The Art of Teaching Empathy: Feasibility and Impact of Online Art-Based Education on Interns’ Empathy. A Pilot Quasi-Experimental Mixed Methods study
Bibliographic record
Abstract
Introduction. Empathy is an essential attribute for a physician of excellence. Nevertheless, its instruction has been left out in most medical curricula, and some studies have shown a decrease in empathy during training. Since empathy requires both cognitive and emotional competence, its instruction can be very challenging. Although several studies have addressed how art-based education can foster empathy, there is a need for more robust evidence- based research with rigorous study designs. Therefore, this pilot project aimed to explore the feasibility and impact of art-based education on empathy in Brigham & Women's Hospital’s (BWH) interns. Methods. A mixed methods quasi-experimental pilot design was used, in which semi-structured interviews were embedded within a pilot quasi-experimental trial. A total of 70 interns of the BWH were enrolled in the study and designated to the intervention or control group. The curriculum consisted of two art-based sessions focused on empathy for the intervention group, delivered online necessitated by the global COVID-19 pandemic. The control group followed education as usual, which consisted of two empathy-focus sessions, part of their Humanistic Curriculum course. Two instruments with known validity, the Toronto Empathy ii Questionnaire (TEQ) and the Jefferson Scale of Physician Empathy (JSPE), were used pre- and post-intervention to measure empathy level. Additionally, after the intervention, qualitative data were collected to add new insights to understand the art-based curriculum’s impact. Results. Concerning the pilot piece, the participation rate was 30.6%. Three themes emerged from the qualitative analysis regarding acceptability: “limits of the virtual environment”, “benefits of the sessions”, and “session appraisal”. Regarding the art-based curriculum’s impact, quantitative analysis showed no association between the TEQ scores (p=0.136) and the JSPE scores (p=0.352), and the art-based curriculum. The qualitative analysis revealed how the curriculum impacted students’ empathy, with two main themes: “perceived impact” and “non-perceived impact”. Conclusion. We were unable to determine the online art-based curriculum’ feasibility to teach empathy to medical interns since the results were inconclusive, when considered in the current pandemic context. Regarding its impact on empathy, we were unable to find a significant association; however, this may result from low student participation due to COVID-19, which likely resulted in the study being underpowered. Despite this, the qualitative analysis showed a tendency of the sessions to positively influence students' reflections and actions towards empathy, raising the question of how we should be approaching the assessment of this complex construct.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".