A peer mentoring initiative across medical residency programs
Bibliographic record
Abstract
Purpose Several studies have shown benefits of peer mentoring on wellness among medical students and health care professionals. Peer mentorship has also been pointed as having interesting potential for International Medical Graduates. However, the literature on peer mentoring at the residency level is very limited. The purpose of this paper is to assess the benefits of a resident-led pilot peer-mentoring initiative at McGill University. Design/methodology/approach Over 2 years, 17 residents from various residency programs were put in contact with a volunteer peer mentor by e-mail. The structure of the mentorship was flexible. A survey using Likert scale and free text responses was sent to all the participants. Findings There were response rates of 65 percent for mentees and 59 percent for mentors. The majority of mentees thought the service was either moderately helpful (18 percent) or helpful (36 percent). Several residents noted that communication by e-mails and lack of in-person contacts were a limitation in the mentorship experience. The most frequent challenge that led to consult the service was immigration or arrival from another province. Originality/value The results show that the program can be helpful to medical residents, is cost-effective, flexible and could be adapted and replicated elsewhere. In the future, the program will adjust to tend toward a more structured frame, highlighting the importance of in-person contacts. The small sample size of participants and the recall bias are some limitations of our study.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".