Academic Stress and Depressive Symptoms in High School Students: A Random Intercept Cross‐Lagged Panel Model and Cross‐Lagged Panel Network Analysis

Despite evidence linking academic stress and depressive symptoms, cross-sectional designs cannot reveal their developmental dynamics, and total-scale scores obscure symptom-level complexity and intervention targets. We applied the random intercept cross-lagged panel model (RI-CLPM) and cross-lagged panel network (CLPN) analysis to 307 Chinese adolescents (58.63% female) to examine the relationship between academic stress and depressive symptoms from the aggregate to the symptom level and to identify key nodes. Results from the RI-CLPM indicated a positive association between academic stress and depressive symptoms at the between-person level. At the within-person level, Time-1 academic stress predicted a reduction in Time-2 depressive symptoms. CLPN results revealed complex reciprocal influences: 'People were unfriendly' and 'I felt hopeless about the future' were initially vulnerable and later progressed to 'I felt sad' and 'I thought my life had been a failure'. Early drivers included 'I thought my life had been a failure' and 'I felt that people dislike me', whereas over time 'I was unhappy' and 'I felt hopeless about the future' gained predictive importance. The study revealed temporal relationships between academic stress and depressive symptoms and identified potential targets, providing evidence and implications for prevention and intervention.

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Publication Details

Journal
Stress and Health
Published
2026-10-29
DOI
https://doi.org/10.1002/smi.70240
Primary Topic
Student Stress and Coping
Type
article
Field-Weighted Citation Impact
0.00

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article

Academic Stress and Depressive Symptoms in High School Students: A Random Intercept Cross‐Lagged Panel Model and Cross‐Lagged Panel Network Analysis

Tianyuan Ji, Yang Yang, Lin Lin, Tianyun Xu et al.
6 links
Stress and Health
Student Stress and Coping
article

Academic Stress and Depressive Symptoms in High School Students: A Random Intercept Cross‐Lagged Panel Model and Cross‐Lagged Panel Network Analysis

Tianyuan Ji, Yang Yang, Lin Lin, Tianyun Xu, Xiuxiao Zhang
article en

Abstract

Despite evidence linking academic stress and depressive symptoms, cross-sectional designs cannot reveal their developmental dynamics, and total-scale scores obscure symptom-level complexity and intervention targets. We applied the random intercept cross-lagged panel model (RI-CLPM) and cross-lagged panel network (CLPN) analysis to 307 Chinese adolescents (58.63% female) to examine the relationship between academic stress and depressive symptoms from the aggregate to the symptom level and to identify key nodes. Results from the RI-CLPM indicated a positive association between academic stress and depressive symptoms at the between-person level. At the within-person level, Time-1 academic stress predicted a reduction in Time-2 depressive symptoms. CLPN results revealed complex reciprocal influences: 'People were unfriendly' and 'I felt hopeless about the future' were initially vulnerable and later progressed to 'I felt sad' and 'I thought my life had been a failure'. Early drivers included 'I thought my life had been a failure' and 'I felt that people dislike me', whereas over time 'I was unhappy' and 'I felt hopeless about the future' gained predictive importance. The study revealed temporal relationships between academic stress and depressive symptoms and identified potential targets, providing evidence and implications for prevention and intervention.

Stress and HealthVol. 42(6)
Tianjin Normal University (CN), Beijing Normal University (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 5%
Student Stress and Coping
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Academic Stress and Depressive Symptoms in High School Students: A Random Intercept Cross‐Lagged Panel Model and Cross‐Lagged Panel Network Analysis — Tianyuan Ji, Yang Yang, et al. · Stress and Health (2026) | TGRS Research Map | TGRS