Burnout syndrome in Nova Scotia dental hygienists during the COVID-19 pandemic: Maslach Burnout Inventory.
Bibliographic record
Abstract
Background: Burnout syndrome is the result of prolonged occupational stress. The syndrome has 3 dimensions: emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA). This study aimed to examine the prevalence of the 3 dimensions of burnout in dental hygienists in Nova Scotia, Canada, (N = 745) as they returned to work during the COVID-19 pandemic following a furlough; to explore the effect of burnout during COVID-19 on dental hygienists' professional lives; and to determine the tools and methods that dental hygienists use to overcome burnout. Methods: In this cross-sectional study, participants were asked to complete an anonymous survey inclusive of demographic information, employment characteristics, the Maslach Burnout Inventory Human Services Survey for Medical Personnel (MBI-HSS [MP]), and 2 open-ended questions. Results: The response rate was 34.9% (n = 260). Approximately one-third (36.2%) of respondents met the criteria for burnout. Contributors to burnout were time, providing dental hygiene care, expectations of dentists, physical and mental health, lack of autonomy, and the COVID-19 pandemic. Reported mechanisms to overcome occupational stress centred on work-life balance, social support networks, working in a positive environment, and physical activity. Discussion: This study took place during the first wave of the COVID-19 pandemic, which may have influenced the rate of burnout among dental hygienists, particularly within the EE domain where scores were twice as high as those reported in pre-COVID-19 studies. Conclusion: Dental hygienists may be at risk for burnout. Recognizing the signs and symptoms of burnout and implementing healthy behaviours may reduce its detrimental effects.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".