Interventions to support family caregivers of people with advanced dementia at the end of life in nursing homes: A mixed-methods systematic review
Bibliographic record
Abstract
BACKGROUND: Most people with dementia transition into nursing homes as their disease progresses. Their family caregivers often continue to be involved in their relative's care and experience high level of strain at the end of life. AIM: To gather and synthesize information on interventions to support family caregivers of people with advanced dementia at the end of life in nursing homes and provide a set of recommendations for practice. DESIGN: Mixed-Methods Systematic Review (PROSPERO no. CRD42020217854) with convergent integrated approach. DATA SOURCES: Five electronic databases were searched from inception in November 2020. Published qualitative, quantitative, and mixed-method studies of interventions to support family caregivers of people with advanced dementia at the end of life in nursing home were included. No language or temporal limits were applied. RESULTS: In all, 11 studies met the inclusion criteria. Data synthesis resulted in three integrated findings: (i) healthcare professionals should engage family caregivers in ongoing dialog and provide adequate time and space for sensitive discussions; (ii) end-of-life discussions should be face-to-face and supported by written information whose timing of supply may vary according to family caregivers' preferences and the organizational policies and cultural context; and (iii) family caregivers should be provided structured psychoeducational programs tailored to their specific needs and/or regular family meetings about dementia care at the end of life. CONCLUSION: The findings provide useful information on which interventions may benefit family caregivers of people with advanced dementia at the end of life and where, when, and how they should be provided.
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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 | 0.021 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".