Rural end-of-life care from the experiences and perspectives of patients and family caregivers: A systematic literature review
Bibliographic record
Abstract
BACKGROUND: End-of-life care must be relevant to the dying person and their family caregiver regardless of where they live. Rural areas are distinct and need special consideration. Gaining end-of-life care experiences and perspectives of rural patients and their family caregivers is needed to ensure optimal rural care. AIMS: To describe end-of-life care experiences and perspectives of rural patients and their family caregivers, to identify facilitators and barriers to receiving end-of-life care in rural/remote settings and to describe the influence of rural place and culture on end-of-life care experiences. DESIGN: A systematic literature review utilising the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES: Four databases (PubMed, CINAHL, Scopus and Web of Science) were searched in January 2016, using a date filter of January 2006 through January 2016; handsearching of included article references and six relevant journals; one author contacted; pre-defined search terms and inclusion criteria; and quality assessment by at least two authors. RESULTS: A total of 27 articles (22 rural/remote studies) from developed and developing countries were included, reporting rural end-of-life care experiences and perspectives of patients and family caregivers. Greatest needs were informational (developed countries) and medications (developing countries). Influence of rural location included distances, inaccessibility to end-of-life care services, strong community support and importance of home and 'country'. CONCLUSION: Articulation of the rural voice is increasing; however, there still remain limited published rural studies reporting on patient and family caregivers' experiences and perspectives on rural end-of-life care. Further research is encouraged, especially through national and international collaborative work.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".