Twitter and health

Surprisingly little research by sociologists or media studies researchers has investigated how Twitter is used to discuss health and medical issues. Yet there are many interesting issues and topics to explore.

The Healthcare Hashtag Project operated by Symplur, a healthcare social media analytics company, provides a publicly available online resource that demonstrates the diversity of health and medical topics that are discussed on Twitter. When I checked the website in early May 2016, the Project had identified close to 13,000 healthcare topics, over 10,000 hashtags related to healthcare and almost 4,000 contributors to these discussions on Twitter. The diseases that were receiving attention on Twitter on that day included breast cancer, migraine, brain tumours, lymphoma, heart disease, diabetes, lung cancer, attention deficit disorder and leukaemia (these were the top ten trending diseases in order).

The site also shows the ‘influencers’ in the Twitter discussions it documents as well as the latest tweets related to the hashtags it collects. This information demonstrates the sheer diversity of actors who engage in discussions about medical conditions and healthcare on Twitter. The top ten (by mentions) ‘influencers’ for the hashtag #BCSM (denoting ‘breast cancer social media’) were a clinical professor in surgery, four individual breast cancer survivors, a medical school and a research institute, two patient coalitions (one for men with breast cancer and one for young women with breast cancer) and the Journal of the American Medical Association.

The story is quite different if the hashtag #digitalhealth is examined. Another market research company has analysed over 200,000 tweets and almost 30,000 engaged users to identify the top influencers and brands in Twitter discussions using #digitalhealth. The company looked at tweets using this hashtag over a period of four months spanning January to April 2016 and produced a list of the top 100 influencers (based on PageRank analytics that takes into account the number and quality of textual references).

The first four influencers listed (who gained much higher influence scores than any of the 96 others on the list), included Hungarian doctor, genomic scientist, digital health consultant and self-described ‘medical futurist’ Bertalan Mesko, followed by American John Nosta, another digital health consultant who runs his own think tank and is a member of the Google Health Advisory Board. A British health technologist, Alex Butler is next and fourth is American Paul Sonnier, another digital health consultant. These influencers are followed by more representatives of private digital health consulting or technology companies, some tech journalists and a representative from massive American pharmaceutical chain Walgreens. Academics are not well represented in the top 20: only three appear, beginning from number 13 on the list. Practising doctors and individual patients, or organisations for doctors or patients, are scarce.

The most common topics discussed by the top influencers were data (by a long way, accounting for a quarter of the tweets), the Internet of Things and wearable tech. The topics of apps, cancer, artificial intelligence, cybersecurity and telemedicine were the next-most discussed (however, they all received less than 10 per cent of discussion across the tweets).

It is evident from this report that digital health discussions on Twitter (at least those that use #digitalhealth to signify their content) are dominated by commercial and entrepreneurial interests rather than by the experiences of doctors or patients. With the exception of Susannah Fox from the US Department of Health and Human Services, spokespeople from government agencies appear to have little influence in these discussions. This is borne out by the list of top-most influential brands, which are again dominated by commercial enterprises (although the NHS England is included towards the bottom of the top 25).

These data raise some interesting questions for a digital health sociologist. How do voices other than commercial enterprises get heard on Twitter? What makes some conditions or diseases more talked about on Twitter than others? For example, why is breast cancer so prominent — is it because there are far more patient advocates and organisations for patients devoting attention to discussing this , or is it because it is a common form of cancer, or are other factors involved? Why do some practising doctors and medical specialists decide to get involved in Twitter discussions on a particular condition or a digital health technology? How do all the different actors engage with each other –- who pays attention to whom? What kinds of networks are formed between actors from the different groups who are advocates or healthcare providers or developers?

Self-tracking citizenship

An excerpt from Chapter 5 of my new book  The Quantified Self: A Sociology of Self-Tracking.

Nafus and Sherman (2014: 1785) contend that self-tracking is an alternative data practice that is a form of soft resistance to algorithmic authority and to the harvesting of individuals’ personal data. They argue that self-tracking is nothing less than ‘a profoundly different way of knowing what data is, why it is important, who gets to interpret it [sic], and to what ends’. However the issue of gaining access to one’s data remains crucial to questions of data control and use. While a small minority of technically proficient self-trackers are able to devise their own digital technologies for self-tracking and thus exert full control over their personal information, the vast majority must rely on the commercialised products that are available and therefore lose control over where their data are stored and who is able to gain access.

For people who have chronic health conditions, for example, access to their data can be a crucial issue. A debate is continuing over the data that are collected by continuous blood glucose monitoring and whether the patients should have ready access to these data or only their doctors. As one person with diabetes contends on his blog, older self-care blood glucose-monitoring devices produce data that patients can view and act on immediately. Why should the information generated by the newer digitised continuous blood glucose monitors be available only to doctors, who review it some time later, when patients could benefit from seeing their data in real time? A similar issue arises in relation to the information that is collected on heart patients’ defibrillator implants. The data that are conveyed wirelessly to patients’ healthcare professionals cannot be easily accessed by the patients themselves. In jurisdictions such as the United States, the device developers are legally prohibited from allowing patients access to their data (see here).

There is recent evidence that the Quantified Self movement is becoming more interested in facilitating access to personal data for purposes beyond those of individuals. In a post on the Quantified Self website entitled ‘Access matters’, Gary Wolf comments that self-trackers have no legal access to their own data, which they may have collected for years. Nor is there an informal ethical consensus that supports developers in opening their archives to the people who have contributed their information. Wolf and others associated with the Quantified Self movement have begun to campaign for self-trackers to achieve greater access to the personal data that are presently sequestered in the cloud computing archives of developers. They argue for an approach that leads to the aggregation of self-tracked data in ways that will benefit other people than individual self-trackers themselves.

Some Quantified Self movement-affiliated groups have begun to experiment with ways in which self-tracking can be used for community participation and development. Members of the St Louis Quantified Self meeting group, for example, have worked on developing a context-specific app that allows people to input their moods and identify how certain spatial locations within a community affect emotional responses. They are also developing a Personal Environment Tracker that would allow St Louis citizens to monitor their own environmental impact and that of the community in which they live.

The Quantified Self Lab, the technical arm of the Quantified Self mvement, has also announced that it is becoming involved with citizen science initiatives in collaboration with the US Environmental Protection Agency (see here). It has now joined with the Robert Wood Johnson Foundation, an American philanthropic organisation focused on health issues, to work on improving people’s access to their personal data. Both groups are also collaborating with other partners on the Open Humans Network, which is aimed at facilitating the sharing of people’s details about their health and medical statuses as part of a participatory research initiative. Participants who join in this initiative are asked to upload the data that they have collected on themselves through self-tracking devices as well as any other digitised information about their bodies that they are able to offer for use in research studies. Part of the model that the Open Humans Network has adopted is that researchers agree to return to the participants themselves any new data that emerge from projects that use these participants’ information, and participants decide which of their data they allow others to access.

Beyond the Quantified Self movement, a number of initiatives have developed that incorporate the aggregation of self-tracked data with those of others, as part of projects designed to benefit both the individuals who have collected the data and the broader community. Citizen science, environmental activism, healthy cities and community development projects are examples of these types of communal self-tracking endeavours. These initiatives, sometimes referred to as ‘citizen sensing’ (Gabrys, 2014), are a form of crowdsourcing. They may involve the use of data that individuals collect on their local environs, such as air quality, traffic levels or crime rates, as well as on their own health indicators – or a combination of both. These data may be used in various ways. Sometimes they are simply part of collective projects undertaken at the behest of local agencies, but they may also be used in political efforts to challenge governmental policy and agitate for improved services or planning. The impetus may come from grassroots organisations or from governmental organisations; the latter construe it as a top-down initiative or as an encouragement towards community development.

Self-tracked data here become represented as a tool for promoting personal health and wellbeing at the same time as community and environmental development and sustainability. As these initiatives suggest, part of the ethical practice of self-tracking, at least for some practitioners, may involve the notion of contributing to a wider good as well as collecting data for one’s own purposes. Access to large data sets – rendering these data sets more ‘open’ and accessible to members of the public – becomes a mode of citizenship that is distributed between self, community and physical environment. This idea extends the entrepreneurial and responsible citizen ideal by incorporating expectations that people should not only collect their own, personal information for purposes of self-optimisation but should also contribute it to tailored, aggregated big data that will benefit many others, in a form of personal data philanthropy: self-tracking citizenship, in other words.

References

Gabrys, J. (2014) Programming environments: environmentality and citizen sensing in the smart city. Environment and Planning D: Society and Space, 32 (1), 30-48.

Nafus, D. and Sherman, J. (2014) This one does not go up to 11: the Quantified Self movement as an alternative big data practice. International Journal of Communication, 8 1785-1794.

 

 

 

 

 

Self-tracking practices as knowledge technologies

An edited excerpt from the concluding chapter of my book The Quantified Self: A Sociology of Self-Tracking.

As I have remarked in this book’s chapters, via the mainstream self-tracking devices and software that are available, certain aspects of selfhood and embodiment are selected for monitoring while a plethora of others are inevitably left out, ignored, or not even considered in the first place. Those aspects that are selected become more visible, while others are obscured or neglected through this process. The technologies themselves, including the mobile, wearable and ‘anti-wearable’ sensor-embedded objects and the software that animate them, tend to be the product of a narrow demographic of designers: white, well-paid, heterosexual men living in the Global North. In consequence, the tacit assumptions and norms that underpin the design and affordances of self-tracking technologies are shaped by these people’s decisions, preferences and values. Thus, for example, devices such as Apple Watch initially failed to include a menstrual cycle tracker as part of its built-in features (Eveleth, 2014); sexuality self-tracking apps focus on male sexual performance and competitive displays of prowess (Lupton, 2015); apps that use westernised concepts and images of health and the human body are inappropriate for Aboriginal people living in remote areas of Australia (Christie and Verran, 2014). How people from outside this demographic might engage or not with these technologies and how technologies might be better designed to acknowledge the diversity of socioeconomic advantage, cultures and sexual identities are subjects rarely pondered upon in the world of technology design …

At the same time as self-tracking practices are reductive and selective, they are also productive. They bring into being new knowledges, assemblages, subjectivities and forms of embodiment and social relations. In Chapter 2 I referred to the four types of technology identified by Foucault, which work together to produce knowledges on humans. Acts of reflexive self-monitoring involve all four of these knowledge technologies. Via prosumption, self-trackers generate data on themselves (technologies of production); they manipulate and communicate the symbols, images, discourses and ideas related to their own data and the devices that generate these data (technologies of sign systems); they are involved in strategies that are designed to assist them in participating in certain forms of conduct for specific ends (technologies of power); and all of these practices are overtly and deliberately directed at performing, presenting and improving the self (technologies of the self).

What is particularly intriguing about this expertise is that it both operates at the level of the ‘nonexpert’ (the self-tracker), where it is configured, and is inextricably interbound into the digital data economy and the forms of government regulation of the body politic. The authority of the knowledgeable expert on human life is dispersed among members of the lay public to a greater extent than ever before. However, the shared nature of this authority and expertise also undermines the power that self-trackers possess over their own information. Reflexive self-monitors are able to generate their own truth claims about trackers’ own bodies/selves, but these trackers are increasingly unable to control how these truth claims are used by other actors or what the potential ramifications for their own life chances and opportunities are once these data come under the control of others.

 

Pregnancy apps and gender stereotypes

Pregnant women and those experiencing the early years of motherhood have used online forums for many years to share experiences and seek information. Now there are hundreds of apps that have been designed for similar purposes. As part of an integrated research program looking at apps and other digital media for pregnancy and parenting, I have been researching these apps using several approaches. In a survey of 410 Australian women who were pregnant or who had given birth in the past three years, I found that almost three-quarters had used at least one pregnancy app, while half of the women who already had children reported using a parenting app (see here for an open access report on this survey and here for a journal article about it).

With Gareth Thomas from Cardiff University, I have also conducted a critical analysis of the content of pregnancy apps themselves. This involved analysing all pregnancy-related apps offered in the two major app stores, the Apple App Store and Google Play. We examined the app descriptions, looking for how the developers marketed their apps and what they offered. See here and here for articles that have been published from this analysis. Update: we have now published an article focusing on apps for expectant fathers here.

This study found that the apps designed for pregnant women represent pregnancy as a state in which women must maintain a high degree of vigilance over their own bodies and that of their foetuses. Many apps promoted this level of self-monitoring, often seeking to render the practices aesthetically-pleasing by using beautiful images of foetuses or allowing women to take ‘belfies’ (belly selfies) and share these on social media.

Among the most surprising of our findings were the large numbers of pregnancy-related games designed for entertainment. These include pregnancy pranks such as fake foetal ultrasounds to fool people into thinking someone is pregnant. We also found many games for little girls that are on the market. The encourage girls to give pregnant women ‘make-overs’ so that they will ‘feel more confident’ and look beautiful, ready for the birth. Some even let players perform a caesarean section on the characters, who remain glamorous and serene even on the operating table. The types of messages about pregnancy and childbirth that are promoted to their young female users are troubling.

Other apps are directed at men who are becoming fathers, although there were far fewer of these apps compared with those for pregnant women. We noticed from our analysis of these apps that even though quite a few of them are marketed as being written ‘by men, for men’, they typically portray the father as a bumbling fool, who requires simplistic or jokey information to keep him interested in the impending birth of his child. Men are advised not to stare at attractive women and to constantly reassure their partners that they find them attractive. Foetuses are compared to beer bottles so that men can learn about foetal development in supposedly unthreatening ways.

Our overall finding, therefore, is the highly stereotypical gendered representations of pregnant women and expectant fathers in these apps. Women are encouraged to use apps to achieve the ideal of the self-monitoring ‘good mother’, closely tracking their bodies because they have their foetus’s best interests at heart in every action they take. They are expected to celebrate their pregnancy and changing bodies – there is little room for ambivalence. Their male partners, on the other hand, are assumed to be uninterested and to require nudging to act in a supportive role to their partners.  And little girls are encouraged to accept and perpetuate the ‘yummy mummy’ stereotype in playing the pregnancy games that are marketed to them, and to view caesarean sections as a quick and easy way to give birth.

Living Digital Data research program

People’s encounters and entanglements with the personal digital data that they generate is a new and compelling area of research interest in this age of the ascendancy of digital data. Members of the public are now called upon to engage with a variety of forms of information about themselves and to confront the complexities of how these details are used by others. Personal digital data assemblages are configured as human bodies, digital devices, code, data, time and space come together.

 

Personal digital data assemblages smartart

Personal digital data assemblages

 

Over the past few years I have been researching the social aspects of personal digital data: how people understand and conceptualise these data, how they use their data, what people know about where their personal data go and how their data are used by second and third parties.I have analysed the metaphors that are used to describe digital data, the politics of digital data, the types of data that are collected by apps and self-tracking devices, how people use these software and devices and how personal digital data are materialised, or rendered into visualisations or three-dimensional objects. I have sought to theorise the ontology of personal digital data, drawing particularly sociomaterialism, feminist technoscience, cultural geography and sensory studies. (See My Recent Publications for further details.)

I am bringing these research questions together under a program that I have named ‘Living Digital Data’. This title builds on my conceptualisation of digital data as ‘lively’ in a number of ways.

 

 

Lively data smartart

Lively Data

 

 

The first element of the vitality of digital data relates to the ways in which they are generated and what happens thereafter. The personal digital information that is constantly generated contributes to data assemblages that are heterogeneous and dynamic, their character changing as more data points are added and others removed. Digital data may be described as having their own social lives as they circulate in the digital data economy and are purposed and repurposed. Second, digital data constitute forms of knowledge about human (and nonhuman) life itself and hence possess another type of vitality. Third, personal digital data have impacts on people’s lives, shaping the decisions and actions that people make and those that other people make about them.  The profiles constructed from these data can influence decisions about the opportunities people have to travel, access employment, credit or insurance, the people that they meet on online dating sites, the knowledges that they hold about themselves and their bodies and those of intimate others. Finally, personal digital data are forms of livelihoods, contributing to the commodification and capitalisation of information. Indeed, they may be described as a form of biocapital, which possesses many forms of value beyond the personal: for research, commercial, security, managerial and governmental agencies.

This approach recognises the entanglements of personal digital data assemblages with human action. Not only are personal digital data assemblages partly comprised of information about human action, but their materialisations are also the products of human action, and these materialisations can influence future human action.

Rather than refer to data literacy or data management skills, I take up the term ‘data sense’ to encapsulate a broader meaning of ‘data sense’ that includes human senses (sight, sound, touch, smell and taste) and how these are part of people’s responses to data and also acknowledges the role played by digital sensors in the act of ‘sense-making’; or coming to terms with digital data.

 

Data sense smartart

Data Sense

 

My 2015 publications

Here are my publications that came out in 2015.

Book

  • Lupton, D. (2015) Digital Sociology. London: Routledge.

Book chapters

  • Lupton, D. (2015) Digital sociology. In Germov, J. and Poole, M. (eds), Public Sociology: An Introduction to Australian Society, 3rd St Leonards: Allen & Unwin.
  • Lupton, D. (2015) Donna Haraway: the digital cyborg assemblage and the new digital health technologies. In Collyer, F. (ed), The Palgrave Handbook of Social Theory in Health, Illness and Medicine. Houndmills: Palgrave Macmillan.

Peer-reviewed journal articles

Report

  • Lupton, D. and Pedersen, S. (2015) ‘What is Happening with Your Body and Your Baby’: Australian Women’s Use of Pregnancy and Parenting Apps. Available here.

Public understanding of personal digital data

One of the research projects I am conducting, with Mike Michael from the University of Sydney, is investigating the public understanding of digital data. We are experimenting with using novel methods (for sociologists at least!) in our project, which combines focus group discussions with cultural probes.

In the discussion groups, we wanted to go beyond the usual approach of simply asking questions of people. We wanted to invite people to think and work together playfully and creatively. We therefore decided to employ cultural probes to stimulate thought, discussion and debate, involving asking people to work together as a group or in pairs to generate material artefacts. Cultural probes are objects or tasks that are designed to be playful and provocative so as to encourage people to think in new ways about technologies. They are particularly valued for their ability to address intimate or controversial issues, to act as ‘irritants’ to engage people’s responses.

We asked people in our focus groups (held in Sydney) to engage in three collaborative tasks that we devised for them.

  1. The Daily Big Data Task. This task asked participants to work together as a group to draw a timeline on a huge piece of paper of a typical person’s day and adding the ways in which data (digital or otherwise) may be collected on that person.
  2. The Digital Profile Card Game. This task involved small groups to use cards with socio-demographic details on them to construct a profile of an individual, speculate about their characteristics and discuss how this information could be used.
  3. The Personal Data Machine. In this activity, participants were asked to work in pairs to design two data-gathering devices: one that they would find useful to use to collect any kind of data about themselves, and one for collecting data on another person. They were asked to write notes or make drawings describing their devices.

After each task the group came together to talk about the artefacts they had created or handled and what their implications were.

Earlier this year, we published a short piece in Discover Society that outlined some of our initial findings. A new article in the journal Public Understanding of Science, entitled ‘Toward a manifesto for the public understanding of big data’ has just been published. We are currently working on another article that presents our empirical work in greater detail.

In the ‘manifesto’ article, we pointed out that there are many intersections between research on the public understanding of digital data with the literatures on the public understanding of science and public engagement with science and technology. These are bodies of work that have been devoted to making sense of the intersections between how citizens engage with scientific knowledge, including not only consuming but producing this knowledge. Indeed, it may be contended that members of the public have been ‘prosumers’ of scientific knowledge long before the emergence of digital data (that is, both acting to consume and produce scientific information), particularly when they are engaging in citizen activism or citizen science initiatives.

There are many examples of citizens participating in activities that either contribute to or challenge accepted scientific beliefs. This critical approach has led to the development of a public engagement with science and technology model, in which ‘the public’ and ‘scientific expertise’ are not contrasted with each other. Rather, it is acknowledged that each draws their definitions from the other, contributing to hybrid assemblages of knowledges. The public are both the subjects and objects of scientific research and data, just as they are of digital data.

Our research project findings suggest that we may be seeing a transformation in attitudes in response to the controversies and scandals in relation to the use of people’s personal data that have received a high level of public attention over the past two and a half years, potentially reshaping concepts of privacy. What emerged from our focus groups is a somewhat diffuse but quite extensive understanding on the part of the participants of the ways in which data may be gathered about them and the uses to which these data may be put.

It was evident that although many participants were aware of these issues, they were rather uncertain about the specific details of how their personal data became part of big data sets and for what this information was used. While the term ‘scary’ was employed by several people when describing the extent of data collection in which they are implicated and the knowledge that other people may have about them from their online interactions and transactions, they struggled to articulate more specifically what the implications of such collection were.

On the other hand, when the participants were designing their ‘Personal Data Machines’, it was evident from their creations that they appreciated and enjoyed the opportunity not only to collect detailed information about themselves, but also on other people: partners, children and other family members and co-workers. Some imagined devices included those that monitored other people’s dreams or snooped on partners’ phone call metadata to check if they were unfaithful. Other people described a lie-detecting device, one that could track commercial competitors’ activities, another that revealed the salary of their workmates (so that the user could know if they were being fairly remunerated) and a dating device that could scan a prospective partner’s hand or face and reveal their financial assets and criminal record details.

In some cases, it seems, too much information is never enough. The seductions of data can be very appealing, not just for commercial enterprises or national security agencies.

 

Self-tracking, social fitness and biovalue

I have just completed a chapter for the forthcoming volume The Sage Handbook of Social Media. The chapter addresses the intersections of self-tracking for health and medical purposes with social media platforms and rationales. As I argue in the chapter, the expanded array of digitised devices that are available for self-tracking and the capacity of many of these technologies to interact with social media platforms have encouraged self-trackers to share the details that they collect about themselves with others. I begin with a description of self-tracking and the sociomaterial theoretical foundations on which the chapter rests. This is followed with an overview of the technologies that are available for health and medical self-tracking and for self-trackers to share their data. The discussion section of the chapter presents an analysis of the new forms of value that personal health and medical data have attracted in the digital data economy, and the moral and political repercussions of encouraging people to participate as socially fit citizens. The chapter ends with outlining key questions for further research.

The full pre-print of the chapter is available here.

Who owns your personal health and medical data?

09/01/15 -- A moment during day 1 of the 2-day international Healthcare and Social Media Summit in Brisbane, Australia on September 1, 2015. Mayo Clinic partnered with the Australian Private Hospitals Association (APHA), a Mayo Clinic Social Media Health Network member to bring this first of it's kind summit to Queensland's Brisbane Convention & Exhibition Centre. (Photo by Jason Pratt / Mayo Clinic)

Presenting my talk at the Mayo Clinic Social Media and Healthcare Summit (Photo by Jason Pratt / Mayo Clinic)

Tomorrow I am speaking on a panel at the Mayo Clinic Healthcare and Social Media Summit on the topic of ‘Who owns your big data?’. I am the only academic among the panel members, who comprise of a former president of the Australian Medical Association, the CEO of the Consumers Health Forum, the Executive Director of a private hospital organisation and the Chief Executive of the Medical Technology Association of Australia. The Summit itself is directed at healthcare providers, seeking to demonstrate how they may use social media to publicise their organisations and promote health among their clients.

As a sociologist, my perspective on the use of social media in healthcare is inevitably directed at troubling the taken-for-granted assumptions that underpin the jargon of ‘disruption’, ‘catalysing’, ‘leveraging’ and ‘acceleration’ that tend to recur in digital health discourses and practices. When I discuss the big data phenomenon, I evoke the ‘13 Ps of big data‘ which recognise their social and cultural assumptions and uses.

When I speak at the Summit, I will note that the first issue to consider is for whom and by whom personal health and medical data are collected. Who decides whether personal digital data should be generated and collected? Who has control over these decisions? What are the power relations and differentials that are involved? This often very intimate information is generated in many different ways – via routine online transactions (e.g. Googling medical symptoms, purchasing products on websites) or more deliberately as part of people’s contributions to social media platforms (such as PatientsLikeMe or Facebook patient support pages) or as part of self-tracking or patient self-care endeavours or workplace wellness programs. The extent to which the generation of such information is voluntary, pushed, coerced or exploited, or indeed, even covert, conducted without the individual’s knowledge or consent, varies in each case. Many self-trackers collect biometric data on themselves for their private purposes. In contrast, patients who are sent home with self-care regimes may do so reluctantly. In some situations, very little choice is offered people: such as school students who are told to wearing self-tracking devices during physical education lessons or employees who work in a culture in which monitoring their health and fitness is expected of them or who may be confronted with financial penalties if they refuse.

Then we need to think about what happens to personal digital data once they are generated. Jotting down details of one’s health in a paper journal or sharing information with a doctor that is maintained in a folder in a filing cabinet in the doctor’s surgery can be kept private and secure. In this era of using digital tools to generate and archive such information, this privacy and security can no longer be guaranteed. Once any kind of personal data are collected and transmitted to the computing cloud, the person who generated the data loses control of it. These details become big data, part of the digital data economy and available to any number of second or third parties for repurposing: data mining companies, marketers, health insurance, healthcare and medical device companies, hackers, researchers, the internet empires themselves and even national security agencies, as Edward Snowden’s revelations demonstrated.

Even the large institutions that are trusted by patients for offering reliable and credible health and medical information online (such as the Mayo Clinic itself, which ranks among the top most popular health websites with 30 million unique estimated monthly visitors) may inadvertently supply personal details of those who use their websites to third parties. One recent study found that nine out of ten visits to health or medical websites result in data being leaked to third parties, including companies such as Google and Facebook, online advertisers and data brokers because the websites use third party analytic tools that automatically send information to the developers about what pages people are visiting. This information can then be used to construct risk profiles on users that may shut them out of insurance, credit or job opportunities. Data security breaches are common in healthcare organisations, and cyber criminals are very interested in stealing personal medical details from such organisations’ archives. This information is valuable as it can be sold for profit or used to create fake IDs to purchase medical equipment or drugs or fraudulent health insurance claims.

In short, the answer to the question ‘Who owns your personal health and medical data?’ is generally no longer individuals themselves.

My research and that of others who are investigating people’s responses to big data and the scandals that have erupted around data security and privacy are finding that concepts of privacy and notions of data ownership are beginning to change in response. People are becoming aware of how their personal data may be accessed, legally or illegally, by a plethora of actors and agencies and exploited for commercial profit. Major digital entrepreneurs, such as Apple CEO Tim Cook, are in turn responding to the public’s concern about the privacy and security of their personal information. Healthcare organisations and medical providers need to recognise these concerns and manage their data collection initiatives ethically, openly and responsibly.

Digital Sociology now out

Digital Sociology has now been published (click here for the Amazon link and here for the publisher’s link).

 

The publisher’s blurb is below:

Digital Sociology

We now live in a digital society. New digital technologies have had a profound influence on everyday life, social relations, government, commerce, the economy and the production and dissemination of knowledge. People’s movements in space, their purchasing habits and their online communication with others are now monitored in detail by digital technologies. We are increasingly becoming digital data subjects, whether we like it or not, and whether we choose this or not.

The sub-discipline of digital sociology provides a means by which the impact, development and use of these technologies and their incorporation into social worlds, social institutions and concepts of selfhood and embodiment may be investigated, analysed and understood. This book introduces a range of interesting social, cultural and political dimensions of digital society and discusses some of the important debates occurring in research and scholarship on these aspects. It covers the new knowledge economy and big data, reconceptualising research in the digital era, the digitisation of higher education, the diversity of digital use, digital politics and citizen digital engagement, the politics of surveillance, privacy issues, the contribution of digital devices to embodiment and concepts of selfhood and many other topics.

Digital Sociology is essential reading not only for students and academics in sociology, anthropology, media and communication, digital cultures, digital humanities, internet studies, science and technology studies, cultural geography and social computing, but for other readers interested in the social impact of digital technologies.