Hope and advance care planning in patients with end stage renal disease: qualitative interview study
Bibliographic record
Abstract
OBJECTIVE: To understand hope in the context of advance care planning from the perspective of patients with end stage renal disease. DESIGN: Qualitative in-depth interview study. SETTING: Outpatient department of a university affiliated nephrology programme. PARTICIPANTS: 19 patients with end stage renal disease purposively selected from the renal insufficiency, haemodialysis, and peritoneal dialysis clinics. RESULTS: Patients' hopes were highly individualised and were shaped by personal values. They reflected a preoccupation with their daily lives. Participants identified hope as central to the process of advance care planning in that hope helped them to determine future goals of care and provided insight into the perceived benefits of advance care planning and their willingness to engage in end of life discussions. More information earlier in the course of the illness focusing on the impact on daily life, along with empowerment of the patient and enhancing professional and personal relationships, were key factors in sustaining patients' ability to hope. This helped them to imagine possibilities for a future that were consistent with their values and hopes. The reliance on health professionals to initiate end of life discussions and the daily focus of clinical care were seen as potential barriers to hope. CONCLUSIONS: Facilitated advance care planning through the provision of timely appropriate information can positively enhance rather than diminish patients' hope. Current practices concerning disclosure of prognosis are ethically and psychologically inadequate in that they do not meet the needs of patients.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".