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Background and aims: Sleep disruptions increase the risk of substance misuse. Substance use-especially stimulants-can increase acute and chronic sleep dysfunction. This study aimed to estimate the associations between sleep disturbance and stimulant use over time among participants with stimulant use disorder (StUD).
Design: In this secondary analysis, a Random Intercept Cross-Lagged Panel Model (RI-CLPM) was used to assess sleep disturbance and stimulant use over 8 weeks among participants with StUD.
Setting: United States of America.
Participants: The analysis included 793 participants with StUD enrolled across 3 randomized controlled trials in the National Institute on Drug Abuse’s Clinical Trials Network (CTN): CTN-0037, CTN-0048 and CTN-0068.
Measurements: Self-reported sleep disturbance was harmonized as a binary indicator across trial measures at each week. Stimulant use days per week were captured by Timeline Follow Back. Baseline covariates included age, sex, race/ethnicity, employment status, presence of depressive symptoms, any psychiatric history, treatment arm and trial.
Findings: Sleep disturbance was associated with a higher average number of stimulant use days the following week [β = 0.15, 95% confidence interval (CI) = 0.09, 0.22, P < 0.001], and greater stimulant use was linked to increased odds of subsequent sleep disturbance (odds ratio = 1.20, 95% CI = 1.14, 1.26, P < 0.001).
Conclusions: Higher-than-usual stimulant use appears to be associated with increased likelihood of sleep disturbance the following week, and vice versa.
Related protocols: CTN-0037, CTN-0048, CTN-0068
Sleep disturbance may play a role in cocaine use outcomes and, hence, may be a potential therapeutic target for cocaine use disorder (CUD). Research in this area, which has largely relied on resource-intensive polysomnography, would be facilitated by identifying a self-report sleep measure predictive of CUD outcomes and by a better understanding of the mechanisms by which sleep may impact CUD outcomes.
This study, a secondary analysis of CTN-0046 (Smoking Cessation and Stimulant Treatment), tested the predictive validity of the Pittsburgh Sleep Quality Index (PSQI), a self-report assessment of past-month sleep quality. To better understand potential mechanisms, mediation models relating sleep disturbance to CUD outcomes were evaluated.
The PSQI was collected at baseline; the outcomes of interest were cocaine and drug abstinence at end-of-treatment (weeks 9-10). Potential mediators, measured in weeks 1-8, were: cocaine craving (Brief Substance Craving Scale); and anxiety and depression symptoms (Hospital Anxiety and Depression Scale). Mediation techniques were used to evaluate mediation effects separately and jointly.
The majority of participants (58.3%) had baseline sleep disturbance. Sleep disturbance was not a significant predictor of end-of-treatment abstinence when regressed without consideration of mediators. Cocaine craving, anxiety, and depression were significant mediators, both separately and jointly, of an effect of baseline sleep disturbance on end-of-treatment abstinence.
Conclusions: This exploratory analysis suggests that there may be an indirect relationship between self-reported sleep quality and substance use outcomes in cocaine-dependent patients, mediated by craving, anxiety, and depression.
Related protocols: CTN-0046
This is the Results Article for CTN-0057-Ot.
The majority of the U.S. health care resources are utilized by a small population characterized as high-risk, high-need persons with complex care needs (e.g., adults with multiple chronic conditions). Substance use disorders (SUDs) and mental health disorders (MHDs) are a driver of poor health and additional healthcare costs, but they are understudied among high-need patients. This study examined the prevalence and correlates of SUDs and MHDs among adults with high-risk diabetes, who are patients at the top 10% risk score for developing poor outcomes (hospital admission or death). A risk algorithm developed from Duke University Health System electronic health record (EHR) data was used to identify patients with high-risk diabetes for targeting home-based primary care. The EHR data of the 263 patients with high-risk diabetes were analyzed to understand patterns of SUDs and MHDs to inform care-coordinating efforts
Results found that both SUDs and MHDs were prevalent:
- Any SUD: 48.3%; Alcohol: 12.5%; Tobacco: 38.8%; Drug: 23.2%
- Any MHD: 74.9%; Mood: 53.2%; Sleep: 37.3%; Anxiety: 32.7%; Schizophrenia/Psychotics/Delusional: 14.8%; Dementia/Delirium/Amnestic/Cognitive: 14.4%; Adjustment: 9.1%
Overall, 81% of the same had SUD or MHD. Elevated odds of SUD were noted among men (tobacco, alcohol) and those who were never married (alcohol, cannabis). African American race (vs. other race/ethnicity) was associated with lower odds of anxiety disorders.
Conclusions: This study is the first to document a comprehensive pattern of SUD and MHD prevalence among adults with high-risk diabetes. While data are limited to one large academic health system, they provide clinical evidence revealing that 82% of patients with high-risk diabetes had SUD and/or MHD record in their EHRs, highlighting a need for developing service models to optimize high-risk care.
Related protocols: CTN-0057-Ot
This study examined the longitudinal association between reductions in cannabis use and changes in anxiety, depression, sleep quality, and quality of life. Secondary analyses were conducted based on data from a cannabis use disorder medication trial in 302 adults, NIDA Clinical Trials Network protocol CTN-0053, Achieving Cannabis Cessation: Evaluating N-Acetylcysteine Treatment (ACCENT). Changes in symptoms of anxiety and depression, sleep quality, and quality of life were assessed in relation to changes in cannabis use during the 12-week trial of treatment.
Based on the slope of individual cannabis use trajectory, the sample was classified into two groups (Cannabis Use Reduction, n=152 vs. Cannabis Use Increase, n=150) which was included as a binary covariate in subsequent modeling. Controlling for demographics (age, gender, race/ethnicity), treatment condition, and time-varying tobacco and alcohol use, separate latent growth curve models showed a significant association between the Cannabis Use Reduction group and improvement (i.e., lower values in slope) in anxiety, depression, and sleep quality over the observation period, but not in quality of life.
Conclusions: These results indicate a longitudinal relationship between reductions in cannabis use and improvements in anxiety, depression, and sleep quality. Clinicians treating patients with co-occurring cannabis use and problems with anxiety, depression, or sleep quality should attend to cannabis use reduction as a component of treatment.
Related protocols: CTN-0053
Sleep disruption appears not only to reflect a symptom of posttraumatic stress disorder (PTSD), but also a unique vulnerability for its development and maintenance. Studies examining the impact of psychosocial treatments for PTSD on sleep symptoms are few and no studies to date have examined this question in samples with co-occurring substance use disorders. This study is a secondary analysis of a large clinical trial comparing two psychological treatments for co-occurring PTSD and substance use disorders (National Drug Abuse Treatment Clinical Trials Network protocol CTN-0015, “Women’s Treatment for Trauma and Substance Use Disorders”). Women (n=353) completed measures of PTSD at baseline, end of treatment, and 3-, 6-, and 12-month follow-ups. Results indicated that the prevalence of insomnia, but not nightmares, decreased during treatment, and that 63.8% of participants reported at least 1 clinical-level sleep symptom at the end of treatment. Improvement in sleep symptoms during treatment was associated with better overall PTSD outcomes over time.
Conclusions: These results extend the existing literature to suggest that residual sleep disruption following PTSD treatment is common in women with co-occurring PTSD and substance use disorders. Although based on the design of the study, no causal conclusions can be drawn, the findings imply that among those with clinical-level residual sleep disruption, risk for continuation or exacerbation of overall PTSD symptoms may be higher. Consideration of the addition of interventions targeted to sleep disruption may be indicated in those with PTSD and SUD, or considered as an adjunctive intervention if residual sleep disruption is present at the time of treatment completion.
Related protocols: CTN-0015