Development and validation of a predictive scoring tool for family violence risk assessment
Main Article Content
Keywords
Family violence, Risk assessment, Predictive scoring tool, Early intervention
Abstract
Background: Family violence, encompassing intimate partner violence, child abuse, and elder abuse, poses significant public health challenges globally. Early detection remains difficult due to underreporting and reliance on unstructured clinical judgments. There is a need for a predictive tool to systematically assess and stratify family violence risk. Objective: To develop and validate a predictive scoring tool that integrates individual, relational, and contextual factors to assess the risk of family violence, aiming to enhance early detection and inform timely interventions in clinical practice. Methods: A cross-sectional observational study was conducted in Phitsanulok, Thailand, involving 548 participants aged 18 and above, recruited from community and healthcare settings. Data were collected using a structured questionnaire covering individual factors (e.g., age, gender, mental health status), relationship factors (e.g., marital satisfaction, substance abuse), and social/community factors (e.g., social support, neighborhood violence). Family violence involvement was measured through self-reports and official records. Bivariate and multivariate analyses identified significant risk factors, which were weighted to develop the predictive scoring tool. Results: Key risk factors identified included childhood exposure to domestic violence (r = 0.77), power imbalances and rigid gender norms (r = 0.79), substance abuse (r = 0.74), emotional distress (r = 0.72), and economic stressors (r = 0.70). The scoring tool demonstrated strong predictive accuracy, with a correlation of r = 0.82 (p < 0.001) between the total risk score and violence severity. Using a cut-off score of ≥31 to predict any reported violence yielded a sensitivity of 94% and specificity of 72%. Conclusions: The developed predictive scoring tool effectively stratifies families by risk level, facilitating early identification and targeted interventions. Its integration into clinical practice could shift the approach to family violence from reactive to proactive, potentially reducing incidence and associated harms. Further research should focus on external validation and longitudinal studies to assess the tool's impact on outcomes.
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