Rural residents' perspectives on the rural ‘good death’: a scoping review
Bibliographic record
Abstract
The 'good death' is one objective of palliative care, with many 'good death' viewpoints and research findings reflecting the urban voice. Rural areas are distinct and need special consideration. This scoping review identified and charted current research knowledge on the 'good' rural death through the perspectives of rural residents, including rural patients with a life-limiting illness, to identify evidence and gaps in the literature for future studies. A comprehensive literature search of English language articles (no date filter applied) was conducted in 2016 (2 January to 14 February) using five library databases. Reference lists of included articles, recent issues of eight relevant journals and three grey literature databases were also hand-searched. Twenty articles (for 17 studies and one systematic review) were identified after a two-phase screening process by two reviewers, using pre-determined inclusion criteria. Data from each study were extracted and charted, analysed using a thematic analysis of the included articles' content, and with a quantitative analysis of the scoping review. These papers revealed data collected from rural patients with a life-limiting illness and family caregivers, rural healthcare providers, the wider rural community, rural community leaders and rural health administrators and policy makers. Rural locations were heterogeneous. Residents from developed and developing countries believe a 'good death' is one that is peaceful, free of pain and without suffering; however, this is subjective and priorities are based on personal, cultural, social and religious perspectives. Currently, there is insufficient data to generalise rural residents' perspectives and what it means for them to die well. Given the extreme importance of a 'good death', there is a need for further studies to elicit rural patient and family caregiver perspectives.
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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 | 0.016 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".