Preschool and preadolescent antecedents of externalizing problems: a machine learning approach.
This study used a data-driven approach to elucidate the relative importance of child, maternal, and mother-child dyadic characteristics in predicting externalizing problems across two critical stages, preschool and preadolescence, that mark the development of externalizing problems. Data (N = 1,364)...
| Published in: | European Child & Adolescent Psychiatry Vol. 34; no. 11; pp. 3401 - 3414 |
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| Main Authors: | , |
| Format: | research tables/charts Journal Article |
| Published: |
Springer Nature
Nov2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189593490&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189593490 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10188827 EJ3 jtl: European Child & Adolescent Psychiatry issn: 10188827 maglogo: N pubinfo: dt: Nov2025 vid: 34 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 189593490 185441542 189593490 189593490 10.1007/s00787-025-02754-1 189593490 ppf: 3401 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Preschool and preadolescent antecedents of externalizing problems: a machine learning approach. aug: au: Yang, Yaqi Wang, Yiji affil: https://ror.org/02n96ep67 Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, 200062, Shanghai, China sug: subj: Child Behavior Disorders Etiology Child Behavior Disorders Risk Factors Risk Assessment Machine Learning Methods Funding Source Human Male Female Child, Preschool Child Descriptive Statistics Models, Theoretical Mother-Child Relations Secondary Analysis Prospective Studies Random Forest Random Sample Semi-Structured Interview Interrater Reliability T-Tests Chi Square Test Effect Size Bivariate Statistics Correlational Studies Depression Symptoms Child Behavior Checklist Checklists Scales Child, Preschool: 2-5 years Child: 6-12 years Male Female ab: This study used a data-driven approach to elucidate the relative importance of child, maternal, and mother-child dyadic characteristics in predicting externalizing problems across two critical stages, preschool and preadolescence, that mark the development of externalizing problems. Data (N = 1,364) were collected through maternal reports and observations during preschool and preadolescence. Using the random forest algorithm in machine learning, the results showed that the predictive models differed between preschool and preadolescence. For preschool antecedents of externalizing problems, maternal characteristics, such as depressive symptoms, education, and sensitivity, emerged as the most highly ranked predictors, followed by mother-child dyadic characteristics. Moreover, for preadolescent antecedents of externalizing problems, mother-child dyadic characteristics, including conflict and positive relationship, were identified as the top predictors, with maternal characteristics playing a secondary role. While child characteristics were relatively less influential across both age groups, child negative reactivity emerged as a salient predictor during preadolescence. The findings contribute data-driven evidence to elucidate the relative importance of preschool and preadolescent antecedents of externalizing problems, with maternal characteristics playing a central role in early childhood and mother-child dynamics becoming most important during preadolescence. Interventions targeting externalizing problems should be developmentally sensitive, with preschool programs emphasizing maternal well-being and early relational foundations, while preadolescent programs prioritize strengthening the mother-child relationships and addressing dyadic challenges. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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