ArticlePsychosocial intervention2023
Systematic Investigation of Meta-Analysis Data on Treatment Effectiveness for Physical, Psychological, and Sexual Intimate Partner Violence Perpetration.
Article in Psychosocial intervention, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interventions for Perpetrators of Intimate Partner Violence: An Umbrella Review of Systematic Reviews.Aggressive behavior · 2026Pooled it
- A Multi-Disciplinary Approach to Intimate Partner Violence: A Qualitative Study of the Perpetrators' Experiences.Journal of interpersonal violence · 2026Article
- Neuropsychological Predictors of Treatment Dropout Among Intimate Partner Violence Perpetrators.Journal of Intelligence · 2026Article
- Preliminary Effectiveness of an Intimate Partner Violence Intervention in Reducing Recidivism Among Criminal Justice-Involved Individuals in Switzerland.Journal of interpersonal violence · 2026Article
- Auditable cross-instrument detection of unusual multivariate psychiatric response configurations using a semantically aligned covariance subspace.medRxiv : the preprint server for health sciences · 2026Article
- Interpretable Machine Learning to Identify Risk Factors for Recidivism in Intimate Partner Violence.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Treatment Resistant Perpetrators of Intimate Partner Violence: Research Advances.Psychosocial intervention · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Intimate partner violence can lead to physical, economical, mental, and sexual well-being issues, and even death, and it is most commonly experienced by women. There exist a number of treatment models for the prevention and treatment of intimate partner violence (IPV). In this study, we provided a comprehensive meta-regression analysis of the effectiveness of batterer treatment programs, with a view to characterizing the interplay between different forms of IPV (physical, psychological, and sexual). Using meta-regression, we explore the effect sizes and whether IPV treatment methods have distinct impacts on the outcomes. We use the difference normalized by pretreatment mean and variance foldchange to uncover the relationship between different violence subtypes and how they drive each other. Specifically, our study found that studies with more pre-treatment psychological and/or sexual violence, lead to less favorable outcomes while the studies that start with more physical violence are able to demonstrate their effects more effectively. Results of this study can be used to help the clinician effectively select the treatment for the perpetrator based on the violence type and severity of violence in order to more effectively treat the needs for each specific relationship.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.