ReviewJournal of affective disorders2025
The sleep-anxiety dysregulation model of alcohol use disorder risk: A nine-year longitudinal machine learning study.
Review in Journal of affective disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSleep disturbances are a known risk factor for alcohol use, yet their long-term predictive value for alcohol use disorder (AUD)-especially in the context of co-occurring anxiety symptoms-remains understudied. The present study thus applied machine learning with internal validation to evaluate how sleep disturbances predict nine-year AUD symptoms in midlife adults. It also introduces the Sleep-Anxiety Dysregulation Model of AUD Risk, which posits that sleep and anxiety symptoms confer shared vulnerability via disrupted arousal regulation.
methodCommunity-dwelling midlife adults (N = 1,054) completed clinical interviews, self-reports, and a seven-day actigraphy protocol to assess demographics, psychiatric symptoms, anxiety severity, subjective sleep, and objective actigraphy sleep indices. A five-fold nested cross-validated random forest identified potentially nonlinear and interactive predictors. The baseline model included 41 variables.
resultsThe final multivariable model explained over two-fifths of the variance in nine-year AUD symptoms (R
conclusionsResults underscore the shared contribution of sleep and anxiety disturbances to long-term AUD risk. The proposed Sleep-Anxiety Dysregulation Model of AUD Risk offers an integrative framework suggesting that AUD symptoms may emerge via chronic arousal dysregulation, including heightened physiological reactivity. Externally validating this model may inform preventive strategies targeting distal risk processes underlying AUD.
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