Evaluation of a Flexible Artist-Facilitated Storytelling Intervention on a Palliative Care Unit
Bibliographic record
Abstract
CONTEXT: Narrative interventions have been shown to be appropriate and feasible in palliative care for patients, caregivers, and healthcare professionals alike. However, such interventions lack customizability, are resource and time intensive, and are often facilitated by clinical staff who have minimal training in story development. OBJECTIVES: Evaluate a single, brief, artist-facilitated storytelling session on a palliative care unit and analyze stories with the five elements of close reading in narrative medicine. METHODS: A professional storyteller facilitated sessions with patients, caregivers, and healthcare professionals on a palliative care unit, starting with an open-ended question (e.g., "What story do you want to tell?"). Through a convergent parallel mixed-methods design, participants quantitatively assessed the appropriateness, acceptability, feasibility, worthwhileness, meaningfulness, and emotional resonance of the intervention, triangulated with rapid analysis of a semi-structured interview with the storyteller. We subsequently analyzed story content with the five elements of close reading in narrative medicine. RESULTS: From 18 sessions, patients (n = 6), caregivers (n = 8), and healthcare professionals (n = 6), found the storytelling session acceptable, appropriate, feasible, meaningful and worthwhile. The storyteller perceived participants as enthusiastic and appreciative. She recommended storytellers be available, accessible, and adaptable to participants' time and energy. Patient and caregiver stories described the palliative care unit as a calm site of reflection, and framed illness as a journey. Healthcare professionals' stories reflected pride in and gratitude for their work. CONCLUSIONS: A single, brief, artist-facilitated storytelling session is acceptable, feasible, and appropriate on a palliative care unit. Story content focused on the benefits of palliative care.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".