Resilience factors associated with physical function in vulnerable older adults from four countries
Bibliographic record
Abstract
Abstract Background Adverse childhood experiences (ACEs) include an array of maltreatment and they have been shown to confer higher risks of early mobility loss and ultimately disablement in older ages. This study aims to identify resilience factors associated with physical function in a diverse sample of older adults (65-74 years) from the 2012 International Mobility in Aging Study (IMIAS) who reported ACEs. Methods 2002 participants were recruited from Kingston, Ontario; St. Hyacinthe, Quebec; Tirana, Albania; Manizales, Colombia; and Natal, Brazil. Economic ACEs were classified by self-report of at least one-poor childhood economic status, childhood hunger, parental unemployment-before the age of 15 years. The Short Physical Performance Battery was used to measure physical function; a score of < 8 was considered poor. Associations between hypothesized resilience factors (education, social support, expressed gender roles) and physical function were identified via bivariate analysis and logistic regression; after adjusting for sex, age, and sample site. Results Nearly half (46%) the participants reported economic ACES. High levels of education (OR 0.39; CI: 0.22-0.66) and social support from family (OR: 0.52; CI: 0.36-0.76), partners (OR: 0.47; CI: 0.29-0.74), and friends (OR: 0.59; CI: 0.38-0.92), as well as masculine (OR:0.49; CI: 0.29-0.83) and androgynous (0.48; CI: 0.30-0.77) gender roles, protected against poor physical function for those reporting childhood economic ACEs. Conclusions Despite encountering economic ACEs, those who achieved high relative levels of education, greater levels of support, as well as those characterized by masculine or androgynous gender roles, were more likely to maintain good physical performance in older ages compared to those with low education, no social support, and those classified as undifferentiated gender roles. Findings highlight critical points of intervention for those who experienced ACES. Key messages These findings imply that the associated negative physical health outcomes of ACEs can be delayed or eliminated via exposure to certain protective factors. Economic ACE exposure may be unavoidable, but there are resilience factors that could be promoted to foster the better health across the life course.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".