Factors influencing mobile health utilisation among patients with diabetes in Sichuan, China: a cross-sectional study based on Andersen's behavioural model

Abstract

Background: The development of mobile health (mHealth) in China has tremendous potential, especially for diabetes, which is one of the major chronic diseases affecting hundreds of millions of people. However, research on the current use of mHealth by patients with diabetes and the factors influencing their decision-making is insufficient. Most existing studies have approached the subject from a technological perspective and often overlooked the identity of patients as users of mHealth services. Based on the Andersen behavioural model, this study aimed to investigate the factors affecting patients' adoption of mHealth, with a special emphasis on individual patient characteristics, and provided recommendations for the promotion of mHealth and the management of diabetes.

Method: This was a cross-sectional study. A convenience sample survey was conducted in one tertiary hospital and two community health service centres, and an anonymous self-administered questionnaire survey was conducted among patients with diabetes. Based on Andersen's behavioural model, the questionnaire divided the influencing factors into predisposing factors, enabling factors and need factors. Multivariate logistic regression analysis was used to explore the factors influencing the utilisation of mHealth.

Results: A total of 533 questionnaires were valid. In this study, 36.8% of patients with diabetes used mHealth services. Among the predisposing factors, having better education and mHealth knowledge were found to be facilitators of mHealth utilisation, and employment status was a factor associated with mHealth utilisation. Among the enabling factors, patients with internet access and living in urban areas were more likely to have access to mHealth, and higher health literacy positively influenced mHealth utilisation. Among the need factors, self-assessed health status was linked to mHealth utilisation, and diabetes duration had a negative impact on mobile health utilisation.

Conclusions: The rate of mobile health utilisation remained low. In the future, improvements can be made in multiple aspects, such as policy, promotion, infrastructure and health education, to advance the development of mobile health and the management and control of diabetes.

Keywords: Behavior; Chronic Disease; Health informatics.

Figure 1. A diagram of the theoretical framework of Andersen’s behavioural model. CCI, Charlson Comorbidity Index; DM, diabetes mellitus.

Figure 2. Flowchart of participant enrolment.