Reclaiming wellness: Key factors in restoring optimal well-being in the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: This study examines characteristics of older adults who have regained optimal well-being at the end of the three-year study. The definition of optimal well-being used in this study refers to having adequate social support, high levels of older adults' subjective perception of their aging process, physical health, mental health, happiness and life satisfaction and being free of limitations in Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs), disabling pain or discomfort, severe mental illness or cognitive decline in the preceding year. METHODS: A secondary data analysis was conducted using the first two waves of data from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA), a large, national, longitudinal study on aging. The sample included 8332 older adults who were not in optimal well-being at baseline and aged 60+ at time 2. Bivariate and multivariable binary logistic regression analyses were used to examine which baseline characteristics were associated with achieving optimal well-being approximately three years later. RESULTS: The prevalence of optimal well-being at time 2 was higher among respondents who, at baseline, were younger, married, physically active, not obese, non-smokers, had higher income, without sleeping problems, diabetes, arthritis, osteoporosis, and achieved at least two of the four wellness domains (i.e., physical, psychological and emotional, social, and self-rated wellness) were more likely to be in optimal well-being at time 2 than their counterparts. CONCLUSIONS: Old age does not necessarily result in poor physical health, nor is a decline in well-being inevitable. Almost one in four respondents who were in less than optimal well-being at baseline regained well-being over the ensuing approximately 3 years. Further research could investigate the association between policies and programs and their support for older adults in regaining optimal well-being in later life after a period of suboptimal well-being.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".