P14: “Invisible hence inexistent?”: Sexual violence in older adults
Bibliographic record
Abstract
Objective:Although sexual violence (SV) is increasingly recognized as a major public health problem, older people are ignored in policies and practices on SV. Research on prevalence and impact of SV in older adults is limited and Belgian figures on the subject are non-existent. This mixed-methods study aimed to better understand the nature, magnitude and mental health impact of SV in older adults in Belgium.Methods:We conducted face-to-face interviews trough structured questionnaires with 513 older adults (70+) across Belgium and 100 old age psychiatry patients. Quantitative data were triangulated with qualitative data from 15 in-depth interviews with older SV victims.Results:Over 44% of Belgian older adults and 57% of old age psychiatry patients experienced SV during their lifetime, 8% and 7% respectively in the past 12-months. Lifetime exposure to SV was associated with depression (p=0.001), anxiety (p=0.001) and PTSD in older adults with chronic disease/disability (p=0.002) or lower education level (p<0.001). A minority of victims (40%) disclosed their experiences to their informal network and 4% sought professional help. Older victims are willing to share their experiences, but ask health care workers to initiate the conversation.Conclusions:This study highlights the importance of recognizing older adults as a risk group for SV and the need for tailored care for older victims. Health care professionals working with older adults need to be qualitatively trained to initiate a conversation around SV and its mental health impact in old age through training, screening tools and care procedures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".