“Brought to life through imagery” – animated graphic novels to promote empathic, patient-centred care in postgraduate medical learners
Bibliographic record
Abstract
BACKGROUND: Empathy levels decline through medical training. This has been associated with poor patient and physician outcomes, and strategies to combat this decline are increasingly recognized as critical aspects of medical education. The aim of this study was to qualitatively determine factors associated with empathy decline, and to assess the impact of a comics/graphic novel-based curriculum on enhancing empathy and a patient-centered approach to care in post-graduate medical learners. METHODS: Fourth and fifth year residents in the Adult and Pediatric Endocrinology and Metabolism Program at the University of Toronto were recruited from the 2017 cohort of the Empathy, Humanism & Comics course. Participants completed a 12-month curriculum, viewing a total of four animated graphic novels over six sessions. At the end of the course participants were interviewed either individually or in a focus group. A coding framework of emerging themes was developed based on consensus between the three authors using a qualitative descriptive approach and the constant-comparison method. RESULTS: Analysis of coded interview data revealed four themes. 1. The curriculum accurately reflected and addressed issues in real world medical practice; 2. The comics curriculum facilitated holistic development; 3. Participants appreciated the comics as an educational medium; 4. Participant feedback on the curriculum. The importance of empathy was noted, while participants acknowledged their own empathy decline and increased burnout. Stressors included increasing responsibility, long work hours, and competing work-life responsibilities. They felt the sessions developed resilience, an appreciation for the patient perspective, and communication skills. They appreciated the comics as a novel and engaging educational modality. Feedback on the effectiveness and relevancy of the curriculum was variable. CONCLUSIONS: Residents appreciated sharing difficult experiences and seeking support. They acknowledged the curriculum as a commitment to wellness and felt it reduced burnout and improved empathy. The comics were viewed as an effective reminder of the patient perspective. Variable curriculum feedback highlights the challenge in designing a course for adult learners. Future investigations may include the development and incorporation of similar curricula in other post-graduate residency training programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".