JOURNAL ARTICLE

Testing the Spillover Effect of Intimate Partner Violence Victimization on Emotionally Abusive and Harsh Parenting Practices: The Application of Propensity Score Matching.

  • Published In: Journal of Interpersonal Violence, 2025, v. 40, n. 5/6. P. 1199 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Debowska, Agata; Inglot, Grzegorz; Piasek, Rafal; Sokol, Grzegorz; Horeczy, Beata; Hales, George K.; Boduszek, Daniel 3 of 3

Abstract

This article examines the association between recent intimate partner violence (IPV) victimization and negative parenting practices—specifically emotionally abusive and harsh parenting—among community-based mothers of young children in Poland. Using a quasi-experimental design with propensity score matching (PSM) to control for 11 confounding variables (including financial distress, self-esteem, childhood violence history, mental distress, social support, and COVID-19-related stressors), the study found that although IPV-positive mothers initially reported higher levels of abusive parenting, these differences became statistically nonsignificant after matching. These results challenge the spillover hypothesis that IPV victimization directly leads to increased negative parenting when confounding factors are accounted for. The study highlights the importance of rigorous methodology in IPV research and calls for further investigation into IPV's impact on parenting across diverse populations.

Additional Information

  • Source:Journal of Interpersonal Violence. 2025/03, Vol. 40, Issue 5/6, p1199
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:0886-2605
  • DOI:10.1177/08862605241258998
  • Accession Number:182849066
  • Copyright Statement:Copyright of Journal of Interpersonal Violence is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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