Background: Although maternal childhood maltreatment has been associated with offspring externalizing symptoms, little is known about the potential mechanisms that contribute to breaking the intergenerational effect of maternal childhood maltreatment.
Objective: The current study aimed to (a) investigate the intergenerational effect between maternal childhood maltreatment and offspring externalizing symptoms in the Chinese family; (b) examine maternal supportive and harsh parenting as potential mediators of this intergenerational effect; and (c) explore the moderating roles of paternal support parenting, as well as paternal harsh parenting, in this mediation process of maternal supportive and harsh parenting.
Participants And Setting: The sample consisted of 1111 mother-father-child triads from Beijing, recruited when the children were one and three years old.
Methods: Mothers completed the Childhood Trauma Questionnaire, and both parents completed the Infant-Toddler Social and Emotional Assessment and Comprehensive Early Childhood Parenting Scale.
Results: Our results showed that maternal childhood maltreatment was a risk factor for offspring externalizing symptoms at T2 (β = 0.24, t = 6.51, p < .001), and this effect was mediated by maternal supportive (indirect effect = 0.03, 95%CI = [0.02, 0.05]) and harsh parenting (indirect effect = 0.03, 95%CI = [0.02, 0.07]) at T1. Furthermore, paternal harsh parenting moderated the indirect effect of maternal childhood maltreatment on child externalizing symptoms through maternal supportive parenting.
Conclusions: These findings contribute to our understanding and provide valuable information for disrupting the intergenerational effect of maternal childhood maltreatment.
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http://dx.doi.org/10.1016/j.chiabu.2024.107004 | DOI Listing |
Psychosoc Interv
January 2025
Universidad de Córdoba Spain Universidad de Córdoba, Spain.
The aims of this research work were twofold: (1) to validate the factor structure of the Spanish version of the Emotionality, Activity and Sociability Temperament Survey (EAS) and (2) to analyse the relationship between child temperament, and parental stress and rewards, testing the possible moderating roles of gender and social support. The reference population was a group of mothers and fathers with children in early childhood education (aged 0-5). For the first study, we used a sample of 701 subjects (70.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Department of Clinical Dentistry, Faculty of Medicine, University of Bergen, Bergen, Norway.
Background: In the last years, artificial intelligence (AI) has contributed to improving healthcare including dentistry. The objective of this study was to develop a machine learning (ML) model for early childhood caries (ECC) prediction by identifying crucial health behaviours within mother-child pairs.
Methods: For the analysis, we utilized a representative sample of 724 mothers with children under six years in Bangladesh.
Crim Behav Ment Health
January 2025
Institute of Psychology, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany.
Background: This article is dedicated to David Farrington who was a giant in criminology and, in particular, a pioneer in studying developmental pathways of delinquent and antisocial behaviour. Numerous studies followed his work. Systematic reviews of his and others' research described between two and seven (mainly 3-5) trajectories.
View Article and Find Full Text PDFBMJ Open
January 2025
Department of Medicine, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
Objective: The study aims to assess the effect of intrauterine metformin exposure on offspring adiposity measures in childhood.
Design: Systematic review and meta-analysis.
Data Sources: Medline, Embase and Cochrane Central were searched from inception to 4 October 2024.
Eur Respir Rev
January 2025
Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
Introduction: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.
Methods: 10 databases were searched.
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