EXPERIENCES OF VIOLENCE ACROSS LIFE COURSE AND ITS ASSOCIATION WITH MOBILITY DISABILITY IN OLDER AGE
Bibliographic record
Abstract
Background: Life course exposure to violence may lead to disability in old age. We examined associations between life course violence and mobility disability in older participants of the International Mobility in Aging Study (IMIAS). Methods: During the IMIAS 2012 baseline survey, men and women aged 65–74 years were recruited at five cities (n=1995): Kingston and Saint-Hyacinthe (Canada), Tirana (Albania), Manizales (Colombia), and Natal (Brazil). Mobility was assessed by the SPPB and by two questions on difficulty in walking and climbing stairs. Childhood physical abuse history and the HITS instrument were used to gather information on childhood exposure to violence and violence by intimate partners or family members. Multivariate logistic regression analysis models were constructed to explore associations between violence and mobility disability. Results: Psychological violence either perpetrated by partner or family was more frequent than physical violence. Compared to men, women were more often victims of all types of violence. Experiences of childhood physical abuse and adult physical violence either by family or partner were related to mobility disability (adjusted for age, sex, childhood socioeconomic status, education and research site). Those exposed to physical violence by a partner showed 40% to 63% greater odds of mobility disabilities. Those exposed to childhood physical abuse showed 43% to 69% greater odds of mobility disabilities. Gender was not an effect modifier for the relationships between any form of violence and mobility. Conclusion: Our results provide evidence for the detrimental effects of life course exposure to violence on mobility 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".