Use of latent profile analysis and k-means clustering to identify student anxiety profiles.

ABSTRACT:

Background

Anxiety disorders are often the first presentation of psychopathology in youth and are considered the most common psychiatric disorders in children and adolescents. This study aimed to identify distinct student anxiety profiles to develop targeted interventions.

Methods

A cross-sectional study was conducted with 9738 students in Yingshan County. Background characteristics were collected and Mental Health Test (MHT) were completed. Latent profile analysis (LPA) was applied to define student anxiety profiles, and then the analysis was repeated using k-means clustering.

Results

LPA yielded 3 profiles: the low-risk, mild-risk and high-risk groups, which comprised 29.5, 38.1 and 32.4% of the sample, respectively. Repeating the analysis using k-means clustering r

SUBMITTER: Liu F 

PROVIDER: S-EPMC8728926 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature