The Effect of a 2-Week Pre-clerkship Residency Exploration Program on Specialty Interest and Understanding of Physical Medicine and Rehabilitation
Bibliographic record
Abstract
OBJECTIVE: To assess the effect the Pre-clerkship Residency Exploration Program (PREP) had on student career interest and improving understanding of physical medicine and rehabilitation (PMR). DESIGN: During a 2-week program, students were exposed to a PMR elective, workshop, career presentation, and panel discussion with PMR residents. Interest and understanding were assessed using pre- and postprogram questionnaires. SETTING: PREP was held at a Canadian medical school during the summer between the second and third years of undergraduate medical training. PARTICIPANTS: Second-year medical student participants (N=40) (26 women and 14 men, aged 20 to >30 y) were randomly selected from 74 applicants at a Canadian medical school. INTERVENTIONS: Of the 40 program participants, 20 participated in a PMR elective and specialty-specific workshop. The full cohort of 40 participants participated in the PMR career presentation and PMR resident panel discussion. MAIN OUTCOME MEASURE: Primary outcome measure was an increase in understanding of the PMR specialty. RESULTS: Understanding of the roles and responsibilities of physiatrists increased significantly, with larger trends in those with greater exposure time. After PREP, comfort level in common PMR procedures also significantly increased. Higher exposure time was correlated with an increased top 3 career selection. Student interest in PMR did not significantly change after the program. CONCLUSION: Although no statistically significant effects were found from the 2-week PREP in this population in terms of career choice, benefits were found in the participants comfort with PMR procedures and understanding the roles and responsibilities of physiatrists. A brief exposure as part of a 2-week summer elective is beneficial for career decision planning and may be feasible to implement in medical curricula.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".