Identifying and understanding the health and social care needs of older adults with multiple chronic conditions and their caregivers: a scoping review
Bibliographic record
Abstract
BACKGROUND: As the population is aging, the number of persons living with multiple chronic conditions (MCC) is expected to increase. This review seeks to answer two research questions from the perspectives of older adults with MCC, their caregivers and their health care providers (HCPs): 1) What are the health and social care needs of community-dwelling older adults with MCC and their caregivers? and 2) How do social and structural determinants of health impact these health and social care needs? METHODS: We conducted a scoping review guided by a refinement of the Arksey & O'Malley framework. Articles were included if participants were 55 years or older and have at least two chronic conditions. We searched 7 electronic databases. The data were summarized using thematic analysis. RESULTS: Thirty-six studies were included in this review: 28 studies included participants with MCC; 12 studies included HCPs; 5 studies included caregivers. The quality of the studies ranged from moderate to good. Five main areas of needs were identified: need for information; coordination of services and supports; preventive, maintenance and restorative strategies; training for older adults, caregivers and HCPs to help manage the older adults' complex conditions; and the need for person-centred approaches. Structural and social determinants of health such as socioeconomic status, education and access influenced the needs of older adults with MCC. CONCLUSION: The review highlights that most of the needs of older adults with MCC focus on lack of access to information and coordination of care. The main structural and social determinants that influenced older adults' needs were their level of education/health literacy and their socioeconomic status.
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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 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| 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".