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Using games to identify adolescents at risk for substance misuse-a proof-of-concept study.

Kammarauche Aneni^1,2, Ching-Hua Chen³, Jenny Meyer¹

¹Yale Child Study Center, Yale School of Medicine, New Haven, CT, United States.

Frontiers in Health Services

|May 18, 2026

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Digital games show limited success in predicting adolescent substance use risk using gameplay data. Further research is needed to develop effective game-based digital biomarkers for early intervention.

Area of Science:

Adolescent health
Digital biomarkers
Substance use prevention

Background:

Early identification of adolescents at risk for substance use is crucial for intervention.
Traditional screening tools face barriers like adolescent reluctance and privacy concerns.
Digital games offer a low-burden method to collect behavioral data as potential digital biomarkers.

Purpose of the Study:

To explore the utility of game log data for predicting adolescent substance use.
To assess the feasibility of using gameplay-derived metrics as digital biomarkers.

Main Methods:

Analyzed game log data from 160 adolescents (ages 11-14) playing an HIV prevention game.
Extracted 240 behavioral metrics related to executive function, decision-making, and inhibitory control.

Keywords:

adolescents cognitive function digital biomarkers game-based assessment in-game data substance misuse substance use screening

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Trained machine learning models to predict substance use and drug-refusal self-efficacy.

Main Results:

Machine learning models demonstrated insufficient predictive accuracy for clinical use (mean AUC <0.6).
No model met the minimum threshold (AUC ≥0.7) for clinical utility.
Sensitivity and F-1 scores were also below clinically relevant levels for both substance use and self-efficacy prediction.

Conclusions:

Extracting reliable behavioral markers from naturalistic digital game environments presents significant challenges.
Game-based digital biomarkers hold potential for scalable screening but require further refinement.
Study limitations highlight areas for future research into the feasibility of in-game data for substance use risk assessment.