Paramedicine and mental health: a qualitative analysis of limitations to education and practice in Ontario
Bibliographic record
Abstract
Purpose Paramedics increasingly attend to mental health-related emergencies; however, there has been little evaluation of the mental health training for paramedics. This study aims to analyze the fit between paramedicine pedagogy, patient needs and the conditions for paramedics’ skill development. Design/methodology/approach Data were collected in a single, qualitative, critical ethnographic case study of pre-hospital mental health and psychosocial care in paramedicine in Ontario, Canada. Transcripts from interviews (n = 46), observation (n ∼ 90h) and document analysis were thematically analyzed using a constant comparative method. The study is theoretically grounded in a feminist political economy framework. Findings Tensions are explored in relation to the pedagogy of paramedicine and the conditions of work faced by paramedics. The paper presents challenges and insufficiencies with existing training, the ways in which certain work and training are valued and prioritized, increased emergency care and training needs and the limitations of training to improving care. Research limitations/implications Recommendations include more comprehensive didactic training, including the social determinants of health; scenario training; practicum placements in mental health or social services; collaboration with mental health and social services to further develop relevant curriculum and potential inclusion of service users. Originality/value This paper addresses the lack of mental health pedagogy in Ontario and internationally and the need for further training pre-certification and while in the workforce. It presents promising practices to ameliorate mental health training and education for paramedics.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".