Early warning model for depression and anxiety among adolescent students: an empirical study based on Guilin

High risk of depression and anxiety, academic stress, FACESCV and CDRISC score are the influencing factors affecting the occurrence of depression and anxiety in adolescent students in Guilin.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2026-01-07
DOI
https://doi.org/10.3389/fpubh.2025.1685203
Primary Topic
Child and Adolescent Psychosocial and Emotional Development
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Early warning model for depression and anxiety among adolescent students: an empirical study based on Guilin

Ruizhe Wang, X. Chen, Qianwen Liao, Yingxin Tan et al.
Frontiers in Public Health
Child and Adolescent Psychosocial and Emotional Development
article

Early warning model for depression and anxiety among adolescent students: an empirical study based on Guilin

Ruizhe Wang, X. Chen, Qianwen Liao, Yingxin Tan, Na Li, Hao Wang, Lin Lu, Yijun Wang, Xuemei Xu, Mochen Zhang, Qingpo Ma
article en

Abstract

High risk of depression and anxiety, academic stress, FACESCV and CDRISC score are the influencing factors affecting the occurrence of depression and anxiety in adolescent students in Guilin.

Frontiers in Public HealthVol. 13
Guangxi Normal University (CN), Guangzhou University (CN), Zhongshan Hospital (CN), Shenzhen Third People’s Hospital (CN)
Division of Graduate Education
Quality Education
Openalex Percentile: Top 96%
Child and Adolescent Psychosocial and Emotional Development
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.