Critical appraisal skills of family physicians in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Our primary objective in this study was to measure family physicians' knowledge of the key elements that go into assessing the validity and interpreting the results in three different types of studies: i) a randomized controlled trial (RCT); ii) a study evaluating a diagnostic test; and iii) a systematic review (SR). Our secondary objectives were to determine the relationship between the above skills and age, gender, and type of practice. METHODS: We obtained a random sample of 1000 family physicians in Ontario from the College of Family Physicians of Canada database. These physicians were sent a questionnaire in the mail with follow-up mailings to non-responders at 3 and 8 weeks. The questionnaire was designed to measure knowledge and understanding of the basic concepts of critical appraisal skills. Based on the responses to the questions an Evidence Based Medicine (EBM) Knowledge Score was determined for each physician. RESULTS: A response rate of 30.2% was achieved. The respondents were younger and more likely to be recent graduates than the population of Ontario Family Physicians as a whole. This was an expected outcome. Just over 50% of respondents were able to answer questions concerning the critical appraisal of methods and the interpretation of results of research articles satisfactorily. The average score on the 12-point EBM Knowledge Scale was 6.4. The younger physicians scored higher than the older physicians, and academic physicians scored higher than community-based physicians. Scores of male and female physicians did not differ. CONCLUSIONS: We have shown that in a population of physicians which is younger than the general population of physicians, about 50% have reasonable knowledge regarding the critical appraisal of the methods and the interpretation of results of a research article. In general, younger physicians were more knowledgeable than were older physicians. EBM principles were felt to be important to the practice of medicine by 95% of respondents.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".