Decision aids for home and community care: a systematic review
Bibliographic record
Abstract
OBJECTIVES: Decision aids (DAs) for clients in home and community care can support shared decision-making (SDM) with patients, healthcare teams and informal caregivers. We aimed to identify DAs developed for home and community care, verify their adherence to international DA criteria and explore the involvement of interprofessional teams in their development and use. DESIGN: Systematic review reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES: Six electronic bibliographic databases (MEDLINE, Embase, CINAHL Plus, Web of Science, PsycINFO and the Cochrane Library) from inception to November 2019, social media and grey literature websites up to January 2021. ELIGIBILITY CRITERIA: DAs designed for home and community care settings or including home care or community services as options. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently reviewed citations. Analysis consisted of a narrative synthesis of outcomes and a thematic analysis. DAs were appraised using the International Patient Decision Aid Standards (IPDAS). We collected information on the involvement of interprofessional teams, including nurses, in their development and use. RESULTS: After reviewing 10 337 database citations and 924 grey literature citations, we extracted characteristics of 33 included DAs. DAs addressed a variety of decision points. Nearly half (42%) were relevant to older adults. Several DAs did not meet IPDAS criteria. Involvement of nurses and interprofessional teams in the development and use of DAs was minimal (33.3% of DAs). CONCLUSION: DAs concerned a variety of decisions, especially those related to older people. This reflects the complexity of decisions and need for better support in this sector. There is little evidence about the involvement of interprofessional teams in the development and use of DAs in home and community care settings. An interprofessional approach to designing DAs for home care could facilitate SDM with people being cared for by teams. PROSPERO REGISTRATION NUMBER: CRD42020169450.
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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 | 0.028 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".