ESTABLISHING THE FEASIBILITY OF CROWDSOURCING TO STUDY VALUE-BASED DECISION-MAKING IN SUBSTANCE USE DISORDERS

Substance use disorders (SUDs) are characterized by repeated choices to use drugs despite adverse consequences. Value-based decision-making theory posits that choices are guided by predicted values of available options which are updated based on outcomes. Computational modeling of reinforcement learning (RL) during choice tasks has shown promise for uncovering latent mechanisms of decision-making. Recruiting people with SUD is difficult, but crowdsourcing offers an alternative for accelerating data collection. However, the validity of computational modeling using online choice task data has not been well-established. This thesis aimed to use the online crowdsourcing platform Prolific to 1) compare online and in-person choice data from non-SUD controls and 2) survey SUD histories of individuals to inform selection of future study samples. Averaged choice and trial-by-trial RL outcomes were tested for similarities using equivalence testing and for differences using null hypothesis testing. Evidence of value-based decision-making was observed online and in-person, although differences on key choice and RL outcomes (e.g., rich choices, perseveration estimates) indicated nonequivalence between groups. In addition, people endorsing problematic use of alcohol, cannabis, and nicotine were available on Prolific. Overall, these results support the feasibility of using crowdsourced data for studying RL mechanisms of decision-making in people with SUDs

546 Using Contingency Management to Understand the Cardiovascular, Immune and Psychosocial Benefits of Reduced Cocaine Use: A Protocol for a Randomized Controlled Trial

OBJECTIVES/GOALS: Contingency management (CM) procedures yield measurable reductions in cocaine use. This poster describes a trial aimed at using CM as a vehicle to show the biopsychosocial health benefits of reduced use, rather than total abstinence, the currently accepted metric for treatment efficacy. METHODS/STUDY POPULATION: In this 12-week, randomized controlled trial, CM was used to reduce cocaine use and evaluate associated improvements in cardiovascular, immune, and psychosocial well-being. Adults aged 18 and older who sought treatment for cocaine use (N=127) were randomized into three groups in a 1:1:1 ratio: High Value ($55) or Low Value ($13) CM incentives for cocaine-negative urine samples or a non-contingent control group. They completed outpatient sessions three days per week across the 12-week intervention period, totaling 36 clinic visits and four post-treatment follow-up visits. During each visit, participants provided observed urine samples and completed several assays of biopsychosocial health. RESULTS/ANTICIPATED RESULTS: Preliminary findings from generalized linear mixed effect modeling demonstrate the feasibility of the CM platform. Abstinence rates from cocaine use were significantly greater in the High Value group (47% negative; OR = 2.80; p = 0.01) relative to the Low Value (23% negative) and Control groups (24% negative;). In the planned primary analysis, the level of cocaine use reduction based on cocaine-negative urine samples will serve as the primary predictor of cardiovascular (e.g., endothelin-1 levels), immune (e.g., IL-10 levels) and psychosocial (e.g., Addiction Severity Index) outcomes using results from the fitted models. DISCUSSION/SIGNIFICANCE: This research will advance the field by prospectively and comprehensively demonstrating the beneficial effects of reduced cocaine use. These outcomes can, in turn, support the adoption of reduced cocaine use as a viable alternative endpoint in cocaine treatment trials