This is a relatively new cross-sectional survey on the willingness of patients with hypertension to use digital health tools, which covered 1089 people with hypertension from different economic backgrounds, revealing a certain representativeness. Our survey found that 42.7% of hypertensive patients were willing to use digital health tools, and WDH was associated with higher education, good medicine adherence and blood pressure self-monitoring. Also, the results showed that most WDH patients wanted to receive scientific blood pressure monitoring, self-administration of medical adherence and common knowledge about hypertension.
We searched a large number of articles about social media for health care, which show the organic combination of social media and medical health. A systematic review reviewed 45 social media use improvements in chronic disease management, showing that social media, especially Facebook and blogs, provides social, spiritual, and empirical support for chronic diseases. These platforms are thus highly likely to improve patient health [15]. Research by Julie Redfern of the George Institute of Global Health in Australia found that social media (Tweets) can disseminate cardiovascular health information and education quickly, efficiently and globally, and discovered that social media has great potential to promote cardiovascular disease education, cognition and comprehensive management [16]. Facebook, as a social media platform, was also found to have a good auxiliary function for clinical treatment of cardiovascular disease [17, 18]. Social media were widely used in chronic diseases and clinical research, but there are few studies on self-management of patients with hypertension [19, 20]. Secondly, the social media platforms which are currently being applied and studied are mainly based on popular software (such as Facebook, Tweets, SMS, etc.) in western countries. To the best of our knowledge, this is the first study to explore the willingness of using local social media as a health tool in China. We can assume that WeChat will provide an advanced and intelligent way for self-management of hypertension patients in the community.
In a recent longitudinal survey, Levine et al. [21] found that older people with an average age of 75 used digital health at a lower rate than their younger counterparts, but this rate increased modestly from 2011 to 2014, highlighting the rising importance of mobile technology in people’s lives. A population-based survey of the use of a national smartphone and health apps among Germans in 2017 also identified age as a correlate for mobile health applications use: younger people were more engaged [22], and our study confirmed this for hypertensive study population as well. In addition, our results contribute to previous findings on literacy-related disparities in access to mobile technologies by revealing an association between WDH and education level [23]. Therefore, when age and literacy levels are correlated with WDH, programmers should consider the needs of older and less educated people when developing applications. Numerous efforts should be made in the future to break the rigid relationship between ageing and the digital gap to make digital technology more acceptable and easier to use.
We contributed to the preliminary evidence of the correlation of WDH with blood pressure self-management and medical adherence. Patients with poor blood pressure management and medical adherence are relatively reluctant to use digital health tools, which may be the result of a combination of factors such as age, smartphone maturity, personal income, tool trust, and so on. The relationship between blood pressure management and WDH may be explained by socioeconomic variables. Indeed, we found that possession of university degrees and employment were related to the use of WeChat and mobile health tools, and further research on this correlation is needed. More studies are needed on the features of effective digital health tool programs. Social media and health application effectiveness information based on evidences from rigorous research designs should be provided to users. Given the sheer number of applications available, the market transparency will be increased. Not only government guidelines and regulations, but also WHO recommendations could help people choose effective and appropriate applications [24]. The first attempt in this regard was directed at the MEDDEV guidelines 2.1/6 for the European market and the US Food and Drug Administration (FDA) guidelines for the US market [25, 26]. While these are not legally binding, they provide a direction for developers and consumers of mobile health applications. Furthermore, as the features develop, whether social media can be regarded as a newly integrated digital health tool and replace the function-pure applications, needs more trials to prove conclusively.
We found differences in age and literacy rates in the use of mobile technology. Therefore, application developers and researchers should consider the needs of older people and those with lower education levels, for example, to provide customized features that are tested in intervention studies [16, 24]. Simultaneously, advocacy activities should be carried out to train older people to use mobile technology, improve the health literacy of the population, and reduce the inequalities resulting from technological advances.
Limitation
Due to the cross-sectional character of the survey, changes could not be checked, including associations of digital health tools and their characteristics with actual blood pressure and behavior management. The patient’s economic situation has not yet been included in the questionnaire, making the association of income with blood pressure management and digital health tools impossible to determine at this moment. Previous studies have found that the use of apps is associated with higher incomes [27]. Another aspect is that the characteristic of the questionnaire limited the conclusions that could be drawn from the results. For example, BMI was calculated based on self-reported weight and height which is a possible source of bias. The study enrolled patients in hospitals and communities. When there is a significant difference in admission rate between hospitals communities, admission rate bias is unavoidable.
Furthermore, a large number of analyses were conducted which could have increased the probability of type I errors (ie, stating an effect when none was present). However, our research is exploratory. Nonetheless, in addition to the uncorrected results, we decided to report the multiplicity corrected results following a recommendation by Streiner [28], who discussed arguments for and against a correction of multiplicity. Namely, our ambition involves providing a large informational basis that can be further examined in future research.
