Background: Substance use disorders (SUDs) are prevalent and compromise health and wellbeing. Scalable solutions, such as digital therapeutics, may offer a population-based strategy for addressing SUDs. Two formative studies supported the feasibility and acceptability of the relational agent Woebot, an animated screen-based social robot, for treating SUDs (W-SUDs) in adults. Participants randomized to W-SUDs reduced their substance use occasions from baseline to end-of-treatment (EOT) relative to a waitlist control.
Objective: To further develop the evidence base, the current randomized trial extends follow-up to 1-month post-treatment and will test the efficacy of W-SUDs relative to a psychoeducational control.
Methods: This study will recruit, screen, and consent 400 adults online reporting problematic substance use. Following baseline assessment, participants will be randomized to 8 weeks of W-SUDs or a psychoeducational control. Assessments will be conducted at weeks 4, 8 (EOT), and 12 (1-month post-treatment). Primary outcome is past-month number of substance use occasions, summed across all substances. Secondary outcomes are number of heavy drinking days, the percent of days abstinent from all substances, substance use problems, thoughts about abstinence, cravings, confidence to resist substance use, symptoms of depression and anxiety, and work productivity. If significant group differences are found, we will explore moderators and mediators of treatment effects.
Conclusions: The current study builds upon emerging evidence of a digital therapeutic for reducing problematic substance use by examining sustained effects and testing against a psychoeducational control condition. If efficacious, the findings have implications for scalable mobile health interventions for reducing problematic substance use.
Trial registration: NCT04925570.
Keywords: Artificial intelligence; Randomized controlled trial; Relational conversational agent; Substance-related disorders.
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