000			04436nab a22002897a 4500
999			_c8202 _d8202
005			20250625151639.0
008			230530s2020 -nz||||| |||| 00| 0 eng d
040			_aAFVC
100			_aWalsh, Matthew C. _98303
245			_aExploring the protective factors of children and families identified at highest risk of adverse childhood experiences by a predictive risk model _cMatthew C. Walsh, Sophie Joyce, Tim Maloney and Rhema Vaithianathan _ban analysis of the growing up in New Zealand cohort
260			_bElsevier, _c2020
500			_aChildren and Youth Services Review, 2020, 108: 104556
520			_aAims 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. Methods We used multiple waves of the Growing Up in New Zealand (GUiNZ) study which follows a cohort of children and their families (n = 5562). Children were coded to reflect the number of adversities they experienced by 54 months based on standard measures of Adverse Childhood Experiences (ACEs) (Felitti et al., 1998). A PRM was trained to predict two or more ACEs experienced by 54 months using only administrative data available at birth and routinely held by the government, and the most at-risk children (comprising the top 20% of risk) were retained for our analysis. This study examines potential protective factors associated with having no observed ACEs despite being predicted to be at high risk of ACEs. We coded these factors from multiple waves of mother and partner surveys, with 749 factors identified as candidate protective factors. These 749 factors were coded into conceptual domains using previous literature: mother-partner, family finances, parent health and wellbeing, community or neighborhood, or parent-child. Forward, backward and multivariable regressions were utilized to identify factors with the strongest associations with having no observed ACEs despite being in the high risk GUiNZ group of children. Results Of the whole cohort, 790 children were identified as being at greatest risk. Of these, 164 experienced no observed ACEs. The 749 protective factors that were tested fell into the following domains: mother-partner relationship (9%), family finances (23%), parent health and wellness (14%), community or neighborhood (36%), and parent-child relationship (9%). Those that were significantly associated with high risk children with no observed ACEs were from the following domains: mother-partner relationship (40%), family finances (22%), parent health and wellness (15%), community or neighborhood (13%), and parent-child relationship (13%). Conclusions Our findings suggest that important protective factors exist in the domain mother-partner relationship. While many of these factors might not be mutable, these results are suggestive of a useful domain for program designers and policy-makers to consider when serving high risk families. They might also be useful factors on which to focus when approaching families for recruitment into services. (Authors' abstract). Record #8202
650		0	_aADVERSE CHILDHOOD EXPERIENCES _94089
650			_aDATA ANALYSIS _9181
650		0	_aGrowing Up in New Zealand study (GUiNZ) _98305
650			_aPREDICTIVE RISK MODELLING _94928
650			_aPROTECTIVE FACTORS _94270
651		4	_aNEW ZEALAND _92588
700			_aJoyce, Sophie _98306
700			_aMaloney, Tim _95617
700			_aVaithianathan, Rhema _94305
773			_tChildren and Youth Services Review, 2020, 108: 104556
830			_aChildren and Youth Services Review _94699
856			_uhttps://doi.org/10.1016/j.childyouth.2019.104556 _yDOI: 10.1016/j.childyouth.2019.104556
942			_2ddc _cARTICLE