Network analysis of sleep disorders, depression and anxiety symptoms among community older adults

The central symptoms and their intricate connections in the network play an importance role in gaining the underlying pathological mechanisms, as well as potential interventions for comorbidity in community older adults.

Authors

Institutions

Publication Details

Journal
BMC Geriatrics
Published
2025-09-24
DOI
https://doi.org/10.1186/s12877-025-06381-y
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
6.35

Funders

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

Network analysis of sleep disorders, depression and anxiety symptoms among community older adults

Aoyi Tang, Peiyuan Qiu, Jing Huang, Silin Ye et al.
3 citations
BMC Geriatrics
Mental Health Research Topics
6.35
article

Network analysis of sleep disorders, depression and anxiety symptoms among community older adults

Aoyi Tang, Peiyuan Qiu, Jing Huang, Silin Ye, Qianrui Li, Fei Chen, Linyang Song
article en
3 citations

Abstract

The central symptoms and their intricate connections in the network play an importance role in gaining the underlying pathological mechanisms, as well as potential interventions for comorbidity in community older adults.

BMC GeriatricsVol. 25(1)
Sichuan University (CN), West China Hospital of Sichuan University (CN), State Key Laboratory of Oral Diseases
China Medical Board, National Natural Science Foundation of China, Sichuan University, West China Hospital, Sichuan University
Openalex Percentile: Top 3%
Mental Health Research Topics
6.35
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.