Stakeholder involvement in care transition planning for older adults and the factors guiding their decision-making: a scoping review
Bibliographic record
Abstract
OBJECTIVE: To synthesise the existing literature on care transition planning from the perspectives of older adults, caregivers and health professionals and to identify the factors that may influence these stakeholders' transition decision-making processes. DESIGN: A scoping review guided by Arksey and O'Malley's six-step framework. A comprehensive search strategy was conducted on 7 January 2021 to identify articles in five databases (MEDLINE, Embase, CINAHL Plus, PsycINFO and AgeLine). Records were included when they described care transition planning in an institutional setting from the perspectives of the care triad (older adults, caregivers and health professionals). No date or study design restrictions were imposed. SETTING: This review explored care transitions involving older adults from an institutional care setting to any other institutional or non-institutional care setting. Institutional care settings include communal facilities where individuals dwell for short or extended periods of time and have access to healthcare services. PARTICIPANTS: Older adults (aged 65 or older), caregivers and health professionals. RESULTS: 39 records were included. Stakeholder involvement in transition planning varied across the studies. Transition decisions were largely made by health professionals, with limited or unclear involvement from older adults and caregivers. Seven factors appeared to guide transition planning across the stakeholder groups: (a) institutional priorities and requirements; (b) resources; (c) knowledge; (d) risk; (e) group structure and dynamic; (f) health and support needs; and (g) personality preferences and beliefs. Factors were described at microlevels, mesolevels and macrolevels. CONCLUSIONS: This review explored stakeholder involvement in transition planning and identified seven factors that appear to influence transition decision-making. These factors may be useful in advancing the delivery of person and family-centred care by determining how individual-level, group-level and system-level values guide decision-making. Further research is needed to understand how various stakeholder groups balance these factors during transition planning in different health contexts.
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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 | 0.056 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".