What Factors Shape Self-Reported Health Among Community-Dwelling Older Adults? A Scoping Review
Bibliographic record
Abstract
Self-reported health is a predictive measure of morbidity and mortality across populations. A comprehensive understanding of the factors that shape self-reported health among community-dwelling older adults, a growing population globally, is lacking. The aim of this review was to summarize the factors that are associated with self-reported health among this population and identify key areas for future research. Accordingly, we conducted a scoping review using the stage-wise framework developed by Arksey and O'Malley. We summarized 42 factors, as identified in 30 publications, and organized them into four categories. Key factors shaping self-reported health included the presence of chronic conditions and depressive symptoms. As the population of community-dwelling older adults continues to increase, there remains a need to understand how these identified factors shape self-reported health. To date, empirical research has been limited to observational and cross-sectional designs. There is a need to further explore these factors in longitudinal data.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".