Aneni Kammarauche, Chen Ching-Hua, Meyer Jenny, Cho Youngsun T, Lipton Zachary Chase, Kher Saatvik, Jiao Megan G, Gomati de la Vega Isabella, Umutoni Feza Anaise, McDougal Robert A, Fiellin Lynn E
Child Study Center, Yale School of Medicine, New Haven, CT, United States.
Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, United States.
JMIR Res Protoc. 2023 Nov 23;12:e46990. doi: 10.2196/46990.
Adolescents at risk for substance misuse are rarely identified early due to existing barriers to screening that include the lack of time and privacy in clinic settings. Games can be used for screening and thus mitigate these barriers. Performance in a game is influenced by cognitive processes such as working memory and inhibitory control. Deficits in these cognitive processes can increase the risk of substance use. Further, substance misuse affects these cognitive processes and may influence game performance, captured by in-game metrics such as reaction time or time for task completion. Digital biomarkers are measures generated from digital tools that explain underlying health processes and can be used to predict, identify, and monitor health outcomes. As such, in-game performance metrics may represent digital biomarkers of cognitive processes that can offer an objective method for assessing underlying risk for substance misuse.
This is a protocol for a proof-of-concept study to investigate the utility of in-game performance metrics as digital biomarkers of cognitive processes implicated in the development of substance misuse.
This study has 2 aims. In aim 1, using previously collected data from 166 adolescents aged 11-14 years, we extracted in-game performance metrics from a video game and are using machine learning methods to determine whether these metrics predict substance misuse. The extraction of in-game performance metrics was guided by literature review of in-game performance metrics and gameplay guidebooks provided by the game developers. In aim 2, using data from a new sample of 30 adolescents playing the same video game, we will test if metrics identified in aim 1 correlate with cognitive processes. Our hypothesis is that in-game performance metrics that are predictive of substance misuse in aim 1 will correlate with poor cognitive function in our second sample.
This study was funded by National Institute on Drug Abuse through the Center for Technology and Behavioral Health Pilot Core in May 2022. To date, we have extracted 285 in-game performance metrics. We obtained institutional review board approval on October 11, 2022. Data collection for aim 2 is ongoing and projected to end in February 2024. Currently, we have enrolled 12 participants. Data analysis for aim 2 will begin once data collection is completed. The results from both aims will be reported in a subsequent publication, expected to be published in late 2024.
Screening adolescents for substance use is not consistently done due to barriers that include the lack of time. Using games that provide an objective measure to identify adolescents at risk for substance misuse can increase screening rates, early identification, and intervention. The results will inform the utility of in-game performance metrics as digital biomarkers for identifying adolescents at high risk for substance misuse.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46990.
由于存在筛查障碍，包括临床环境中缺乏时间和隐私，有药物滥用风险的青少年很少能被早期识别。游戏可用于筛查，从而减轻这些障碍。游戏中的表现受工作记忆和抑制控制等认知过程的影响。这些认知过程的缺陷会增加药物使用的风险。此外，药物滥用会影响这些认知过程，并可能影响游戏表现，游戏表现可通过反应时间或任务完成时间等游戏内指标来衡量。数字生物标志物是从数字工具中生成的测量值，可解释潜在的健康过程，并可用于预测、识别和监测健康结果。因此，游戏内表现指标可能代表认知过程的数字生物标志物，可为评估药物滥用的潜在风险提供一种客观方法。
这是一项概念验证研究的方案，旨在调查游戏内表现指标作为与药物滥用发展相关的认知过程的数字生物标志物的效用。
本研究有两个目标。在目标1中，我们使用之前从166名11至14岁青少年收集的数据，从一款电子游戏中提取游戏内表现指标，并使用机器学习方法来确定这些指标是否能预测药物滥用。游戏内表现指标的提取以对游戏内表现指标的文献综述和游戏开发者提供的游戏指南为指导。在目标2中，我们将使用来自30名玩同一电子游戏的青少年新样本的数据，测试在目标1中确定的指标是否与认知过程相关。我们的假设是，在目标1中能预测药物滥用的游戏内表现指标将与我们第二个样本中的认知功能差相关。
本研究由美国国家药物滥用研究所通过技术与行为健康试点核心中心于2022年5月资助。截至目前，我们已提取了285个游戏内表现指标。我们于2022年10月11日获得了机构审查委员会的批准。目标2的数据收集正在进行中，预计于2024年2月结束。目前，我们已招募了12名参与者。目标2的数据分析将在数据收集完成后开始。两个目标的结果将在后续出版物中报告，预计于2024年底发表。
由于包括时间不足在内的障碍，对青少年进行药物使用筛查并未始终如一开展。使用能够提供客观测量方法以识别有药物滥用风险青少年的游戏，可以提高筛查率、早期识别率和干预率。研究结果将为游戏内表现指标作为识别药物滥用高风险青少年的数字生物标志物的效用提供依据。
国际注册报告识别码（IRRID）：DERR1-10.2196/46990。
