Différences et similitudes dans la perception de la schizophrénie entre les omnipraticiens et la population générale québécoise
Bibliographic record
Abstract
This paper presents results concerning the perceptions and attitudes of Quebec physicians towards patients with schizophrenia and compares data obtained from a previous poll to data drawn from answers of five common questions asked to the general population. A short questionnaire with 5 items selected earlier from a broader questionnaire submitted to the general population, has been distributed to Quebec physicians. These items inquired about the perceptions and attitudes of physicians towards schizophrenia. A randomized sample of physicians was performed. Three thousand and five hundred (3 500) physicians were selected and distributed questionnaires. A response rate of 29 %, a little more than one thousand (1003 responses) was observed, 46 % women and 54 % men. The authors have found significant differences between physicians and the general population in the tendency of wanting to offer help to those suffering from schizophrenia (physicians = 58 % versus general population : 45 %). Also, a higher percentage of physicians (72 %) have expressed feelings of compassion towards patients with schizophrenia versus 27 % in the general population. Results indicate that physicians, with a family member suffering from schizophrenia, are less comfortable discussing openly about the family member's illness (26 % versus 48 %). With regards to preconception of the severity of schizophrenia, in the field of health, and more specifically mental health, there are no differences observed amongst the physicians and the general population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".