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Record W3022423136 · doi:10.1101/2020.04.24.20077990

Prevalence and Nature of Sexual Violence in Older Adults in Europe: A Critical Interpretive Synthesis of Evidence

2020· preprint· en· W3022423136 on OpenAlexaff
Anne Nobels, Christophe Vandeviver, Marie Beaulieu, Adina Cismaru Inescu, Laurent Nisen, Nele Van Den Noortgate, Tom Vander Beken, Gilbert Lemmens, Inês Keygnaert

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsReproductive healthPublic healthSexual violenceGerontologyNonprobability samplingHealth carePsychologyMedicinePolitical scienceNursingCriminologyPopulationEnvironmental health

Abstract

fetched live from OpenAlex

ABSTRACT Sexual violence (SV) is an important public health issue with a potential major impact on victims and their peers, offspring and community. However, SV in older adults is under-researched. This paper aims to establish the prevalence and nature of SV in older adults in Europe, link this with existing policies and health care workers’ response to sexual health needs in older age and critically revise the current used frameworks in public health research. We applied a Critical Interpretative Synthesis. After the first phase of purposive sampling we included 14 references. Another 14 references were included after the second phase of theoretical sampling. We ultimately included 16 peer-reviewed articles and 12 documents from the grey literature. 0.0% to 3.1% of older adults in Europe were sexually victimised in the past year. Lifetime prevalence of SV was 6.3%. Information on specific risk factors and assailants committing SV in old age is non- existing. Although in theory policy makers increasingly recognise the importance of sexual health in older age, SV in older adults is not mentioned in policy documents on sexual and reproductive health and rights and ageing. In clinical practice, the sexual health needs of older adults remain often unmet. Knowledge about SV in older adults is still limited. Ongoing research does not fully grasp the complexity of SV in older adults. Greater awareness about this topic could contribute to a revision of current policies and health care practices, leading to more tailored care for older victims of SV.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.346
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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