Digital health technologies configure a certain type of practising medicine and public health, a certain type of patient or lay person and a specific perspective on the human body. The techno-utopian approach to using digital health technologies tends to assume that these tacit norms and assumptions are shared and accepted by all the actors involved, and that they are acting on a universal human body. Yet a cursory examination of surveys of digital health technology use demonstrates that social structural factors such as age, gender, education level, occupation and race/ethnicity, as well as people’s state of health and their geographical location play a major role in influencing how such technologies are taken up among lay people or the extent to which they are able to access the technologies.
An American study of the use of some digital health technologies using representative data collected by the National Cancer Institute in 2012, for example, found no evidence of differences by race or ethnicity, but significant differences for gender, age and socioeconomic status (Kontos et al. 2014). Female respondents were more likely to use online technologies for health-related information, as were younger people (under less than 65) and those of higher socioeconomic status. People of low socioeconomic status were less likely to go online to look for a healthcare provider, use email or the internet to connect with a doctor, track their personal health information online, using a website to track to help track diet, weight or physical activity or download health information to a mobile device. However they were more likely to use social media sites to access or share health information. Women were more likely than men to engage in all of these activities.
While there is little academic research on how different social groups use apps, market research reports have generated some insights. One report showed that women install 40 per cent more apps than men and buy 17 per cent more paid apps. Men use health and fitness apps slightly more (10 per cent) than women (Koetsier 2013). A Nielsen market report on the use of wearable devices found that while men and women used fitness activity bands in equal numbers, women were more likely to use diet and calorie counter apps (Nielsen 2014).
As these findings suggest, gender is one important characteristic that structures the use of digital health technologies. The digital technology culture is generally male-dominated: most technology designers, developers and entrepreneurs are male. As a result, a certain blindness to the needs of women can be evident. For example, when the Apple Health app was announced in 2014, destined to be included as part of a suite of apps on the Apple Watch, it did not include a function for the tracking of menstrual cycles (Eveleth 2014). Gender stereotypes are routinely reproduced in devices such as health and medical apps. As I noted in my study of sexuality and reproduction self-tracking apps, the sexuality apps tend to focus on documenting and celebrating male sexual performance, with little acknowledgement of women’s sexuality, while reproduction apps emphasise women’s over men’s fertility.
App designers and those who develop many other digital technologies for medical and health-related purposes often fail to recognise the social and cultural differences that may influence how people interact with them. Just as cultural beliefs about health and illness vary from culture to culture, so too do responses to the cultural artefacts that are digital health technologies. Aboriginal people living in a remote region of Australia, for example, have very different notions of embodiment, health and disease from those that tend to feature in the health literacy apps that have been developed for mainstream white Australian culture (Christie and Verran 2014). It is therefore not surprising that a review of the efficacy of a number of social media and apps developed for health promotion interventions targeted at Aboriginal Australians found no evidence of their effectiveness or benefit to this population (Brusse et al. 2014).
Few other analyses have sought to highlight the cultural differences in which people respond to and use digital health technologies. This kind of research is surely imperative to challenge existing assumptions about ‘the user’ of these technologies and provide greater insights into their benefits and limitations.