Medical students as human subjects in educational research
Bibliographic record
Abstract
INTRODUCTION: Special concerns often arise when medical students are themselves the subjects of education research. A recently completed large, multi-center randomized controlled trial of computer-assisted learning modules for surgical clerks provided the opportunity to explore the perceived level of risk of studies where medical students serve as human subjects by reporting on: 1) the response of Institutional Review Boards (IRBs) at seven institutions to the same study protocol; and 2) the thoughts and feelings of students across study sites about being research subjects. METHODS: From July 2009 to August 2010, all third-year medical students at seven collaborating institutions were eligible to participate. Patterns of IRB review of the same protocol were compared. Participation burden was calculated in terms of the time spent interacting with the modules. Focus groups were conducted with medical students at each site. Transcripts were coded by three independent reviewers and analyzed using Atlas.ti. RESULTS: The IRBs at the seven participating institutions granted full (n=1), expedited (n=4), or exempt (n=2) review of the WISE Trial protocol. 995 (73% of those eligible) consented to participate, and 207 (20%) of these students completed all outcome measures. The average time to complete the computer modules and associated measures was 175 min. Common themes in focus groups with participant students included the desire to contribute to medical education research, the absence of coercion to consent, and the low-risk nature of the research. DISCUSSION: Our findings demonstrate that risk assessment and the extent of review utilized for medical education research vary among IRBs. Despite variability in the perception of risk implied by differing IRB requirements, students themselves felt education research was low risk and did not consider themselves to be vulnerable. The vast majority of eligible medical students were willing to participate as research subjects. Participants acknowledged the time demands of their participation and were readily able to withdraw when those burdens became unsustainable.
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 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 | 0.291 | 0.256 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".