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Cited by 304

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Longitudinal Trajectories of Self-System Processes and Depressive Symptoms Among Maltreated and Nonmaltreated Children

Kim, Jungmeen, Cicchetti, Dante·2006·Child Development

Abstract

This study used latent growth modeling to investigate longitudinal relationships between self-system processes and depressive symptoms among maltreated (n=142) and nonmaltreated children (n=109) aged 6–11 years. On average, self-esteem and self-agency increased and depressive symptoms decreased over time. Multivariate growth modeling indicated that, regardless of gender, physical abuse was negatively related to initial levels of self-esteem, and physical abuse and physical neglect were positively associated with initial levels of depressive symptoms. Emotional maltreatment was predictive of changes in self-esteem and changes in depressive symptoms. Initial levels of self-esteem were negatively associated with initial levels of depressive symptoms. The findings contribute to enhancing our understanding of the developmental processes whereby early maltreatment experiences are linked to later maladjustment.

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Crossref · 10.1111/j.1467-8624.2006.00894.x

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Metadata

Authors
Kim, J., & Cicchetti, D.
Venue
Child Development
Published
2006-05-01
Volume
77
Issue
3
Pages
624-639
ISSN
  • 0009-3920 (ISSN-L)
  • 1467-8624
OpenAlex
W2138378851
Cited by
304
References
9
FWCI
11.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Longitudinal Trajectories of Self-System Processes and Depressive Symptoms Among Maltreated and Nonmaltreated Children. https://app.cochat.ai/papers/10.1111/j.1467-8624.2006.00894.x
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Kim, J., & Cicchetti, D. (2006). Longitudinal Trajectories of Self-System Processes and Depressive Symptoms Among Maltreated and Nonmaltreated Children. Child Development. https://doi.org/10.1111/j.1467-8624.2006.00894.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.