Informal carer support needs, facilitators and barriers in transitional care for older adults from hospital to home: A scoping review
Bibliographic record
Abstract
AIM: To synthesise evidence about informal carers' (carers) experience of their support needs, facilitators and barriers regarding transitional care of older adults with multimorbidity. BACKGROUND: Carers provide crucial support for older adults during care transitions. Although health practitioners are well positioned to support carers, system factors including limited healthcare resources can compromise the quality of care transitions. DESIGN: Scoping review. METHODS: Searches were undertaken of the published literature. Five databases were searched including MEDLINE, CINAHL, EMBASE, PsycINFO and the Cochrane Library. Two reviewers independently screened articles to identify relevant studies. Studies were retrieved from January 2000 to July 2022. Data were extracted and tabulated for study characteristics, support needs, facilitators and barriers. Key themes and patterns were synthesised across the studies. RESULTS: Eighteen studies including N = 3174 participants were retrieved. Most studies (n = 13) employed qualitative designs. Five studies used surveys. Carers reported their need to: be involved in coordinated discharge planning; advocate and be involved in decision-making; and receive community-based follow-up. Carers described facilitators and barriers in four themes: (1) relationships with the older adult and health practitioners, (2) being involved in coordinated discharge planning; (3) communication and information strategies; and (4) community-based follow-up. Synthesis of themes across all studies resulted in the identification of five areas of research: carers' health literacy; community-based care; carers' involvement in transitional care planning; inpatient and community health practitioners' communication skills; and culturally diverse carers' experiences. CONCLUSION AND RELEVANCE TO CLINICAL PRACTICE: The review highlights the importance of quality communication and relationships between carers, older adults, health practitioners and health organisations. Although information and education are important there is a need for further research to examine systems that support communication between carers, older adults and health practitioners and health literacy for all carers including culturally diverse carers.
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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 | 0.022 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".