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Network analysis of the depressive symptom profiles in Asian patients with depressive disorders: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP‐AD)
Author(s) -
Park SeonCheol,
Jang Eun Young,
Xiang YuTao,
Kanba Shigenobu,
Kato Takahiro A.,
Chong MianYoon,
Lin ShihKu,
Yang ShuYu,
Avasthi Ajit,
Grover Sandeep,
Kallivayalil Roy A.,
Udomratn Pichet,
Chee Kok Yoon,
Tanra Andi J.,
Tan ChayHoon,
Sim Kang,
Sartorius Norman,
Park Yong Chon,
Shinfuku Naotaka
Publication year - 2020
Publication title -
psychiatry and clinical neurosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 74
eISSN - 1440-1819
pISSN - 1323-1316
DOI - 10.1111/pcn.12989
Subject(s) - medical prescription , major depressive disorder , psychiatry , depressive symptoms , depression (economics) , medicine , centrality , mood , anxiety , mathematics , combinatorics , economics , pharmacology , macroeconomics
Aim We aimed to estimate the network structures of depressive symptoms using network analysis and evaluated the geographic regional differences in theses network structures among Asian patients with depressive disorders. Methods Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP‐AD), the network of the ICD‐10 diagnostic criteria for depressive episode was estimated from 1174 Asian patients with depressive disorders. The node strength centrality of all ICD‐10 diagnostic criteria for a depressive episode was estimated using a community‐detection algorithm. In addition, networks of depressive symptoms were estimated separately among East Asian patients and South or Southeast Asian patients. Moreover, networks were estimated separately among Asian patients from high‐income countries and those from middle‐income countries. Results Persistent sadness, fatigue, and loss of interest were the most centrally situated within the network of depressive symptoms in Asian patients with depressive disorders overall. A community‐detection algorithm estimated that when excluding psychomotor disturbance as an outlier, the other nine symptoms formed the largest clinically meaningful cluster. Geographic and economic variations in networks of depressive symptoms were evaluated. Conclusion Our findings demonstrated that the typical symptoms of the ICD‐10 diagnostic criteria for depressive episode are the most centrally situated within the network of depressive symptoms. Furthermore, our findings suggested that cultural influences related to geographic and economic distributions of participants could influence the estimated depressive symptom network in Asian patients with depressive disorders.