‘I think most of it comes down to the social determinants of health’: older adults’ views on primary and community care restructuring
Bibliographic record
Abstract
Abstract Social determinants of health (SDH) impact older adults’ ability to age in place, including their access to primary and community care services. Yet, older service users are infrequently consulted on the design and delivery of health services; when they are consulted, there is scant recruitment of those who are Indigenous, racialized and/or rural. This study aimed to identify SDH for socially and culturally diverse community-dwelling older adults and to understand their views on how primary and community care restructuring might address these SDH. We recruited a diverse group of 83 older adults (mean = 75 years) in Western Canada and compared quantitative and qualitive data. The majority resided rurally, identified as women, lived with complex chronic disease (CCD), had low income and/or lived alone; nearly a quarter were Indigenous or Sikh. Indigenous status correlated with income; gender correlated with income and living situation. Thematic analysis determined that income, living situation, living rurally, Indigenous ancestry, ethno-racial minority status, gender and transportation were the main SDH for our sample. Income was the most predominant SDH and intersected with more SDH than others. Indigenous ancestry and ethno-racial minority status – as SDH – manifested differently, underscoring the importance of disaggregating data and/or considering the uniqueness of ‘BIPOC’ groups. Our study suggests that SDH models should better reflect ageing and living rurally, that policy/decision makers should prioritize low-income and ethno-racial minority populations and that service providers should work with service users to ensure that primary and community care (restructuring) addresses their priorities and mitigates SDH.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".