Pan-Canadian study of psychiatric care (PCPC): protocol for a mixed-methods study
Bibliographic record
Abstract
INTRODUCTION: The Canadian population has poor and inequitable access to psychiatric care despite a steady per-capita supply of psychiatrists in most provinces. There is some quantitative evidence that practice style and characteristics vary substantially among psychiatrists. However, how this compares across jurisdictions and implications for workforce planning require further study. A qualitative exploration of psychiatrists' preferences for practice style and the practice choices that result is also lacking. The goal of this study is to inform psychiatrist workforce planning to improve access to psychiatric care by: (1) developing and evaluating comparable indicators of supply of psychiatric care across provinces, (2) analysing variations and changes in the characteristics of the psychiatrist workforce, including demographics and practice style and (3) studying psychiatrist practice choices and intentions, and the factors that lead to these choices. METHODS AND ANALYSIS: A cross-provincial mixed-methods study will be conducted in the Canadian provinces of British Columbia, Manitoba, Ontario and Nova Scotia. We will analyse linked-health administrative data within three of the four provinces to develop comparable indicators of supply and characterise psychiatric services at the regional level within provinces. We will use latent profile analysis to estimate the probability that a psychiatrist is in a particular practice style and map the geographical distribution of psychiatrist practices overlayed with measures of need for psychiatric care. We will also conduct in-depth, semistructured qualitative interviews with psychiatrists in each province to explore their preferences and practice choices and to inform workforce planning. ETHICS AND DISSEMINATION: This study was approved by Ontario Tech University Research Ethics Board (16637 and 16795) and institutions affiliated with the study team. We built a team comprising experienced researchers, psychiatrists, medical educators and policymakers in mental health services and workforce planning to disseminate knowledge that will support effective human resource policies to improve access to psychiatric care in Canada.
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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 | 0.053 | 0.041 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.081 | 0.009 |
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".