Relationship Between Online Health Information Acquisition and Shared Decision-Making Among Patients With Diabetes: Cross-Sectional Survey Study

Background: Shared decision-making allows patients and clinicians to make decisions together to help determine the most appropriate option. Patients need comprehensive health information to participate and evaluate different options during the shared decision-making process. Patients with diabetes need to constantly monitor their health status. They experience an array of health information needs during their ongoing health management. Online health information acquisition is a common behavior among patients with diabetes, and online information can impact the interaction between patients with diabetes and health care providers. Objective: This study explored the relationship between 2 types of online health information acquisition behavior (active online health information seeking and incidental online health information acquisition) and shared decision-making. It also investigated the mediating role of eHealth literacy during the information acquisition process among US patients with diabetes aged 18 to 44 years. Methods: Participants were patients with diabetes aged 18 to 44 years in the United States and were recruited by a survey company, Centiment. The sampling process matched the national distribution of gender and age in the United States. An online survey questionnaire was distributed through Qualtrics. A total of 558 valid responses were collected. The average age of the sample was 35.91 (SD 6.04) years. Among the sample, 260 participants were men, 291 participants were women, and 7 participants identified their gender as other. Bivariate analyses and partial least squares structural equation modeling were used for data analysis. All data analyses were performed in R. Results: The prevalences of active online health information seeking (mean 3.97, SD 0.78) and incidental online health information acquisition (mean 4.27, SD 0.78) were high among participants. Education was a key factor related to eHealth literacy (P<.001) and shared decision-making (P<.001). Model testing indicated that active online health information seeking was related to eHealth literacy (β=.192, 95% CI .067-.320) and shared decision-making (β=.234, 95% CI .123-.346). Incidental online health information acquisition was related to eHealth literacy (β=.335, 95% CI .205-.461). eHealth literacy was related to shared decision-making (β=.441, 95% CI .334-.536). Therefore, eHealth literacy partially mediated the relationship between active online health information seeking and shared decision-making, while it fully mediated the relationship between incidental online health information acquisition and shared decision-making. Conclusions: This study contributes to the ongoing development of health communication strategies and the modification of health information training programs for patients with diabetes. The need for the information industry to deliver accurate and easy-to-understand health information to the public to support their decision-making process and encourage positive health behaviors is urgent.