Protective factors of children and families at highest risk of adverse childhood experiences : an analysis of children and families in the Growing Up in New Zealand data who “beat the odds” M.C. Walsh, S. Joyce, T. Maloney and R. Vaithianathan
By: Walsh, Matthew C
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Contributor(s): Joyce, Sophie | Maloney, Tim | Vaithianathan, Rhema.
Material type: 
BookPublisher: Wellington, New Zealand : Ministry of Social Development, 2019Description: electronic document (31 pages) ; PDF file.ISBN: 978-1-98-854158-7.Subject(s): Centre for Social Data Analytics, AUT University | ADVERSE CHILDHOOD EXPERIENCES | CHILDREN AT RISK | DATA ANALYSIS | Growing Up in New Zealand study (GUiNZ) | INTERPERSONAL RELATIONSHIPS | LONGITUDINAL STUDIES | PREDICTIVE RISK MODELLING | PROTECTIVE FACTORS | SOCIOECONOMIC FACTORS | NEW ZEALANDOnline resources: Click here to access online | Access the website | About GUiNZ Summary: The present report analyses the Growing Up in New Zealand (GUiNZ) birth cohort to identify protective factors for at-risk children who “beat the odds”. For the purpose of illustration, we build a predictive risk model using variables that are observed prenataly or at-birth in the GUiNZ data. These are mainly economic and demographic factors, and are chosen because they are typically available in administrative data. We use a predictive risk model to identify children who are at the highest risk of being exposed to Adversities of Childhood Experiences (ACEs) by 54 months. Children are classified as “beating the odds” if they are in the highest 20% risk group based on the predictive risk model, but by age 54 months have not experienced a single ACE.(From the Policy statement). For background information about this research and a related report, follow the link. Record #6223
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Access online
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Family Violence library | Online | Available | ON19040018 |
April 2019
The present report analyses the Growing Up in New Zealand (GUiNZ) birth cohort to identify protective factors for at-risk children who “beat the odds”. For the purpose of illustration, we build a predictive risk model using variables that are observed prenataly or at-birth in the GUiNZ data. These are mainly economic and demographic factors, and are chosen because they are typically available in administrative data. We use a predictive risk model to identify children who are at the highest risk of being exposed to Adversities of Childhood Experiences (ACEs) by 54 months. Children are classified as “beating the odds” if they are in the highest 20% risk group based on the predictive risk model, but by age 54 months have not experienced a single ACE.(From the Policy statement). For background information about this research and a related report, follow the link. Record #6223
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