A grounded theory model for reducing stigma in health professionals in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The Mental Health Commission of Canada was formed as a national catalyst for improving the mental health system. One of its initiatives is Opening Minds (OM), whose mandate is to reduce mental health-related stigma. This article reports findings from a qualitative study on antistigma interventions for healthcare providers, which includes a process model articulating key stages and strategies for implementing successful antistigma programmes. METHOD: The study employed a grounded theory methodology. Data collection involved in-depth interviews with programme stakeholders, direct observation of programmes, a review of programme documents, and qualitative feedback from programme participants. Analysis proceeded via the constant comparison method. A model was generated to visually present key findings. RESULTS: Twenty-three in-depth interviews were conducted representing 18 different programmes. Eight programmes were observed directly, 48 programme documents were reviewed, and data from 1812 programme participants were reviewed. The analysis led to a four-stage process model for implementing successful antistigma programmes targeting healthcare providers, informed by the basic social process 'targeting the roots of healthcare provider stigma'. CONCLUSION: The process model developed through this research may function as a tool to help guide the development and implementation of antistigma programmes in healthcare contexts.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it