Network structure of reward sensitivity and its temporal interactions with depression

A cross‐lagged panel network analysis

Bibliographic Data

ID21344231
AuthorsXiaoyan Bi (0009-0004-6854-9339, School of Education Guangzhou University Guangzhou China), Shutao Ma (School of Educational Science South China Normal University Guangzhou China), Hongbo Cui (School of Education Guangzhou University Guangzhou China), Liang Zhang (0000-0001-9041-1150, State Key Laboratory of Cognitive Science and Mental Health Institute of Psychology, Chinese Academy of Sciences Beijing China, corresponding author), Yankun Ma (0000-0001-6605-3103, School of Education Guangzhou University Guangzhou China, corresponding author)
Year2026
Volume67
Issue6
Pages951-962
Publication date2026-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Child Psychology and Psychiatry (JOURNAL)
Journal identifiersISSN: 0021-9630 • E-ISSN: 1469-7610
PublisherWiley (PUBLISHER • GB)
DOI10.1111/jcpp.70094
PMID41414831
OpenAlexW4417488524
LanguageEN
References cited63

BACKGROUND: Reward sensitivity plays a crucial role in shaping emotional and behavioural responses, yet its internal structure and dynamic interplay with depression remain underexplored. This study systematically examined the network structure of reward sensitivity and its associations with depression using a network analysis framework. METHODS: = 14.32, 52.82% female), we constructed multiple cross-sectional and bridge networks, as well as a cross-lagged panel network model (CLPN). RESULTS: (1) Cross-sectional network analysis reveals that positive feedback serves as the core node in the depression group, while hobbies dominate in the healthy group; (2) bridging network analysis identifies hobbies and positive affect as key bridging nodes linking reward sensitivity and depression; (3) CLPN analysis demonstrates that greater engagement in hobbies at baseline significantly predicts lower levels of depression 6 months later. CONCLUSIONS: This study provided a novel network perspective on the structural and temporal characteristics of reward sensitivity in depression. The findings underscored the importance of targeting specific reward types in intervention strategies and personalised mental health approaches

Intervention (counseling) · Network analysis · Network model · Network structure · Perspective (graphical) · Sensitivity (control systems) · Functional Brain Connectivity Studies · Mental Health Research Topics · Personality Disorders and Psychopathology

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