Bibliographic record
Abstract
BACKGROUND: Burnout is the result of unmanaged stress that has been shown to affect those working in the healthcare professions. Although much research has been conducted on burnout among nurses, physicians and other health professionals, there is limited documentation on the phenomenon among dietitians. The purpose of this study was to establish the prevalence of burnout among dietitians in Ontario, Canada, determine the demographic variables associated with burnout, and compare these results with burnout data for other healthcare professionals. METHODS: The Maslach Burnout Inventory-Human Services Survey and a demographic questionnaire were emailed to registered dietitians. RESULTS: The dietitians surveyed experienced a moderate amount of emotional exhaustion (mean = 19.96), a low level of depersonalisation (mean = 4.31) and a moderate sense of personal accomplishment (mean = 38.61). Statistically significant relationships were found between years as a dietitian and personal accomplishment (r = 0.16; P = 0.05), age and personal accomplishment (r = 0.15; P = 0.01), hours worked per week and emotional exhaustion (r = 0.17; P = 0.01) and hours worked per week and depersonalisation (r = 0.14; P = 0.01). There were no significant differences in mean burnout scores across the five areas of practice. Over 57% of dietitians had scores indicative of moderate to high levels of burnout overall. CONCLUSIONS: Although dietitians have lower levels of burnout compared to other healthcare professionals, moderate levels of emotional exhaustion and only moderate levels of personal accomplishment remain workplace issues for this professional group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".