Characteristics of mental health literacy measurement in youth: a scoping review of school-based surveys
Bibliographic record
Abstract
Mental health literacy (MHL) was introduced 25 years ago as knowledge and beliefs about mental disorders which aid in their recognition, management, or prevention. This scoping review mapped the peer-reviewed literature to assess characteristics of secondary school-based surveys in school-attending youth and explore components of school-based programs for fostering MHL in this population. The search was performed following the method for scoping reviews by the Joanna Briggs Institute (JBI). Searches were conducted in four scientific databases with no time limit, although all sources had to be written in English. Primary studies (N = 44) provided insight into MHL surveys and programs for school-attending youth across 6 continents. Studies reported that most youth experience moderate or low MHL prior to program participation. School-based MHL programs are relatively unified in their definition and measures of MHL, using closed-ended scales, vignettes, or a combination of the two to measure youth MHL. However, before developing additional interventions, steps should be taken to address areas of weakness in current programming, such as the lack of a standardized tool for assessing MHL levels. Future research could assess the feasibility of developing and implementing a standard measurement protocol, with educator perspectives on integrating MHL efforts into the classroom. Identifying the base levels of MHL amongst school-attending youth promotes the development of targeted programs and reviewing the alignment with program components would allow researchers to build on what works, alter what does not, and come away with new ways to approach these complex challenges, ultimately advancing knowledge of MHL and improving levels of MHL.
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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 | 0.090 | 0.267 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.035 | 0.037 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".