Examining the Role of Third Sector Organization Volunteers in Facilitating Hospital-to-Home Transitions for Older Adults – a Collective Case Study
Bibliographic record
Abstract
Introduction: With increasing attention to models of transitional support delivered through multisectoral approaches, third-sector organizations (TSOs) have supported community reintegration and independent living post-hospitalization. This study aimed to identify the core elements of these types of programs, the facilitators, and barriers to service implementation and to understand the perspectives of providers and recipients of their experiences with the programs. Methods and Analysis: A collective case study collected data from two UK-based 'Home from Hospital' programs. An inductive thematic analysis generated rich descriptions of each program, and analytical activities generated insights across the cases. Results: Programs provided a range of personalized support for older adults and addressed many post-discharge needs, including well-being assessments, support for instrumental activities of daily living, psychosocial support, and other individualized services directed by the needs and preferences of the service user. Results suggest that these programs can act as a 'safety net' and promote independent living. Skilled volunteers can positively impact older adults' experience returning home. Conclusions: When the programs under study are considered in tandem with existing evidence, it facilitates a discussion of how TSO services could be made available more widely to support older adults in their transition experiences.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 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".