Localized Disparities in Socioeconomic Disadvantages and Concentration of Child Protection Services: Exploratory Spatial Data Analysis and Latent Trait Modeling (WITHDRAWN)

Background/Purpose: Exploratory spatial data analysis and latent trait modeling of localized socioeconomic disadvantages provide a potential opportunity for the development of prevention services aimed at reducing the impacts of difficult social and economic living conditions and exceptional intervention by the state through child protection services. Despite increasing interest in localized policy strategies, the availability of rigorous approaches to population-based data manipulation, and associations with child protection service concentration, is limited. This paper explores the creation of population-based social and economic composite indices, and the point at which vulnerability indices begin to predict the concentration of child protection services.

Methods: Localized jurisdictions represent 166 territorial aggregations used to organize the delivery of provincial government services. This study draws data from various sources: (1) longitudinal administrative data from Quebec's child protection agencies; (2) 2006 and 2011 Canadian Census data; (3) intra-province health and social services spending, and utilisation data; (4) school data from the Ministry of Education; (5) social assistance payments data from the Ministry of Employment; and, (6) public transportation data. Factorial analysis was used to create six localized composite indices – weighted for child population – of well-being vulnerabilities, including: (1) child protection service concentration; (2) socioeconomic disadvantages; (3) psychosocial service consultations; (4) academic functioning; (5) access to health and social services; and, (6) social prevention spending. Exploratory spatial data analysis in ArcGIS was used to visualize the localized distribution of vulnerability indices, and unidimensional latent trait modeling in Mplus 7 was used to understand the extent to which vulnerability estimates discriminate in favor of a high localized concentration of child protection services.

Results: Preliminary results suggest that jurisdictional disparities in social and economic vulnerability contribute to the increase likelihood of localized concentration child protection services. Specifically, as financial poverty, schooling issues and psychosocial service consultations monotonically increase, the probability of localized child protection service concentration increases.

Conclusions and Implications: This study testifies to the advantages of exploratory spatial data analysis in understanding the aggregations of families with children living in situations of social and economic vulnerability and associated child protection service concentration. The results of this study also provide a better understanding of potential localized targets for prevention action to support families with children living in social and economic vulnerability.