Literature DB >> 23260115

Understanding risk and protective factors for child maltreatment: the value of integrated, population-based data.

Emily Putnam-Hornstein1, Barbara Needell, Anne E Rhodes.   

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.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23260115     DOI: 10.1016/j.chiabu.2012.08.006

Source DB:  PubMed          Journal:  Child Abuse Negl        ISSN: 0145-2134


  8 in total

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Authors:  Paula S Nurius; Sara Green; Patricia Logan-Greene; Sharon Borja
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2.  Sentinel Events Preceding Youth Firearm Violence: An Investigation of Administrative Data in Delaware.

Authors:  Steven A Sumner; Matthew J Maenner; Christina M Socias; James A Mercy; Paul Silverman; Sandra P Medinilla; Steven S Martin; Likang Xu; Susan D Hillis
Journal:  Am J Prev Med       Date:  2016-10-11       Impact factor: 5.043

3.  Predicting Teen Dating Violence Perpetration.

Authors:  Joseph R Cohen; Ryan C Shorey; Suvarna V Menon; Jeff R Temple
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4.  Childhood Adversity among Court-Involved Youth: Heterogeneous Needs for Prevention and Treatment.

Authors:  Patricia Logan-Greene; B K Elizabeth Kim; Paula S Nurius
Journal:  J Juv Justice       Date:  2016

5.  Risk factors for maltreatment-related infant hospitalizations in New York City, 1995-2004.

Authors:  Susan M Mason; Patricia G Schnitzer; Valery A Danilack; Beth Elston; David A Savitz
Journal:  Ann Epidemiol       Date:  2018-06-02       Impact factor: 3.797

6.  Troubled childhoods cast long shadows: Childhood adversity and premature all-cause mortality in a Swedish cohort.

Authors:  Josephine Jackisch; Lars Brännström; Ylva B Almquist
Journal:  SSM Popul Health       Date:  2019-10-28

7.  Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review.

Authors:  Fadzai Chikwava; Reinie Cordier; Anna Ferrante; Melissa O'Donnell; Renée Speyer; Lauren Parsons
Journal:  PLoS One       Date:  2021-03-24       Impact factor: 3.240

8.  Do socioeconomic and birth order gradients in child maltreatment differ by immigrant status?

Authors:  Kathleen S Kenny; Ariel Pulver; Patricia O'Campo; Astrid Guttmann; Marcelo L Urquia
Journal:  J Epidemiol Community Health       Date:  2020-09-16       Impact factor: 3.710

  8 in total

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