Acceptance of Mhealth by Patients with Cardiovascular Diseases: the Structural Model of Health Applications Use

Abstract

Many researchers have noted the problem of adherence to drug treatment in patients with cardiovascular diseases (CVD). Mobile health (mHealth) technologies can have a significant positive impact on changing patient behavior, preventing and preventing exacerbations (recurrences) of cardiovascular diseases (CVD). To put this approach into practice, first of all, it is necessary to find out the possibilities of using mHealth for patients with CVD.Aim. To study the acceptance of medical applications by patients with CVD, and also to assess patients’ attitudes towards personal responsibility for maintaining their health in the context of using mHealth.Materials and Methods. Partial least squares structural equation modeling in the Smart-PLS environment was used to implement the UTAUT model (the unified theory of acceptance and use of technology), which included 10 constructs: Use of Applications, Intention to Use, Performance Expectancy, Social Influence, Facilitating Conditions, Attitude towards the use of Applications, Anxiety, Patient’s Role, Role of Prevention and Value of Information. The study included 437 patients with CVD who had experience using medical applications: female (253) and males (184), average age 47.95±5.22 years.Results. Constructs Performance Expectancy, Social Influence, Facilitating Conditions, and Value of Information had a direct positive effect on construct Intention to use of health Applications and explained 59,3 % of the variance this construct. The positive influence of the construct Intention to use of Applications and Attitude towards the use of Applications explained 61,2 % of the variance in the construct Use of Applications. The construct Anxiety indirectly, through Attitude towards the use of Applications, had a negative impact on the construct Use of Applications. 41,4 % of the variance of construct the Value of Information, that is, an understanding of the need for medical literacy, was determined by the Social Influence construct, as well as an understanding of the role of personal responsibility for health and CVD prevention.Conclusion. Patients with CVD understand the importance of personal participation in maintaining their health and are ready to use mHealth to prevent the disease and develop behavior aimed at reducing modifiable risk factors for CVD. One of the barriers to mHealth adoption may be patients’ fear of using medical applications on their own. Acceptance of mHealth technologies by patients with CVD to improve the effectiveness of treatment will be possible if there are appropriate technical conditions and social support that creates a trusting, professional, understandable and attractive image of mHealth.