Adaptation of a school-based mental health literacy curriculum: from Canadian to English classrooms
Bibliographic record
Abstract
Abstract Background School-based mental health literacy (MHL) interventions are increasingly trialled outside of the country in which they were developed. However, there is a lack of published studies that qualitatively explore their cultural adaptation. This study investigated the reasons for adaptations made and suggested to a Canadian MHL curriculum (The Guide) within the English school context. Method Semi-structured interviews were conducted with 11 school staff responsible for the planning and/or implementation of The Guide across three schools in the South East of England, as part of the Education for Wellbeing (EfW) feasibility study. Transcripts were analysed using a hybrid, deductive-inductive thematic analysis. Results Adaptations made and suggested included dropping and emphasising content, and adapting language, examples and references. Most adaptations were proactive and related to The Guide's implementation methods, including developing more interactive and student-led approaches. Staff Capacity and Expertise , Timetabling, and Accessibility of Resources were identified as logistical reasons for adaptations. Philosophical reasons included Consistency of Messages , Student Characteristics , Reducing Stigma and Empowering Students , National and Local Context, and Appropriate Pedagogic Practices . Conclusion Overall, recommendations were for immediately implementable lesson plans informed by teachers' knowledge about best pedagogic practices in England. Adequate training, attended by both senior leadership and those implementing, was also emphasised. While ensuring that the core components are clear, MHL interventions should be developed with a necessary level of flexibility to accommodate contextual characteristics. Future research should ensure that adaptations are captured through process and implementation evaluations conducted alongside efficacy trials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".