Examining Critical Thinking Skills in Family Medicine Residents.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Our objective was to determine the relationship between critical thinking skills and objective measures of academic success in a family medicine residency program. METHODS: This prospective observational cohort study was set in a large Canadian family medicine residency program. Intervention was the California Critical Thinking Skills Test (CCTST), administered at three points in residency: upon entry, at mid-point, and at graduation. Results from the CCTST, Canadian Residency Matching Service file, and interview scores were compared to other measures of academic performance (Medical Colleges Admission Test [MCAT] and College of Family Physicians of Canada [CCFP] certification examination results). RESULTS: For participants (n=60), significant positive correlations were found between critical thinking skills and performance on tests of knowledge. For the MCAT, CCTST scores correlated positively with full scores (n=24, r=0.57) as well as with each section score (verbal reasoning: r=0.59; physical sciences: r=0.64; biological sciences: r=0.54). For CCFP examination, CCTST correlated reliably with both sections (n=49, orals: r=0.34; short answer: r=0.47). Additionally, CCTST was a better predictor of performance on the CCFP exam than was the interview score at selection into the residency program (Fisher's r-to-z test, z=2.25). CONCLUSIONS: Success on a critical thinking skills exam was found to predict success on family medicine certification examinations. Given that critical thinking skills appear to be stable throughout residency training, including an assessment of critical thinking in the selection process may help identify applicants more likely to be successful on final certification exam.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".