Skip to main content

Part of the book series: Child Maltreatment Solutions Network ((CMSN))

  • 109 Accesses

Abstract

The field of child maltreatment science has seen significant investment and growth in the use of administrative data to conduct research that informs policies and practices affecting child protective services (CPS) and child welfare system activities. Administrative data refers to data collected by public agencies to support day-to-day operations, record keeping, billing, or similar activities. Research utilizing administrative data not only offers a number of advantages, such as availability of large, population-level samples and greater time- and cost-efficiencies but also poses challenges such as limits to input on the scope or content of data systems, and possible limits or barriers to access. Increasingly, child maltreatment researchers are working with administrative data from child welfare and other systems (e.g., health care, education, justice, or other public systems) to create integrated data systems, which expand the range of outcomes and research questions that may be investigated through administrative data resources. This chapter provides a brief overview of the strengths and limitations of administrative and integrated data systems, as well as providing a summary of the areas addressed by chapters in the volume.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Brownell, M. D., & Jutte, D. P. (2013). Administrative data linkage as a tool for child maltreatment research. Child Abuse & Neglect, 37(2–3), 120–124.

    Article  Google Scholar 

  • Cancian, M., Yang, M., & Slack, K. S. (2013). The effect of additional child support income on the risk of child maltreatment. Social Service Review, 87(3), 417–437.

    Article  Google Scholar 

  • Christen, P. (2012). Data matching: Concepts and techniques for record linkage, entity resolution, and duplicate detection. Springer.

    Book  Google Scholar 

  • Connell, C. M., Bergeron, N., Katz, K. H., Saunders, L., & Tebes, J. K. (2007). Re-referral to Child Protective Services: The influence of child, family, and case characteristics on risk status. Child Abuse & Neglect, 31, 573–588.

    Article  Google Scholar 

  • Connell, C. M., Vanderploeg, J. J., Katz, K. H., Caron, C., Saunders, L., & Tebes, J. K. (2009). Maltreatment following reunification: Predictors of subsequent child protective services contact after children return home. Child Abuse & Neglect, 33, 218–228.

    Article  Google Scholar 

  • DeHart, D., & Shapiro, C. (2017). Integrated administrative data & criminal justice research. American Journal of Criminal Justice, 42(2), 255–274.

    Article  Google Scholar 

  • Fang, X., Brown, D. S., Florence, C. S., & Mercy, J. A. (2012). The economic burden of child maltreatment in the United States and implications for prevention. Child Abuse & Neglect, 36(2), 156–165.

    Article  Google Scholar 

  • Fantuzzo, J. W., Perlman, S. M., & Dobbins, E. K. (2011). Types and timing of child maltreatment and early school success: A population-based investigation. Children and Youth Services Review, 33(8), 1404–1411.

    Article  Google Scholar 

  • Fix, R. L., & Nair, R. (2020). Racial/ethnic and gender disparities in substantiation of child physical and sexual abuse: Influences of caregiver and child characteristics. Children and Youth Services Review, 116, 105186.

    Article  Google Scholar 

  • Fluke, J. D., Yuan, Y. T., & Edwards, M. (1999). Recurrence of maltreatment: An application of the National Child Abuse and Neglect Data System (NCANDS). Child Abuse & Neglect, 23(7), 633–650.

    Article  Google Scholar 

  • Fluke, J. D., Shusterman, G. R., Hollinshead, D. M., & Yuan, Y. T. (2008). Longitudinal analysis of repeated child abuse reporting and victimization: Multistate analysis of associated factors. Child Maltreatment, 13(1), 76–88.

    Article  PubMed  Google Scholar 

  • Garcia, A. R., Metraux, S., Chen, C.-C., Park, J. M., Culhane, D. P., & Furstenberg, F. F. (2018). Patterns of multisystem service use and school dropout among seventh-, eighth-, and ninth-grade students. The Journal of Early Adolescence, 38(8), 1041–1073.

    Article  Google Scholar 

  • Glasson, E. J., & Hussain, R. (2008). Linked data: Opportunities and challenges in disability research. Journal of Intellectual and Developmental Disability, 33(4), 285–291.

    Article  PubMed  Google Scholar 

  • Harron, K., Goldstein, H., & Dibben, C. (Eds.). (2015). Methodological developments in data linkage. John Wiley & Sons.

    Google Scholar 

  • Herzog, T. N., Scheuren, F. J., & Winkler, W. E. (2007). Data quality and record linkage techniques. Springer Science & Business Media.

    Google Scholar 

  • Holbrook, H. M., & Hudziak, J. J. (2020). Risk factors that predict longitudinal patterns of substantiated and unsubstantiated maltreatment reports. Child Abuse & Neglect, 99, 104279.

    Article  Google Scholar 

  • Hurren, E., Stewart, A., & Dennison, S. (2017). New methods to address old challenges: The use of administrative data for longitudinal replication studies of child maltreatment. International Journal of Environmental Research and Public Health, 14(9), 1066–1077.

    Article  PubMed  PubMed Central  Google Scholar 

  • Johnson-Motoyama, M., Ginther, D. K., Phillips, R., Beer, O. W., Merkel-Holguin, L., & Fluke, J. (2022). Differential response and the reduction of child maltreatment and foster care services utilization in the US from 2004 to 2017. Child Maltreatment, 10775595211065761.

    Google Scholar 

  • Jonson-Reid, M., & Drake, B. (2008). Multisector longitudinal administrative databases: An indispensable tool for evidence-based policy for maltreated children and their families. Child Maltreatment, 13(4), 392–399.

    Article  PubMed  PubMed Central  Google Scholar 

  • Jonson-Reid, M., Drake, B., Chung, S., & Way, I. (2003). Cross-type recidivism among child maltreatment victims and perpetrators. Child Abuse & Neglect, 27(8), 899–917.

    Article  Google Scholar 

  • Jud, A., Fegert, J. M., & Finkelhor, D. (2016). On the incidence and prevalence of child maltreatment: A research agenda. Child and Adolescent Psychiatry and Mental Health, 10(1), 1–5.

    Article  Google Scholar 

  • Kim, H., & Drake, B. (2019). Cumulative prevalence of onset and recurrence of child maltreatment reports. Journal of the American Academy of Child & Adolescent Psychiatry, 58(12), 1175–1183.

    Article  Google Scholar 

  • Kohl, P. L., & Barth, R. P. (2007). Child maltreatment recurrence among children remaining in-home: Predictors of re-reports. In R. Haskins, F. Wulczyn, & M. B. Webb (Eds.), Child protection: Using research to improve policy and practice (pp. 207–225). Brookings Institution Press.

    Google Scholar 

  • Maguire-Jack, K., Font, S. A., & Dillard, R. (2020). Child protective services decision-making: The role of children’s race and county factors. American Journal of Orthopsychiatry, 90(1), 48.

    Article  PubMed  Google Scholar 

  • Penner, A. M., & Dodge, K. A. (2019). Using administrative data for social science and policy. RSF: The Russell Sage Foundation Journal of the Social Sciences, 5(2), 1–18.

    Article  PubMed  PubMed Central  Google Scholar 

  • Peterson, C., Florence, C., & Klevens, J. (2018). The economic burden of child maltreatment in the United States, 2015. Child Abuse & Neglect, 86, 178–183.

    Article  Google Scholar 

  • Putnam-Hornstein, E., Simon, J. D., Eastman, A. L., & Magruder, J. (2015). Risk of re-reporting among infants who remain at home following alleged maltreatment. Child Maltreatment, 20(2), 92–103. https://doi.org/10.1177/1077559514558586

    Article  PubMed  Google Scholar 

  • Putnam-Hornstein, E., Foust, R., Cuccaro-Alamin, S., Prindle, J., Nghiem, H., Ahn, E., & Palmer, L. (2022). A population-based study of mental health diagnoses and child protection system involvement among Medicaid-insured children. The Journal of Pediatrics.

    Google Scholar 

  • Rebbe, R., Mienko, J. A., Brown, E., & Rowhani-Rahbar, A. (2019). Hospital variation in child protection reports of substance exposed infants. The Journal of Pediatrics, 208, 141–147. e142.

    Google Scholar 

  • Ryan, J. P., Herz, D., Hernandez, P. M., & Marshall, J. M. (2007). Maltreatment and delinquency: Investigating child welfare bias in juvenile justice processing. Children and Youth Services Review, 29(8), 1035–1050.

    Article  Google Scholar 

  • Ryan, J. P., Jacob, B. A., Gross, M., Perron, B. E., Moore, A., & Ferguson, S. (2018). Early exposure to child maltreatment and academic outcomes. Child Maltreatment, 23(4), 365–375.

    Article  PubMed  Google Scholar 

  • Shlomo, N. (2019). Overview of data linkage methods for policy design and evaluation. In N. Crato & P. Paruolo (Eds.), Data-driven policy impact evaluation: How access to microdata is transforming policy design (pp. 47–65). Springer.

    Chapter  Google Scholar 

  • Soneson, E., Das, S., Burn, A.-M., Van Melle, M., Anderson, J. K., Fazel, M., Fonagy, P., Ford, T., Gilbert, R., & Harron, K. (2022). Leveraging administrative data to better understand and address child maltreatment: A scoping review of data linkage studies. Child Maltreatment, 10775595221079308.

    Google Scholar 

  • Vidal, S., Prince, D., Connell, C. M., Caron, C. M., Kaufman, J. S., & Tebes, J. K. (2017). Maltreatment, family environment, and social risk factors: Determinants of the child welfare to juvenile justice transition among maltreated children and adolescents. Child Abuse & Neglect, 63, 7–18. https://doi.org/10.1016/j.chiabu.2016.11.013

    Article  Google Scholar 

  • Yampolskaya, S. (2017). Research at work: Administrative data and behavioral sciences research. Families in Society, 98(2), 121–125.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian M. Connell .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Connell, C.M. (2023). Introduction and Volume Overview. In: Connell, C.M., Crowley, D.M. (eds) Strengthening Child Safety and Well-Being Through Integrated Data Solutions. Child Maltreatment Solutions Network. Springer, Cham. https://doi.org/10.1007/978-3-031-36608-6_1

Download citation

Publish with us

Policies and ethics