“Time does not heal all wounds”: mental health impact of sexual victimisation in old age
Bibliographic record
Abstract
Abstract Background Sexual violence (SV) has an important impact on mental health. Childhood sexual abuse is linked to internalizing disorders in later life. In older adults, SV occurs more often than previously believed. Moreover, health care workers lack the skills to adequately address SV in later life. Studies researching the mental health impact of lifetime SV, i.e. SV that happened during childhood, adulthood and old age, are currently lacking. In this study we research the association between lifetime sexual victimization and adverse mental health outcomes in older adults, and its moderators. Methods Between July 2019 and March 2020, 513 older adults living in Belgium participated in a structured face-to-face-interview. Selection occurred via a cluster random probability sampling with a random walk finding approach. Depression, anxiety and post-traumatic stress syndrome (PTSD) were measured using validated scales. Suicide attempts and self-harm were questioned during lifetime and in the past 12-months. SV was measured using behaviorally specific questions based on a broad definition of SV. Results Over 44% experienced lifetime SV, 8% in the past 12-months. Rates for depression, anxiety and PTSD were 27%, 26% and 6%. Almost 2% committed suicide, 1% reported self-harm in the past 12-months. Lifetime SV was linked to depression (p =.001), anxiety (p =.001), and PTSD in participants with a chronic illness/disability (p = .002) or no/lower education (p <.001). We found no link between lifetime SV and suicide attempts or self-harm in the past 12-months. Conclusions Lifetime SV is linked to mental health problems in late life. Tailored mental health care for older SV victims is necessary. Therefore, capacity building of professionals and development of clinical guidelines and care procedures are urgently needed. Key messages The mental health impact of sexual victimisation continues into old age. Tailored mental health care for older SV victims and capacity building of professionals are of the utmost importance.
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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 | 0.014 | 0.001 |
| 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 | 0.000 | 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".