Unmasking Elder Abuse: Depression and Dependency in the Post-Pandemic Era
Bibliographic record
Abstract
The aim of this study was to analyze elder abuse in people over 65 years of age and its relationship with some risk factors-depression symptoms, dependency, gender and age-in the Spanish population. METHODS: = 6.46), including the Abbreviated Yesavage Scale to assess depression, the Katz Index for Basic Activities of Daily Living to assess dependency, and the American Medical Association and the Canadian Task Force Questionnaire to assess suspicion of abuse. RESULTS: A prevalence of 40.72% of suspected abuse, of 5.99% of established depression, and of 1.20% of severe dependence was obtained. The prevalence of abuse was higher in the population with dependency (75%) than without dependency (37%). In the case of depression, the prevalence of abuse was 70% for people with established depression and 35.4% for people without depression. CONCLUSION: Women have higher rates of abuse than men, although this difference is not statistically significant. The same occurs with age. Nevertheless, having established depression and dependency are confirmed risk factors for suffering abuse.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".