Activating Empathy Through Art in Cancer Communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The Aesthetics of Health (AOH) undergraduate visual art studies course at the University of Texas at Austin aimed to enhance art students' awareness of cancer's impact not only medically but also socially, emotionally, financially, and spiritually and to examine how this experience might impact students' artwork, capacity for empathy, and connection to audience. Methods: During the spring 2021 semester, the AOH course instructors employed assorted pedagogical methods, including art, illness narrative, and community engagement, in special sessions led by professors, community practice artists, and cancer experts, respectively, as well as oral storytelling by those with lived experience of cancer (ie, cancer patients, posttreatment survivors, and loved ones). For the course's final project, the 15 student-artists created self-selected media works combining health and activism and displayed them in public spaces, including online. Student-artists took the Toronto Empathy Questionnaire during the first and last weeks of the course and provided feedback. Two group interviews were also held with cancer storytellers following their participation. Results: Student-artists' average score on the Toronto Empathy Questionnaire increased from 52.46 at pretest to 55.38 at posttest. Student-artists and storytelling participants also reported having positive experiences. Conclusions: The AOH course's social practice approach encouraged student-artists to realize new ideas and relationships and modestly increased their capacity for empathy. The AOH framework demonstrates promise for increasing empathy through the arts in other educational, clinical, and artistic institutions. Further research is needed with larger sample sizes to measure the impact of the course and to demonstrate its potential for addressing burnout and moral distress.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it