Perceptions of the Learning Environment Among Medical Students With Disabilities and the Impact of Program Access
Bibliographic record
Abstract
PURPOSE: Negative learning environment experiences may contribute to burnout for medical students with disabilities (MSWD). This study explores MSWD's perceptions of the learning environment and the effects of program access (having received or not needing accommodations). METHOD: The authors analyzed the Association of American Medical Colleges Year Two Questionnaire data from 2019 and 2020, comparing nondisabled students, MSWD with program access, and MSWD without program access (having not received or requested an accommodation, despite a need). Three learning environment measures were examined: how schools fostered students' personal and professional development; a shortened Medical School Learning Environment Scale (MSLES); and subscales on emotional climate, student-faculty interactions, and student-student interactions. Responses were compared across the 3 groups using chi-square and ANOVA tests with post-hoc pairwise comparisons. RESULTS: Of the 23,898 respondents, 10.2% (2,438) self-reported a disability. Among those, 83.6% (2,039) reported program access, and 13.9% (340) reported lack of program access. Students without disabilities (21,008) reported higher agreement that their school fostered their development as a person (72.2%, 15,172) and physician (90.9%, 19,089) compared with MSWD with access (65.6%, 1,312 and 89.0%, 1,778, P < .001). MSWD without access reported lower agreement than both groups (43.7%, 149 and 80.1%, 273, P < .001). There were no differences regarding the MSLES statement about high-performance standards ( F (2, 23742) = 2.35, P = .095). For the 8 remaining MSLES statements and for all 3 subscales, nondisabled students reported significantly higher agreement than MSWD with and without access, and MSWD with access had higher agreement than those without. CONCLUSIONS: This nationally representative study demonstrates that MSWD perceive the learning environment less favorably than their nondisabled peers. Program access partially mitigates these differences, underscoring the critical role of accommodations and the need to address structural barriers to access.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".