A national survey of burnout amongst Canadian Royal College of Physicians and Surgeons of Canada emergency medicine residents
Bibliographic record
Abstract
BACKGROUND: In recent years, there has been growing interest in the field of physician wellness and burnout. The prevalence of burnout is non-uniform between medical specialties and is most prevalent amongst emergency medicine physicians. Importantly, burnout can be observed amongst individuals early in their medical careers, including medical students and residents. Despite ample studies in other populations, there is no national perspective of burnout amongst Canadian Royal College of Physicians and Surgeons of Canada (RCPSC)Emergency Medicine (EM) residents. METHODS: Our study surveyed Canadian residents undergoing EM training though the RCPSC via local program directors using an anonymous electronic form. Basic demographic characteristics and residents' contemplation of suicide were surveyed. The Maslach Burnout Inventory - Human Services Survey (MBI-HSS) for medical personnel was used to assess burnout on three dimensions (emotional exhaustion, depersonalization and personal accomplishment). RESULTS: A total of 65 valid responses were collected from eight of 14 eligible institutions (response rate = 30%). Respondents are primarily male (58%) and in their postgraduate year (PGY) 1-3 (71%). Overall, 62% of residents met the threshold for burnout according to a widely cited definition of burnout using the MBI-HSS. Additionally, 14% contemplated suicide during their training. There was no statistical significance in burnout rates between male and female responders or between residents in different stages of training. CONCLUSION: Our results suggest significant burnout amongst Canadian EM residents. These results point to an important opportunity to better support EM residents during their training to improve wellness and reduce burnout.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".