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Record W4401890645 · doi:10.1177/08862605241270057

A Successful Sexual Assault Resistance Program Also Reduced Intimate Partner Violence

2024· article· en· W4401890645 on OpenAlexafffund
Paula C. Barata, Tanja Samardžić, Misha Eliasziw, Charlene Y. Senn, H. Lorraine Radtke, Karen L. Hobden, Wilfreda E. Thurston

Bibliographic record

VenueJournal of Interpersonal Violence · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of WindsorUniversity of CalgaryUniversity of Guelph
FundersCanadian Institutes of Health ResearchClinical Trials Fund, Canadian Institutes of Health Research
KeywordsDomestic violencePoison controlMedicineGeneralizability theorySexual violenceSuicide preventionSexual abuseInjury preventionSexual assaultFamily medicinePsychiatryPsychologyNursingMedical emergencyDevelopmental psychology

Abstract

fetched live from OpenAlex

Despite several parallels between intimate partner violence (IPV) and sexual assault (SA), programs designed to reduce either of these forms of violence against women rarely evaluate the impact on both IPV and SA. Accordingly, we investigated whether one such program (the Enhanced Assess, Acknowledge, Act (EAAA) Sexual Assault Resistance program), designed to help university-aged women resist SA, could also reduce subsequent IPV. Women university students who were enrolled in the Sexual Assault Resistance Education (SARE) randomized controlled trial examining the impact of the EAAA program on SA, were recruited immediately after completing the last survey in the SARE trial. From this trial, 153 women completed the IPV substudy, which included an additional survey. Occurrence of IPV was assessed using the Composite Abuse Scale. Of the 93 new relationships reported by 66 women in the control group, the 1-year risk of IPV was 26.8%. In contrast, of the 113 new relationships reported by 87 women in the EAAA program group, the 1-year risk of IPV was 12.2%. Effectively, the EAAA program significantly reduced the 1-year risk of IPV by 54.4% ( p = .037, 95% CI [2.9%, 79.8%]). Our findings suggest that the EAAA program is effective in reducing the risk of IPV and highlights the generalizability of programming that targets the foundational underpinning of multiple forms of gender-based violence.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.028
GPT teacher head0.372
Teacher spread0.344 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2024
Admission routes2
Has abstractyes

Explore more

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