Network analysis of mental health literacy and depressive/anxiety symptoms in patients under maintenance hemodialysis: a cross-sectional study of multicenter data.

Authors

Guifang Xue, Yupei Li, Ziying Ling, Xueni Zhang, Liming Yuan, Xiujuan Lin, Huaihong Yuan, Lin Chen

Published in

Scientific reports. Volume 16. Issue 1. Aug 03, 2026. Epub Aug 03, 2026.

Abstract

To explore the network structures and gender differences of mental health literacy (MHL) and depressive/anxiety symptoms in maintenance hemodialysis (MHD) patients and identify core symptoms and bridge symptoms. We used convenience sampling to recruit 757 MHD patients from 6 hospitals in Sichuan Province, China. The Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Scale (GAD-7), and the Chinese version of the Multidimensional Mental Health Literacy Scale (MMHL) were used for assessment. A network model was constructed, with centrality indicators and bridge strength calculated, network comparison tests and stability and accuracy tests were performed. The total score of MHL significantly negatively correlates with depressive symptoms (r = -0.22) and anxiety (r = -0.18). PHQ4 (Feeling tired or having little energy) and GAD4 (Trouble relaxing) showed higher strength centrality (1.205 and 1.184 respectively), while the strength of MHL2 (beliefs) was relatively high in the MHL cluster (0.546). In the bridge symptom analysis, the bridge strength of MHL2 (beliefs) was the highest (0.253), and PHQ3 (Trouble falling or staying asleep, or sleeping too much) was the key bridge symptom (0.143). Of note, significant difference was observed in the network structure between genders (p = 0.034). Our study mapped the complex interplay between MHL and depressive/anxiety symptoms in MHD patients. Fatigue is the core symptom, while the beliefs dimension of MHL and sleep problems are the key bridging symptoms. Future interventions should focus on fatigue, sleep, enhancing MHL knowledge, and reshaping positive beliefs, while considering gender-specific factors.

PMID:
42637902
Bibliographic data and abstract were imported from PubMed on 25 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.