In many voices: exploring end-of-life care through patient, caregiver and physician narratives
Bibliographic record
Abstract
As the focus on end-of-life care intensifies, so too does the need to better understand the experiences of patients, caregivers and physicians. Delivering empathetic care requires a shared understanding of illness and its meaning and impact. The narratives of patients, caregivers and physicians each offer a distinct perspective on clinical experiences, yet comparative research is uncommon. This study compares written narratives about end-of-life illness and care by these groups.We created an archive of 332 first-person written narratives about end of life (patient=65, caregiver=156, physician=111) published between 1 January 2010 and 31 December 2019 through searching public domains (eg, national newspapers), personal blogs, and academic and literary journals in Canada. A comparative narrative analysis was conducted for patterns of content (eg, theme) and strategy (eg, characterisation).All three groups wrote about feeling gratitude. Patients also emphasised coping with change and carrying on. Caregivers further focused on grieving loss, and physicians most often wrote about valuing humanism. Physicians were most likely to ascribe agency to someone (ie, patients) or something (ie, death) other than themselves and to decentre themselves in the story. Patients and physicians most often made the patient the main character of their stories, while caregivers were as likely to centre the story on themselves as on the patient. Physicians were most likely to describe death as a source of tension, while patients and caregivers described the illness experience, often comparing it to battle. Physicians and caregivers tended to write testimonies, while patients wrote quests.Narrative research can illuminate unique aspects of end-of-life care. While death is a shared experience, each group approaches it differently. The disconnects have potential consequences for how end of life is experienced-whether patients' values are honoured, whether caregivers receive support, and whether physicians experience burn-out. We need to foster learning experiences that integrate these unique perspectives into medical education and practice, including leveraging the affordances of studying written narratives towards this end.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".