Exploring the therapeutic power of narrative at the end of life: a qualitative analysis of narratives emerging in dignity therapy
Bibliographic record
Abstract
OBJECTIVE: To understand the therapeutic effect of a narrative intervention, specifically dignity therapy, in patients at the end-of-life. To examine the thematic dimensions and shared narrative features of the stories that emerge in dignity therapy and theorise their relationship to the intervention's clinical impact. DESIGN: Resident physicians, as part of an educational intervention, co-administered the dignity therapy protocol with the principal investigator. Interviews were transcribed, edited, and then, within a week, read back to the patient and provided as a document for the patient to keep. A constant comparative approach was taken to identify narratives and thematic patterns. PARTICIPANTS: 12 Patients at the end-of-life were administered dignity interviews by 12 resident physicians, accompanied by the principal investigator. SETTING: Palliative care settings in two University of Toronto academic hospitals. RESULTS: Three narrative types emerged, each containing several themes. Evaluation narratives create a life lived before illness, with an overarching theme of overcoming adversity. Transition narratives describe a changing health situation and its meanings, including impact on family and on one's world view. Legacy narratives discuss the future without the patient and contain the parables and messages to be left for loved ones. CONCLUSIONS: While the interview protocol guides patients' responses, the commonality of narrative structures across interviews suggests that patients draw on experiences with two familiar genres: the eulogy and the medical interview, to create a narrative order during the chaos of dying. The dignity interview's resonance with these genres appears to facilitate a powerful, and perhaps unexpected sense of agency.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".