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Record W2088971518 · doi:10.1177/1049731512474103

Interventions to Reduce Distress in Adult Victims of Rape and Sexual Violence

2013· article· en· W2088971518 on OpenAlexafffund
Cheryl Regehr, Ramona Alaggia, Jane A Dennis, A. T. Pitts, Michael Saini

Bibliographic record

VenueResearch on Social Work Practice · 2013
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychological interventionClinical psychologyAnxietyDistressPsychologyEye movement desensitization and reprocessingCognitive therapyCognitionCognitive restructuringPsychiatryMedicinePosttraumatic stress

Abstract

fetched live from OpenAlex

Objectives: This article presents a systematic evaluation of the effectiveness of interventions aimed at reducing distress in adult victims of rape and sexual violence. Method: Studies were eligible for the review if the assignment of study participants to experimental or control groups was by random allocation or parallel cohort design. Results: Six studies including 405 participants met eligibility criteria. Meta-analyses revealed that specific cognitive and behavioral interventions (cognitive-processing therapy, prolonged exposure therapy, and eye movement desensitization reprocessing) had a statistically significant effect on posttraumatic stress disorder and depression symptoms in comparison to the control groups. Other outcomes that had demonstrated improvement included anxiety, guilt, and dissociation. Conclusion: Many studies assessing the effectiveness of interventions for decreasing trauma symptoms combine victims of sexual violence in adulthood with other trauma-based samples despite the profound differences in these experiences. This review again points to the need for increased research that focuses specifically on the effectiveness of treatment models for adult victims of sexual 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 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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.238
GPT teacher head0.552
Teacher spread0.314 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations42
Published2013
Admission routes2
Has abstractyes

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