title: Understanding risk and protective factors for child maltreatment: the value of integrated, population-based data.
abstract: In this article, we argue for expanded efforts to integrate administrative data systems as a "practical strategy" for developing a richer understanding of child abuse and neglect. Although the study of child maltreatment is often critiqued for being atheoretical, we believe that a more pressing concern is the absence of population-based and prospective epidemiological data that can be used to better understand the distribution and interacting nature of risk and protective factors for maltreatment. We begin by briefly addressing the relevance of empirical observations to etiological theories of child maltreatment. Although the latter is widely cited as critical to the development of effective prevention and intervention responses, less attention has been paid to the role of population-based data in the development of theories relevant to highly applied research questions such as those pertaining to child abuse and neglect. We then discuss how child protection data, in isolation, translates into a relatively narrow range of questions that can be asked and answered, with an inherently pathology-focused construction of risks and little attention paid to strengths or protective factors. We next turn to examples of recent findings--spanning multiple countries--emerging from information integrated across data systems, concluding by calling for expanded administrative data linkages in an effort to better understand and prevent child maltreatment.
authors.affiliation: University of Southern California, School of Social Work, Los Angeles, CA 90089-0411, USA.
authors.forename: Emily
authors.initials: E
authors.lastname: Putnam-Hornstein
authors.forename: Barbara
authors.initials: B
authors.lastname: Needell
authors.forename: Anne E
authors.initials: AE
authors.lastname: Rhodes
mesh_terms: D002648:Child; D002649:Child Abuse / Q000517:prevention & control*; D002675:Child, Preschool; D004813:Epidemiology; D006801:Humans; D033181:Information Dissemination; D008498:Medical Record Linkage; D012307:Risk Factors