Longitudinal Integrated Clerkships for Medical Students: An Innovation Adopted by Medical Schools in Australia, Canada, South Africa, and the United States
Bibliographic record
Abstract
PURPOSE: Integrated clinical clerkships represent a relatively new and innovative approach to medical education that uses continuity as an organizing principle, thus increasing patient-centeredness and learner-centeredness. Medical schools are offering longitudinal integrated clinical clerkships in increasing numbers. This report collates the experiences of medical schools that use longitudinal integrated clerkships for medical student education in order to establish a clearer characterization of these experiences and summarize outcome data, when possible. METHOD: The authors sent an e-mail survey with open text responses to 17 medical schools with known longitudinal integrated clerkships. RESULTS: Sixteen schools in four countries on three continents responded to the survey. Fifteen institutions have active longitudinal integrated clerkships in place. Two programs began before 1995, but the others are newer. More than 2,700 students completed longitudinal integrated clerkships in these schools. The median clerkship length is 40 weeks, and in 15 of the schools, the core clinical content was in medicine, surgery, pediatrics, and obstetrics-gynecology. Eleven schools reported supportive student responses to the programs. No differences were noted in nationally normed exam scores between program participants and those in the traditional clerkships. Limited outcomes data suggest that students who participate in these programs are more likely to enter primary care careers. CONCLUSIONS: This study documents the increasing use of longitudinal integrated clerkships and provides initial insights for institutions that may wish to develop similar clinical programs. Further study will be needed to assess the long-term impact of these programs on medical education and workforce initiatives.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".