Development of key messages for adolescents on providing basic mental health first aid to peers: a Delphi consensus study
Bibliographic record
Abstract
AIM: Most young people fail to receive professional treatment for mental disorders; however, they do indicate a preference for sharing problems with peers. This article describes key messages about knowledge and actions to form the basis of a basic mental health first aid (MHFA) course for adolescents to increase recognition of and help seeking for mental health problems by teaching the best knowledge and helping actions a young person can undertake to support a peer with a mental health problem. METHODS: The Delphi method was used to achieve consensus among Australian and Canadian youth mental health experts regarding the importance of statements that describe helping actions a young person can take, and information they should have, to support a friend with a mental health problem. There were two expert panels, one consisting of 36 youth mental health consumer advocates and the other of 97 Youth MHFA instructors. Panellists rated each statement according to how appropriate it would be as a basic mental health first aid message for both a junior adolescent (12-15 years) and a senior adolescent (16-18 years). RESULTS: Out of 98 statements, 78 were endorsed as key basic MHFA messages for junior adolescents and 81 were endorsed for senior adolescents. CONCLUSION: The study has identified key messages for adolescents on how they can help a peer. These messages will form the basis of the curriculum for an MHFA course for adolescents, which will aim to facilitate early recognition of and help seeking for mental health problems in adolescents.
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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 | 0.114 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".