What socio-economic factors determine place of death for people with life-limiting illness? A systematic review and appraisal of methodological rigour
Bibliographic record
Abstract
BACKGROUND: Socio-economic factors play important roles in place of death. However, up-to-date knowledge on socio-economic determinants for place of death is warranted including analysis of collinearity between socio-economic determinants. AIM: To examine associations between socio-economic determinants (social class, deprivation level in area of residence, income, education, occupation, urbanisation) and place of death among adult patients with life-limiting illnesses. Furthermore, to describe how these factors are operationalised and examined for collinearity. DESIGN: A systematic review was performed (PROSPERO, record: CRD42018091218) and quality was assessed using the Newcastle-Ottawa Scale. DATA SOURCES: A comprehensive search of PubMed, Embase, CINAHL, Scopus and PsycINFO was conducted for studies published from 1 January 2008 until the date of the search (23 March 2018) in English or Scandinavian languages. RESULTS: Of the 1599 unique citations identified, 34 studies were eligible. Dying at home was to a high degree associated with better financial situation and living in rural areas. Furthermore, hospital death was associated with a high level of deprivation in the area of residence and being employed. Regarding educational level, we found mixed and inconclusive results. CONCLUSION: Inequalities concerning place of death were found, and attention towards socio-economic inequality concerning place of death is necessary, especially in patients with a poor financial status, patients living in deprived and metropolitan areas and patients who are employed. Furthermore, we found a low degree of assessment for collinearity and adjustment of socio-economic variables. These issues should be considered in planning of future studies of socio-economic determinants for place of death.
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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 | 0.050 | 0.212 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 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".