Violence against children: An application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to the Crime Survey for England and Wales
Authors: Tura, F., Tseloni, A., Tompson, L.
Journal: Child Abuse and Neglect
Publication Date: 01/03/2026
Volume: 173
eISSN: 1873-7757
ISSN: 0145-2134
DOI: 10.1016/j.chiabu.2026.107930
Abstract:Background: Violence victimization in childhood is a significant public health and social justice concern. Yet there is limited evidence on how multiple, overlapping identities relate to children's experiences of non-familial violence. Objectives: This study examines differences in violence victimization rates among children in different social groups. In doing so, we seek to demonstrate the application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) as a method for intersectional analysis. Participants and setting: The study uses nine years of pooled data from the 10–15 Crime Survey for England and Wales (2011–2019), including a total sample of 26,106 children aged 10–15 years old. Methods: Logistic MAIHDA models were employed to analyse the likelihood of experiencing violence victimization across intersectional social groups defined by combinations of four social identities (sex, age, ethnicity, disability status). Results: Most of the differences in violence victimization across intersectional social groups are explained by individual characteristics like disability, sex, ethnicity, and age. Interaction effects between these characteristics add little beyond their separate (additive) impacts. Predicted probabilities show that disabled boys are among the most likely to experience violence victimization. Conclusion: The study underscores the need for targeted policies and interventions to reduce violence against children, particularly those who are disabled. It also serves as a case study for researchers interested in using MAIHDA to explore intersectionality in crime against children (or any other outcomes) and inform harm prevention strategies.
https://eprints.bournemouth.ac.uk/41737/
Source: Scopus
Violence against children: An application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to the Crime Survey for England and Wales.
Authors: Tura, F., Tseloni, A., Tompson, L.
Journal: Child Abuse Negl
Publication Date: 28/01/2026
Volume: 173
Pages: 107930
eISSN: 1873-7757
DOI: 10.1016/j.chiabu.2026.107930
Abstract:BACKGROUND: Violence victimization in childhood is a significant public health and social justice concern. Yet there is limited evidence on how multiple, overlapping identities relate to children's experiences of non-familial violence. OBJECTIVES: This study examines differences in violence victimization rates among children in different social groups. In doing so, we seek to demonstrate the application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) as a method for intersectional analysis. PARTICIPANTS AND SETTING: The study uses nine years of pooled data from the 10-15 Crime Survey for England and Wales (2011-2019), including a total sample of 26,106 children aged 10-15 years old. METHODS: Logistic MAIHDA models were employed to analyse the likelihood of experiencing violence victimization across intersectional social groups defined by combinations of four social identities (sex, age, ethnicity, disability status). RESULTS: Most of the differences in violence victimization across intersectional social groups are explained by individual characteristics like disability, sex, ethnicity, and age. Interaction effects between these characteristics add little beyond their separate (additive) impacts. Predicted probabilities show that disabled boys are among the most likely to experience violence victimization. CONCLUSION: The study underscores the need for targeted policies and interventions to reduce violence against children, particularly those who are disabled. It also serves as a case study for researchers interested in using MAIHDA to explore intersectionality in crime against children (or any other outcomes) and inform harm prevention strategies.
https://eprints.bournemouth.ac.uk/41737/
Source: PubMed
Violence against children: An application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to the Crime Survey for England and Wales
Authors: Tura, F., Tseloni, A., Tompson, L.
Journal: Child Abuse and Neglect
Publication Date: 16/02/2026
Publisher: Elsevier
eISSN: 1873-7757
ISSN: 0145-2134
https://eprints.bournemouth.ac.uk/41737/
Source: Manual
Violence against children: An application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to the Crime Survey for England and Wales.
Authors: Tura, F., Tseloni, A., Tompson, L.
Journal: Child abuse & neglect
Publication Date: 01/2026
Volume: 173
Pages: 107930
eISSN: 1873-7757
ISSN: 0145-2134
DOI: 10.1016/j.chiabu.2026.107930
Abstract:Background
Violence victimization in childhood is a significant public health and social justice concern. Yet there is limited evidence on how multiple, overlapping identities relate to children's experiences of non-familial violence.Objectives
This study examines differences in violence victimization rates among children in different social groups. In doing so, we seek to demonstrate the application of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) as a method for intersectional analysis.Participants and setting
The study uses nine years of pooled data from the 10-15 Crime Survey for England and Wales (2011-2019), including a total sample of 26,106 children aged 10-15 years old.Methods
Logistic MAIHDA models were employed to analyse the likelihood of experiencing violence victimization across intersectional social groups defined by combinations of four social identities (sex, age, ethnicity, disability status).Results
Most of the differences in violence victimization across intersectional social groups are explained by individual characteristics like disability, sex, ethnicity, and age. Interaction effects between these characteristics add little beyond their separate (additive) impacts. Predicted probabilities show that disabled boys are among the most likely to experience violence victimization.Conclusion
The study underscores the need for targeted policies and interventions to reduce violence against children, particularly those who are disabled. It also serves as a case study for researchers interested in using MAIHDA to explore intersectionality in crime against children (or any other outcomes) and inform harm prevention strategies.https://eprints.bournemouth.ac.uk/41737/
Source: Europe PubMed Central