Using Video Games to Improve the Sexual Health of Young People Aged 15 to 25 Years: Rapid Review
Bibliographic record
Abstract
BACKGROUND: Sexually transmitted infections and unintended pregnancies among young people remain public health concerns in many countries. To date, interventions that address these concerns have had limited success. Serious games are increasingly being used as educational tools in health and professional public education. Although acknowledged as having great potential, few studies have evaluated the use of serious games in sexual health education among young people, and to date, there have been no published reviews of these studies. OBJECTIVE: This study aims to assess the effects of video game-based sexual health interventions for risky sexual behavior in young people aged between 15 and 25 years. METHODS: A rapid review of randomized controlled trials and quasi-randomized controlled trials was performed. The search included the following bibliographic databases: Cochrane Central Register of Controlled Trials, Embase, MEDLINE, PsycINFO, and Scopus. A total of 2 reviewers independently screened 50% (35/70) of the retrieved articles during the full-text screening phase. RESULTS: From a total of 459 identified citations, after removing duplicates, 327 (71.2%) articles were deemed eligible for title and abstract screening. Of the 327 articles, 70 (21.4%) full texts were screened, from which 10 (3.1%) articles (evaluating 11 different games) were included in the review. The findings highlighted the considerable diversity in video game-based interventions and assessed sexual health outcomes. Although there were some promising findings in outcome studies using game-based interventions, the results across studies were mixed. CONCLUSIONS: Although game interventions for sexual health have been in existence for almost three decades, relatively few studies have evaluated them, and the results of previous outcome studies have been mixed. Moreover, there is little clarity regarding which specific elements of a game facilitate positive outcomes. We provide recommendations for future researchers developing video game-based interventions to improve sexual health in young people.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".