Accelerated 3-Year MD Pathway Programs: Graduates’ Perspectives on Education Quality, the Learning Environment, Residency Readiness, Debt, Burnout, and Career Plans
Bibliographic record
Abstract
Abstract Purpose To compare perception of accelerated and traditional medical students, with respect to satisfaction with education quality, and the learning environment, residency readiness, burnout, debt, and career plans. Method Customized 2017 and 2018 Medical School Graduation Questionnaires (GQs) were analyzed using independent samples t tests for means and chi-square tests for percentages, comparing responses of accelerated MD program graduates (accelerated pathway [AP] students) from 9 schools with those of non-AP graduates from the same 9 schools and non-AP graduates from all surveyed schools. Results GQ completion rates for the 90 AP students, 2,573 non-AP students from AP schools, and 38,116 non-AP students from all schools in 2017 and 2018 were 74.4%, 82.3%, and 83.3%, respectively. AP students were as satisfied with the quality of their education and felt as prepared for residency as non-AP students. AP students reported a more positive learning climate than non-AP students from AP schools and from all schools as measured by the student–faculty interaction (15.9 vs 14.4 and 14.3, respectively; P < .001 for both pairwise comparisons) and emotional climate (10.7 vs 9.6 and 9.6, respectively; P = .004 and .003, respectively) scales. AP students had less debt than non-AP students (P < .001), and more planned to care for underserved populations and practice family medicine than non-AP students from AP schools (55.7% vs 33.9% and 37.7% vs 9.4%; P = .002 and < .001, respectively). Family expectations were a more common influence on career plans for AP students than for non-AP students from AP schools and from all schools (26.2% vs 11.3% and 11.7%, respectively; P < .001 for both pairwise comparisons). Conclusions These findings support accelerated programs as a potentially important intervention to address workforce shortages and rising student debt without negative impacts on student perception of burnout, education quality, or residency preparedness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".