Progress in researches on latent class analysis based subtyping of depression
10.3969/j.issn.1674-8115.2018.06.016
- Author:
Cheng-Lei WANG
1
Author Information
1. Division of Mood Disorder, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
- Publication Type:Journal Article
- Keywords:
Depression;
Latent class analysis;
Subtyping
- From:
Journal of Shanghai Jiaotong University(Medical Science)
2018;38(6):676-679
- CountryChina
- Language:Chinese
-
Abstract:
Depression is a highly heterogeneous syndrome. Homogeneous subtypes according to symptomatology of illness may contribute to development of individualized treatment, assessment on outcomes and prognosis. Latent class analysis is a flexible statistical approach to determine classes with similar symptom profiles in a heterogeneous group, which has been widely used in data-driven subtyping of depression to increase accuracy of subtyping. This article reviewed existing symptom-based subtypes of depression and findings of researches on latent class analysis based illness subtyping.
