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Exploring the protective factors of children and families identified at highest risk of adverse childhood experiences by a predictive risk model: An analysis of the growing up in New Zealand cohort

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  • Walsh, Matthew C.
  • Joyce, Sophie
  • Maloney, Tim
  • Vaithianathan, Rhema

Abstract

With increasing access to integrated administrative data, and advances in predictive analytics, it is both theoretically possible and practically feasible to use predictive risk models (PRMs) to automatically risk stratify entire birth-cohorts as to their risk of experiencing multiple adversities in childhood (Vaithianathan et al., 2013, 2018; Rouland & Vaithianathan, 2018). Such automated screening tools allow agencies to identify families at highest risk and offer them preventive services in a timely fashion. However, little is known about what protective factors might exist amongst families who are identified as high risk by PRMs. Identifying protective factors is an important step in designing preventive services for families identified by PRM tools as well as helping social workers take a strengths-based approach to these families.

Suggested Citation

  • Walsh, Matthew C. & Joyce, Sophie & Maloney, Tim & Vaithianathan, Rhema, 2020. "Exploring the protective factors of children and families identified at highest risk of adverse childhood experiences by a predictive risk model: An analysis of the growing up in New Zealand cohort," Children and Youth Services Review, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:cysrev:v:108:y:2020:i:c:s0190740919302968
    DOI: 10.1016/j.childyouth.2019.104556
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    References listed on IDEAS

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