Risk factors for elder abuse in the Global South: a case study in northeastern Colombia
Bibliographic record
Abstract
OBJECTIVES: Elder abuse has become a neglected public health issue and represents one of the most significant challenges for the older population. In response, this study identified risk factors for elder abuse based on the clinical and sociodemographic characteristics of a sample of older adults. METHOD: A cross-sectional study with a correlational scope was conducted to evaluate 543 older adults from northeastern Colombia. The Elder Abuse Scale, Barthel Index, Montreal Cognitive Assessment, State-Trait Anxiety Inventory (STAI), and Yesavage Geriatric Depression Scale were applied. Data analysis was performed using binomial logit models. RESULTS: The identified risk factors for physical abuse included being single, symptoms of depression, and expected cognitive performance. For psychological abuse, depressive symptoms, being divorced/separated or in a common-law relationship, being female, and high trait anxiety test scores were identified as risk factors. For neglect, being a Jehovah's Witness, having depressive symptoms, living in urban areas, and having a suspected neurocognitive disorder were identified as risk factors. Lastly, the risk factors for financial abuse were suspected neurocognitive disorder, depressive symptoms, being in a common-law relationship or single, and being employed. CONCLUSION: Overall, the protective factors highlighted were not practicing religion, functional independence, and living with relatives in urban areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".