Child neglect is the most common form of reported maltreatment in the United States. Even though studies have shown that child abuse and neglect share many common risk factors, some research suggests that are certain factors that are specific to neglect. Knowing whether or not there is a need to alter services according to subtypes of child neglect requires we have a better understanding of how or if risk and protective factors vary by maltreatment type. Very few studies have attempted to understand what may discriminate between various neglecting behaviors. The present study helps to build knowledge about the subtypes of neglect while addressing some of the methodological challenges in this area.
Methods:
Data for the present study is drawn from two sources. The first data source is the National Surveys of Child and Adolescent Well-Being, NSCAW-II (N = 2,648), and second one is the administrative data (N = 5,787) from a large study at the St. Louis metropolitan region. Both data sets provided information on subtypes of neglect, but NSCAW-II offers us the ability to examine substance abuse, or domestic violence related neglect and regional dataset provided medical neglect and emotional neglect. While some research suggests that many families in contact with child welfare have multiple co-occurring problems. This study applied variable-oriented approach (multinomial regression analysis) in helping us understand how to target key risk factors, and person-oriented approach (latent class analysis) to identify meaningful groups with particular patterns.
Results:
We found that family characteristics differed for physical neglect compared to lack of supervision neglect across a number of dimensions in both datasets in bivariate analyses though this was greatly attenuated in multinomial models for NSCAW data. Also, both bivariate and multivariate models using both data sets indicated a number of practically important (effect size) differences between cases reported for multiple types of neglect and supervisory neglect. On the other hand, the results the LCA showed that a 5-class and 6-class were the best models for NSCAW-II and the regional data. With classes contained families with different subtypes of neglect in the NSCAW data, most of the risk factors didn’t show much variation across the 5 classes. For the regional data, while there were variations between risk factors, most of all subtypes of neglect hung together across the 6 classes.
Conclusions and Implications:
The present study did find variation in risk and demographic factors using two different datasets with different forms of data. This was only true, however, for the variable based approaches. The person-oriented analytic models were less informative in regard to subtypes but were consistent with the idea of CPS families facing multiple risk factors- most classes had high probabilities for multiple risk factors in both datasets. It is possible that the “iceberg theory” best captures the dynamics between the risk factors and children reported for different subtypes of neglect. If this is true, then the intervention programs for child neglect may need to focus on the cumulative risk of the family.