Compassion Fatigue and Burnout Among Health Care Professionals: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Compassion fatigue and burnout among health care professionals are growing concerns, impacting the well-being of both providers and patients. OBJECTIVE: This scoping review aims to map existing evidence on the levels of compassion satisfaction, burnout, and secondary traumatic stress among health care professionals while identifying factors influencing their professional quality of life. METHODS: We will conduct a scoping review using established methods proposed by Arksey and O'Malley and Levac et al, also incorporating the recommendations of the Joanna Briggs Institute for scoping reviews and reporting guidelines. EMBASE, ERIC, PubMed, Science Direct, Scopus, and Web of Science will be searched from March 2019 to March 2024, with an update closer to the time of manuscript submission. Gray literature sources will also be searched. Publications that contain primary studies, systematic reviews, meta-analyses, and clinical guidelines addressing compassion fatigue and burnout prevention in health care professionals will be selected for inclusion. Extracted data items will include study characteristics, interventions for the prevention of compassion fatigue and burnout, measures of compassion satisfaction, burnout, and secondary traumatic stress, as well as the quality of reporting and methodology. RESULTS: A narrative synthesis with summary tables will be used to describe our findings. The review is expected to be completed by December 2025, and the search strategy has been developed and pilot-tested. CONCLUSIONS: Our findings will help identify gaps in the literature with respect to compassion fatigue and burnout prevention strategies for health care professionals. This review will provide a comprehensive overview of current research, informing future interventions and policies aimed at improving health care professionals' well-being and job satisfaction. TRIAL REGISTRATION: Open Science Framework r83cu; https://osf.io/r83cu. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/66360.
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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 | 0.094 | 0.085 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.101 | 0.020 |
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".