A Network Analysis of Medication Literacy and Associated Psychological Factors in Patients with Coronary Heart Disease and Diabetes

Xin Liang 1,*, Miaoji Lu1,*, Lewen Zou1, Ciyu Chen2, Xinhui Huang1, Lixia Li3, Junfeng Zhang4, Rui Wang11School of Nursing, Guangdong Pharmaceutical University, Guangzhou, Guangdong, People’s Republic of China; 2Department of Neurology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, People’s Republic of China; 3School of Public Health, Guangdong Pharmaceutical University, Guangzhou, Guangdong, People’s Republic of China; 4Department of Nursing, Songshan Lake Central Hospital ofDongguan City, Dongguan, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Rui Wang, School of Nursing, Guangdong Pharmaceutical University, 283 Jianghai Avenue, Haizhu District, Guangzhou, Guangdong, 510310, People’s Republic of China, Email ruiruiwang2008@163.comJunfeng Zhang, Department of Nursing, Songshan Lake Central Hospital of Dongguan City, Dongguan, Guangdong, 523320, People’s Republic of China, Email feng06140119@126.comPurpose: To investigate the level of medication literacy and explore the conditional associations among medication literacy, beliefs about medicines, self-efficacy for appropriate medication use, and illness perceptions in patients with coronary heart disease and comorbid diabetes mellitus using network analysis.Methods: A convenience sample of 417 patients with coronary heart disease and diabetes mellitus was recruited from two Grade A tertiary hospitals and a community health center in Guangdong, China between January and August 2025. Measures included a general information questionnaire, the Self-Assessment Scale for Medication Literacy in Patients with Coronary Heart Disease Comorbidity Diabetes, the Chinese version of the Beliefs about Medicines Questionnaire-Specific, the Chinese version of the Self-Efficacy for Appropriate Medication Use Scale, and the Chinese version of the Brief Illness Perception Questionnaire. Statistical analyses were conducted using SPSS 27.0 and R Studio. The network structure was estimated with the EBICglasso algorithm. Expected influence was used to identify central nodes, and bridge expected influence was used to identify bridge nodes. The stability and accuracy of the network were examined using case-dropping and bootstrap procedures.Results: The average score of medication literacy was 77.09± 10.29. The network showed that the edge weight between node S1 (medication use under difficult circumstances) and node M5 (calculation) was 0.24, which was the largest among cross-network edges. The average node predictability was 48.6%. M2 (comprehension) had the largest expected influence index (0.89), and MB1 (necessity of medication) had the largest bridge expected influence index (0.35). The 95% confidence intervals for the edge weights were narrow. The correlation stability coefficients for both expected influence and bridge expected influence were 0.751.Conclusion: Patients with coronary heart disease and diabetes mellitus exhibited a moderate level of medication literacy. Network analysis identified M2 (comprehension) as a core node and MB1 (necessity of medication) as a key bridge node, suggesting that they may be considered potential priorities for assessment and intervention development.Keywords: coronary heart disease, diabetes mellitus, medication literacy, network analysis