Empathic concern and professional characteristics associated with clinical empathy in French general practitioners
Bibliographic record
Abstract
OBJECTIVE: Clinical empathy, i.e. the ability of physicians to adopt patient perspective, is an essential component of care, which depends in part on empathic concern, i.e. compassionate emotions felt for others. However, too much empathic concern can be challenging for physicians. Aim of this study was to examine physician practice characteristics that could explain clinical empathy beyond empathic concern. We were also interested in testing whether professional reflective activities, such as Balint group attendance or clinical supervision, might make clinical empathy less dependent on empathic concern. METHODS: A total of 295 French general practitioners (response rate of 37%) completed self-reported questionnaires on empathic concern and clinical empathy, using the Toronto empathy questionnaire (TEQ) and the Jefferson scale of physician empathy (JSPE), respectively. We also recorded information on their professional practice: professional experience, duration of consultations, and participation in Balint groups or being a clinical supervisor. Hierarchical regression analyses were carried out with clinical empathy as dependent variable. RESULTS: Empathic concern was an important component of clinical empathy variance. The physician practice characteristics 'consultation length' and 'being a Balint attendee or a supervisor,' but not 'clinical experience' made a significant and unique contribution to clinical empathy beyond that of empathic concern. Participating to one reflective activity (either Balint group attendance or clinical supervision) made clinical empathy less dependent on empathic concern. CONCLUSION: Working conditions such as having enough consultation time and having the opportunity to attend a professional reflective activity support the maintenance of clinical empathy without the burden of too much empathic concern.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".