Latent class analysis risk profiles: An effective method to predict a first re-report of maltreatment?

Hyunil Kim, Melissa Jonson-Reid, Patricia Kohl, Chien jen Chiang, Brett Drake, Derek Brown, Tim McBride, Shenyang Guo

Research output: Contribution to journalArticlepeer-review

Abstract

Recurrence of child maltreatment is a significant concern causing substantial individual, family and societal cost. Variable-based approaches to identifying targets for intervention may not reflect the reality that families may experience multiple co-occurring risks. An alternative approach was tested using baseline data from the National Survey of Child and Adolescent Well-being (NSCAW) I and II to develop Latent Class Analysis models of family risk classes using variables derived from prior studies of re-reporting. The samples were collected approximately 10 years apart offering a chance to test how the approach might be impacted by demographic or policy shifts. The association between baseline classes and later re-reports was tested using both samples. A two-class model of high versus low presence of baseline risk resulted that was strongly associated with later likelihood of re-report and results were relatively stable across the two studies. Person-centered approaches may hold promise in the early identification of families that require a more comprehensive array of supports to prevent re-reports of maltreatment.

Original languageEnglish (US)
Article number101792
JournalEvaluation and Program Planning
Volume80
DOIs
StatePublished - Jun 2020

Keywords

  • Child maltreatment
  • Child maltreatment report
  • Latent class analysis
  • Risk profile

ASJC Scopus subject areas

  • Business and International Management
  • Social Psychology
  • Geography, Planning and Development
  • Strategy and Management
  • Public Health, Environmental and Occupational Health

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