Nurse‐led adult palliative care models in low‐ and middle‐income countries: A scoping review
Bibliographic record
Abstract
AIMS: To map evidence on the nature and extent of use of nurse-led palliative care models in low- and middle-income countries serving adults with life-limiting conditions. DESIGN: A scoping review of the literature was undertaken. DATA SOURCES: A systematic search was performed from database inception to March 2022 in: Medline, EMBASE, CINAHL, Wiley Cochrane Library, SCOPUS, Web of Science, SciELO and Global Health. Main search terms included: Nurse-led AND Palliative care AND Low-and middle-income countries. Grey literature was searched from Proquest Dissertations and Theses Global, the World Health Organization and selected palliative care websites. We searched the reference list of included articles for additional studies. REVIEW METHODS: We used the framework by Arksey and O'Malley and the PRISMA-ScR guidelines. Titles and abstracts were screened by one reviewer and full text by two reviewers. Thematic analysis was used to synthesize data and results are presented descriptively using themes and categories. RESULTS: Eighteen studies were included, with majority from Sub-Saharan Africa (10/20). Three nurse-led palliative care models emerged: nurse-led empowering care, nurse-led symptom control and nurse-led multicomponent palliative care. They served particularly cancer and HIV patients and were delivered in person or by telehealth care. Reported outcomes were adherence to therapy, improved self-care ability, improved quality of life and increased access to palliative. CONCLUSIONS: The use of nurse-led palliative care in low- and middle-income countries is in its developing stages and seems feasible. Nursing roles in in low- and middle-income countries need to be expanded by developing advanced practice nurses and nurse practitioner programmes, with palliative care content. More impact evaluation studies on the use of nurse-led palliative care models in these countries are needed. IMPACT: This review highlights nurse-led care models that can enhance access and quality of life of patients with life-limiting conditions in low- and middle-income countries.
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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 | 0.020 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".