Using Video Games to Improve the Sexual Health of Young People Aged 15 to 25 Years: Rapid Review
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».