Conducting a narrative medicine workshop in ambulatory palliative care: A feasibility and exploratory study
Bibliographic record
Abstract
OBJECTIVES: This pilot study aimed to assess the feasibility and impact of a narrative medicine group for patients receiving palliative care. METHODS: This pilot study aimed to assess the feasibility of a six-session, physician-led narrative medicine group for patients receiving palliative care. Ten patients were recruited by their outpatient providers. Symptom severity and patient dignity scores were collected pre-intervention, at the mid-point, and post-intervention using the Patient Dignity Inventory (PDI) and Edmonton Symptom Assessment Survey (ESAS). Qualitative reports of pain, expectations, and anticipated challenges were collected before the intervention. Participant interviews were conducted after the intervention to assess overall experience in the group, challenges experienced, recommendations for future endeavors, and general feedback. RESULTS: No significant changes in PDI or ESAS scores were observed at baseline, 3 weeks, and 6 weeks. Participants reported overall satisfaction, with 8 of 9 participants stating they "strongly agree" they would participate in the group again and recommend the group to others. Qualitative responses indicated benefits in the realms of relating to other patients, subjective reduction in pain, and relieving feelings of isolation. SIGNIFICANCE OF RESULTS: A narrative medicine group for ambulatory patients receiving palliative care appeared to be both beneficial and feasible when delivered through a virtual format. A randomized trial with a larger sample is needed to fully assess the impacts of engaging in narrative work on symptom burden, survival, and quality of life.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".