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Bibliographic record
Abstract
Working with young people: the impact of mental health awareness programmes in schools in the UK and Canada The persistent and disabling nature of psychiatric stigma has led to the establishment of global programmes to challenge the negative stereotypes and discriminatory responses that generate social disability, but these initiatives are rarely evaluated. This study compares the effectiveness of school-based interventions with young people aged 14-16 aimed at increasing mental health literacy and challenging neg-ative stereotypes associated with severe mental illness in sites in Canada and the UK. In both countries, short educational sessions were delivered involving a facilitator with direct experience of mental illness. Students in Canada at baseline (N=1501) were significantly more aware than those in the UK (N=635) that schizophrenia is not a split personality, that mental illness is prevalent and that it is a myth that people with schizophrenia are any more likely to be violent than members of the general population. Both the UK and Canada pro-grammes had a favourable impact on students factual recall and reported attitudes at first follow-up. The cumulative proportion of stu-dents expressing no social distance across 4 key items improved over time in both the UK (N=512) and Canada (N=634). Therefore, this study shows that short educational workshops can produce positive change in young people’s views of mental illness. However, more robust evaluations are needed to assess the long-term impact of both short and integrated whole school approaches to increasing mental health literacy across the globe.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.009 |
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".