ArticleAlcohol, clinical & experimental research2026
Sleep variability as an important marker of treatment outcomes in a clinical sample receiving psychotherapy treatment for alcohol use disorder.
Article in Alcohol, clinical & experimental research, 2026. 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 highly prevalent among individuals with alcohol use disorder (AUD). Although sleep often improves during AUD treatment, associations with treatment outcomes have been inconsistent and have focused primarily on mean sleep parameters rather than daily within-person variability. Sleep variability is an emerging marker of physiological dysregulation and is linked to negative symptoms that may sustain alcohol use.
methodsAdults with AUD (N = 80) completed a 7-day daily sleep diary and clinical assessments before and after a 12-session outpatient psychotherapy treatment for AUD. Multilevel models examined pre- to post-treatment changes in sleep variability. Multiple regression models tested whether changes in sleep variability predicted changes in alcohol use and psychosocial outcomes. All analyses used Bayesian estimation.
resultsVariability in sleep onset latency (SOL; estimate = -4.43, 95% CI [-7.12, -1.40]), sleep midpoint (estimate = -18.77, 95% CI [-31.29, -4.13]), sleep efficiency (estimate = -1.87, 95% CI [-3.01, -0.61]), and number of awakenings (estimate = -0.17, 95% CI [-0.29, -0.04]) decreased across treatment. Variability in SOL emerged as the most robust predictor, with greater reductions in variability in SOL being associated with greater reductions in percentage drinking days (estimate = 0.01, 95% CI [0.001, 0.02]), drinks per drinking day (estimate = 0.10, 95% CI [0.001, 0.20]), and negative consequences from alcohol use (estimate = 0.51, 95% CI [0.24, 0.79]). Notably, improvements in mean-level sleep parameters were not associated with improvements in any treatment outcomes.
conclusionsThese results suggest that sleep variability, particularly in SOL, may be an important marker of treatment response and a potential target for future intervention above and beyond mean-value sleep parameters. Future research would benefit from further examination into what drives changes in sleep variability as well as potential added benefits of adapting AUD treatments to include components that target sleep consistency.
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