Beliefs about causes of major depression: Clinical and treatment correlates among African Americans in an urban community.

JOURNAL OF CLINICAL PSYCHOLOGY(2018)

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摘要
ObjectivesMajor depression is increasingly viewed in the United States public as a medical disorder with biological and psychosocial causes. Yet little is known about how causal attributions about depression vary among low-income racial minorities. This study examined beliefs about causes of depression and their demographic, clinical and treatment correlates in a lower income African American sample. MethodVolunteers (N=110) aged 24-79 years, who participated in a family study of depression, completed a 45-item questionnaire on their beliefs about the causes of depression. We used multidimensional scaling (MDS) to cluster items into causal domains and multivariate regression analyses to test associations of causal domains with demographic and clinical characteristics and treatments received. ResultsThree causal domains, conceptualized as Eastern culture/supernatural (ECS), Western culture/natural/psychosocial (WCN-P), and /neurobiological (WCN-N) attributions, were derived from MDS clusters. WCN-P was most commonly endorsed (50%-91%) and ECS least endorsed as causes of depression (10-44%). This pattern held across gender, age, educational levels, and diagnostic category. WCN-N items were moderately endorsed, with some distinction between genetic causes and other biological causes. WCN-N was positively associated with medication as opposed to other forms of treatment (B=1.17; p=.049). ConclusionAmong low-income African Americans, beliefs about causes of depression are varied but broadly consistent explanatory models that include a combination of psychosocial causes with genetic/biological contributions. For certain individuals, supernatural and natural causal attributions may coexist without dissonance. Causal attributions may be associated with types of treatment accepted and have implications for treatment compliance and adherence.
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关键词
Blacks,causal attributions,cluster analysis,depression,illness perceptions
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