Effects of YouTube Health Videos on Mental Health Literacy in Adolescents and Teachers: Randomized Controlled Trial
Bibliographic record
Abstract
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
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".