Volunteer-supported Care Transition Interventions for People Living with Dementia: A Secondary Analysis of a Scoping Review
Bibliographic record
Abstract
Introduction: Rising dementia rates can worsen the strain on the healthcare system and increase hospital admissions. Hospitals decondition persons living with dementia (PLWD), for which volunteers can offer support. We reviewed existing literature on volunteer-led/supported care transition services available to PLWD, assessing PLWD representation and the extent to which their needs are addressed. Methods: We conducted a secondary analysis of a scoping review examining volunteer and third-sector personnel providing post-discharge support. Of the review's 49 articles, we considered services offered to PLWD and persons with cognitive impairment (PWCI). The Camberwell Assessment of Needs for the Elderly (CANE) guided the thematic analysis. Results: Four of our nine selected articles highlighted services supporting PLWD, though only one was developed explicitly for them. The most common themes of needs targeted or met were physical health (n = 7), company (n = 7), food (n = 6), medications (n = 6), and psychological distress (n = 6). Discussion: We described the characteristics and outcomes of these volunteer-led/supported care transition interventions. Comparing the leading PLWD needs against those the interventions primarily addressed revealed potential oversight of their most critical needs. However, volunteers remain valuable in supporting discharged community-dwelling PLWD. Conclusion: In hospital-to-home care transitions, volunteer-led/supported transitional care models benefit PLWD and their caregivers. However, few available interventions explicitly focus on this patient population. Therefore, this is an opportunity to understand better how volunteers and third-sector organizations could optimally support those living during care transitions through an integrated care approach.
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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 | 0.035 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.024 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".