EXPLORING EMPATHY IN PEDIATRICS RESIDENTS AT AN URBAN CHILDREN’S HOSPITAL IN CANADA
Bibliographic record
Abstract
Abstract BACKGROUND Empathy is fundamental to the physician-patient relationship, promoting both patient compliance and increased treatment efficacy. Studies attempting to quantify changes in empathy during residency are inconsistent in their findings; those examining paediatrics training specifically, are no more definitive. The mixed conclusions may stem from the use of self-reporting scores, which may fail to capture the essence of the effect. OBJECTIVES This study aimed to explore the state, and map a trajectory, of empathy in paediatrics residents, to identify factors influencing the learning and retention of empathy. DESIGN/METHODS This qualitative descriptive study was conducted at an urban children’s hospital in Canada. A constructivist phenomenological approach was used. Participants were recruited for semi-structured interviews via a purposive sampling strategy; thereafter, a thematic analysis was employed. Emerging themes were discussed at research meetings. Sufficiency was felt to be achieved after ten interviews. RESULTS Senior residents reported an overall increase in empathy, in part attributed to a better understanding of paediatric illnesses and greater perspective of the impact on families. There appeared to be a reconciliation with the changing shape of their empathy: managerial and administrative responsibilities could be performed empathically if patient priorities remained a central objective. Challenges to the retention of empathy correlated with published literature: time constraints, compassion fatigue and burnout with poor coping, and the hidden curriculum. Empathy was learned from role modelling by peers, preceptors, and other health care providers. Resident resilience, as a product of personal adversity, was protective against the loss of empathy; this could be considered in the postgraduate admissions process, and should be fostered with resident wellness strategies. Residents advocated for increased autonomy and patient ownership, and fuller exposure to longitudinal care, including the patient’s social context and home life, both of which could be considered as additions to residency training curricula to increase resident empathy. CONCLUSION Residents demonstrated an increase in empathy during training. Resident resilience is valuable in protecting empathy and could be considered in admissions processes. Longitudinal clinics and home visits should be considered as additions to residency training curricula.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".