Risk and resilience models in child development.

Child development Developmental processes Protective factors Resilience models Risk models

Journal

Advances in child development and behavior
ISSN: 0065-2407
Titre abrégé: Adv Child Dev Behav
Pays: United States
ID NLM: 0370417

Informations de publication

Date de publication:
2024
Historique:
medline: 12 9 2024
pubmed: 12 9 2024
entrez: 11 9 2024
Statut: ppublish

Résumé

This chapter provides the most comprehensive review of risk and resilience models for child development thus far, synthesizing these interdisciplinary frameworks for ease of use in research and practice. This review specifically focuses on process models with broader conceptualizations of risk and resilience that have effects across multiple developmental domains. Risk and resilience models alike agree that alleviating risk factors is beneficial for children's development, including risks ranging from proximal issues with households (e.g., instability) and caregivers (e.g., insecure attachment, abuse) to relatively distal influences like structural racism and socioeconomic status. Resilience models further add that children who experience risks are not inherently doomed to poorer outcomes, but can draw upon positive factors in development to combat negative effects from risk, which cannot always be avoided. Major positive factors include loving relationships, educational resources, and cultural assets. Risk and resilience are highly multidisciplinary fields that have contributed much to our understanding of human development, with ample room for continued growth. Understanding of risk and resilience processes, especially during sensitive developmental periods like early childhood, provides valuable insight for prevention and intervention research and practices. Risk and resilience models share an interest in deciphering the developmental processes that hinder and help children across domains so that kids can live their best lives, resulting in a better off society for all.

Identifiants

pubmed: 39260902
pii: S0065-2407(24)00020-X
doi: 10.1016/bs.acdb.2024.06.005
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

132-163

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

S Alexa McDorman (SA)

Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States. Electronic address: samcdor@umd.edu.

Ellie K Taylor-Robinette (EK)

Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States.

Rachel R Romeo (RR)

Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States.

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Classifications MeSH