The perception of support may not only reflect the actual support that has been given or received, but may in addition partially reflect the person’s personality and how the person processes social interactions. Furthermore, support processes between couple members are dynamic in nature which is probably better captured by observing interactions between patients and partners, than by using self-report measures.

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ConcludingremarksThe present thesis has shown that it is important to consider the interplay between patients’ individual characteristics and patients’ social environment when explaining psychological outcomes. The results indicate that positive support behavior of the partner may compensate for patients’ vulnerable characteristics whereas negative support behavior seems to aggravate the negative effects of vulnerability within the patient. As diabetes can be considered as a stressor shared by both the patient and the partner, it was proposed and demonstrated that patients as well as partners may benefit from positive support behaviors in terms of high relationship satisfaction, but may be harmed by negative support behaviors. Moreover, positive support may compensate the detrimental effects of negative support, in both patients and partners. Finally, it was shown that information on fellow patients may boost patients’ motivation to manage their disease when this information matches the patients’ regulatory orientations.

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Footnotes

¹Totesttherobustnessofthesefindings,wealsoexaminedtheassociationsbetweenregulatoryfocusandtwoothermeasuresofdistressinthe‘coupleswithdiabetesdataset’(notpreviouslypresented).Again,promotionfocusshowednosignificant,oronlyveryweakcorrelationswithgeneraldistress(CES-D)andwithdiabetes-relateddistress(PAID)(respectivelyr=.11,p=.04,andr= .10,p= .07).Preventionfocuswasmoderatelyassociatedwithgeneraldistressandwith diabetes-related distress (respectively r = .45, p < .001, and r = .31, p < .001). It seemsthat,dependingonthespecificinstrumentthatisusedtomeasuredistress,correlationswithprevention focus may be somewhat stronger. However, associations between promotionfocusand(diabetes-related)distressremainweakornonsignificant.

²We also tested associations between the ABO and other psychological outcomes. Activeengagement was negatively related to general distress, although not always significantly,whileprotectivebufferingandoverprotectionwerebothpositivelyrelatedtogeneraldistress,again,notalwayssignificantly.Reverseassociationswerefoundforrelationshipsatisfaction.Thatis,activeengagementwaspositivelyrelatedtorelationshipsatisfaction,whileprotectivebufferingandoverprotectionwerebothnegativelyrelatedtorelationshipsatisfaction.Again,theseassociationswerenotalwayssignificant.

³Correlationsofpromotionfocusandpreventionfocusweremoderatetorelativelyhigh(.59-.69)andtherewerenosignificantdifferencesinmeanscoresbetweenthefourassessmentpoints (F(3,207) = 0.98, p = .41, and F(3,206) = 2.01, p = .11, for promotion and preventionfocusrespectively.

4Inchapter2weshowedthatthemeanscoreondiabetes-relateddistresswas18.3withanSDof16.7.TheresultsofthischapterwerebasedontheT1sampleofpatientswhosepartnersalsocompletedthequestionnaire.IfwelookattheT1samplewhichincludesallpatientsthenthe mean score seems comparable (M = 18.5, SD = 17.3). Also the screening questionnaire(T0)showedacomparablemeanscoreof18.2,withanSDof16.5.AtT0,55(10.9%)ofthe503patientsthatcompletedthequestionnairehadascoreof40orhigher,whichisindicativeofmoreseverediabetes-relateddistress.AtT1,42(12.4%)ofthe340patientshadaPAIDscoreof40orhigher.

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Summary

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Summary

The present thesis focuses on psychosocial outcomes in individuals dealing with diabetes, by taking both an intrapersonal and interpersonal perspective. The burden of a demanding and unending self-management regimen and the prospect of possible complications may negatively affect psychological well-being and adjustment of those individuals confronted with this disease. However, some individuals will be more negatively affected by the disease than others. This may depend on their personality and the way they appraise the disease (intrapersonal factors), but also on their social environment, such as their intimate partner and other patients with diabetes (interpersonal factors).

In chapter 1 we explain the intrapersonal and interpersonal factors that we investigated more in detail. One of the intrapersonal factors that were considered to be relevant for psychosocial outcomes is called regulatory focus. Regulatory focus is an individual characteristic and consists of two self-regulatory systems; promotion and prevention focus. Individuals with a strong promotion focus are oriented toward obtaining positive outcomes in life, whereas individuals with a strong prevention focus are oriented toward avoiding negative outcomes. These different orientations can be expected to be differently related to psychosocial adaptation. Other intrapersonal factors that we were interested in were patients’ self-efficacy, that is, whether patients believe they are capable of performing certain behaviors, and patients’ glycemic control which refers to the typical levels of blood sugar. Finally, the role of gender was explored throughout the chapters since previous studies have indicated that certain interpersonal factors may have a stronger impact on women’s than on men’s psychosocial outcomes.

The interpersonal factors that were considered to be important for psychosocial adaptation are support behavior and social comparison. In this thesis, we distinguished between three ways of providing support: active engagement, protective buffering, and overprotection. Active engagement refers to a support behavior in which the partner uses constructive problem-solving methods, like involving the significant other in discussions, inquiring how the other feels and asking about the help and information needed. In general, active engagement can be viewed as positive support behavior. Protective buffering means hiding one’s concerns, denying one’s worries, concealing discouraging information, preventing the significant other from thinking about the illness, and yielding in order to avoid disagreement. Overprotection means that the partner underestimates the patient’s capabilities, resulting in unnecessary help, excessive praise for accomplishments, or attempts to restrict activities. Although perhaps well-intended, both protective buffering and overprotection have been found to be associated with less positive psychological outcomes. Furthermore, active engagement and protective buffering are support behaviors that can be enacted by both patients and partners, whereas overprotection is support behavior that is more typically enacted by partners. Another interpersonal factor that is explained in chapter 1 is social comparison, which can

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consist of upward and downward comparisons. Upward comparison refers to comparing yourself with other individuals who are doing better than you are (e.g. in terms of diabetes management and disease outcomes), so-called upward targets. Downward comparison refers to comparing yourself with other individuals who are doing worse than you are, so-called downward targets. In chapter 1 we explain how social comparison information may boost patients’ motivation to manage their diabetes.

At the end of chapter 1 we give an outline of the thesis. It is explained that throughout the chapters we do not only focus on how the intrapersonal and interpersonal factors are separately associated with individuals’ psychosocial outcomes, but that we also investigate the combined impact of these factors.

In this thesis we made use of data from two different groups of respondents. Three of the four chapters report on data collected in a study of psychosocial adaptation in individuals confronted with diabetes. In this study, 690 eligible, consecutive patients with type 1 and 2 diabetes requiring insulin from the northern part of the Netherlands were approached by their physician during a check-up visit to complete a short screening questionnaire. This short questionnaire was filled out and returned by 507 patients. Of these patients, 419 (82.6%) indicated to have an intimate partner. For the purposes of this study, we were interested in the larger questionnaires (T1 – T4) that were sent to both patients and their partners after patients had filled out the short questionnaire. Three to four months separated the administration of the first three questionnaires, and five to six months separated the third and fourth questionnaire. There were 223 couples who completed the T1 questionnaire. Chapter 2 reports on data collected in another study. In this study (a large national survey), 5500 persons of 55 years and older from different areas in the Netherlands were asked to participate. In total, a number of 2497 respondents (45.4%) completed the questionnaire. For the purposes of our study, we only used the data of 477 respondents with an intimate partner and who reported having diabetes, asthma, or heart disease when presented a list with several health problems.

Chapter 2 looked at the combined impact of patients’ regulatory focus and partners’ support behavior on levels of distress in patients. This chapter refers to chronic diseases (including diabetes) in which the patient can exert control over the course of the disease by engaging in several self-management behaviors. We argue that in persons with these chronic diseases an individual characteristic such as regulatory focus (i.e., promotion and prevention focus) may have an important influence on levels of distress. We further argue how support behaviors of their partner may create a promotion-focused or prevention-focused environment and how these support behaviors (i.e., active engagement, protective buffering, and overprotection) as such may alter the influence of patients’ regulatory focus. The results showed that partners’ support behaviors moderated the negative association between promotion focus and distress in that this association was

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only found when patients reported that their partner engaged in relatively low levels of active engagement or relatively high levels of protective buffering and overprotection. Patients reported relatively low levels of distress when they received high levels of active engagement or low levels of protective buffering and overprotection, regardless of whether they had a weak or a strong promotion focus. Active engagement appears to buffer against high distress in patients with a weak promotion focus, while protective buffering and overprotection appear to aggravate distress in these patients. The positive association between prevention focus and distress was not consistently found to be moderated by partner support.

Chapter 3 specifically focuses on overprotection as a support behavior. We aimed to identify both how and when overprotection is associated with diabetes-related distress in patients. We reasoned that overprotective behavior by the partner may confer the message to the patient that the partner has little confidence in the patient’s ability to deal with the disease effectively. This lack of confidence of the partner may lead patients to doubt their own ability to manage the disease, thus lowering their levels of self-efficacy. In turn, lower levels of diabetes-specific self-efficacy may increase diabetes-related distress. It was indeed found that diabetes-specific self-efficacy mediated the association between overprotection by the partner and diabetes-related distress. In addition, it was hypothesized that this mediated association would be stronger in certain subgroups of patients. The first subgroup that was identified included patients with relatively poor glycemic control. These results supported our reasoning that patients who feel less self-efficacious (because they are overprotected) will experience more diabetes-related distress when confronted with a poor glycemic control because these patients are less confident about their ability to improve their glycemic control. The second subgroup of patients for whom the mediated association was strongest included female patients. The explanation is that lower levels of self-efficacy are more strongly associated with distress in female patients than in male patients, because diabetes may have a higher salience to women compared to men. Previous research has for example shown that female patients reported a higher impact of diabetes on daily life than male patients. If one perceives the diabetes as highly salient, one may become even more distressed when one feels little self-efficacious in dealing with this disease. The findings of chapter 3 highlight the importance of studying both how and when partner support is associated with distress in patients.

In chapter 4 we examine the associations between support behavior, i.e. active engagement and protective buffering, and relationship satisfaction. In the majority of previous studies, associations like these were only investigated in patients. However, diabetes is not only an individual affair, but a couple’s affair as well. This means that behaviors like active engagement and protective buffering can be enacted by both

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patients and partners. Therefore, in our study, we focused on partners’ psychosocial outcomes as well. Using a dyadic data analytic approach, that takes into account the interdependence between patients and partners we found relationship satisfaction to be positively associated with active engagement, and negatively with protective buffering. Moreover, we found a moderating effect, in that the negative association between protective buffering and relationship satisfaction was only present when levels of active engagement were relatively low. The results were found in both patients and partners and support the idea that less adequate support behavior such as protective buffering may only be perceived as negatively intended when at the same time, one receives low levels of active engagement. In this situation, one may believe that the other person pretends everything is fine because he or she does not care at all. Received buffering is then viewed as negative behavior and is likely to have negative effects on relationship satisfaction. In contrast, received protective buffering may be perceived as less negatively intended when at the same time, one receives high levels of active engagement. In this situation, the other person’s buffering can be perceived as an attempt not to add more distress. Therefore, received buffering may not be associated with less relationship satisfaction, since it is not viewed as negative behavior under these circumstances. The findings in this chapter illustrate the need to consider adequate and less adequate support behaviors simultaneously, and to study the effects on both patients and partners.

In the previous chapters we also investigated the role of gender, by examining whether gender moderated the associations we had found. Chapter 3 explicitly focused on the role of gender and found support for a moderating effect of gender. However, the interactive effects of regulatory focus and partner support in chapter 2 were not further qualified by gender, nor were the interactive effects of active engagement and protective buffering in chapter 4. The main effects in these chapters were also not consistently moderated by gender. The results show that it is not clear when partner support may have a stronger impact on women than on men, and that more research is necessary.

In chapters 2, 3, and 4 we have demonstrated that the intimate partner may influence psychosocial outcomes in patients. The research question in chapter 5 is whether other persons in the social environment may have an impact on the patient. More specifically, the aim was to determine the impact of social comparisons with fellow patients on patients’ motivation to manage their diabetes. Social comparison can consist of upward and downward comparisons. Traditionally, it has been proposed that upward comparisons may motivate and inspire individuals. However, in chapter 5 we demonstrate that not only upward, but also downward comparison information may motivate patients, depending on their regulatory focus and self-efficacy. Patients were presented with a fictitious interview with either an upward comparison target (a fellow patient showing adequate self-care behaviors and experiencing optimal disease outcomes) or a downward comparison

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target (a fellow patient showing less adequate self-care behaviors and experiencing negative disease outcomes). It was found that comparison targets that matched patients’ regulatory focus increased patients’ motivation, whereas comparison targets that did not match patients’ regulatory focus showed no impact on patients’ motivation. That is, it was shown that high promotion-focused patients reported more motivation than low promotion-focused patients when confronted with the upward target. High prevention-focused patients reported more motivation than low prevention-focused patients when confronted with the downward target. This latter finding was qualified by patients’ self-efficacy, as it applied only to patients with relatively high levels of self-efficacy. This interactive effect of self-efficacy is in line with the reasoning that only patients with a strong prevention focus who believe they can avoid the negative outcomes represented by the downward comparison target will be motivated by this target. Patients who have a strong prevention focus but who do not believe they can avoid the negative outcomes experienced by the downward comparison target, will not be motivated by this target. The results of chapter 5 indicate that when using comparison targets to encourage self-care activities in persons with diabetes, these targets need to be tailored to patients’ individual characteristics.

Finally, in chapter 6 we discuss the main findings of the thesis. Four overall conclusions are drawn. The first conclusion is that patients with vulnerable individual characteristics or with poor disease outcomes (i.e., a weak promotion focus or a poor glycemic control) may be at risk of experiencing high levels of (diabetes-related) distress, especially when their partner provides inadequate support. The second conclusion is that the negative effects of protective buffering on relationship satisfaction may be compensated for by high levels of active engagement, in both patients and partners. The third conclusion is that we did not find consistent gender differences with regard to associations between support behavior and psychosocial outcomes. Lastly, the fourth conclusion is that social comparison information is most likely to boost patients’ motivation to manage their disease when this information is congruent with patients’ regulatory focus. We explain the theoretical and clinical implications of each of these conclusions and suggestions for future research are provided. Altogether, it is concluded that it is important to consider the interplay between patients’ individual characteristics and patients’ social environment when explaining psychosocial outcomes.

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Samenvatting

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Samenvatting

Dit proefschrift richt zich op psychosociale uitkomsten bij individuen met diabetes en hun partners, vanuit zowel een intrapersoonlijk als een interpersoonlijk perspectief. Diabetes vraagt veel van patiënten in termen van de zelfzorggedragingen die iedere dag uitgevoerd moeten worden. Ook hebben patiënten te maken met het vooruitzicht van complicaties die zich in de toekomst kunnen ontwikkelen. Een chronische ziekte als diabetes kan dan ook een negatief effect hebben op iemands welbevinden. Echter, bij sommige personen zal dit negatieve effect groter zijn dan bij anderen. Dit kan te maken hebben met iemands persoonlijkheid en hoe iemand tegen de diabetes aankijkt en er mee om gaat (intrapersoonlijke factoren), maar kan ook te maken hebben met de sociale omgeving zoals de partner en andere patiënten met diabetes (interpersoonlijke factoren).

Hoofdstuk 1 geeft een uitleg van de intrapersoonlijke en interpersoonlijke factoren die we hebben onderzocht. Een van de intrapersoonlijke factoren die relevant werden geacht voor psychosociale uitkomsten is zelfregulerende focus. Zelfregulerende focus is een individueel kenmerk welke bestaat uit twee zelfregulerende systemen; promotie- en preventiefocus. Personen met een sterke promotiefocus zijn georiënteerd op het behalen van positieve uitkomsten in het leven, terwijl personen met een sterke preventiefocus georiënteerd zijn op het vermijden van negatieve uitkomsten. Er werd verwacht dat promotie- en preventiefocus verschillend zouden samenhangen met psychosociale adaptatie. Andere intrapersoonlijke factoren waar we in geïnteresseerd waren zijn de zelfeffectiviteit van patiënten, dat wil zeggen het geloof dat patiënten hebben in hun eigen vaardigheid om bepaalde gedragingen uit te voeren, en de glykemische instelling van patiënten, dat wil zeggen de gemiddelde bloedsuikerwaarden van een patiënt. Tot slot wordt in hoofdstuk 1 geslacht als intrapersoonlijke factor besproken. Eerder onderzoek suggereert dat bepaalde interpersoonlijke factoren een grotere invloed op psychosociale uitkomsten van vrouwen zou hebben dan op die van mannen.

De interpersoonlijke factoren die belangrijk werden geacht voor psychosociale adaptatie zijn partnersteun en sociale vergelijking. In dit proefschrift onderscheidden we drie vormen van partnersteun, te weten actieve betrokkenheid, beschermend bufferen en overbescherming. Actieve betrokkenheid is steungedrag waarbij de partner probleemoplossende methodes toepast, zoals de patiënt bij discussies betrekken, en het actief luisteren en informeren naar gevoelens en gedachten van de patiënt. Actieve betrokkenheid kan over het algemeen worden gezien als positief steungedrag. Beschermend bufferen wordt gekenmerkt door het vermijden van negatieve gevoelens en het wegwuiven van zorgen en twijfels van de patiënt. Overbescherming houdt in dat de partner de vaardigheden van de patiënt onderschat, wat ertoe leidt dat de partner onnodige hulp geeft, overvloedige complimenten geeft aan de patiënt, of de patiënt probeert te weerhouden van bepaalde activiteiten. Hoewel beschermend bufferen en overbescherming waarschijnlijk goed bedoeld zijn lijken ze beide een minder positief

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effect te hebben op de ontvanger. Verder is het zo dat actieve betrokkenheid en beschermend bufferen gedrag is dat door zowel patiënten als partners getoond kan worden, terwijl overbescherming gedrag is dat vooral getoond wordt door partners. Een andere interpersoonlijke factor die uitgelegd wordt in hoofdstuk 1 is sociale vergelijking dat zowel opwaarts als neerwaarts kan plaatsvinden. Opwaartse vergelijking wil zeggen dat je jezelf vergelijkt met anderen die het beter doen dan jijzelf of er beter aan toe zijn (bijvoorbeeld in termen van zelfzorggedragingen of ziekte-uitkomsten), zogeheten opwaartse rolmodellen. Neerwaartse vergelijking wil zeggen dat je jezelf vergelijkt met anderen die het slechter doen dan jijzelf of er slechter er aan toe zijn, zogeheten neerwaartse rolmodellen. In hoofdstuk 1 leggen we uit hoe sociale vergelijkingsinformatie patiënten kan motiveren om aan hun diabetesregulatie te werken.

Aan het slot van hoofdstuk 1 geven we een overzicht van het proefschrift. Er wordt uitgelegd dat we in de verschillende hoofdstukken niet alleen onderzoeken hoe de intrapersoonlijke en interpersoonlijke factoren apart samenhangen met psychosociale uitkomsten, maar dat we ook kijken naar het gecombineerde effect van deze factoren.

Voor dit proefschrift is gebruik gemaakt van data van twee verschillende groepen respondenten. Drie van de vier hoofdstukken rapporteren over data uit een onderzoek naar psychosociale adaptatie in individuen met diabetes en hun partners. In dit onderzoek zijn 690 patiënten met type 1 of type 2 diabetes die afhankelijk zijn van insuline uit het noorden van Nederland benaderd door hun internist om een korte vragenlijst in te vullen. Deze korte vragenlijst werd ingevuld en teruggestuurd door 507 patiënten. Van deze patiënten gaven 419 patiënten (82.6%) aan dat ze een partner hadden. Voor het doel van het huidige onderzoek waren we geïnteresseerd in de grotere vragenlijsten (T1 – T4) die naar patiënten en hun partners werd gestuurd nadat ze de korte vragenlijst hadden ingevuld. Tussen de eerste drie vragenlijsten zaten steeds drie tot vier maanden, en tussen de derde en vierde vragenlijst zat vijf tot zes maanden. De T1 vragenlijst is ingevuld door 223 paren. Hoofdstuk 2 rapporteert over een andere onderzoeksgroep. De data die gebruikt is in dit hoofdstuk maakte deel uit van een groot nationaal vragenlijstonderzoek waarbij 5500 personen van 55 jaar en ouder uit verschillende delen van Nederland gevraagd om deel te nemen. In totaal hebben 2497 respondenten (45.4%) de vragenlijst ingevuld. Voor het doel van ons onderzoek hebben we een selectie gemaakt van respondenten met een partner die aangaven dat ze diabetes, astma, of een hart- en vaatziekte hadden. Er waren 477 respondenten die in deze selectie vielen.

Hoofdstuk 2 richt zich op het gecombineerde effect van de zelfregulerende focus van de patiënt en het steungedrag van de partner op psychische klachten van de patiënt. Dit hoofdstuk heeft betrekking op chronische ziektes (waaronder diabetes) waarbij de patiënt zelf een zekere mate van controle kan uitoefenen op het verloop van de ziekte door verschillende zelfzorggedragingen uit te voeren. We stellen dat in personen met een

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dergelijke ziekte een kenmerk als zelfregulerende focus (promotie- en preventiefocus) een belangrijke invloed kan hebben op psychische klachten. Vervolgens zetten we uiteen hoe bepaalde vormen van partnersteun een promotiegerichte of preventiegerichte omgeving kunnen creëren en hoe deze steun (actieve betrokkenheid, beschermend bufferen en overbescherming) als zodanig de invloed van zelfregulerende focus van de patiënt kan wijzigen. De resultaten lieten zien dat deze drie vormen van partnersteun het negatieve verband tussen promotiefocus en psychische klachten modereerden, en wel zo dat dit verband alleen gevonden werd in patiënten die aangaven dat hun partner relatief weinig actieve betrokkenheid liet zien of relatief veel beschermend bufferen of overbescherming. Patiënten rapporteerden relatief weinig psychische klachten wanneer patiënten veel actieve betrokkenheid ontvangen of weinig beschermend bufferen of overbescherming, ongeacht of patiënten een zwakke of sterke promotiefocus hebben. De resultaten suggereren dat actieve betrokkenheid patiënten met een lage promotiefocus beschermt tegen psychische klachten terwijl beschermend bufferen en overbescherming psychische klachten juist lijken te verergeren in deze patiënten. Het positieve verband tussen preventiefocus en psychische klachten werd niet consistent gemodereerd door partnersteun.

Hoofdstuk 3 richt zich specifiek op overbescherming door de partner. Het doel was om zowel helder te krijgen hoe als wanneer overbescherming gerelateerd is aan diabetesgerelateerde psychische klachten in patiënten. De redenering is dat overbeschermend gedrag door de partner de boodschap bij de patiënt overbrengt dat de partner weinig vertrouwen heeft in de vaardigheden van de patiënt om op een goede manier de diabetes te reguleren. Dit gebrek aan vertrouwen kan ertoe leiden dat ook de patiënt weinig vertrouwen heeft in zijn of haar eigen vaardigheden met betrekking tot het omgaan met de diabetes, zodat zijn of haar zelfeffectiveit daalt. Deze lagere diabetesspecifieke zelfeffectiviteit kan er weer toe leiden dat diabetesgerelateerde psychische klachten toenemen. Er werd inderdaad gevonden dat het verband tussen overbescherming en diabetesgerelateerde psychische klachten gemedieerd werd door diabetesspecifieke zelfeffectiviteit. Daarnaast was de verwachting dat dit gemedieerde verband sterker zou zijn in bepaalde subgroepen van patiënten. De eerste subgroep die geïdentificeerd werd betrof patiënten met een relatief slechte glykemische instelling. De resultaten ondersteunden de redenering dat patiënten die een lagere zelfeffectiviteit hebben (bijvoorbeeld omdat ze worden overbeschermd) meer diabetesgerelateerde psychische klachten ervaren omdat deze patiënten zich onzeker voelen over hun vaardigheid om hun glykemische instelling te verbeteren. De tweede subgroep van patiënten voor wie het gemedieerde verband het sterkst was betrof vrouwelijke patiënten. De verklaring voor deze bevinding is dat een lagere zelfeffectiviteit sterker samenhangt met psychische klachten omdat diabetes voor vrouwelijke patiënten een belangrijkere

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plaats in het leven zou innemen dan voor mannelijke patiënten. Zo heeft eerder onderzoek aangetoond dat vrouwen sterker dan mannen aangeven dat de diabetes een grote invloed op hun leven heeft. Wanneer de diabetes als zeer saillant wordt ervaren dan kan het als des te meer vervelend worden ervaren wanneer iemand het gevoel heeft niet effectief te zijn in het omgaan met deze ziekte. De bevindingen van hoofdstuk 3 onderstrepen het belang om onderzoek zowel te richten op de vraag hoe partnersteun samenhangt met psychische klachten in patiënten als op de vraag onder welke condities dit verband bestaat.

In hoofdstuk 4 bestuderen we verbanden tussen steungedrag (actieve betrokkenheid en beschermend bufferen) en relatietevredenheid. Een groot deel van eerdere studies heeft dergelijke verbanden alleen bij patiënten onderzocht. Echter, het omgaan met de diabetes is niet zozeer een individuele aangelegenheid van de patiënt maar ook de partner wordt hierbij betrokken. Steungedrag als actieve betrokkenheid en beschermend bufferen kan dan ook door zowel patiënten als partners toegepast worden. In ons onderzoek hebben we deze verbanden daarom niet alleen bij patiënten onderzocht, maar ook bij partners. We hebben gebruik gemaakt van een dyadische data-analyse benadering waarbij rekening wordt gehouden met de afhankelijkheid die bestaat tussen patiënten en partners. Relatietevredenheid liet een positieve samenhang zien met actieve betrokkenheid, en een negatieve samenhang met beschermend bufferen. Verder werd er een modererend effect gevonden, en wel zo dat het negatieve verband tussen beschermend bufferen en relatietevredenheid alleen gevonden werd wanneer er sprake was van relatief weinig actieve betrokkenheid. De resultaten werden zowel bij patiënten als partners gevonden en ondersteunen het idee dat er alleen negatieve intenties aan steungedrag zoals beschermend bufferen worden toegeschreven wanneer iemand tegelijkertijd weinig actieve betrokkenheid door de ander waarneemt. Men denkt in dit geval bijvoorbeeld dat de ander buffert, dus net doet alsof er niets aan de hand is, omdat het hem of haar niets kan schelen. Het beschermend bufferen wordt in deze situatie gezien als negatief gedrag en zal waarschijnlijk de relatietevredenheid verminderen. Daarentegen zullen er minder sterk negatieve intenties aan beschermend bufferen worden toegeschreven wanneer men tegelijkertijd veel actieve betrokkenheid door de ander waarneemt. Het bufferen van de ander wordt dan bijvoorbeeld opgevat als een poging om de psychische klachten niet te verergeren. Beschermend bufferen zal in die situatie de relatietevredenheid niet verlagen omdat het bufferen niet als negatief gedrag wordt gezien onder deze omstandigheden. De bevindingen in dit hoofdstuk illustreren de noodzaak om positief en negatief steungedrag samen te bestuderen en om de verbanden zowel in patiënten als in partners te onderzoeken.

In de voorgaande hoofdstukken is tevens de rol van geslacht onderzocht, dat wil zeggen, we hebben gekeken of geslacht de gevonden verbanden modereerde. In hoofdstuk 3

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werd het modererende effect van geslacht expliciet onderzocht en ook gevonden. Echter, de interactie-effecten van zelfregulerende focus en partnersteun in hoofdstuk 2, en de interactie-effecten van actieve betrokkenheid en beschermend bufferen in hoofdstuk 4 werden niet verder gekwalificeerd door geslacht. Ook de hoofdeffecten van partnersteun in deze hoofdstukken werden niet consistent gemodereerd door geslacht. De resultaten wijzen er op dat het niet duidelijk is wanneer partnersteun een sterker effect op vrouwen heeft dan op mannen, en dat hier meer onderzoek naar nodig is.

In de hoofdstukken 2 tot en met 5 hebben we laten zien hoe partnersteun van invloed kan zijn op psychosociale uitkomsten in patiënten. In hoofdstuk 5 wordt de vraag gesteld of andere patiënten met diabetes van invloed kunnen zijn op de patiënt. Meer specifiek gesteld was het doel om de invloed te onderzoeken van sociale vergelijkingen met andere patiënten op de motivatie van de patiënt om zijn of haar diabetes te reguleren. Sociale vergelijking kan zowel opwaarts als neerwaarts plaatsvinden. In eerder onderzoek werd over het algemeen gesteld dat vooral opwaartse vergelijkingen motiverend kunnen werken. In hoofdstuk 5 tonen we echter aan dat ook neerwaartse vergelijking patiënten een motiverende werking kunnen hebben, afhankelijk van de zelfregulerende focus van de patiënt en diens zelfeffectiviteit. Patiënten kregen een fictief interview te lezen met een opwaarts rolmodel (een patiënt die adequate zelfzorggedragingen uitvoerde en weinig tot geen last had van de diabetes) of met een neerwaarts rolmodel (iemand die niet de adequate zelfzorggedragingen vertoonde en fysiek en mentaal last had van de diabetes). De resultaten lieten zien dat rolmodellen die in overeenstemming waren met de zelfregulerende focus een positief effect hadden op de motivatie van patiënten om de diabetes te reguleren. Patiënten met een sterke promotiefocus rapporteerden een sterkere motivatie dan patiënten met een zwakke promotiefocus wanneer ze het interview met het opwaartse rolmodel hadden gelezen. Patiënten met een sterke preventiefocus rapporteerden een sterkere motivatie dan patiënten met een zwakke preventiefocus wanneer ze het interview met het neerwaartse rolmodel hadden gelezen. Deze laatste bevinding werd nog eens gekwalificeerd door zelfeffectiviteit; het was namelijk alleen van toepassing op patiënten met een relatief hoge zelfeffectiviteit. Dit interactie-effect ondersteunde de redenering dat patiënten alleen gemotiveerd worden door het negatieve rolmodel wanneer ze een sterke preventiefocus hebben en wanneer ze geloven dat ze in staat zijn om de negatieve uitkomsten te vermijden die worden weergegeven door het neerwaartse rolmodel. Patiënten die een sterke preventiefocus hebben maar er niet van overtuigd zijn dat ze de negatieve uitkomsten kunnen vermijden zullen niet gemotiveerd raken door dit neerwaartse rolmodel. De resultaten van hoofdstuk 5 wijzen er op dat als men rolmodellen in de praktijk wil toepassen om patiënten te motiveren om zelfzorggedragingen uit te voeren, men deze moet aanpassen aan individuele kenmerken van patiënten.

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Ten slotte worden in hoofdstuk 6 de belangrijkste bevindingen besproken. Er worden vier globale conclusies getrokken. De eerste conclusie is dat patiënten met kwetsbare individuele kenmerken of met negatieve ziekte-uitkomsten (bv. een zwakke promotiefocus of een slechte glykemische instelling) het gevaar lopen om (diabetesgerelateerde) psychische klachten te ervaren, met name wanneer ze inadequate steun ontvangen van hun partner. De tweede conclusie is dat de negatieve effecten van beschermend bufferen op relatietevredenheid gecompenseerd kunnen worden wanneer er tegelijkertijd sprake is van veel actieve betrokkenheid. De derde conclusie is dat we geen consistente geslachtsverschillen hebben gevonden met betrekking tot de verbanden tussen steungedrag en psychosociale uitkomsten. De vierde conclusie tot slot is dat sociale vergelijkingsinformatie de motivatie van de patiënt om aan de diabetesregulatie te werken kan verhogen wanneer deze informatie overeenkomt met de zelfregulerende focus van de patiënt. We gaan vervolgens in op de theoretische en klinische implicaties van elk van deze conclusies en geven suggesties voor toekomstig onderzoek. Al met al kan gesteld worden dat het belangrijk is om oog te hebben voor de wisselwerking tussen individuele kenmerken van de patiënt en de sociale omgeving van de patiënt wanneer men psychosociale uitkomsten wil verklaren.

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Dankwoord/Acknowledgements

Graag wil ik hier iedereen bedanken die een bijdrage heeft geleverd aan de totstandkoming van dit proefschrift. Allereerst wil ik alle respondenten bedanken voor het invullen van de uitgebreide en pittige vragenlijsten. Zonder jullie geduldige medewerking had ik dit proefschrift nooit kunnen schrijven. Vervolgens wil ik mijn begeleiders bedanken met wie ik zeer plezierig heb samengewerkt:

Prof.dr. M. Hagedoorn. Beste Mariët, als dagelijks begeleider was jij zeer nauw betrokken bij het onderzoek. Jij was voor mij gedurende het promotietraject een inspirerend voorbeeld (of om in de terminologie van het proefschrift te blijven: een positief rolmodel); ik heb heel veel van je geleerd. Ik stond dikwijls versteld van je vakinhoudelijke kennis. Je constructieve feedback was er niet alleen op gericht om mij te verbeteren, maar vooral om mij zelf te laten ontdekken hoe iets verbeterd kon worden. We hebben veelvuldig overleg gehad, en na zo’n overleg had ik vaak nóg meer zin en energie om er weer tegen aan te gaan.

Prof.dr. T.P. Links. Beste Thera, jij wist altijd tijd te vinden om stukken door te lezen en van commentaar te voorzien, hoe druk je het ook had. Je stimuleerde me om oog te hebben voor de klinische praktijk en de resultaten hier naar toe te vertalen. Ik vond het fijn dat ik mocht meelopen tijdens een van je spreekuren. Ik vond het mooi te zien dat je niet alleen geïnteresseerd was in de bloedsuikerwaarden, maar bovenal in het welzijn van de patiënt. Tot slot ben je onmisbaar geweest bij het leggen van de contacten in Heerenveen en Drachten. Het is mede dankzij jouw overtuigingskracht en enthousiasme dat dit onderzoek überhaupt heeft kunnen plaatsvinden.

Prof.dr. R. Sanderman. Beste Robbert, jij hebt er met jouw commentaar mede voor gezorgd dat artikelen net even wat meer cachet kregen. Ook droeg je suggesties aan voor aanvullende analyses waardoor een verhaal een stuk interessanter werd. Daarnaast toonde je interesse in mijn ontwikkeling en heb je er bijvoorbeeld voor gezorgd dat ik ervaring kon opdoen in het begeleiden van scriptiestudenten. Als laatste wil ik je bedanken dat ik ook voor andere zaken zoals sollicitatieperikelen bij je aan kon kloppen.

Prof.dr. B.H.R. Wolffenbuttel. Beste Bruce, we zijn dit project gestart met Robbert en jou als promotoren. Doordat de beide vrouwelijke copromotores op een gegeven moment tot hoogleraar zijn benoemd zijn de rollen wat gewisseld. Deze rolwisselingen zorgden ervoor dat jij meer vanaf de zijlijn betrokken was bij het onderzoek. Ik wil je hartelijk danken voor je betrokkenheid vanuit deze positie, en voor het feit dat je me hebt gestimuleerd om helder en bondig te schrijven.

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Dr. J.C. Keers. Beste Joost, jij bracht zowel psychologische vakkennis als diabetesspecifieke kennis in, wat zeer waardevol is geweest voor dit onderzoek. Dank hiervoor. Ook wil ik je bedanken voor het feit dat je me geïntroduceerd hebt bij het team in Beatrixoord, en voor je hulp bij het leggen van de contacten in Drachten.

Dr. J. Bouma. Beste Jelte, je staat niet als officiële begeleider op papier, maar je hebt wel degelijk een begeleidende functie gehad tijdens het promotietraject. Je wierp een kritische en (ont)nuchtere(nde) blik op zaken, maar daarnaast heb ik toch vooral ook veel complimenten van je mogen ontvangen, wat erg stimulerend werkte.

De leden van de leescommissie, prof.dr. Arie Dijkstra (RuG), prof.dr. Denise de Ridder (UU) en prof.dr. Frank Snoek (VUmc) wil ik hartelijk danken voor het lezen en beoordelen van het manuscript.

De medewerkers van de poliklinieken van de ziekenhuizen in Heerenveen en Drachten ben ik zeer erkentelijk voor hun medewerking aan het onderzoek. Dr. Daling, dr. Adriaanse, dr. Wesche, dr. Blaauwwiekel, dr. Beentjes, dr. Numan en dr. Kroon wil ik bedanken voor hun ondersteuning en voor het benaderen van patiënten voor deelname aan het onderzoek. De secretaresses en baliemedewerkers wil ik ook hartelijk bedanken voor hun medewerking. Petra en Ypie, bedankt voor de heerlijke soep wanneer ik vrijdags langskwam.

Naast mijn begeleiders zijn er twee co-auteurs die ik in het bijzonder wil bedanken. Marie Louise Luttik, ik wil jou graag bedanken voor het inbrengen van je kennis over psychosociale problemen bij patiënten met hart- en vaatziekten. Ilse Stuive, dankzij jou ligt er nu een mooi artikel waarin we gebruik hebben gemaakt van geavanceerde dyadische data analyses. Jouw hulp bij deze analyses was onmisbaar. Je hebt uitgebreide documenten gemaakt met uitleg zodat ik ook zelf uit de voeten kon met MLwiN. Dank voor alle tijd die je er in hebt gestoken en voor het geduldig beantwoorden van al mijn vragen betreffende het uitvoeren van de analyses.

Het diabetesteam in Beatrixoord bestaande uit onder meer Madelein Schotman, Ingrid Stoelinga, Linda Faber, Rita Wesselius, Heike Mesch, Janine Kramer en Elsa Pieterman wil ik hartelijk danken voor hun medewerking aan het onderzoek en voor het feit dat ik mee heb mogen lopen tijdens een aantal dagen van het diabetesrevalidatieprogramma.

Wijlen Willem Lok wil ik bedanken voor het mooie veldwerkprogramma waarmee ik de logistiek van het onderzoek goed kon bijhouden, en voor de invoerbestanden. Truus

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van Ittersum, hartelijk dank dat je mij steeds de meest recente literatuurlijsten toe hebt gestuurd en voor je hulp wanneer ik gedoe had met Reference Manager. Eric van Sonderen, bedankt dat ik met zowel onbenullige als grotere statistische vragen bij je aan kon kloppen. Ans Smink, hartelijk dank voor je uitleg over het veldwerkprogramma, en voor het feit dat ik voor vragen over praktische zaken bij je terecht kon. Roy Stewart wil ik bedanken voor zijn hulp bij MLwiN toen Ilse Stuive één keer niet aanwezig was om mij met raad en daad bij te staan. Franziska de Jong en Ans de Jong, hartelijk dank voor het invoeren van een groot deel van de vragenlijsten. Dit heeft mij veel werk uit handen genomen. Elsbeth Kleinlugtenbelt, dank voor je hulp bij het coderen van de doelen en ik vond het heel leuk dat ik je heb mogen begeleiden bij je bachelorscriptie. Lisa Jewett, thank you for close reading the article on the role models.

De wekelijkse ‘labmeetings’ waren naast erg nuttig ook erg gezellig. Mariët, Lihua, Franziska, Nynke en Meirav, dank hiervoor.

Inge Henselmans, Merlijne Jaspers, en Andrea Fokkens wil ik bedanken voor de gezellige (lunch)bijeenkomsten waarin we onze laatste loodjes en heel veel andere dingen bespraken. Merlijne, ik vond het ontzettend leuk en gezellig om samen met jou in de promovendiraad te zitten.

Al mijn collega’s van de 5e wil ik eveneens hartelijk danken voor de gezelligheid en de prettige werksfeer, waarbij ik Meirav Dagan in het bijzonder wil noemen. Meirav, I enjoy(ed) our biking trips and other get-togethers with you and Ishay.

Merlijne en mijn zusje Hinke: ik vind het erg leuk dat jullie mijn paranimfen willen zijn.

Tot slot mijn vrienden, (schoon)familie waaronder mijn heit en mem, pake, Hinke, Hendrik, David en natuurlijk mijn Ate: ik ben er erg trots op dat ik jullie nu eindelijk kan laten zien waar ik de afgelopen jaren mee bezig ben geweest.

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SHAREandpreviousdissertations

Groningen Graduate School of Medical Sciences - Research Institute SHARE

This thesis is published within the research program Health Psychology Research (HPR) of the Research Institute SHARE of the Groningen Graduate School of Medical Sciences (embedded in the University Medical Center Groningen / University of Groningen). More information regarding the institute and its research can be obtained from our internetsite: www.rug.nl/share.

Previous dissertations from the program Health Psychology Research:

Andela RM (2009) FrailtyintheclinicalpracticeofnursingcareSupervisors: prof dr R Sanderman, prof dr JPJ SlaetsCo-supervisor: dr A Dijkstra

Henselmans I (2009) Psychologicalwell-beingandperceivedcontrolafterabreastcancerdiagnosisSupervisors: prof dr AV Ranchor, prof dr R SandermanCo-supervisor: dr J de Vries

Dijk GC van (2008) CareofpeoplewhoarePowerlessinDailyLiving(PDLcare);atheoreticalapproachSupervisor: prof dr R SandermanCo-supervisor: dr A Dijkstra

Barbareschi G (2008) Socioeconomicstatusandthecourseofqualityoflifeincoronaryheartdiseaseandcancer;fromdescriptiontowardanexplanationSupervisor: prof dr R Sanderman

Hinnen SCH (2008) DistressandspousalsupportinwomenwithbreastcancerSupervisors: prof dr R Sanderman, prof dr AV Ranchor, prof dr M Hagedoorn

Visser A (2007) Children’sfunctioningfollowingparentalcancerSupervisors: prof dr HJ Hoekstra, prof dr WTA van der GraafCo-supervisor: dr JEHM Hoekstra-Weebers

Huizinga GA (2006) TheimpactofparentalcanceronchildrenSupervisor: prof dr HJ HoekstraCo-supervisors: dr JEHM Hoekstra-Weebers, dr WTA van der Graaf

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Dobre D (2006) TreatmentofheartfailureandpatientoutcomesinreallifeSupervisors: prof dr FM Haaijer-Ruskamp, prof dr R Sanderman, prof dr DJ van VeldhuisenCo-supervisors: dr AV Ranchor, dr MLJ de Jongste

Fleer J (2006) QualityoflifeoftesticularcancersurvivorsSupervisors: prof dr HJ Hoekstra, prof dr DTh Sleijfer, prof dr EC KlipCo-supervisor: dr JEHM Hoekstra-Weebers

Arnold R (2004) QualityoflifeinchronicobstructivepulmonarydiseaseandchronicheartfailureSupervisors: prof dr R Sanderman, prof dr GH KoëteCo-supervisors: dr AV Ranchor, dr MJL De Jongste

Keers JC (2004) Diabetesrehabilitation;effectsandutilisationofamultidisciplinaryeducationprogrammeSupervisors: prof dr R Sanderman, prof dr ROB GansCo-supervisors: dr J Bouma, dr TP Links

Pool G (2003) Survivingtesticularcancer;sexualityandotherexistentialissuesSupervisors: prof dr HBM van de Wiel, prof dr DTh Sleijfer, prof dr HJ HoekstraCo-supervisor: dr MF van Driel

Stiegelis HE (2003) Alifelessordinary;cognitiveadaptationandpsychologicalfunctioningamongcancerpatientstreatedwithradiotherapySupervisors: prof dr R Sanderman, prof dr AP BuunkCo-supervisor: dr M Hagedoorn

Heuvel ETP van den (2002) Supportingcaregiversofstrokepatients;aninterventionstudySupervisors: prof dr B Meyboom-de Jong, prof dr R SandermanCo-supervisors: dr LP de Witte, dr LM Schure

Schroevers MJ (2002) Short-andlong-termadaptationtocancer;acomparisonofpatientswithathegeneralpopulationSupervisor: prof dr R SandermanCo-supervisor: dr AV Ranchor

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Hoekstra-Weebers JEHM (2000) ParentaladaptationtopediatriccancerSupervisors: prof dr EC Klip, prof dr WA KampsCo-supervisor:: dr JPC Jaspers

Doeglas DM (2000) Functionalability,socialsupportandqualityoflife:alongitudinalstudyinpatientswithearlyrheumatoidarthritis Supervisors: prof dr WJA van den Heuvel, prof dr R SandermanCo-supervisor: dr ThPBM Suurmeijer

Nijboer C (2000) Caregiving to patients with colorectal cancer: a longitudinal study oncaregivingbypartnersSupervisors: prof dr GAM van den Bos, prof dr R SandermanCo-supervisor: dr AHM Triemstra

Tiesinga LJ (1999) Fatigue and Exertion Fatigue: from description through validation toapplicationoftheDutchFatigueScale(DUFS)andtheDutchExertionFatigueScale(DEFS)Supervisors: prof dr WJA van den Heuvel, prof dr ThWN DassenCo-supervisor: dr RJG Halfens

Jong GM de (1999)Stress,stressmanagementandissuesregardingimplementationSupervisors: prof dr PMG Emmelkamp, prof dr JL PescharCo-supervisor:: dr R Sanderman

Alberts JF (1998)Theprofessionalizedpatient:socioculturaldeterminantsofhealthservicesutilizationSupervisor: prof dr WJA van den HeuvelCo-supervisor: dr R Sanderman

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Documents

University of Groningen Psychosocial outcomes in diabetes ...9 Diabetes is a serious chronic disease that has evolved into a major public health issue. Treatment of diabetes consists