The effects of a teacher-led online mental health literacy program for high school students: a pilot cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Adolescents are vulnerable to mental health problems, and this vulnerability may be enhanced in situations such as the present COVID-19 pandemic. Online mental health literacy (MHL) education may help adolescents maintain/improve their mental health, especially in situations where face-to-face education is difficult. AIMS: )" delivered online to grade 10 students in their classrooms. METHODS: group (n = 115 (3 classes)) or a control group (n = 155 (4 classes)) at the class level. The program consisted of a 20-minute session which included an animated video. The students completed a self-report questionnaire pre- and post-intervention assessing outcomes including: "Knowledge about mental health/illnesses", "Recognition of necessity to seek help", "Intention to seek help", and "Unwillingness to socialize with people having mental illness". Mixed effects modeling was employed for analyses. RESULTS: All outcomes were significantly improved in the intervention group compared to the control group post-intervention, except for "intention to seek help". CONCLUSIONS: The present study shows the effectiveness of an online MHL intervention while identifying the need for the development of effective online programs targeting adolescents' "intention to seek help".
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".