In the past couple of decades, health care sectors worldwide have experienced an increasing number of demands for more advanced treatment and care, earlier discovery of diseases and chronic conditions, and the treatment of a growing number of patients [1
]. At the same time, self-care
and patient empowerment
have emerged as important phenomena in the context of health and disease management and for supporting the work of health care providers. Within these two related concepts, the patients become active participants who engage in self-care
through assuming a central role in the “action-taking” in their health and health care [2
]. Coupled with the advancements in and the spread of digital technologies, digital health technologies [3
] are being designed and developed in the hope of providing better care [4
]. Mobile health technologies are argued to “translate everyday processes into information” [5
] (p. 80), including physical activity and bodily dys/functions. Because of people’s tendency to carry their mobile phones everywhere and close to their bodies [6
], mobile health applications offer new and interesting possibilities for health promotion [3
], self-diagnosing [7
], as well as promoting patient empowerment and reducing health care costs [3
]. These technologies have caught the attention of health care sector policymakers, politicians, and the media, who tend to present digital health technologies in largely uncritical ways [9
]. In Norway, this discourse portrays mobile health applications as sources of empowerment
, health management
, and a more efficient
and patient-centered health care
], without demonstrating the actual use of these technologies by patients.
In August 2016, the Norwegian Technology Council (Teknologirådet; NTC), which serves as an independent advisory board to the Norwegian government, contributed to this discourse on mobile health applications by publishing a list of the so-called “Mobile Health Solutions” [11
]. This list was part of their ongoing “Mobile Health” project. The intention was to give an overview of existing mobile health applications that can perform health measurements and self-tests, as well as to provide information on whether these solutions were approved by the American Food and Drug Administration or are provided with the CE mark, meaning that they adhere to current EU regulations. In a supplementary leaflet, the NTC discusses medical diagnostics as expensive and dependent on laboratories, hospitals, and medical offices. An alternative to these costly examinations are mobile self-tests that can be purchased without health care services functioning as an intermediary, which, according to the NTC, may relieve the health care system of expenditures and contribute to the earlier discovery of diseases. In other words, the technologies were presented in a medical as well as economic discourse.
The NTC’s list of mobile health solutions has inspired several newspaper articles in Norway and, as a result of the NTC’s status as a national advisory board, this list is used in governmental policy-making. Recent governmental proposals present the new health technologies as what Lupton [9
] refers to as “magic bullets”, by stating that “new technologies give better possibilities of mastering one’s own life and health” (translated from Norwegian, [12
]). The Norwegian media also frequently refer to mobile health applications as “solutions” [8
] and thus confirm Lupton’s [9
] observation of largely uncritical accounts by the popular media and in public health publications.
There is a growing critical discourse surrounding digital health technologies, which argues that simple accounts, such as the “Mobile Health Solutions” list presented by the NTC, strengthen the ongoing processes of increased surveillance and digitalization of health care. Furthermore, such accounts may support technological and social divides, thus promoting specific political agendas that are increasingly persuading patients into tracking and monitoring the body [13
]. According to Hofmann [4
], digital health technology alters the responsibility of humans and institutions. This shift in the locus of responsibility can be explained as part of the patient-centered health care movement and empowerment
of patients. In a more critical perspective, this shift can be understood as efforts to promote a form of citizenship in which citizen behave productively and in the interest of the state by voluntarily engaging in self-surveillance to improve their health and reduce health care expenditure [15
The differences in understanding digital health technologies, between actors such as the NTC and actors in the field of critical research, can be understood in terms of different visions of the potential of technology and, more importantly, what constitutes a disease and what is a meaningful way to track a body. The NTC’s account contains several visions: the cost vision, which presents disease as a governmental and social cost and technology can mediate a cost-reduction; the commercial vision, which sees profit opportunities for Norwegian tech companies; and the medical vision, which presents self-tracking as an opportunity for bettering research and treatment of diseases. These visions also contribute to the creation of technology needs and design requirements that further reinforce the dominant discourse on digital health technologies. The “Mobile Health Solutions” list is a product of the vision and interests of the NTC. Although the technologies on the NTC list have not been developed or designed by the NTC, the list mediates visions and epistemologies of what it means to track the body, what constitutes a disease, and how a disease is enacted.
Technology establishes how we act toward a disease by contributing to the discovery, diagnosis, and treatment of diseases [16
], but tends to “tell partial stories of much larger lives” [5
] (p. 80), meaning that the data collected by the technology might not take into the account the fluid lines dividing health and disease in a patient’s life. Feeding this information back to the users constitutes moral actions and may have implications for the proclaimed empowerment
of patients, who have an embodied and often conflicting vision
of their body and disease. In this paper, we will focus on visions of health and disease mediated by technologies and ask: how can patients negotiate the visions mediated by mobile health technologies to become more empowered knowers
of their body?
Aim of the Article
In this article, we will focus on the tension resulting from the different visions mediated, inscribed in, re-produced, and promoted by digital health technologies. We understand visions as generative, often future-oriented, constructs that inspire, shape, and mobilize a wide variety of activities, such as technology design, research, discourses, funding, policy, and perceptions. With our particular focus, we aim to contribute to the growing body of critical inquiries into digital health technologies by proposing an analytical classification system drawn from social studies and medical philosophy, which is based on three perspectives on disease, namely disease, illness, and sickness. The three perspectives represent often contested but interlinked visions and epistemologies or ways of knowing in health care policy and practice, including the issue of who can be a knower in health care. Patient empowerment and patient-centered health care envision a role for the patient as an active participant, which entails the role of a knower in his or her health and care.
Exploring the visions shaping the design, promotion, and use of mobile health applications enables us to understand how patients negotiate these visions. We do this by applying our classification system to two data sets. The first set consists of the NTC’s list of “Mobile Health Solutions”. This dataset represents the vision of the NTC as well as the visions of the design and development team of each of the technologies on the list. The second dataset consists of empirical material on the use of mobile health applications. This data is extracted from interviews with 15 young patients diagnosed with Inflammatory Bowel Disease (IBD). The patients took part in a larger project on the transition from child-centered to adult-oriented health care services. We present the two sets of data to draw attention to the disconnections between the various visions.
The remainder of this paper is structured as follows: Firstly, we will present the background concepts and literature that have informed the research approach of this article. In this section, we will focus on the concept of vision
and the three perspectives central to our analysis—disease, illness,
. In Section 3
, we will explain our research approach – the classification system, and the datasets. Our data includes testimonies on the use of mobile health applications by young patients, highlighting the ways in which patients use and appropriate various applications. We have split our analysis and discussion into two separate sections. Section 4
presents the analysis and discussion of the overall functionality of the analyzed mobile health applications based on the list by the NTC and the applications reported by the young patients. Section 5
presents an analysis and discussion based on the use and appropriation of mobile health applications by the young patients, followed by a discussion on patient empowerment
and the design of mobile health technologies. Lastly, we describe our suggestions for future work on the design of mobile health applications and present our concluding remarks in Section 6
Central to mobile health applications is the tracking of bodily functions and physical activity, commonly referred to as self-tracking or quantified self
. Self-tracking activities are linked to the empowerment of patients through the promise of offering new knowledge about the body, which might lead to new practices, bodily changes, and better health outcomes [3
]. In the context of institutionalized health care, knowledge of the body and the disease has always been fundamental to diagnosis, treatment, and care. To prescribe the appropriate treatment or care, a disease must be localized and quantified [19
]. Inherent in the individual meetings between patients and health care institutions, or the process of diagnosing taking place between a doctor or a patient, is the distinction between knowing subjects
, the medical practitioners, and objects known
, the patients [19
]. Mol [19
] (p. 27) describes this meeting as an enactment
of the medical gaze: “[w]hen doctor and patient act together in the consultation room, they jointly give shape to the reality of the patient’s hurting legs”. This enactment is by no means homogeneous, as this enactment depends on, and is entwined with, various technologies to “render the body more visible” [10
]. Due to the entwinement of medical practice with medical technology, e.g., stethoscopes or x-ray machines, medicine can be understood as technoscience
]. Medical technologies extend the practitioner’s vision
beyond the skin of the patient to quantify and to allow for the localization of pathologies. This technoscientific process, performed by the medical practitioners, is negotiated with the patients and their experiences, and results in knowledge of the patient’s body that can be treated and cared for with current medical and pharmaceutical knowledge.
Due to the diffusion of digital health technologies, the medical gaze
is now re-negotiated, explored, and shared by other actors, and makes aspects of the patients’ lives that were, until now, out of reach of the health care institutions, accessible to them [18
]. As a result, both health care professionals and patients participate in producing descriptions of the body that can be redistributed, technologized, and capitalized [9
]. The data doubles,
the digital data collected about the individual and portraying her in a certain way [5
], unfold in the relationship between users and their technologies and add value to aspects of the body and to activities that before were deemed without value [14
Much like the medical instruments, self-tracking and self-measurement technologies are perceived as offering insights that are objective and factual, rather than embodied and situated [13
]. Perhaps this reflects the dominant understanding of science among the general population in Western societies, which is based on “disembodied scientific objectivity”, which Donna Haraway describes as “visions from nowhere” [21
]. Haraway [24
] argues that a vision is always from somewhere; it is situated
in epistemologies, knowledge, policies, practices, and discourses. A vision also requires instruments of vision [21
]. Thus, digital health technologies mediate
the vision of medical practitioners as well as the situated visions of people who designed the technology.
One needs to proceed cautiously within the terminology of vision and mediation to not confuse technologies with tools to visualize or to extend our bodies. Verbeek [25
] (p. 393) explains that “human beings and their world are products of mediation, not a starting point”. Although technologies can be understood as tools for “recrafting our bodies”, they should also be seen as means to enforce meanings [24
] (p. 164). It is the designers who translate “the world into a problem of coding
] and inscribe a specific vision of the world in new technological artifacts [26
]. Consequently, whose vision is inscribed into digital health technologies becomes a question of who can be a knower of a body and how this knowledge can be obtained.
Can one be both an object known
and a knowing subject
within the technology-mediated visions of health and disease? We looked for a place to start addressing this question in the writings of Annemarie Mol and Donna Haraway. Mol [19
] introduced the concept of enactment
of the medical gaze, which enables the understanding that the medical gaze is as much a situated vision
as the vision of the patient. The patient and the doctor can be understood as having their particular visions, epistemologies, and interests and enacted them in their meetings. This coalition between Mol’s enactment and Haraway’s situated visions allows us to illuminate the various visions and assumptions about patient empowerment: who can be the knower of a body that is mediated in and through technologies.
Visions of Disease
There are varying visions on disease, and this has significant implications, not only for medical science and practice, but also for the way in which we structure our societies, what research we fund, and who can be called a patient. Because the productivity of societies is argued to be structured around health and disease, what constitutes a disease is highly political. Among others, Mol [19
] explains how medical practitioners contribute to the maintenance of the social order in modern societies. If a person is ill, she must seek medical assistance. The doctor then either sanctions the patient’s behavior or “sends [her] back to work” [19
] (p. 57) and hence exert social control. Yet, the precise definition of the concept of disease is lacking and has been the subject of discussion in medical philosophy.
In a discussion of the slipperiness of the disease concept, Hofmann [27
] explains that there are three relating and overlapping perspectives for analyzing disease: illness, disease,
). The terms are defined by Hofmann [27
] as follows: Illness,
or “being sick”, is a term meant to describe the (negative and) subjective experience characterized by pain, suffering, symptoms, and syndromes. Disease,
or “having a disease”, implies findings and classifications executed by medical professionals and is characterized by signs and markers. Sickness
, or the “sick role”, refers to being perceived as sick in the social context and is characterized by social behavior. The sick role has been discussed extensively in the context of functionalist theory, e.g., [28
], and in terms of the implications for the patient-doctor relationship [19
Although the three perspectives differ epistemologically and each has its knowers and ways of knowing the body and its disease, the perspectives are related and dependent on each other. Räikkä [31
] argues that “[a]lthough the medical concept and the social concept may be closely related in many ways, neither is reducible to the other. The fact that a condition qualifies as a disease in the medical sense does not by itself entail that it qualifies as a disease in the social sense, or vice-versa” [31
] (p. 359). Nevertheless, each perspective is favored by the group whose practice and understanding they represent and support. Health care professionals favor the disease
perspective as it is most instrumental to them and is grounded in their discipline, epistemology, and practice. In Foucault’s words, knowledge of disease
is “the doctor’s compass” [20
], and the signs and markers that constitute this perspective allow for correct diagnosis and administration of treatment. The illness perspective positions patients as the knowers of their pain and suffering, but is also gaining importance in health care due to its link to well-being [32
]. The renegotiation of the illness
perspectives in patient-doctor relationships aims toward the legitimization of the sickness
of the patients, which may be important for the patient’s identity. The importance of sickness for the identity of patients has been explored, by among others Pols [34
], in a study of people with Chronic Obstructive Pulmonary Disease (COPD). Pols showed that patients needed a form of presence or visibility of their disease to create a social position within which they could have productive lives. In the study, the technologies aiding the patients, mobility scooters, helped to make the patient’s invisible disease visible to others and validated their sickness role.
3. Research Approach
Our focus on visions and the enactment of these visions guided our research approach. To elucidate the various visions inscribed in and mediated by mobile health applications, we developed a classification system based on Hofmann’s three perspectives, disease
, and sickness
], to visualize with which of these visions the various mobile health applications were affiliated (Table 1
). According to Bowker and Star [35
] (p. 10), a classification system “is a set of boxes (metaphorical or literal) into which things can be put to some kind of work—bureaucratic or knowledge production”. Our system is based on our analytical framework, which maps the affinity
of each mobile application with the three perspectives on disease. Affinity is a concept drawn from Haraway, who suggests the term affinity
instead of identity
may be helpful for understanding the relation between the disease perspectives and the data set because the technologies should not be categorized based on being identified
as representing certain perspectives, but rather by having an affinity
with these perspectives. As presented in the previous section, each of the disease-perspectives represents different phenomena and units that are measured and analyzed to establish the disease
. These units can be both qualitative (e.g., embodied experiences of pain) and quantitative (e.g., glucose levels or body temperature). Our classification system is based on the understanding that the collection and representations of different types of data in the various functions in mobile technologies support different phenomena; e.g., a sign, such as a fever, can be measured using a thermometer and represented by a number (quantitative), or appear as a symptom, a feeling of being warmer than usual and be represented as a qualitative account of this specific experience. We divided the three perspectives further into subcategories that would aid us in analyzing and structuring the various visions inscribed in mobile health technologies. The subcategories are (i) the type of data; (ii) unit of analysis for the technology; and (iii) means for analysis that best support the applicable perspective. To exemplify, if a mobile application collects numerical values on body temperature and analyzes the data for the user to determine the right course of action, the application is categorized as a disease-affiliated technology in our classification system. Our analysis of mobile health applications was based on a deductive content analysis [36
It is important to stress that there is space within this classification system for overlapping perspectives within each of the analyzed technologies. One perspective does not exclude another, but it may have a stronger affinity. For instance, although an application might measure markers, such as blood sugar, and analyze this data through the use of an algorithm, the data might still encourage “a relation to life events” and allow for “establishment of patient’s own causalities”. As such, the classification system provides a first ordering of the data, which will be presented in the following section, followed by a discussion and a second ordering of the affiliations based on the use of health applications by the young patients.
The data for our analysis consist of two separate sets. The first set consists of the 18 applications and wearables suggested by the NTC [11
]. The NTC’s list is continuously updated with new technologies and consisted of 83 “mobile health solutions” at the time of data collection (02.05.2017). In our analysis, we only included the applications and wearables that are available in Norway.
The second set of data consists of six mobile applications, whose use and non-use was reported by 15 young patients aged 13–25 (six male and nine female patients), diagnosed with IBD. They were interviewed as part of a larger project regarding the transition from pediatrics to adult health care services. The participants were interviewed using the Transition Cards method [37
], a qualitative card sorting method that we specifically designed to address the various aspects surrounding young patients in transitioning from pediatrics to adult medicine. In addition to asking the participants to sort cards representing important people, things, skills,
into categories representing the various stages of transition, we were also interested in their use of digital health technologies. The overall goal was to understand the potential of mobile health technologies in supporting them in the process of transition. The patients were recruited while receiving treatment at two hospitals, the Akershus University Hospital and the Central Hospital in Vestfold. The medical staff decided whether the patients were well enough to participate and introduced them to the study. The patients received an information leaflet and a consent form, which they signed upon meeting the researcher. The research was registered and approved by the ethical board at both hospitals and by the Norwegian Social Science Data Services (NSD). The overall data from the interviews were analyzed using deductive thematic analysis [38
], but the mobile health applications that the patients reported on during the interview were analyzed according to the classification system in this article. We have discussed the findings regarding the participant’s technology needs and current technology use in a previous article [39
4. Visions of Disease
Our first analysis using our classification system is based on the list of 18 applications and wearables suggested by the NTC and six mobile applications whose use and non-use was reported by the participants in the study on health care transitions (see Table 2
and Table 3
We found that 14 of the 18 mobile technologies on the NTC list have an affinity with the disease perspective. Two of the technologies can be placed within the overlap between illness and disease, and two in the overlap between the disease and sickness perspective. The list presented a strong presence of digital health tests and a focus on diagnostics, which supports the NTC’s note to the ministry, in which they presents mobile technologies as means to achieve efficiency and cost-reduction in the Norwegian health care system.
Three of the six health-related mobile applications selected and used by the participants (Table 3
), have an affinity with the illness
perspective. The IBD app was the only disease-
specific application within that data set. All interviewees reported on their non-use of this app, even though the IBD app was recommended by their doctors [39
]. Two of the apps had a double affinity, disease/sickness, and disease/illness.
Interestingly, none of the 24 technologies could be analyzed as representing only the sickness perspective, which was perhaps due to the focus on self-management both in the list provided by the NTC and in the accounts given by the young patients.
The findings from the analysis of the mobile applications used by the patients indicated that young patients had a different set of “mobile health solutions”, which represents contesting visions when compared with the applications presented by the NTC. Our analysis of the data indicated that the patients valued health applications that facilitated them to become the knowers of their bodies and illness. We will discuss this in the following sections.
4.1. Knowing Devices
Ten out of the 18 mobile health solutions listed by the NTC required additional measuring devices. Positioned within the disease-vision, they required additional instruments in contrast to the rest of the analyzed technologies, which only used the mobile phone. These additional instruments, such as lenses, blood sugar meters, blood pressure meter, wristband, and stethoscope, could send data to the user’s phone. They provide data of higher accuracy and detail by coming closer to the body, enhancing the view of the body, and even getting inside the body through breaching the skin.
The medical practitioners, the receivers of the data sent by several of these applications, were not the only knowers of the body. This is illustrated by the example of the skin anomaly technologies: three out of the six technologies for diagnosing and tracking skin anomalies required additional lenses to provide high-detail images of the patient’s skin. The technologies mediated an understanding that neither the patient’s eyes nor the phone’s camera was accurate enough to identify and analyze the skin anomalies correctly. The existence of additional devices might also lead to a situation in which patients view stand-alone mobile applications as limited in their ability to gain knowledge about their skin. The relatively high price of these additional lenses, (around $1400 for DermLite), indicate that the average patient will not be able to afford some of these devices. Another three devices (#3, #12, #18) were designed for patients who have diabetes. Here the novelty was the mobile application itself, which accompanied the measuring device and which could visualize the data produced by the device, as opposed to stand-alone glucose measuring devices.
In her comparison between the logic of care and the logic of choice, Mol discussed blood sugar meters [40
]. In the logic of choice, the patients become customers and are empowered to choose both their care and the technologies supporting this care. Similarly to other customers, patients are invited to enter the market to buy attractive products, which are marketed in positive terms and “buy as much kindness and attention as they can afford” [40
]. The autonomy to choose, whether a patient wants to buy an additional device or not, is presented as a kind of empowerment
. On the other hand, this empowerment
is undermined when the choice includes expensive products, which are unaffordable to most patients. Since the purchase of expensive medical technologies is the task of the medical institutions, expensive technologies will reinforce the medical gaze, not only in terms of knowing the disease, but also in terms of who controls these instruments of vision.
4.2. Knowledge Work
The first ordering in our classification work showed that knowledge of the body and disease required work by the patient. Only two of the technologies in our sample can generate data without manual input or specific measuring actions performed by the users. These two technologies were the NTC-suggested Embrace watch, which is a wristband developed for people who have epilepsy, and the “Luftambulanse” (Air Ambulance) application discussed by one of our participants, which is a mobile application that generates user’s GPS location in case of an emergency. All other mobile applications and devices required the user to insert the data through manually: (i) taking pictures of their skin, body, stool; (ii) inserting their symptoms and health data, such as weight, body temperature and also pain and its severity; (iii) puncturing their skin to insert test strips into the blood sugar meters, strapping on the blood pressure meter or placing the stethoscope against their chest; (iv) placing their fingers against the phone’s camera and flashlight, and (v) writing down their symptoms. Moreover, several of the mobile technologies suggested by the NTC are dependent on another person assisting the user in producing data, e.g., in the case of UMSkinCheck, which requires someone else to take pictures of the user. Similarly, the functionality of the PoopMD, which is aimed at diagnosing newborns and infants, depends on the parents to take pictures of their child’s stool.
The work of the patients and their helper-technologies, such as adjusting their bodies and translating their embodied symptoms into text or numbers, feeds data into the mobile applications for analysis and/or categorization. The majority of the results are visualized in the form of graphs or marked as requiring medical consultation, after algorithmic analysis. In a few of the technologies, however, the patients can share their data with others as well as their physicians.
4.3. Patient Empowerment
The majority of the analyzed applications, except for the illness-affiliated ones, view the user as a provider of data
about the body to the application, and not necessarily as knowers or decision-makers about their health. It is hard to know if the patients, and not just their bodies, are included in the vision of the technologies, as the data about their bodies are in fact disembodied
. The technologies’ vision is limited to the input they can process. The results of algorithmic analyses are often perceived as more “factual” and “credible” than the users” embodied and subjective experience and might be rooted in the cultural notion that “seeing” makes knowledge reliable [5
]. In other words, algorithmic analyses are perceived as “better” knowers of the body than the patients themselves. These cultural beliefs, combined with techno-utopianism, result in a view of algorithms as offering a new form of logic and expertise, described by Lupton and Jutel [7
] as “algorithmic authority”.
Regardless of the authority of algorithms and patients’ pre-diagnostic work, the results of the produced by these mobile health applications are always presented in ways that portray qualified
doctors as the final decision makers, advisors, and knowers [7
]. Without facilitating a critical understanding
of the results and possible methodical flaws of digital health technologies, patients may be left more anxious and with a worsened illness
than prior to the information or information visualization provided by the app. Furthermore, diagnoses and results generated by the applications do not offer access to medical treatment nor further laboratory tests or qualify the users for sick leave; the task of diagnosing and granting access to health care resources remains with the medical practitioners [7
]. This challenges discourses that link digital health technologies to patient empowerment
In two of the mobile health applications used by the participants in our study, it was the patient, rather than the algorithm, who had the authority to decide whether the patient should contact a medical professional. Here, the patient can be viewed as the knower of the (her) body and the one who decides whether she would like to seek care and treatment. The role of the health professionals in these two applications is two-fold. In the case of the Air Ambulance app (#19), the user contacts the emergency department and forwards her coordinates, in order to be transported to the hospital. In the case of the Emergency Medicine Handbook application (#23), which supports medical personnel to assess the severity and treatment of patients at the emergency ward, the patient assesses if the severity of her symptoms requires a visit to the emergency ward. Such use of the application puts the patient in the position of the knower of her body, while the health care professionals assume the role of resource managers. These two mobile applications represent a traditional approach to health care; only the means of contacting the practitioner have changed.
Apart from the three applications affiliated with the illness perspective (#19, #20, #24), all of the mobile health technologies in the sample relied on medical practitioners, either for diagnosing, treatment or evaluation. Also, six of the applications (#6, #11, #14, #15, #16, #23) were developed for health practitioners; their usage by patients could be compared with patients using analog stethoscopes without any knowledge to support the understanding of the data the technology produces. The analysis according to the classification system demonstrates a strong presence of disease-affiliated technologies on the NTC’s list. Combined with the recommendations from the patients’ physicians, the support surrounding the disease affiliated applications seems to lack attention to (i) the interests and epistemologies inscribed in mobile health applications (e.g., the “IBD app” was developed by a pharmaceutical company) and to (ii) the unforeseen uses of these technologies.
6. Concluding Remarks
This article contributes toward the critical discourse surrounding digital health technologies by providing a classification system to identify various visions of disease inscribed in and mediated by these technologies. The proposed classification system can be helpful in structuring critical analyses of mobile health technologies, which in this study led to questioning of the proclaimed empowerment of patients through such technologies. The data from our interviews with young patients challenged the classification system by showing examples of how users resist and appropriate technologies, often in unforeseen ways that extend the purpose and vision inscribed in these technologies. Haraway [24
] argues that we become empowered by figuring out, and learning to manipulate, the code that organizes society. In our examples, we illustrate this kind of empowerment by describing how patients appropriate mobile health technologies to fit their life and knowledge. For example, the patient using the “Headache diary” (#22) chose to apply her own knowledge to the data, instead of following the app’s requirements that would allow her doctor to become the knower. Because of the unforeseen and alternative ways in which patients may appropriate mobile health applications, it is important to critically investigate and explore alternative use as well as non-use of health applications and self-tests; to use this knowledge to evaluate the emerging policies; and to design technologies based on the understanding that health application might have a profound impact on how people view and deal with their illness.
We found in our analysis a confirmation of Verbeek’s [41
] argument that the mediating role of technology implies a “fundamental unpredictability”. Through analyzing the visions inscribed and mediated by technologies, and juxtaposing these against the use context and reported use and non-use of mobile health technologies, we demonstrated the importance of critical investigations of technologies. We have used this insight to suggest that it is important, in the pursuit of technology-supported patient empowerment,
to include patients’ visions in the design of health care technologies and to enable patients to assume the position of expert knowers of their body. This suggestion is grounded in the insight that patients have many roles, contesting identities, and symptom-free periods, in which tracking of a disease might be undesirable and unwelcome. The NTC’s understanding of mobile health applications as “solutions” is based on the perception that the diagnoses and treatment of diseases is still the task of medicine. This perspective challenges the patient empowerment
discourse woven into the various technological and popular presentations of mobile health applications. The analysis and discussion presented in this paper suggests that empowerment
may also mean that patients choose to remove or not to download mobile health applications or that they may alter the application’s intended use or they may manipulate the data to present themselves as adhering patients. In the design of mobile health technologies, it is important to remember that they “create opportunities, not obligations” [40
]. For health care practitioners, this would imply that they need to open up for the possibility that patients may manipulate their data and establish their own causalities. For the patients, non-use should not lead to a disappearance of patient rights and benefits.