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Record W4400655579 · doi:10.1002/cl2.1423

Interventions for intimate partner violence during the perinatal period: A scoping review

2024· review· en· W4400655579 on OpenAlexaff
Olivia Mercier, Sarah Fu, Rachel Filler, Alexie Leclerc, Kari Sampsel, Karine Fournier, Mark Walker, Shi Wu Wen, Katherine A. Muldoon

Bibliographic record

VenueCampbell Systematic Reviews · 2024
Typereview
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsDomestic violencePerinatal periodPsychological interventionMedicinePregnancyPsychologyObstetricsPsychiatryMedical emergencyPoison controlSuicide prevention

Abstract

fetched live from OpenAlex

Abstract Background Intimate partner violence (IPV) is a prevalent global health problem. IPV that occurs before pregnancy often continues during the perinatal period, resulting in ongoing violence and many adverse maternal, obstetrical, and neonatal outcomes. Objectives This scoping review is designed to broadly capture all potential interventions for perinatal IPV and describe their core components and measured outcomes. Search Methods We conducted a search for empirical studies describing IPV interventions in the perinatal population in June 2022. The search was conducted in MEDLINE, EMBASE, PsycInfo, CINAHL, Cochrane Central Register of Controlled Trials, Web of Science, Applied Social Sciences Index & Abstracts, ClinicalTrials.gov and MedRxiv. Hand searching of references from select articles was also performed. Selection Criteria Included studies described an intervention for those experiencing IPV during the perinatal period, including 12 months before pregnancy, while pregnant or in the 12 months post‐partum. The search encompassed January 2000 to June 2022 and only peer‐reviewed studies written in either English or French were included. Included interventions focused on the survivor exposed to IPV, rather than healthcare professionals administering the intervention. Interventions designed to reduce IPV revictimization or any adverse maternal, obstetrical, or neonatal health outcomes as well as social outcomes related to IPV victimization were included. Data Collections and Analysis We used standard methodological procedures expected by The Campbell Collaboration. Main Results In total, 10,079 titles and abstracts were screened and 226 proceeded to full text screening. A total of 67 studies included perinatal IPV interventions and were included in the final sample. These studies included a total of 27,327 participants. Included studies originated from 19 countries, and the majority were randomized controlled trials ( n = 43). Most studies were of moderate or low quality. Interventions included home visitation, educational modules, counseling, and cash transfer programs and occurred primarily in community obstetrician and gynecologist clinics, hospitals, or in participants' homes. Most interventions focused on reducing revictimization of IPV ( n = 38), improving survivor knowledge or acceptance of violence, knowledge of community resources, and actions to reduce violence ( n = 28), and improving maternal mental health outcomes ( n = 26). Few studies evaluated the effect of perinatal IPV interventions on obstetrical, neonatal or child health outcomes. Authors' Conclusion(s) The majority of intervention studies for perinatal IPV focus on reducing revictimization and improving mental health outcomes, very few included obstetrical, neonatal, and other physical health outcomes. Future interventions should place a larger emphasis on targeting maternal and neonatal outcomes to have the largest possible impact on the lives and families of IPV survivors and their infants.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.376
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.176
GPT teacher head0.478
Teacher spread0.303 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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