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Improving Early Diagnosis of Child Neglect for a Better Response in Healthcare Settings. | LitMetric

AI Article Synopsis

Article Abstract

Early diagnosis of child neglect is an ongoing challenge with consequences of the child's safety, health, and effective referral for intervention. This study aims to obtain a selected set of family, maternal, and dyadic variables of the immediate caregiving environment for diagnosis, preventive, and intervention responses in healthcare settings. Mothers and their children under five years old: 51 in the neglected group (NG) and 89 in the non-neglected control group (CG), were recruited through pediatric primary care services and social services in Spain. Family demographics, adverse events, childhood maltreatment, maternal psychopathologies, personality variables, and observed mother-child interactions were assessed. Gradient boosting analyses were applied for the contributor's relative importance (), followed by logistic regression and discriminant analyses for those with higher . Parametric analyses showed high diagnostic accuracy (80-82% of NG and 92% of CG) for risky factors of child neglect: having a physically neglected and depressed mother, living in families in need of financial assistance, and large families; and for protective factors: having an older mother and showing higher mother-child emotional availability. Identifying a select group of features makes early diagnosis and preventive intervention more effective for mitigating the impact of child neglect and building mother-child resilience.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535148PMC
http://dx.doi.org/10.3390/children8100859DOI Listing

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