Wang Liyuan, Christensen John L, Jeong David C, Miller Lynn C
Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, 90007.
Department of Communication, University of Connecticut, Storrs, CT, 06269.
Comput Human Behav. 2019 Jan;90:388-396. doi: 10.1016/j.chb.2018.08.025. Epub 2018 Aug 13.
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.
叙事游戏中，用户与虚拟主体进行互动，这类游戏越来越多地被用于健康干预，以改变目标行为。在虚拟社交互动中，基于类似现实生活中的情境线索，过去的行为可以预测虚拟选择。在此，基于学习和互动理论，我们研究了在虚拟干预之后，社交互动中的选择是否可能对未来行为变化具有特别的诊断意义。为了验证这一点，我们需要：（1）针对目标受众（如同性恋男性中具有性风险的年轻男性（YMSM）），设计一个情境化风险（如涉及饮酒）场景（如与伴侣多喝一杯）；（2）在此情境中纳入基于证据的虚拟干预（如促进减少饮酒）；（3）在针对该目标受众的与智能体（IA）进行的虚拟约会游戏场景干预中设定并记录一个虚拟选择（水或酒）；（4）评估干预前及干预后6个月YMSM的饮酒情况。通过使用带有智能体（IA）和饮酒量测量的社会优化学习环境（SOLVE）干预游戏，我们发现虚拟选择水（相对于虚拟选择酒）能显著预测现实生活中的饮酒量变化。此外，人格因素（如行为趋近系统）能预测虚拟选择和饮酒量变化。我们对这些研究结果的意义进行了讨论。
