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Development of a prediction model for child maltreatment recurrence in Japan: A historical cohort study using data
Hiroyuki Horikawa1, S Pilar Suguimoto2, Patou Masika Musumari3
1Shiga Prefectural Mental Health and Welfare Center, Mureyama-so House, Kasayama 8-Chome 5-130, Kusatsu City, Shiga, 525-0072, Japan; Department of Global Health and Socio-epidemiology, Kyoto University School of Public Health, Science Frontier Laboratory Room 204, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
Insights
A prediction model identified six key factors for child maltreatment recurrence within one year. These factors can help welfare services develop targeted preventive strategies for at-risk children.
Area of Science:
- Child Welfare
- Public Health
- Forensic Psychology
Background:
- Child maltreatment recurrence poses significant risks to child well-being.
- Effective prediction models are crucial for timely intervention and prevention strategies.
Purpose of the Study:
- To develop and validate a prediction model for the first recurrence of child maltreatment within one year of the initial report.
- Identify key risk factors associated with maltreatment recurrence.
Main Methods:
- Historical cohort study utilizing administrative data from 716 child maltreatment cases.
- Multivariate logistic regression analysis to identify predictive variables for recurrence.
- Development of a linear prediction model based on six identified risk factors.
Main Results:
- Six significant predictors for child maltreatment recurrence were identified: child's age (9-13 years), offender's age (<40 years), offender's history of childhood maltreatment, household financial instability, lack of community oversight, and organizational referral source.
- The developed prediction model achieved a sensitivity of 45.2% and a specificity of 82.4%.
Conclusions:
- The identified factors and prediction model can aid in assessing the risk of recurrent child maltreatment.
- Findings support the development of targeted preventive strategies by child and family welfare administrations to mitigate recurrence risks.
Abstract:
To develop a prediction model for the first recurrence of child maltreatment within the first year after the initial report, we carried out a historical cohort study using administrative data from 716 incident cases of child maltreatment (physical abuse, psychological abuse, or neglect) not receiving support services, reported between April 1, 1996 through March 31, 2011 to Shiga Central Child Guidance Center, Japan. In total, 23 items related to characteristics of the child, the maltreatment, the offender, household, and other related factors were selected as predictive variables and analyzed by multivariate logistic regression model for association with first recurrence of maltreatment. According to the stepwise selection procedure six factors were identified that include 9-13year age of child (AOR=3.43/95%CI=1.52-7.72), <40year age of the offender (AOR=1.65/95%CI=1.09-2.51), offender's history of maltreatment during childhood (AOR=2.56/95%CI=1.31-4.99), household financial instability or poverty (AOR=1.64/95%CI=1.10-2.45), absence of someone in the community who could watch over the child (AOR=1.68/95%CI=1.16-2.44), and the organization as the referral source (AOR=2.21/95%CI=1.24-3.93). Using these six predictors, we generated a linear prediction model with a sensitivity and specificity of 45.2% and 82.4%, respectively. The model may be useful to assess the risk of further maltreatment and help the child and family welfare administrations to develop preventive strategies for recurrence.
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