From Uncertainty to Confidence: Peer-Led Research and the Formation of Medical Academic Identity
Bibliographic record
Abstract
Background: Undergraduate research is vital for developing critical thinking and academic identity in medical students, yet traditional models often fail to overcome institutional and personal barriers. Peer-led approaches may offer more accessible, supportive environments that promote deeper engagement and leadership in research. Methods: This study evaluated medical students’ experiences in a peer-led research initiative from 2022 to 2024. Students were then invited to complete a qualitative questionnaire reflecting on their perceptions towards research, development in research skills, confidence, and academic identity. Results: Code saturation was achieved after 9 responses (N = 15). Participants reported intrinsic interest, peer encouragement, and opportunities to publish as motivating factors. The peer-led model made research feel more approachable, fostering technical growth and academic confidence. Peer mentorship and a gradual learning structure were especially valued. While challenges such as workload and team dynamics emerged, students reported growth in resilience and self-reflection. Conclusions: Peer-led research initiatives can effectively support academic identity formation by integrating motivation, support, and skill development. Despite obstacles, students gained competence and confidence.
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 | 0.012 | 0.368 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".