Socioeconomic inequalities in resilience and vulnerability among older adults: a population-based birth cohort analysis
Bibliographic record
Abstract
ABSTRACTBackground:Aging is associated with declines in physical capability; however, some individuals demonstrate high well-being despite this decline, i.e. they are "resilient." We examined socioeconomic position (SEP) and resilience and the influence of potentially modifiable behavioral resources, i.e. social support and leisure time physical activity (LTPA), on these relationships. METHODS: Data came from the Medical Research Council National Survey of Health and Development, a nationally-representative birth cohort study. Resilience-vulnerability at age 60-64 years (n = 1,756) was operationalized as the difference between observed and expected levels of well-being, captured by the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), given the level of performance-based physical capability. SEP was assessed by father's and own social class, parental education, and intergenerational social mobility. PA and structural/functional social support were reported at ages 53 years and 60-64 years. Path analysis was used to examine mediation of SEP and resilience-vulnerability through LTPA and social support. RESULTS: Participants in the highest social class had scores on the resilience to vulnerability continuum that were an average of 2.3 units (β = 0.46, 95% CI 0.17, 0.75) higher than those in the lowest social class. Greater LTPA (β = 0.58, 95% CI 0.31, 0.85) and social support (β = 3.27, 95% CI 2.90, 3.63) were associated with greater resilience; LTPA partly mediated participant social class and resilience (23.4% of variance). CONCLUSIONS: Adult socioeconomic advantage was associated with greater resilience. Initiatives to increase LTPA may contribute to reducing socioeconomic inequalities in this form of resilience in later life.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".