Previously submitted to: JMIR Medical Informatics (no longer under consideration since Mar 31, 2026)
Date Submitted: Oct 4, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Multidimensional Evaluation of the Quality of Hyperglycemia in Pregnancy Information on WeChat Platform in China: A Cross-Sectional Survey
ABSTRACT
Background:
WeChat is a important source of health information for Chinese perinatal women. The quality of its health information and alignment with perinatal women’s needs influence health literacy and self-management in those with hyperglycemia in pregnancy.
Objective:
This study aimed to multidimensionally evaluate the quality and alignment with perinatal women’s needs of hyperglycemia in pregnancy health information on China’s WeChat platform, and identify its overall multidimensional quality patterns.
Methods:
The terms “妊娠期” (pregnancy) and “糖尿病” (diabetes), or “妊娠期” (pregnancy) and “高血糖” (hyperglycemia) were used to search in WeChat, the hottest articles on hyperglycemia in pregnancy were selected. DISCERN was used to evaluate the information’s content quality, Patient Education Materials Assessment Tool (PEMAT) was used to evaluate the information’s understandability and actionability. Specific deficiencies identified in low-scoring items are reported herein. Latent profile analysis (LPA) was used to determine the overall performance patterns of multidimensional quality. Frequency statistics and theme extraction from literature were used to determine the alignment with perinatal women’s information needs. ANOVA was used to analyze variations in DISCERN and PEMAT scores across various information sources. Spearman correlation analysis was used to analyze the relationships between DISCERN and PEMAT scores and different traits of information dissemination.
Results:
A total of 286 hottest articles on the WeChat platform were included, with a DISCERN score of 41.06 (SD 6.46), a PEMAT understandability score of 64.7% (SD 10.3%), an actionability score of 41.6% (SD 20.8%), and a 42.0% (SD 15.7%) alignment between article content and the information needs of perinatal women. The overall performance patterns of information quality falls into three categories: “professional priority-practical lag type” (19%), “usability priority-basic reliability type” (16.5%), and “multidimensional defects-unusable type” (64.5%). The total DISCERN score, scores for the credibility and comprehensiveness dimension scores of DISCERN, and PEMAT actionability scores differed across different sources (p<.05). Weak positive correlations were observed between daily reads counts and likes with comprehensiveness (ρ=0.19, P<.001; ρ=0.15, P=.01), understandability (ρ=0.19, P=.001; ρ=0.171, P=.004), and actionability (ρ=0.21, P<.001; ρ=0.18, P=.002). Additionally, daily retweets counts were weakly positively correlated with actionability (ρ= 0.21 and P<.001).
Conclusions:
The quality of health information on hyperglycemia in pregnancy on WeChat is generally average, characterized by low actionability, limited understandability, and limited alignment with information needs. Overall, the “multidimensional defects-unusable type” is predominant. It is recommended that authors of health information for users with hyperglycemia in pregnancy respond to the sophisticated information demands of perinatal women and comprehensively improve the multifaceted quality of information, thereby enhancing perinatal women’s health literacy and self-management capabilities.
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