Digital interventions for opioid use disorder treatment: A systematic review of randomized controlled trials.

INTRODUCTION: Opioid use disorders are associated with a high burden of disease and treatment gap. Digital interventions can be used to provide psycho-social treatment for opioid use disorders, as an alternative to or together with face-to-face interventions. This review aimed to assess the application and effectiveness of digital interventions to treat opioid use disorder globally. METHODS: The study team searched four electronic databases (PubMed, Psych INFO, Web of Science and Cochrane Central register of controlled trials). The inclusion criteria were: randomized controlled trials, assessment for opioid use before and at least once following intervention, and use of digital interventions. The primary outcomes were opioid use and/or retention in treatment, with data being summarized in tables and a narrative review presented. RESULTS: The initial database search yielded 3542 articles, of which this review includes 20. Nineteen were conducted among adults in the United States. The digital interventions used included web-based, computer-based, telephone calls, video conferencing, automated self-management system, mobile applications and text messaging. They were based on therapeutic education systems, community reinforcement approaches, cognitive behavior therapy, relapse prevention, brief interventions, supportive counselling and motivational interviewing. The studies had mixed findings; of the 20 studies, 10 had statistically significant differences between the treatment groups for opioid abstinence, and four had significant differences for treatment retention. Comparisons were difficult due to varying methodologies. Participants rated the interventions as acceptable and reported high rates of satisfaction. CONCLUSION: The use of digital interventions for opioid use disorder treatment was acceptable, with varying levels of effectiveness for improving outcomes, which is influenced by participant and intervention delivery factors. Further studies in different parts of the world should compare these findings, specifically in low- and middle-income countries.

The prevalence and pattern of cannabis use among patients attending a methadone treatment clinic in Nairobi, Kenya.

BACKGROUND: Cannabis use during methadone treatment may negatively impact treatment outcomes. The aim of this study was to determine the prevalence and pattern of cannabis use among patients attending a methadone treatment clinic in Nairobi, Kenya. METHODS: This was a retrospective study of 874 patients on methadone therapy at a methadone maintenance treatment clinic in Nairobi, Kenya from December 2014 to November 2018. Data on sociodemographic characteristics and drug use patterns based on urine drug screens was collected from patient files. Data was analyzed using Statistical Package for the Social Sciences (SPSS) for windows version 23.0. RESULTS: Point prevalence of cannabis use was 85.8% (95% CI, 83.3 - 88.0) at baseline and 62.7% (95% CI, 59.5 - 65.8) during follow-up. A pattern of polysubstance use was observed where opioids, cannabis and benzodiazepines were the most commonly used drugs. The mean age of the patients was 35.3 (SD 9.0) years with the majority being male, unemployed (76%), (51.4%) had reached primary level of education, and (48.5%) were divorced or separated. University education was associated with reduced risk for cannabis use OR = 0.1 (95% CI, 0.02-0.8, p = 0.031). CONCLUSION: Cannabis use is prevalent among patients attending a methadone treatment clinic in Kenya, suggesting need for targeted interventions to address the problem of cannabis use during methadone treatment.