A decade-long comparison of depressive symptom networks in Asian patients with depressive disorders: Findings from REAP studies in 2023 and 2013
Issued Date
2026-07-15
Resource Type
ISSN
01650327
eISSN
15732517
Scopus ID
2-s2.0-105033030051
Journal Title
Journal of Affective Disorders
Volume
405
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Affective Disorders Vol.405 (2026)
Suggested Citation
Lee S., Kim H.S., Yoon H., Kim E., Kim K., Kim I.B., Yang H.J., Yoon H.J., Kim H.S., Kim G.M., Si T.M., Kallivayalil R.A., Tanra A.J., Chee K.Y., Sim K., Pariwatcharakul P., Lin S.K., Sartorius N., Shinfuku N., Lee S., Toyota E., Lee J.H., Kato T.A., Park S.C. A decade-long comparison of depressive symptom networks in Asian patients with depressive disorders: Findings from REAP studies in 2023 and 2013. Journal of Affective Disorders Vol.405 (2026). doi:10.1016/j.jad.2026.121616 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115857
Title
A decade-long comparison of depressive symptom networks in Asian patients with depressive disorders: Findings from REAP studies in 2023 and 2013
Author's Affiliation
Hanyang University
Chang Gung Memorial Hospital
Chosun University
Hasanuddin University
Siriraj Hospital
Schulich School of Medicine & Dentistry
Inje University
Graduate School of Medicine
Hanyang University College of Medicine
College of Medicine, Pochon CHA University
Kangbuk Samsung Hospital
Taipei City Hospital Taiwan
Texas Woman's University
Kuala Lumpur Hospital
Dong-A University, College of Medicine
Jeju National University School of Medicine
Peking University Sixth Hospital
Hanyang University Guri Hospital
Singapore Institute of Mental Health
Hanyang University Medical Center
Pushpagiri Institute of Medical Sciences and Research Centre
Seinan Gakuin University
Association for the Improvement of Mental Health Programs
Chang Gung Memorial Hospital
Chosun University
Hasanuddin University
Siriraj Hospital
Schulich School of Medicine & Dentistry
Inje University
Graduate School of Medicine
Hanyang University College of Medicine
College of Medicine, Pochon CHA University
Kangbuk Samsung Hospital
Taipei City Hospital Taiwan
Texas Woman's University
Kuala Lumpur Hospital
Dong-A University, College of Medicine
Jeju National University School of Medicine
Peking University Sixth Hospital
Hanyang University Guri Hospital
Singapore Institute of Mental Health
Hanyang University Medical Center
Pushpagiri Institute of Medical Sciences and Research Centre
Seinan Gakuin University
Association for the Improvement of Mental Health Programs
Corresponding Author(s)
Other Contributor(s)
Abstract
Background Network analysis provides a framework for examining interrelationships among symptoms beyond traditional categorical diagnostic models. Objective Data were analyzed from two decade-apart, large-scale, multi-country surveys in Asia. Network structures of depressive symptoms among Asian patients with depressive disorders in 2023 and 2013 were compared. Methods Ten depressive symptom domains, rated by clinicians in accordance with National Institute for Health and Care Excellence (NICE) guidelines, were modeled using the graphical Least Absolute Shrinkage and Selection Operator. Network structures were compared using the Network Comparison Test and evaluated with respect to expected influence centrality, stability, and clustering. Subgroup network structure comparisons were additionally conducted according to gender and geographic region. Results The Network Comparison Test demonstrated significant differences in both network structure and global strength between 2013 and 2023. In 2023, among 2298 patients, depressive symptom networks comprised 38 connections, with the strongest associations observed between low self-confidence and guilt or self-blame and between disturbed sleep and poor or increased appetite; low self-confidence emerged as the most central symptom. In contrast, in 2013, among 1303 patients, 36 connections were identified, with persistent sadness and disturbed sleep forming the strongest association and persistent sadness representing the most central symptom. Substantial subgroup differences in network structure were also observed according to gender and region. Conclusions These differences may reflect contextual influences, including the COVID-19 pandemic and related sociocultural factors. The findings may further identify self-critical symptoms as promising targets for clinical intervention.