Protocol: a cluster randomised control trial study exploring stigmatisation and recovery-based perspectives regarding mental illness and substance use problems among primary healthcare providers across Toronto, Ontario
Bibliographic record
Abstract
INTRODUCTION: Primary care settings are often the first and only point of contact for persons with mental health and/or substance use problems. However, staff experience and training in this area are often limited. These factors as well as a multitude of other components such as structural and systemic stigma experienced by staff can lead to clients being stigmatised, leading to poorer outcomes. By developing a comprehensive intervention for primary care staff working at community health centres (CHCs) aimed at reducing stigma towards people with mental health and substance use problems (MHSUP), we sought to test an innovative and contact-based intervention consisting of staff training, raising awareness, a recovery-focused art programme and an analysis of internal policies and procedures. All of these components can inform and support staff so they can provide better care for people who are experiencing MHSUP. CHC staff members and clients will be included in this project as active participants. METHODS AND ANALYSIS: will be included in the study. Using a variety of measures, including the Opening Minds Scale for Health Care Providers (OMS-HC), Mental Illness: Clinicians Attitudes (MICA) Scale, Modified Bogardus Social Distance Scale, Perceived Devaluation-Discrimination Scale, Discrimination Experience subscale of the Internalized Stigma of Mental Illness (ISMI) Scale and the Recovery Assessment Scale (RAS), we hope to gain a thorough understanding of staff members' attitudes and beliefs and clients' perceptions of staff beliefs and behaviours. In-depth interviews will reveal important themes related to clients' experiences of stigma both within and outside the healthcare setting. ETHICS AND DISSEMINATION: If demonstrated to be successful, this intervention can be used as a model for future initiatives aimed at reducing MHSUP-related stigma among healthcare providers in an organisational context. Adapting this work in other settings is a key strategic goal of this project. The project will also advance knowledge about stigma reduction and the experience of encountering stigma within a healthcare setting. TRIAL REGISTRATION: NCT03043417; Post-results.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.057 | 0.007 |
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".