Self-reported health and the well-being paradox among community-dwelling older adults: a cross-sectional study using baseline data from the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
Abstract Background Self-reported health is a widely used epidemiologic measure, however, the factors that predict self-reported health among community-dwelling older adults (≥65 years), especially those with multimorbidity (≥2 chronic conditions), are poorly understood. Further, it is not known why some older adults self-report their health positively despite the presence of high levels of multimorbidity, a phenomenon known as the well-being paradox. The objectives of this study were to: 1) examine the factors that moderate or mediate the relationship between multimorbidity and self-reported health; 2) identify the factors that predict high self-reported health; and 3) determine whether these same factors predict high self-reported health among those with high levels of multimorbidity to better understand the well-being paradox. Methods A cross-sectional analysis of baseline data from the Canadian Longitudinal Study on Aging was completed (n = 21,503). Bivariate stratified analyses were used to explore whether each factor moderated or mediated the relationship between multimorbidity and self-reported health. Logistic regression was used to determine the factors that predict high self-reported health in the general population of community-dwelling older adults and those displaying the well-being paradox. Results None of the factors explored in this study moderated or mediated the relationship between multimorbidity and self-reported health, yet all were independently associated with self-reported health. The ‘top five’ factors predicting high self-reported health in the general older adult population were: lower level of multimorbidity (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.74-0.76), female sex (OR 0.62, CI 0.57-0.68), higher Life Space Index score (OR 1.01, CI 1.01-1.01), higher functional resilience (OR 1.16, CI 1.14-1.19), and higher psychological resilience (OR 1.26, CI 1.23-1.29). These same ‘top five’ factors predicted high self-reported health among the subset of this population with the well-being paradox. Conclusions The factors that predict high self-reported health in the general population of older adults are the same for the subset of this population with the well-being paradox. A number of these factors are potentially modifiable and can be the target of future interventions to improve the self-reported health of this population.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".