Prevalence and Management of Burnout Among Dental Professionals Before, During, and After the COVID-19 Pandemic: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Burnout syndrome represents a significant challenge in healthcare, impacting dental professionals globally across all geographic, demographic, or socioeconomic backgrounds. Pervasive work-related stress and insufficient management practices highlight the urgent need for enhanced awareness and targeted interventions. OBJECTIVES: This systematic review aimed to evaluate the prevalence, causes, and impacts of burnout among dental professionals and to explore the effectiveness of various occupational health interventions aimed at managing and preventing burnout in the dental sector during different phases of the COVID-19 pandemic. METHODS: We conducted a systematic review following the PRISMA guidelines, searching electronic databases, including PubMed, Scopus, and Web of Science, from January 2014 to April 2024. The eligibility criteria included studies reporting on the prevalence of burnout, interventions to reduce burnout, and the impact of burnout on dental practices. A quality assessment was performed using the Newcastle-Ottawa Scale for observational studies. RESULTS: The findings indicate high levels of emotional exhaustion, depersonalization, and reduced personal accomplishment among dental practitioners, with significant variations influenced by workplace factors, professional relationships, and pandemic-related stresses. Differential effects based on educational level and age were also evident. CONCLUSIONS: This review highlights the urgent need for targeted public health initiatives and occupational health strategies to address and mitigate burnout in dentistry. Emphasizing professional relationships and workplace dynamics could play a crucial role in the prevention and management of burnout (PROSPERO registration no. CRD42024586616).
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".