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Aneni K, Chen CH, Meyer J, Cho YT, Lipton ZC, Kher S, Jiao MG, Gomati de la Vega I, Umutoni FA, McDougal RA, Fiellin LE. Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study. JMIR Res Protoc 2023; 12:e46990. [PMID: 37995115 DOI: 10.2196/46990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 09/06/2023] [Accepted: 10/03/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND 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. OBJECTIVE 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.
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Affiliation(s)
- Kammarauche Aneni
- 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
| | - Ching-Hua Chen
- Center for Computational Health, IBM Research, Yorktown Heights, NY, United States
| | - Jenny Meyer
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Fairfield University, Fairfield, CT, United States
| | - Youngsun T Cho
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Zachary Chase Lipton
- Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburg, PA, United States
| | | | - Megan G Jiao
- McGovern Medical School, UTHealth Houston, Houston, TX, United States
| | | | | | - Robert A McDougal
- Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, United States
- Yale School of Public Health, New Haven, CT, United States
| | - Lynn E Fiellin
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Yale School of Public Health, New Haven, CT, United States
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
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Sulaman I, Hartley S, Elvins R. Therapeutic alliance in the treatment of adolescent substance misuse: a systematic review. Child Adolesc Ment Health 2023. [PMID: 37528449 DOI: 10.1111/camh.12671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/24/2023] [Indexed: 08/03/2023]
Abstract
BACKGROUND Therapeutic alliance has been found to play an influential role in predicting outcomes for adults and adolescents in psychotherapy. However, thus far, the information concerning the impact of therapeutic alliance on outcomes for adolescents in treatment for substance misuse has not yet been critically synthesised. METHODS In accordance with PRISMA guidelines, the current review aimed to systematically collate published research investigating the association between alliance and outcomes for adolescents undergoing substance misuse treatment. Database searching produced 1083 records, with 16 studies meeting eligibility criteria. RESULTS Twelve out of the 16 studies (75%) reported significant alliance-outcome relationships, whereby higher alliance ratings predicted better treatment outcomes, as well as improved engagement and retention in treatment. In addition, the review explored the conditions whereby alliances better predict outcomes, with reference to the alliance rater, the timing of the alliance rating and comorbid diagnoses. These results, however, largely remain inconclusive. CONCLUSIONS The evidence as it stands demonstrates the importance of the therapeutic alliance in predicting outcomes for adolescents in substance misuse treatments. The implications of the review's findings and recommendations for future research are discussed.
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Affiliation(s)
- Iniyah Sulaman
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
- GMMH NHS Foundation Trust, Manchester, UK
| | - Samantha Hartley
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
- CAMHS at Pennine Care NHS Foundation Trust, Manchester, UK
| | - Rachel Elvins
- Royal Manchester Children's Hospital & Salford CAMHS, Manchester, UK
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