Risk of burnout among emergency physicians at a tertiary care centre in Saudi Arabia
Bibliographic record
Abstract
Background: Emergency Medicine physicians are shown to be at increased risk of burnout. In this study, we aimed to assess the risk of burnout among emergency physicians working at one of the largest Emergency Departments in Saudi Arabia. Methods: This is an observational, cross-sectional study based on a structured questionnaire Maslach Burnout Inventory- Human Services Survey (MBI-HSS), which has been previously tested and validated extensively. The study targeted all physicians in the Emergency Department (ED) at a tertiary medical center in Riyadh. A total of 72 emergency physicians were included in the study. Results: Overall, 53 (74%) out of 72 subjects filled the questionnaire. Out of the 53 respondents, 45 (85%) were males and eight (15%) females. The years of practice experience ranged from six months to 24 years, with a median of seven years. Burnout Inventory-Human Services Survey subscale results: Emotional Exhaustion (EE): The mean EE score was 2.72 (SD 1.28), with 21 participants (40%) in the high-risk zone. Depersonalization (DP): The mean DP score was 1.86 (SD 1.31), with 21 participants (40%) in the high-risk zone. Personal Accomplishment (PA): The mean PA score was 4.5 (SD 0.9), with 17 participants (32%) in the high-risk zone. Conclusion: Our results are consistent with previous literature in showing that emergency physicians are at a moderate to high risk of burnout. Decision makers should take serious steps to address the threat, in order to minimize the risk of burnout and its impact on physicians as well as the patient they care for.
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".