There is extensive literature establishing the influence of rumination, hopelessness, and dysfunctional attitudes on depressive symptoms. However, it is unclear whether these vulnerability factors are distinctly related to depressive symptoms or show substantial overlap. In two large samples of undergraduates (Study #1, n = 304; Study #2, n = 491) and two samples of clinically depressed individuals (Study #3, n = 141; Study #4, n = 109, from published studies), questionnaire data were used to examine the relationship between cognitive vulnerability factors and depressive symptoms, along with additional measures of anxiety and stress symptoms. To decompose model fit into its specific and common partitions, we relied on commonality analysis (CA). CA showed that there is substantial overlap in cognitive risk factors for depression. Moreover, we found strong evidence that hopelessness provides a unique statistical contribution to depression. This pattern of findings was stable in healthy as well as clinical samples. Symptom-levels analysis revealed that a specific subset of depressive symptoms are associated with hopelessness. In closing, we showed that CA provides a powerful tool to map unique and overlapping variance between multiple risk factors. Moreover, hopelessness emerged to be an important focus of clinical attention.

Unveiling the structure of cognitive vulnerability for depression: Specificity and overlap

Marchetti, Igor
;
2016-01-01

Abstract

There is extensive literature establishing the influence of rumination, hopelessness, and dysfunctional attitudes on depressive symptoms. However, it is unclear whether these vulnerability factors are distinctly related to depressive symptoms or show substantial overlap. In two large samples of undergraduates (Study #1, n = 304; Study #2, n = 491) and two samples of clinically depressed individuals (Study #3, n = 141; Study #4, n = 109, from published studies), questionnaire data were used to examine the relationship between cognitive vulnerability factors and depressive symptoms, along with additional measures of anxiety and stress symptoms. To decompose model fit into its specific and common partitions, we relied on commonality analysis (CA). CA showed that there is substantial overlap in cognitive risk factors for depression. Moreover, we found strong evidence that hopelessness provides a unique statistical contribution to depression. This pattern of findings was stable in healthy as well as clinical samples. Symptom-levels analysis revealed that a specific subset of depressive symptoms are associated with hopelessness. In closing, we showed that CA provides a powerful tool to map unique and overlapping variance between multiple risk factors. Moreover, hopelessness emerged to be an important focus of clinical attention.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2935606
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