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Efficacy of a Sexual Assault Resistance Program for University Women

2015· article· en· W3038120656 on OpenAlexaffabout
Charlene Y. Senn, Misha Eliasziw, Paula C. Barata, Wilfreda E. Thurston, Ian R. Newby‐Clark, H. Lorraine Radtke, Karen L. Hobden

Bibliographic record

VenueObstetrical & Gynecological Survey · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of GuelphUniversity of Windsor
Fundersnot available
KeywordsMedicineSexual assaultResistance (ecology)Incidence (geometry)Intervention (counseling)Randomized controlled trialUnit (ring theory)Family medicineSuicide preventionPoison controlPsychiatryMedical emergencyPsychologySurgery

Abstract

fetched live from OpenAlex

There is substantial risk among young women attending universities of being sexually assaulted. Over the 4 years of college, the incidence of sexual assault is estimated to be between 20% and 25% and highest during the first 2 years. There has been increasing public awareness of this problem in Canada and in the United States. Universities have faced heightened pressure to develop programs to educate students about sexual assault. Most campus programs currently used, however, have never been formally evaluated or have not been effective in reducing the incidence of sexual assault. Studies evaluating the effectiveness of workshops and other campus programs to help women resist sexual assault or reduce their risk have had inconsistent effects due to deficiencies in design and other problems. Some of these studies showed short-term benefit, but other studies showed no clear benefits at 2, 4, or 6 months. The aim of this open-label, randomized, controlled trial was to determine whether a new, 4-unit, small-group sexual assault resistance program could reduce the 1-year incidence of completed rape among first-year female university students. The study was conducted at 3 universities in Canada from September 2011 to February 2013. First-year female students were randomized to either the Enhanced Assess, Acknowledge, Act Sexual Assault Resistance program (resistance group) or to a control group provided access to brochures on sexual assault. Eligible students had to attend 1 of 4 scheduled sets of intervention sessions during the semester in which they enrolled in the study. The goal of the resistance program was to provide students with the ability to assess risk from acquaintances, overcome emotional barriers in acknowledging danger, and use effective verbal and physical self-defense. Women in the resistance group participated in a 4-unit sexual assault resistance program in which appropriate information was given, and skills taught and practiced. Those in the control group had access to brochures on sexual assault that were available in campus clinics and counseling centers. The primary outcome measure was completed rape and was measured by the Sexual Experiences Survey–Short Form Victimization, during 1 year of follow-up. A total of 893 women were randomized to 1 of 2 groups; 451 were assigned to the resistance group and 442 to the control group. Adherence in the resistance group was high; 91% attended at least 3 of the 4 units. The 1-year risk of completed rape was reduced by nearly 50% in the resistance group compared with the control group: 5.2% versus 9.8%; the relative risk reduction was 46.3%, with a 95% confidence interval of 6.8–69.1; P = 0.02. The incidence of attempted rape was reduced from 9.3% in the control group to 3.4% in the resistance group (relative risk reduction, 63.2%; P < 0.001). These data show that a rigorously designed and executed sexual assault resistance program was successful in substantially reducing the occurrence of rape, attempted rape, and other forms of victimization among first-year university women.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.129
GPT teacher head0.368
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations3
Published2015
Admission routes2
Has abstractyes

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