ADULT DAY CENTRES AND THEIR OUTCOMES ON CLIENTS, CAREGIVERS, AND THE HEALTH SYSTEM: A SCOPING REVIEW
Bibliographic record
Abstract
Purpose of the study: Adult day centers (ADCs) offer a heterogeneous group of services that provide for the daily living, care, nutritional, and social needs of older adults. We sought to conceptually map and identify key gaps and findings from literature focused on ADCs, including the types of programs that exist and their associated outcomes on improving health and strengthening health systems. Design and Methods: We conducted a scoping review by searching five databases for studies evaluating the outcomes of ADCs specifically for community-dwelling older adults. Included studies were conceptually mapped according to the methods used, type of outcome(s) assessed, study population, disease focus, service focus, and health system considerations. The mapping was used to derive descriptive analyses to profile the available literature in the area. Results: ADC use has positive health-related, social, psychological and behavioral outcomes for care recipients and caregivers. There is a substantial amount of literature available on some ADC use outcomes, such as health-related, satisfaction-related and psychological and behavioral outcomes, while less research exists on issues of accessibility and cost-effectiveness. Implications: As the population ages, policymakers must carefully consider how ADCs can best serve each user and their caregivers with their unique circumstances. ADCs have the potential to help shape health system interventions, especially those targeting caregivers and people requiring long-term care support. Due to the variation among types of ADC programs, future research on ADCs should consider different characteristics of ADC programs to better contextualize their results.
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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 | 0.015 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".