Information overload, cognitive fusion, and health literacy among individuals with type 2 diabetes: a moderated network analysis

In the digital age, patients with type 2 diabetes mellitus (T2DM) are exposed to extensive health information, leading to information overload (IO). This overload results in decision-making difficulties, increased cognitive burden, and reduced health literacy (HL). This study investigates the complex relationship among IO, cognitive fusion (CF), and HL, emphasizing the moderating role of CF. A cross-sectional survey was conducted involving 233 patients with T2DM. Participants completed a general information questionnaire, the Information Overload Scale (IOS), the Cognitive Fusion Questionnaire (CFQ), and the Diabetes Health Literacy Scale (DHLS). A moderated network analysis was used to explore the bidirectional associations between IO and HL and to verify the moderating effect of CF. Network analysis revealed several significant bidirectional relationships between IO and HL, with CF showing a significant moderating effect. Reduced CF strengthened the positive effects of “perceived diabetes information overload” and “multi-channel diabetes information stress” on “functional health literacy”, as well as the effect of “increased diabetes information device maintenance” on “interactive health literacy”. “perceived diabetes information overload” had the highest centrality index in the network model, which demonstrated overall good stability. This study advances understanding of the relationships among IO, CF, and HL in patients with T2DM. The findings suggest that interventions aimed at alleviating cognitive rigidity should adopt comprehensive strategies targeting the IO symptom network to enhance HL in this population.

• Publication year

  2026

• Venue

  Scientific Reports

• Publication date

  2026-01-06

• Fields of study

  Medicine, Psychology

• Identifiers
  DOI 10.1038/s41598-025-34279-7PMID 41495359PMCID 12859006
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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