Are illness perceptions about coronary artery disease predictive of depression and quality of life outcomes?☆
Introduction
Coronary artery disease (CAD) is a leading cause of disability in many developed countries, including Australia, where it is the foremost source of total disease burden [1]. Compelling epidemiological evidence indicates disproportionately high rates of depression in patients with CAD [2], [3], [4], [5], [6], [7], [8] and shows that this co-morbidity is associated with at least a twofold increased risk for future cardiac events [2], [9], [10], [11]. Despite recognition of the prevalence and prognostic significance of depression in patients with CAD, relatively little is known about psychosocial factors involved in the aetiology of depression in this population. Several studies have examined the associations between disease-related [5], [12], [13], [14] and socio-demographic risk factors [15], [16], [17], [18] and depression, but the therapeutic value of these data is limited by the inability to modify these variables to improve outcome. The identification of modifiable determinants of depression in CAD patients is therefore a priority.
One promising psychological approach relates to patients' personal beliefs about their illness. Mounting empirical evidence from a range of disease groups (e.g., cancer, psoriasis, asthma, diabetes, haemophilia, and chronic fatigue syndrome [19], [20], [21], [22], [23], [24]), including CAD [25], [26], [27], [28], [29], [30], [31], [32], suggests that these illness beliefs are key determinants of recovery and may represent a potential target for clinical intervention. The association between these personal illness perceptions and recovery is based on a theory of self-regulation [33] that posits individuals as active problem solvers who, in response to illness and other health threats, develop parallel cognitive and emotional representations of the threat. These cognitive illness representations include the number and actual experience of symptoms endorsed as being part of the illness as well as the abstract label given to these symptoms (identity); expectations about the likely duration of the illness (timeline); beliefs about the physical, social, and emotional effects (consequences); perceptions of the extent to which it is amenable to cure or/and control; and beliefs regarding the cause(s) of the condition. According to the theory [33], these combined illness representations provide patients with a conceptual framework in which to process health care advice, which, in turn, determines adjustment to illness.
Amongst patients with CAD, illness beliefs have predominantly been investigated in relation to their impact on adherence to health behaviours, particularly attendance at cardiac rehabilitation [25], [26], [27], [28], [29], [32]. The association between beliefs about CAD and depression has received little attention [25], [29], [30], [31]. One prior study (N=105) investigated the prospective association between illness beliefs and depression and found that changes in angina beliefs over 1 year made near significant contributions (P=.06) to the variance in depressive symptomatology on the Hospital Anxiety and Depression Scale (HADS) [34]. Illness beliefs may impact on other outcomes including health-related quality of life (HRQOL). HRQOL is increasingly recognized as a valued outcome in CAD patients [35], [36] and is reported to predict cardiac end points [37], [38], [39].
The primary aim of the present study was to further investigate the association between illness beliefs and depression. As a secondary outcome, the present study also investigated the extent to which illness beliefs are associated with HRQOL. Since no prior study has investigated illness beliefs in an Australian sample, we also investigated whether these beliefs vary with gender, socioeconomic status (SES), and age.
Consistent with cognitive theories of depression that posit negative cognitive appraisals as a vulnerability for depression [40], [41], we hypothesized that negative or catastrophic perceptions about CAD would predict greater depressive symptomatology. It was also hypothesized that more positive illness appraisals would predict better HRQOL.
Section snippets
Method
To investigate our hypotheses, we conducted a study with recently hospitalized CAD patients in which clinical variables (CAD disease severity, smoking, and co-morbid diabetes) and known socio-demographic (gender [5], [15], [17], [42], age [15], [16], [18], [43], SES [42], [44], [45]) and psychosocial (social support [5], [15], [46], [47], neuroticism [48], [49], [50]) correlates of depression and HRQOL were controlled a priori. Outcome was assessed at two time points to enable analysis of the
Characteristics of the sample
T1 questionnaires were completed by 193 (84%) of the 229 recruited patients. This translates to 37% of the original number of patients treated during the study period, including patients deceased at recruitment and those not eligible for participation. Compared to these nonparticipants, participants were significantly more likely to be male [χ2(1, N=528)=5.93, P=.02] and were, on average, younger [t(526)=3.12, P<.01]. The mean (S.D.) age for participants vs. nonparticipants was 64.14 (10.37)
Discussion
Consistent with our a priori predictions, negative illness appraisals, particularly those associated with the consequences of CAD, were predictive of higher levels of depressive symptomatology at 3 and 9 months following discharge from hospital. This association was statistically significant in the presence of well-known clinical and demographic correlates of depression and the psychosocial risk factors of neuroticism and social support. Although beliefs about consequences contributed modestly
Conclusion
Our findings suggest that illness beliefs are significantly associated with depressive symptomatology and HRQOL in CAD patients. Illness beliefs constitute a meaningful and clinically accessible avenue for improving psychological morbidity and HRQOL in CAD patients, possibly with mitigating effects on cardiac prognosis. It is appropriate for researchers to translate these and other positive findings into interventions of the type described above.
Acknowledgments
We acknowledge Jeromy Anglim for his statistical advice.
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The authors wish to thank the University of Melbourne for their financial contribution to this project.