ArticleAddictive behaviors2022
A preliminary investigation of the role of intraindividual sleep variability in substance use treatment outcomes.
Article in Addictive behaviors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Sleep variability as an important marker of treatment outcomes in a clinical sample receiving psychotherapy treatment for alcohol use disorder.Alcohol, clinical & experimental research · 2026Article
- Reductions in World Health Organization risk drinking level are associated with improvements in sleep problems among individuals with alcohol use disorder.Alcohol and alcoholism (Oxford, Oxfordshire) · 2024Article
- Does sleep relate to next-day cannabis use during treatment? Findings from an adolescent and young adult motivational enhancement and cognitive behavioral therapy plus topiramate intervention.Drug and alcohol dependence · 2023Article
- Bidirectional associations between sleep and addiction across populations: Introduction to the special issue.Addictive behaviors · 2023Article
- Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students.Journal of sleep research · 2023Article
- Sleep and substance use: Practice considerations for social workers.Journal of social work practice in the addictions · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
introductionPoor sleep health is common among individuals in early treatment for substance use disorders (SUDs) and may serve an important role in predicting SUD outcomes. However, sleep parameters have been inconsistently linked with risk of relapse, perhaps because previous research has focused on mean values of sleep parameters (e.g., total sleep time [TST], sleep efficiency [SE], and sleep midpoint [SM]) across multiple nights rather than night-to-night fluctuations (i.e., intraindividual variability [IIV]). The current study assessed sleep across the first week of SUD treatment, with the aim of prospectively examining the relationship between mean and IIV of TST, SE, and SM and treatment completion and relapse within one-month post-treatment.
methodsTreatment-seeking adults (N = 23, M
resultsGreater IIV in TST was associated with higher odds of relapse (OR = 3.55, p =.028). Greater IIV in SM was associated with lower odds of treatment completion, but only when removing mean SM from the model (OR = 0.75, p =.046). DISCUSSION: Night-to-night variability in actigraphy-measured TST is more strongly associated with SUD treatment outcomes than average sleep patterns across the week. Integrating circadian regulation into treatment efforts to improve SUD treatment outcomes may be warranted. Given the small sample size utilized in the present study, replication of these analyses with a larger sample is warranted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.