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Record W4414379780 · doi:10.1080/02673843.2025.2561241

Beyond the gym: Quebec PHE teachers and the challenges of mental health education

2025· article· en· W4414379780 on OpenAlexafffundabout
Beatriz Rosa Angelini, Jordan Koch

Bibliographic record

VenueInternational Journal of Adolescence and Youth · 2025
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGeneralizability theoryMental healthFraming (construction)Promotion (chess)Health promotionContent analysis

Abstract

fetched live from OpenAlex

This article examines how physical and health education (PHE) teachers in Quebec approach mental health education. Drawing on semi-structured interviews with eight high school PHE teachers, our analysis identifies several key barriers that hinder the integration of meaningful mental health content in their classrooms. These include a lack of formal training, large class sizes, persistent stereotypes framing PHE as a non-cognitive subject, and limited instructional time. Additionally, early-career teachers highlighted how widespread use of limited-term teaching contracts in Quebec undermines their ability to build trusting relationships needed to engage students in sensitive discussions about mental health. While the small sample size limits the generalizability of our findings, the in-depth, nuanced accounts provided by participants offer valuable insights into the professional, structural, and relational challenges PHE teachers face. These challenges are not unique to Quebec but reflect broader systemic issues in secondary education related to the promotion of adolescent mental health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0190.006
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.034
GPT teacher head0.421
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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