Aims

This meta-analysis reviewed 15 clinical trials (18 study sites/arms), examining the efficacy of an integrated cognitive-behavioral intervention (CBI) delivered to individuals with an alcohol or other drug use disorder and a co-occurring mental health disorder (AOD/MHD). Outcomes were alcohol or other drug use and mental health symptoms at post-treatment through follow-up.

Methods

The inverse-variance weighted effect size was calculated for each study and pooled under random effects assumptions.

Results

Integrated CBI showed a small effect size for AOD (g = 0.188, P = 0.061; I2 = 86%, τ2 = 0.126, k = 18) and MHD (g = 0.169, P = 0.024; I2 = 58%, τ2 = 0.052, k = 18) outcomes, although only MHD outcomes were statistically significant. Analysis by subgroup suggested that effect magnitude varied by type of contrast condition (integrated CBI + usual care vs. usual care only; integrated CBI vs. a single-disorder intervention), follow-up time point (post-treatment vs. 3-6 months) and primary AOD/MHD diagnosis, although these sub-groups often contained significant residual heterogeneity. In a series of mixed effects, meta-regression models, demographic factors were non-significant predictors of between-study heterogeneity. For AOD outcomes, greater effects were observed in higher quality studies, but study quality was not related to effect size variability for MHD outcomes.

Conclusions

The current meta-analysis shows a small and variable effect for integrated CBI with the most promising effect sizes observed for integrated CBI compared with a single disorder intervention (typically an AOD-only intervention) for follow-up outcomes, and for interventions targeting alcohol use and/or post-traumatic stress disorder. Given the clinical and methodological variability within the sample, results should be considered a preliminary, but important step forward in our understanding of treatment for co-occurring AOD/MHD.

Objective

This meta-analysis examined 30 randomized controlled trials (32 study sites; 35 study arms) that tested the efficacy of cognitive-behavioral therapy (CBT) for alcohol or other drug use disorders. The study aim was to provide estimates of efficacy against three levels of experimental contrast (i.e., minimal [k = 5]; nonspecific therapy [k = 11]; specific therapy [k = 19]) for consumption frequency and quantity outcomes at early (1 to 6 months [kes = 41]) and late (8+ months [kes = 26]) follow-up time points. When pooled effect sizes were statistically heterogeneous, study-level moderators were examined.

Method

The inverse-variance weighted effect size was calculated for each study and pooled under random effects assumptions. Sensitivity analyses included tests of heterogeneity, study influence, and publication bias.

Results

CBT in contrast to minimal treatment showed a moderate and significant effect size that was consistent across outcome type and follow-up. When CBT was contrasted with a nonspecific therapy or treatment as usual, treatment effect was statistically significant for consumption frequency and quantity at early, but not late, follow-up. CBT effects in contrast to a specific therapy were consistently nonsignificant across outcomes and follow-up time points. Of 10 pooled effect sizes examined, two showed moderate heterogeneity, but multivariate analyses revealed few systematic predictors of between-study variance.

Conclusions

The current meta-analysis shows that CBT is more effective than a no treatment, minimal treatment, or nonspecific control. Consistent with findings on other evidence-based therapies, CBT did not show superior efficacy in contrast to another specific modality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background

Cognitive-behavioral therapy (CBT) has long-standing evidence for efficacy in the treatment of alcohol use, yet implementation in clinical practice has been challenging. Delivery of CBT through technology-based platforms, such as web-based programs and mobile applications, has the potential to provide widespread access to this evidence-based intervention. While there have been reviews indicating the efficacy of technology-based delivery of CBT for various psychiatric conditions, none have focused on efficacy for alcohol use. The current meta-analysis was conducted to fill this research gap.

Methods

Descriptive data were used to characterize the nature of the literature on technology-delivered, CBT-based interventions for alcohol use ("CBT Tech"). Inverse-variance-weighted effect sizes were calculated, and random effects, effect sizes were pooled in 4 subgroups.

Results

Fifteen published trials conducted primarily with at-risk or heavy drinkers were identified. Of these studies, 60% explicitly targeted alcohol use moderation. The content of CBT Tech programs varied, ranging from 4 to 62 sessions/exercises, with many programs combining elements of motivational interviewing (47%). With respect to efficacy, CBT Tech as a stand-alone treatment in contrast to a minimal treatment control showed a positive and statistically significant, albeit small effect (g = 0.20: 95% CI = 0.22, 0.38, k_es  = 5). When CBT Tech was compared to treatment as usual (TAU), effects were nonsignificant. However, when CBT Tech was tested as an addition to TAU, in contrast to TAU only, the effect size was positive, significant (g = 0.30: 95% CI = 0.10, 0.50, k_es  = 7), and stable over 12-month follow-up. Only 2 studies compared CBT Tech to in-person CBT, and this pooled effect size did not suggest superior efficacy.

Conclusions

These results show a benefit for technology-delivered, CBT-based interventions as a stand-alone therapy for heavy drinking or as an addition to usual care in specialty substance use settings.

This manuscript aims to contribute to the next phase of mechanisms of behavior change (MOBC) science on alcohol or other drug use. Specifically, we encourage the transition from a basic science orientation (i.e., knowledge generation) to a translational science orientation (i.e., knowledge application or Translational MOBC Science). To inform that transition, we examine MOBC science and implementation science and consider how these two research areas can intersect to capitalize on the goals, strengths, and key methodologies of each. First, we define MOBC science and implementation science and offer a brief historical rationale for these two areas of clinical research. Second, we summarize similarities in rationale and discuss two scenarios where one draws from the other-MOBC science on implementation strategy outcomes and implementation science on MOBC. We then focus on the latter scenario, and briefly review the MOBC knowledge base to consider its readiness for knowledge translation. Finally, we provide a series of research recommendations to facilitate the translation of MOBC science. These recommendations include: (1) identifying and targeting MOBC that are well suited for implementation, (2) use of MOBC research results to inform broader health behavior change theory, and (3) triangulation of a more diverse set of research methodologies to build a translational MOBC knowledge base. Ultimately, it is important for gains borne from MOBC science to affect direct patient care, while basic MOBC research continues to be developed and refined over time. Potential implications of these developments include greater clinical significance for MOBC science, an efficient feedback loop between clinical research methodologies, a multi-level approach to understanding behavioral change, and reduced or eliminated siloes between MOBC science and implementation science.

Background

The development and approval of an efficacious pharmacotherapy for stimulant use disorders has been limited by the lack of a meaningful indicator of treatment success, other than sustained abstinence.

Methods

In March, 2015, a meeting sponsored by Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) was convened to discuss the current state of the evidence regarding meaningful outcome measures in clinical trials for stimulant use disorders. Attendees included members of academia, funding and regulatory agencies, pharmaceutical companies, and healthcare organizations. The goal was to establish a research agenda for the development of a meaningful outcome measure that may be used as an endpoint in clinical trials for stimulant use disorders.

Results and conclusions

Based on guidelines for the selection of clinical trial endpoints, the lessons learned from prior addiction clinical trials, and the process that led to identification of a meaningful indicator of treatment success for alcohol use disorders, several recommendations for future research were generated. These include a focus on the validation of patient reported outcome measures of functioning, the exploration of patterns of stimulant abstinence that may be associated with physical and/or psychosocial benefits, the role of urine testing for validating self-reported measures of stimulant abstinence, and the operational definitions for reduction-based measures in terms of frequency rather than quantity of stimulant use. These recommendations may be useful for secondary analyses of clinical trial data, and in the design of future clinical trials that may help establish a meaningful indicator of treatment success.