Effects of YouTube Health Videos on Mental Health Literacy in Adolescents and Teachers: Randomized Controlled Trial
Notice bibliographique
Résumé
Background Adolescence is a critical period for mental health development, yet prevalences of mental health problems are high among young people. Enhancing mental health literacy in school settings could be an effective strategy for the promotion of mental well-being and prevention of mental health struggles. One promising approach to achieving this goal involves equipping both students and teachers with accessible multimedia resources—such as YouTube Health videos—to enhance their mental health literacy. Objective The study evaluates the effectiveness of a short educational YouTube Health video for promoting mental health literacy in adolescents and teachers. Methods Two independent samples of 352 adolescents and 502 teachers from Germany were recruited from a large panel, representative of the German population with internet access. Participants of each sample were allocated to an experimental group (176 adolescents and 254 teachers) and a control group (176 adolescents and 248 teachers) through randomization. The experimental group watched a YouTube Health video designed to increase mental health literacy, while the control group watched a video similar in style but on a different topic. Before and after watching the publicly available YouTube Health videos, mental health knowledge was assessed as a primary outcome through topic-specific quizzes and a self-report in a web-based survey. In addition, all participants were asked to rate the educational, visual, and overall quality of the YouTube Health videos and their usability in school settings. The primary hypotheses were tested with ANOVAs. The quality and usability items were analyzed descriptively. Results For the adolescents, there were significant main effects of time (F1,350=46.34, P<.001, η2p=0.117) and group (F1,350=6.05, P=.01, η2p=0.017) and a significant time×group interaction (F1,350=39.15, P<.001, η2p=0.101) on stress-specific knowledge, indicating a higher increase in knowledge in the experimental group than in the control group. Similarly, for teachers, significant main effects of time (F1,500=107.31, P<.001, η2p=0.177) and group (F1,500=58.07, P<.001, η2p=0.104) and a significant time×group interaction (F1,500=82.59, P<.001, η2p=0.142) were found. The same pattern of results was observed for the knowledge self-reports in both the students (time: F1,347=103.65, P<.001, η2p=0.230; group: F1,347=8.59, P=.004, η2p=0.024; time×group interaction: F1,347=29.11, P<.001, η2p=0.077) and teachers (time: F1,500=115.40, P<.001, η2p=0.188; group: F1,500=41.16, P<.001, η2p=0.076; time×group interaction: F1,500=64.24, P<.001, η2p=0.114). Overall, the educational, visual, and overall quality of the videos and their usability in school settings were rated as positive by both adolescents and teachers. Conclusions The study findings demonstrate that short educational YouTube Health videos are effective tools for the promotion of mental health literacy among both students and their teachers. Overall, this evaluation paves the way for a wider implementation of mental health education in schools in order to create a more supportive and informed environment to promote mental well-being. Trial Registration German Clinical Trial Register DRKS00036854; https://drks.de/search/en/trial/DRKS00036854/details
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».