Educators’ Perspectives on a Mental Health Check-Up Model for Adolescents: Qualitative Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Schools play a critical role in identifying adolescent mental health needs early, yet the effectiveness of school-based strategies often depends on how well health information is communicated to educators. OBJECTIVE This study explores how pedagogical leaders perceive a proposed model for adolescent mental health check-ups and identifies key factors for designing effective communication tools between healthcare professionals and schools. METHODS Two participatory workshops were conducted with 44 pedagogical coordinators and educational counselors from elite private schools in São Paulo, Brazil. Structured group discussions and collaborative design activities were used to elicit responses to proposed mental health report formats. Data were analyzed thematically using an inductive approach supported by manual coding and cross-checking by two independent reviewers. No software was used; inter-rater reliability was achieved through iterative discussion. RESULTS Participants expressed a strong preference for mental health reports that are clear, context-sensitive, and co-developed with educators. Key themes included the need for pedagogical rather than clinical language, the importance of mediation by coordinators, and the value of aggregate data for family engagement and institutional planning. Co-creation of communication tools was reported to enhance educators’ sense of relevance and confidence in discussing mental health. These preferences were consistently reported across participants regardless of years of experience, suggesting shared epistemic needs across the field. CONCLUSIONS The study highlights the value of user-informed communication models in mental health screening. Co-created tools aligned with pedagogical practices are more likely to be used and trusted. Effective communication design should be prioritized alongside the development of screening instruments themselves. Further research is needed to adapt this approach to low-resource public school contexts.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".