Association between social network types and health information literacy among patients with chronic diseases: a cross-sectional study

To examine the association between social network types and health information literacy among patients with chronic diseases, thereby providing evidence for developing targeted strategies to enhance HIL. This study included 314 chronic disease patients from a Grade III Class A hospital in Zhejiang Province, China, between June 2022 and June 2025. Data were collected using the Social Networks and Support Questionnaire, the Chinese Mandarin version of the Medical Outcomes Study Social Support Survey, the Social Relational Quality Scale, and the Health Information Literacy Self-Rating Scale. Social network structure analysis was performed using R software and UCINET 6.0. Cluster analysis, univariate analysis, and hierarchical multiple linear regression analysis were conducted using SPSS 26.0. The social networks of chronic disease patients can be categorized into three types, including structural networks (60.19%), comprehensive networks (31.85%), and restricted networks (7.96%). Univariate analysis revealed statistically significant differences in HIL levels between patients with comprehensive network patterns and those with structural or restricted network patterns ( p < 0.001). Comprehensive network patterns demonstrated the highest literacy scores (16.01 ± 3.19 points), with structural network users scoring moderately (14.43 ± 3.21 points) and restricted network users scoring lowest (13.28 ± 3.84 points). These differences remained statistically significant after controlling for demographic and disease-related factors ( p < 0.05). Social network type is significantly associated with HIL among individuals with chronic diseases. Optimizing the social networks is a key pathway to enhancing their HIL, and healthcare professionals should pay close attention to this issue.