Virtual prognostication: When virtual alcohol choices predict change in alcohol consumption over 6-months

Narrative games, in which users interact with virtual agents, are increasingly being used in health interventions to change targeted behaviors. In virtual social interactions, based on similar real-life contextual cues, past behavior can predict virtual choices. Here, based on theories in learning and interactivity, we examined the whether following a virtual intervention, choices in social interactions may be particularly diagnostic of future behavior changes. To test this, we needed to: (1) leverage a contextualized risk (e.g., involving alcohol consumption) scenario (e.g., having one more drink with my partner) given a target audience (e.g., sexually risky young men who have sex with men (YMSM)), (2) include within this context an evidence-based virtual intervention (e.g., promoting alcohol reduction), (3) instantiate and record a virtual choice (water or alcohol) in a virtual dating game scenario intervention with IA for that target audience, and (4) assess pre and 6-months post-intervention YMSM's alcohol use. Using a Socially Optimized Learning Environment (SOLVE) intervention game with IA and alcohol use measures, we found that virtual water choice (versus virtual alcohol choice) significantly predicted real-life alcohol consumption change. Furthermore, personality factors (e.g., Behavioral Approach System) predicted virtual choices and alcohol consumption change. Implications of these findings are discussed.