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Record W2792359012 · doi:10.1080/17538157.2018.1433675

Intimate partner violence: a review of online interventions

2018· review· en· W2792359012 on OpenAlexaff
Ebony Rempel, Lorie Donelle, Jodi Hall, Susan Rodger

Bibliographic record

VenueInformatics for Health and Social Care · 2018
Typereview
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsFanshawe CollegeWestern University
Fundersnot available
KeywordsPsychological interventionDomestic violenceAbusive relationshipContext (archaeology)Social supportPoison controlOccupational safety and healthSuicide preventionMedicinePsychologyPublic relationsSocial psychologyNursingPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Violence against women (VAW) is a global social issue affecting health, social, and legal systems. VAW contributes to the inequities with respect to the social determinants of health that many women face today. The onus on self-care in the face of violence remains almost singularly with the victims. Access to information and services in support of women's health and safety is fundamental. However, research gaps exist regarding how women access health information across all stages of an abusive intimate relationship. Given the ubiquity of online access to information, the purpose of this scoping review was to provide an overview of online interventions available to women within the context of intimate partner violence (IPV). Research literature published between 2000 and 2016, inclusive, was reviewed: 11 interventions were identified. Findings suggest that online interventions focused on the act of leaving with less emphasis on the experiences that occur after a woman has left the relationship. In addition, the online interventions concentrated on the individual capacity of the survivor to leave an abusive relationship and demonstrated limited understanding of IPV in relation to the broader social-contextual factors. Findings from this research highlight information gaps for women who require significant support after leaving an abusive relationship.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.783
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.124
GPT teacher head0.505
Teacher spread0.381 · 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 designNot applicable
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

Citations74
Published2018
Admission routes1
Has abstractyes

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