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This paper is in the following e-collection/theme issue:

New Methods (1179) Machine Learning (2225) Natural Language Processing (953) Violence including Domestic Violence/Abuse (166) Validity, Reliability, and Bias (117)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43499, first published .
Removing Biases in Communication of Severity Assessments of Intimate Partner Violence: Model Development and Evaluation

Removing Biases in Communication of Severity Assessments of Intimate Partner Violence: Model Development and Evaluation

Removing Biases in Communication of Severity Assessments of Intimate Partner Violence: Model Development and Evaluation

Authors of this article:

Sverker Sikstrom1 Author Orcid Image ;   Mats Dahl1 Author Orcid Image ;   Emma Claesdotter-Knutsson2, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Dahl M, Ngaosuvan L, Granberg Flintberg J, Silfversparre J, Stille L, Lasota M, Sikström S, Mitra S. Perceptual discrepancies in the experience and reporting of violence against children are more pronounced among social workers compared to laypeople. PLOS One 2025;20(12):e0336900 View
  2. Li Y, Emezue C, Song C, Udmuangpia T. The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review. Journal of Clinical Nursing 2026 View
  3. Tonge A, Hewage S, Cumming S, Walsh C, Abell B, Borg D, Baxter B, Parsons R, Howell T, McPhail S. A brief educational intervention to improve health service responsiveness to intimate partner violence: a mixed methods evaluation. BMC Health Services Research 2026 View