Challenges of medical residency. Are they perceived and addressed differently by international medical graduates, Canadian medical graduates, and preceptors?
Bibliographic record
Abstract
Abstract Background: Residency is an important and challenging part of medical education. Some of these challenges are common to all residents and some are specific to a particular group of residents. A number of studies have addressed the challenges of residency. To our knowledge, the experience of challenges from the perspective of international medical graduates (IMGs), Canadian medical graduates (CMGs), and their preceptors has not been studied in a single residency cohort. This study represents a valuable step in addressing the differential needs of international and Canadian medical graduates and in identifying the way different groups of residents can support each other to function better during residency.Methods: We surveyed residents and preceptors to determine what they perceive to be the greatest challenges for each group during residency. The survey was sent to the program coordinators of all English language psychiatry residency programs in Canada to be distributed to all residents and preceptors. Three reminders were sent, and a prize draw was offered to participants. Mean scale scores were calculated. One-way analyses of variance (ANOVAs) were calculated to compare resident self-ratings between groups, preceptors' ratings of each resident group's challenges, and all four groups' perceptions of the challenges experienced by different groups. To determine the particular types of challenges that residents experience, multivariate analyses of variance (MANOVAs) were also used for item-level comparisons.Results: 177 residents and 82 preceptors completed the survey. We found no significant differences in the mean scale scores for how each group rated their own challenges though the most challenging area was different for each group of residents. Preceptors viewed FIMGs as experiencing the greatest challenges (M = 3.27, SD = 0.066, 95% CI [3.11, 3.41]) and CMGs, the least (M = 2.02, SD = 0.59, 95% CI [1.89, 2.16]; F (2, 227) = 88.030, p < 0.001).Conclusion: Although the degree of challenge perceived by all groups of residents was relatively similar in general, different groups of residents identified different areas of challenges from their own perspective, and these areas differed from those identified by their resident colleagues and preceptors as being challenging for each group. This study highlights the necessity for reviewing the needs, strengths, and challenges of each group of residents and the importance of better communication between preceptors and residents regarding the different areas of challenges.
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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 | 0.034 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.006 | 0.026 |
| Insufficient payload (model declined to judge) | 0.017 | 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; both teacher heads 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".