Provision of Compassionate and Empathic Care as a Well-Being Preservation Tool for Emergency Physicians: A Scoping Review
Bibliographic record
Abstract
Marie-Frédéric Tremblay,1 Frédéric Leblanc,1 Étienne Laroche,1 Virginie Blanchette,2,3 Magali Brousseau-Foley1,2 1Centre intégré universitaire de santé et de services sociaux de la Mauricie et du Centre-du-Québec affiliated to Université de Montréal Faculty of Medicine, Trois-Rivières, Québec, Canada; 2Department of Human Kinetics and Podiatric Medicine, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada; 3VITAM - Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux de la Capitale-Nationale, Quebec, QC, CanadaCorrespondence: Magali Brousseau-Foley, Groupe de médecine familiale universitaire de Trois-Rivières, 731 Rue Sainte-Julie 2e étage, Trois-Rivières, QC, G9A 1X9, Canada, Email magali.brousseau-foley@uqtr.caObjective: Compassion and physician well-being are two key components related to quality care in health including emergency medicine. The objective of this study was to explore the impact of compassion in care on the well-being of emergency physicians. We conducted a scoping review to explore the impact of provision of compassionate care by emergency physicians on their well-being and subconcepts.Methods: Four electronic databases and grey literature were searched to find evidence related to compassion, empathy, self-compassion, and their impact on emergency physicians’ well-being. Following title and abstract review, two reviewers independently screened full-text articles, and extracted data. Data were presented using descriptive statistics and a narrative analysis.Results: A total of 803 reports were identified in databases. Three articles met eligibility criteria for data extraction. None directly examined compassion and well-being. Included studies addressed empathy and burnout in emergency medicine professionals.Conclusion: No high-quality evidence could be found on the topic in the population of interest. Literature related to the topic of compassion in physicians, especially in emergency physicians, a field known for its high demand and stress levels, is currently scarce and additional evidence is needed to better describe and understand the association between physicians’ compassion and well-being.Keywords: compassion fatigue, emergency medicine, empathy, evidence-based emergency medicine, physicians’ role
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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 | 0.013 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".