Association between domestic abuse and violence against older adults and frailty, depression, and nutritional status in an urban Brazilian setting
Bibliographic record
Abstract
Objective: To investigate the association between the risk of violence against older adults and factors such as frailty, depressive symptoms, and nutritional status in a population receiving care in Primary Health Care (PHC). Methods: This was an observational, cross-sectional, and quantitative study conducted between June 2023 and March 2024 in the municipalities of Santa Cruz and Macaíba, Rio Grande do Norte, Brazil. The study included 323 older adults (≥ 60 years old) registered in the PHC system. Data collection utilized validated instruments, including the Hurt, Insult, Threaten, Scream - Elder Abuse Screening Test (H-S/EAST) to assess violence risk, the Conflict Tactics Scales Form R (CTS-1) for classifying violence situations, the Edmonton Frailty Scale (EFS) for frailty, the Geriatric Depression Scale (GDS-15) for depressive symptoms, and the Mini Nutritional Assessment (MNA) for nutritional status. Statistical analyses included descriptive statistics, chi-square tests, Mann-Whitney U tests, Spearman correlations, and binary logistic regression. Results: Among participants, 46.1% were at risk of violence. Absence of verbal aggression, adequate social support, emotional independence, and better functionality were protective factors against violence. Advanced frailty (OR = 2.43), depressive symptoms (OR = 2.49), and malnutrition (OR = 1.52) were significantly associated with the risk of abuse. Logistic regression identified mood (R² = 0.19) and depressive symptoms (R² = 0.19) as the main predictors of violence. Conclusion: A significant association was found between the risk of abuse and multidimensional factors, particularly a history of violent situations, frailty, and depressive symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".