Dentists’ Mental Health: Challenges, Supports, and Promising Practices
Bibliographic record
Abstract
OBJECTIVES: The mental health of dentists, like all health professionals, is a growing concern. The objectives of this study were to identify the mental health challenges experienced by Canadian dentists and to describe the support needs and promising practices to better support them. METHODS: This study used a mixed-methods case study design to gather data from semistructured qualitative interviews and a survey for triangulation. RESULTS: Thirty-six dentists and 17 stakeholders participated in the interviews, and 397 dentists participated in the survey. The interview and survey data revealed that dentists have experienced several challenges personally, professionally, and socially. Around 44% of participating dentists experienced a wide range of mental health issues, including depression, anxiety, and posttraumatic stress disorder. Sex/gender shaped the mental health experiences of female dentists, who reported more stress related to caring responsibilities. They had a higher percentage of mental health issues (50%) than men (37%). Caretaking emerged as the main challenge in the social and personal domain, particularly for female dentists in both survey and interview findings. The dentists' role in practice was one of the most frequently reported professional challenges. While practice owners reported challenges with staff and practice management, associate dentists experienced difficulties with the lack of autonomy and conflicts with office managers and owners. Other challenges reported by participating dentists included patient care responsibilities, loneliness, and isolation. To address these challenges and their impact, dentists and stakeholders identified several support needs and promising practices, including increasing awareness about mental health issues, expanding existing mental health resources, incorporating mental health content in dental education, and encouraging engagement in organized dentistry, particularly for women. CONCLUSIONS: The impact of mental health challenges on dentists' career trajectory and productivity is an ongoing concern in Canada. Gender-specific strategies to support the mental health of dentists should be developed.Knowledge Translation Statement:This study identified the mental health challenges of dentists in Canada to inform the development of interventions and strategies to promote the health and well-being of dentists and dental students. It also highlighted the need for clinicians, students, and individuals in leadership positions in institutions and professional organizations to recognize and consider the working conditions of dentists in various positions to avoid negative consequences on their mental health, reduce the attrition from the professional, and improve patient care outcomes.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".