Topic Modeling Analysis of Mental Health Research on Female Survivors of Domestic Violence in China (2000–2024)

Domestic violence (DV) has been recognized by the World Health Organization as a major global public health issue affecting women’s physical and mental health. In China, DV continues to pose a serious threat to women’s psychological well-being. Although English-language research on this topic has grown in recent years, the overall knowledge structure remains fragmented.

This study applied latent Dirichlet allocation (LDA) topic modeling to analyze 179 English-language abstracts published between 2000 and 2024, retrieved from four major academic databases. The analysis focused on term frequency distribution, identification and classification of latent topics, and temporal trends in topic prevalence over the 24-year period.

The model identified 25 latent topics, which were categorized into four overarching themes: psychological health consequences, risk and protective factors, intervention and support systems, and research methodology and policy perspectives. A marked thematic shift occurred after 2016, with increased emphasis on empirical evaluation and structural determinants, aligning with the implementation of China’s Anti-Domestic Violence Law.

The field has progressed from early descriptive accounts of trauma toward more systematic investigations into risk mechanisms and institutional responses. Nonetheless, important gaps remain, including insufficient attention to perpetrator psychology, the long-term socioeconomic consequences of DV, and the underrepresentation of high-risk or marginalized populations.

This study identified the key thematic structures and temporal trends in research on DV and women’s mental health in China. The findings offer a data-informed foundation for future studies and contribute to the development of culturally responsive public health interventions and evidence-based policy initiatives.