Game Design, Effectiveness, and Implementation of Serious Games Promoting Aspects of Mental Health Literacy Among Children and Adolescents: Systematic Review
Bibliographic record
Abstract
BACKGROUND: The effects of traditional health-promoting and preventive interventions in mental health and mental health literacy are often attenuated by low adherence and user engagement. Gamified approaches such as serious games (SGs) may be useful to reach and engage youth for mental health prevention and promotion. OBJECTIVE: This study aims to systematically review the literature on SGs designed to promote aspects of mental health literacy among adolescents aged 10 to 14 years, focusing on game design characteristics and the evaluation of user engagement, as well as efficacy, effectiveness, and implementation-related factors. METHODS: We searched PubMed, Scopus, and PsycINFO for original studies, intervention development studies, and study protocols that described the development, characteristics, and evaluation of SG interventions promoting aspects of mental health literacy among adolescents aged 10 to 14 years. We included SGs developed for both universal and selected prevention. Using the co.LAB framework, which considers aspects of learning design, game mechanics, and game design, we coded the design elements of the SGs described in the studies. We coded the characteristics of the evaluation studies; indicators of efficacy, effectiveness, and user engagement; and factors potentially fostering or hindering the reach, efficacy and effectiveness, organizational adoption, implementation, and maintenance of the SGs. RESULTS: We retrieved 1454 records through database searches and other sources. Of these, 36 (2.48%) studies describing 17 distinct SGs were included in the review. Most of the SGs (14/17, 82%) were targeted to a universal population of youth, with learning objectives mainly focusing on how to obtain and maintain good mental health and on enhancing help-seeking efficacy. All SGs were single-player games, and many (7/17, 41%) were embedded within a wider pedagogical scenario. Diverse game mechanics and game elements (eg, minigames and quizzes) were used to foster user engagement. Most of the SGs (12/17, 71%) featured an overarching storyline resembling real-world scenarios, fictional scenarios, or a combination of both. The evaluation studies provided evidence for the short-term efficacy and effectiveness of SGs in improving aspects of mental health literacy as well as their feasibility. However, the evidence was mostly based on small samples, and user adherence was sometimes low. CONCLUSIONS: The results of this review may inform the future development and implementation of SGs for adolescents. Intervention co-design, the involvement of facilitators (eg, teachers), and the use of diverse game mechanics and customization to meet the needs of diverse users are examples of elements that may promote intervention success. Although there is promising evidence for the efficacy and effectiveness of SGs for promoting mental health literacy in youth, there is a need for more rigorously planned studies, including randomized controlled trials and real-world evaluations, that involve follow-up measures and the assessment of in-game performance alongside self-reports.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".