A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample

This study introduces a fine-grained framework for deconstructing psychopathological heterogeneity, providing a comprehensive approach to parsing psychopathology. While the framework is preliminarily applied to a large sample from the Chinese population, future studies should integrate multimodal neurobehavioral measures, employ intensive longitudinal designs to track symptom dynamics, and validate its consistency across diverse cultural and regional contexts.

Authors

Institutions

Publication Details

Journal
BMC Psychiatry
Published
2025-07-01
DOI
https://doi.org/10.1186/s12888-025-06960-8
Citations
2
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
4.24

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample

Zhiyong Wu, Ang Hong, Chaoyi Wu, Zhen Wang et al.
2 citations
BMC Psychiatry
Mental Health Research Topics
4.24
article

A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample

Zhiyong Wu, Ang Hong, Chaoyi Wu, Zhen Wang, Chenyu Yuan, Yinqing Fan
article en
2 citations

Abstract

This study introduces a fine-grained framework for deconstructing psychopathological heterogeneity, providing a comprehensive approach to parsing psychopathology. While the framework is preliminarily applied to a large sample from the Chinese population, future studies should integrate multimodal neurobehavioral measures, employ intensive longitudinal designs to track symptom dynamics, and validate its consistency across diverse cultural and regional contexts.

BMC PsychiatryVol. 25(1)
Sun Yat-sen University (CN), Shanghai Jiao Tong University (CN), Shanghai Mental Health Center (CN)
Shanghai Municipal Health Commission
Reduced inequalities
Openalex Percentile: Top 6%
Mental Health Research Topics
4.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.