Mental Health of Canadian Dentists Before and During the COVID-19 Pandemic.
Bibliographic record
Abstract
OBJECTIVES: A growing body of literature highlights the negative impact of the COVID-19 pandemic on the mental health of health care professionals. This paper explores the effects of gender and work/life factors on dentists' mental health before and during the pandemic. METHODS: Data were obtained from a cross-sectional, online survey of Canadian dentists, which was part of a broader study of Canadian professionals' mental health challenges conducted in 2020-2021. Using logistic regression, we compared the influence of life stress, work stress, gender and role in practice on dentists' self-rated mental health before and during the pandemic. RESULTS: Respondents reported that their mental health had worsened during the pandemic. Among survey respondents (n = 397), women dentists (50%) reported worse mental health than men (39%). Those who had higher levels of work and life stress reported more mental health challenges both before and during the pandemic. CONCLUSIONS: Our findings point to the need for more attention to dentists' mental health and highlight the need for gender-sensitive mental health resources and supports for Canadian dentists.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".