Predictive Validity of the Seasonal Beliefs Questionnaire for Discriminating Between Seasonal and Nonseasonal Major Depressive Disorder

PSYCHOLOGICAL ASSESSMENT(2021)

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摘要
The Seasonal Beliefs Questionnaire (SBQ) is a 26-item self-report measure of a winter seasonal affective disorder (SAD)-specific cognitive vulnerability consisting of maladaptive thoughts about the seasons, light availability, and weather conditions. In a known groups comparison, currently depressed adults with SAD had significantly higher SBQ scores than currently depressed adults with nonseasonal major depressive disorder (MDD) and healthy controls, and the MDD group had significantly higher SBQ scores than controls. Using that database, this study explored the predictive validity of using an SBQ cutoff score to differentiate SAD from MDD. Receiver operator characteristic curve analyses used SBQ total score to predict SAD versus MDD, SAD versus control, and MDD versus control status. The SBQ subscale combined score, derived from multivariable logistic regression with SBQ subscales, was examined as an alternative predictor. SBQ total score with a cutpoint of 132 had good predictive ability for distinguishing SAD from MDD (C-statistic = .792, sensitivity = .798, specificity = .794). The SBQ subscale combination score slightly improved predictive ability for the SAD/MDD distinction (C-statistic = .813), with better sensitivity (.930) but worse specificity (.571). In contrast, the score on a generic measure of depressogenic cognitive vulnerability, the Dysfunctional Attitudes Scale, was poor for differentiating SAD from MDD. SBQ total score was excellent in discriminating SAD cases from controls with a cutpoint of 121 (C-statistic = .962, sensitivity = .939, specificity .873), but had poor sensitivity for discriminating MDD cases from controls. Results support using the SBQ to screen for probable SAD in practice settings.
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关键词
seasonal beliefs,cognitive vulnerability,seasonal affective disorder screening,seasonal affective disorder detection,receiver operator characteristic curve analysis
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