A longitudinal and multicentre study of burnout and error in Irish junior doctors
Bibliographic record
Abstract
BACKGROUND: Junior doctors have been found to suffer from high levels of burnout. AIMS: To measure burnout in a population of junior doctors in Ireland and identify if: levels of burnout are similar to US medical residents; there is a change in the pattern of burnout during the first year of postgraduate clinical practice; and burnout is associated with self-reported error. METHODS: The Maslach Burnout Inventory-Human Services Survey was distributed to Irish junior doctors from five training networks in the last quarter of 2015 when they were approximately 4 months into their first year of clinical practice (time 1), and again 6 months later (time 2). The survey assessed burnout and whether they had made a medical error that had 'played on (their) mind'. RESULTS: A total of 172 respondents out of 601 (28.6%) completed the questionnaire on both occasions. Irish junior doctors at time 2 were more burned out than a sample of US medical residents (72.6% and 60.3% burned out, respectively; p=0.001). There was a significant increase in emotional exhaustion from time 1 to time 2 (p=0.007). The association between burnout and error was significant at time 2 only (p=0.03). At time 2, of those respondents who were burned out, 81/122 (66.4%) reported making an error. A total of 22/46 (47.8%) of the junior doctors who were not burned out at time 2 reported an error. CONCLUSION: Current levels of burnout are unsustainable and place the health of both junior doctors and their patients at risk.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".