The longitudinal relationships between parent–child alienation and depression in adolescents: insights of network analysis

Adolescent depression is a major health issue requiring precise interventions. While Network theory guides symptom-targeted interventions, longitudinal studies in community adolescents remain scarce. Ecological Systems Theory indicates parent–child alienation (PA) as a depression disruptor, but how PA influences depressive networks is unknown. This study aims to bridge this gap by examining symptom-level interactions between PA and depression in community adolescents through two-wave network analysis. 1503 Chinese adolescents (mean age = 13.95 ± 2.05 years; 49.63% female) were surveyed at two time points one year apart [baseline (T1), 12-months later (T2)]. Analyses included: T1 cross-sectional depression network (n = 1503), T1/T2 bridge networks (n = 1148 each), and T1 → T2 cross-lagged panel network (CLPN; n = 1148). (1) Anhedonia had the highest expected influence (EI = 1.03) within the T1 depression network. (2) Anhedonia showed the highest bridge EI (BEIT1 = 0.19; BEIT2 = 0.13) linking PA and depression. (3) CLPN revealed bidirectional PA-depression prediction, with stronger prediction effect of depression on subsequent PA than vice versa. Compared with alienation towards father, alienation towards mother predicted subsequent depressive symptoms more strongly. Key paths: “alienation towards mother” predicting subsequent “anhedonia” and “negative mood” (both weight = 0.04); “negative self-esteem” predicting subsequent “alienation towards father (weight = 0.57) /mother (weight = 0.42)”. (4) In CLPN, negative self-esteem was the central symptom (out-EI = 1.52), while anhedonia was the most affected depressive symptom (in-EI = 0.39). This study confirms anhedonia as central symptom within depression network and a core bridge linking PA and depressive symptoms cross-sectionally. Longitudinally, PA and depression bidirectionally predict each other, with depression exerting stronger forward prediction. Furthermore, alienation towards mothers shows stronger prediction on subsequent depressive symptoms. Negative self-esteem functions as an activator and anhedonia as maintainer in CLPN. These findings integrate Network Theory and Ecological Systems Theory to elucidate how PA prompts depression network dynamic and depression self-maintenance pathways. This calls for school-based anhedonia screening for alienated youth and family-focused interventions targeting negative self-esteem and anhedonia.

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Publication Details

Journal
Child and Adolescent Psychiatry and Mental Health
Published
2026-06-18
DOI
https://doi.org/10.1186/s13034-026-01120-6
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
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article

The longitudinal relationships between parent–child alienation and depression in adolescents: insights of network analysis

Zongpei Dai, Ying Hé, XD Sun, Qiaoning Zhou et al.
Child and Adolescent Psychiatry and Mental Health
Mental Health Research Topics
article

The longitudinal relationships between parent–child alienation and depression in adolescents: insights of network analysis

Zongpei Dai, Ying Hé, XD Sun, Qiaoning Zhou, Qin Dai, Wenxiang Jian, Xiaomei Ren
article en

Abstract

Adolescent depression is a major health issue requiring precise interventions. While Network theory guides symptom-targeted interventions, longitudinal studies in community adolescents remain scarce. Ecological Systems Theory indicates parent–child alienation (PA) as a depression disruptor, but how PA influences depressive networks is unknown. This study aims to bridge this gap by examining symptom-level interactions between PA and depression in community adolescents through two-wave network analysis. 1503 Chinese adolescents (mean age = 13.95 ± 2.05 years; 49.63% female) were surveyed at two time points one year apart [baseline (T1), 12-months later (T2)]. Analyses included: T1 cross-sectional depression network (n = 1503), T1/T2 bridge networks (n = 1148 each), and T1 → T2 cross-lagged panel network (CLPN; n = 1148). (1) Anhedonia had the highest expected influence (EI = 1.03) within the T1 depression network. (2) Anhedonia showed the highest bridge EI (BEIT1 = 0.19; BEIT2 = 0.13) linking PA and depression. (3) CLPN revealed bidirectional PA-depression prediction, with stronger prediction effect of depression on subsequent PA than vice versa. Compared with alienation towards father, alienation towards mother predicted subsequent depressive symptoms more strongly. Key paths: “alienation towards mother” predicting subsequent “anhedonia” and “negative mood” (both weight = 0.04); “negative self-esteem” predicting subsequent “alienation towards father (weight = 0.57) /mother (weight = 0.42)”. (4) In CLPN, negative self-esteem was the central symptom (out-EI = 1.52), while anhedonia was the most affected depressive symptom (in-EI = 0.39). This study confirms anhedonia as central symptom within depression network and a core bridge linking PA and depressive symptoms cross-sectionally. Longitudinally, PA and depression bidirectionally predict each other, with depression exerting stronger forward prediction. Furthermore, alienation towards mothers shows stronger prediction on subsequent depressive symptoms. Negative self-esteem functions as an activator and anhedonia as maintainer in CLPN. These findings integrate Network Theory and Ecological Systems Theory to elucidate how PA prompts depression network dynamic and depression self-maintenance pathways. This calls for school-based anhedonia screening for alienated youth and family-focused interventions targeting negative self-esteem and anhedonia.

Child and Adolescent Psychiatry and Mental Health
Army Medical University (CN), Chongqing University of Education (CN), Xinqiao Hospital (CN), The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), Southwest Hospital (CN), Jiangjin Central Hospital (CN), Children's Hospital of Chongqing Medical University (CN), Chongqing Medical University (CN)
Good health and well-being
Openalex Percentile: Top 4%
Mental Health Research Topics
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