Abstract
In this article, I explore knowledge practices in increasingly digitized, data-driven, and personalized healthcare settings by empirically focusing on the “looper community” in type 1 diabetes. This community develops and uses open-source automated insulin delivery systems and frequently criticizes slow innovation cycles and data monopolies of commercial device manufacturers. Departing from the literature on patient knowledge, I argue that studying these knowledge practices at the intersection of digitized and personalized health care, open-source innovation, and patient activism calls for an expansion of the theoretical notions of patient knowledge. Empirically I map out three knowledge practices: technical, including maintenance and repair work; recursive, including the building and maintenance of adjunct care and support structures; and methodological, including scientistic forms of self-experimentation. I propose “elaborative tinkering” to foreground the nuances of when and how patients’ different forms of knowledge practices intertwine and when they are kept apart. This approach offers new concepts for understanding what it means to know as patients in spaces of (chronic) self-care, innovation, and activism.
Keywords
Introduction
How individuals know about their (chronic) diseases is an ongoing concern in the social studies of health and illness. Within different healthcare contexts, scholars of sociology and science and technology studies (STS) have argued for respecting the epistemology of how patients engage with their diseases, bodies, medication, and self-care technologies, emphasizing that patients 1 are more than “important epistemic factors” (Falke 2018, 36) within the biomedical sphere (Epstein 1995; Pols 2013, 2014; Rabeharisoa, Moreira, and Akrich 2014). In this article, I explore patient knowledge practices in increasingly digitized, data-driven, and personalized healthcare settings by focusing on the “looper community” in Germany. Here a group of people with type 1 diabetes (T1D) develops and uses an open-source closed-loop algorithm to automate their insulin delivery and with this also improve their “chronic living” (Wahlberg et al. 2021). In their open-source endeavor, they also shed light on slow innovation cycles of commercial device manufacturers, including their data monopoly.
T1D is a chronic illness where the pancreas stops producing insulin so the affected person needs to administer it exogenously. Individuals’ illness-related knowledge practices consist of measuring their glucose levels multiple times a day and administering insulin according to those measurements. Contemporary T1D self-care is often described as a burdensome practice of repetitive data work for those affected (Jansky 2021; Forlano 2016). In order to care for themselves, people living with T1D constantly need to know how to mediate between different technical devices in, on, and with their bodies, such as insulin pumps and continuous glucose monitors, and the data these technologies generate (Kingod 2018). For individuals with T1D, creating and interpreting data about themselves is a daily necessity and an integral part of their knowledge practices (Mol 2000; Piras and Zanutto 2014; Danesi et al. 2020; Liggins 2020). Even with new digital technologies, they have to be alert and active in every moment of their lives (Kaziunas et al. 2017; Gottlieb and Cluck 2019). In completing their repetitive data work, they encounter black-box algorithms, limited openness regarding the use of the data generated and collected, as well as limited interoperability (Jansky and Langstrup 2022; Gottlieb 2021).
Dissatisfaction with existing self-care technologies foregrounds the slow pace of technological innovation in T1D, device manufacturers’ persistent nontransparency about data-handling, and the associated burdens of living with T1D. In this context, the looper community started to develop and use open-source algorithms to automate parts of the burdensome repetitive data work (Schipp et al. 2021; Lewis 2019). 2 Their critique of current self-care technologies was later also reflected in the community-defining use of the hashtag #WeAreNotWaiting. Loopers are “deliberately non-compliant” (Scibilia 2017) by creating and using automated systems—which commercial providers fail to deliver—in an open-source manner. In practice, this means that loopers created an open-source control algorithm that enables an insulin pump and a continuous glucose monitoring device to communicate with each other and thus take over essential data work (Braune et al. 2021). The algorithm makes small adjustments to the insulin dosage every few minutes as it responds automatically to changing glucose concentrations registered by the continuous glucose monitoring device, intended to keep glucose levels within a predefined target range (Lewis 2019). To set up the systems, loopers need to engage medical devices such as specific insulin pumps and glucose sensors as well as smartphones or smartwatches. They can then access their data on an app, which also graphically represents what the algorithm does and what it predicts. Looping is not a frictionless endeavor and has a material component to it: some loopers tinker with the battery of their glucose sensor to prolong the battery life, others 3D print transmitters. Engaging in the looper community can be interpreted as forms of chronic self-care (Schipp et al. 2021), patient-driven innovation (Demonaco et al. 2019), and activism (Jansky and Langstrup 2022).
Building on seventeen months of ethnographic fieldwork in the German looper community in 2018 and 2019, twenty-eight in-depth interviews and an analysis of public documents, I explore empirically how new patient knowledge practices emerge within this open-source endeavor. I depart from the literature on patient knowledge and argue that the phenomenon of looping points to the need to expand established theories of patient knowledge.
How loopers know is characterized by knowledge practices described in patient knowledge literature, such as tinkering (Mol 2006), practical “know-now” (Pols 2014, 82), and “credibility struggles” (Epstein 1995). Yet, as I explain below, the observed practices are also technical, recursive, and methodological. To account for how these different forms of knowing are intertwined or are kept apart, I suggest the notion of elaborative tinkering. Patients engage in knowledge practices that amount to innovative ways to change their self-care and are characterized by both intimate practices of tinkering for immediate self-care purposes, and practices of scientistic experimentations to build a knowledge base for epistemic legitimacy, for example, by establishing a research project (O’Donnell et al. 2019). Current STS understanding of patient knowledge practices can be improved by empirical accounts of cases situated at the intersection of digitized and personalized health care, open-source innovation, and patient activism.
Theorizing How Patients Know
To make private and often invisible knowledge practices visible, to show that what patients know should be regarded as a legitimate form of knowledge “amidst the multiplicity of forms of knowledge within medical practices” (Pols 2013, 82), scholars of social sciences have theorized that patients know as an “activity of knowing in a particular situation” (Pols 2014, 82) and termed this patient knowledge, first introduced by Jeannette Pols.
The first strand of patient knowledge literature I use in my analysis emphasizes that although patients’ knowledge practices are “practical knowing in action” (Pols 2014, 75), they cannot be thought of in contrast to biomedical knowledge, because they draw from the latter. From an epistemological perspective, this way of knowing might be “messy” in the sense that these practices involve “many different techniques, values, and materials” and aim for an immediate purpose (Pols 2014, 75). Pols (2014, 79) retraces this by empirically looking at how patients were using technological aids provided by the clinic at home. With this, she foregrounds that patient knowledge practices involve coordinating and translating knowledge, technologies, and advice from different sources (Pols 2014, 75). This renders patient knowledge practices neither opposite to medical knowledge nor the same (Pols 2014, 79).
Translating different knowledges, information, and techniques from different sources and constantly adjusting, testing, and experimenting with bodies, selves, technological devices, or medication in the care context have been termed tinkering (Mol 2006; Mol, Moser, and Pols 2010; Winance 2010; Kingod 2018). This notion also gives a theoretical tool to understand patients’ practices of “attentive experimentation” (Mol 2006, 411) in order to live with their disease. Tinkering is not a linear translation process but a constant readjusting, refitting, and readapting of care practices. Tinkering has an important collective component, because it involves more than just the individual affected by the disease: it is always done in (care) collectives (Winance 2010, 102). The collective and distributed aspects of tinkering become even more evident with the emergence of patient communities on social media. These online spaces are essential sites for knowledge production (Kingod 2018, 154).
Looping has a significant health-political component to it, which extends to how people know. The second strand of literature on patient knowledge relevant for my empirical analysis concerns activist ways of knowing in the healthcare sphere. Here, patient knowledge practices are conceptualized as actively engaging in shaping biomedical knowledge. Epstein (1995), for example, reveals how “AIDS knowledge” arose out of what he calls “credibility struggles,” between different actors—activists, the media, politicians, and healthcare professionals—and therefore cannot be thought of in strictly biomedical categories. Rabeharisoa, Moreira, and Akrich (2014) coined the term “evidence-based activism” to capture forms of involvement where patient organizations engage, participate, and intervene in biomedical research practices seeking an immediate benefit for the affected. Concepts like AIDS knowledge and evidence-based activism illustrate how activists contribute and create new understandings of their disease, how their knowledge practices can influence and shape formalized biomedical knowledge, and thus account for the epistemic significance of patients within biomedical knowledge production.
These articulations of the epistemology of patients engaging with their bodies and illnesses have allowed a better understanding of the fact that patients know in relevant ways, without hierarchizing different forms of knowing in the medical sphere. I bring theoretical discussions emerged around the Quantified Self (QS) movement to the literature on patient knowledge to better grasp the methodological, innovative, and communal characteristics of loopers’ knowledge practices and their engagement with personal health data. The QS movement can be described as “a large group of avid self-trackers” (Sharon 2017, 95) and is not related to a specific health condition. Members of this movement focus on creating and interpreting data about themselves and correlate behavior with somatic aspects (Heyen 2020; Villa 2012).
Within the QS movement, the practice of gaining “self-knowledge through numbers” (Wolf 2010) involves creating and engaging with personal (health) data, in what is described as “n = 1 self-experimentation.” This points to coexistence of individualization and communality of knowledge practices that I observed in the looper community. On the one hand, “n = 1” emphasizes that it only needs one-person testing and gaining insights from an experiment. Best described by early QS proponent Kevin Kelly (2016, 241) as “you are testing the variable X against the very particular subject that is your body and mind at one point in time. Who cares whether the treatment works for anyone else? What you want to know is, how does it affect me?” (Kelly 2016, 241)
On the other hand, Jethani (2015, 39) has noted that “n = 1 quantified self-experimentation is only made meaningful in the context of a larger audience.” While the QS movement focuses on individual needs, it has a “significant social component” (Crawford, Lingel, and Karppi 2015, 484). Personal data are not just about gaining information about one’s body; instead, it “becomes a medium for connecting with others by offering a raw glimpse into one’s intimate, private life” (Sharon and Zandbergen 2017, 10). Sharing data and participating in the community and meetups are two defining aspects of the QS movement, with personal data being the language everyone can understand and relate to (Sharon 2017, 111; Pantzar and Ruckenstein 2017, 2).
STS scholarship has variously emphasized that it is not possible to make a clear-cut distinction between biomedical knowledge and what patients know, how they engage with their bodies, with self-care technologies, and with disease. Concepts including “know-now” (Pols 2014, 82), tinkering (Mol 2006), or “credibility struggles” (Epstein 1995) emphasize the practical aspects of knowing, translating, and engaging with different forms of knowledge as patients. All these concepts imply a criticism of the binary and hierarchical notion of knowing common in the biomedical sphere. This skepticism about hierarchical knowledge is a useful point of departure for this article. Yet the contexts and operations through which loopers know are very different from clinical and established healthcare settings and thus lead to new questions. Loopers’ knowledge practices are more closely related to social media communities, such as the QS movement, innovation spaces, and the open-source sphere. By bringing together these different strands of literature, we can account for the complexities of the knowledge practices that emerge when patients leave behind their provided self-care technologies and venture into an open-source innovation endeavor.
Methods and Setting
This article draws on ethnographic fieldwork carried out in the German looper community in 2018 and 2019, and the regional setting influences people’s experiences. Germany is a wealthy Western European country with universal health coverage. And while the cost of much diabetes technology is covered, Germany has also been slow in adopting a digital health infrastructure, compared to other European countries (Bertelsmann Stiftung 2019, 4). For example, Germany is only now discussing electronic patient records. In my fieldwork, I did not remain in one geographic site (Marcus 1995) but followed different actors and stories (Latour 2005, 12). I started my empirical research by participating in a hackathon, and at the same time, I met my gatekeeper, an active community member. I later joined him at a local looper meetup, in which I frequently participated thereafter. I always introduced myself as a researcher and disclosed my research interests (Spradley 1979, 58). I also conducted twenty-eight problem-centered interviews (Reiter and Witzel 2012), predominantly with people who would be considered patients, their relatives, and their healthcare professionals. Participants’ age ranged from twenty-two to eighty-one. They had different educational backgrounds, with more or less experience in technology-related subjects, although most participants had a higher education level. 3 Six participants were healthcare professionals, including two who had no T1D. To better understand public and broader negotiations about looping, I included media reports, blog posts, and statements from regulatory bodies in my analysis. Data gathering and analysis were mutually informed, following an iterative logic. Data collected early on in the analysis served as a starting point to direct the strategy of theoretical sampling (Clarke 2015, 101f).
Technical Setup, Maintenance, and Repair Work
Setting up the system requires determination and technical knowledge. If you don’t have the technical know-how at the beginning, you will by the end. (AndroidAPS 2020)
The looper community is strongly tied to the open-source sphere. This means that instructions and source code to set up a closed-loop system are shared online for everyone to access, use, and modify. In interviews, participants gave detailed accounts of the technical aspects when asked about how they started looping. For many, the open-source setting and knowing the technical details and composition of the systems (which I termed technical
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patient knowledge practices) were central to their looping experiences. However, looping does not mean that people need to program themselves. Many are receivers of code, “cooking” up their own system with recipes. Marcel, a carpenter in his forties, describes the setup process: Yes, everything works with the instructions, which you just have to follow step by step. And when you get error notifications when you start and don’t know what to do, you can quickly find an answer in the [Facebook] group. Everybody has had some error notifications, and if you just look through the posts in the group, you will find an answer. Or, if you have an urgent problem and write to someone more experienced, you will have an answer very quickly. So, it’s a mix of self-work [Eigenarbeit] and feedback from the group.
In these technical descriptions, healthcare professionals are typically not considered part of the setup practices. Another interviewee, Pascal, a sales associate in his thirties, was reluctant to share information about the kind of technical aid he used, because it did not fit the physician’s scope of clinical practice: So, in the clinic with my physicians, I wasn’t quite as open about looping, because I just think it’s none of their business how I manage my diabetes. I think it’s not part of the doctor’s job.
During my fieldwork, many healthcare professionals were not yet familiar with the system. Even for loopers who work in the healthcare sector, the technical sophistication of the system is not necessarily easily accessible. Marieke, a diabetes educator and looper in her forties, refers to the distress of having to acquire a technical vocabulary that was new to her: just the whole vocabulary that’s like a foreign language to me. When I hear sentences like “Have you already booted the ‘xDrip’” or something, I am like, “Yes, wonderful. What is he talking about?” And yes, I had support. If I have questions, as I said, it is quite touching how the community takes care of me.
Using closed-loop-systems is not set-and-forget—it takes much more than a brief moment to set up the technology, which does not run independently thereafter. These sophisticated technical systems have much practical maintenance and repair work attached to them, as documented in a field note: Agnes, Paul and I sit at the lunch table. I sit opposite to them, and we are all eating dessert and drinking espresso; Paul and I are engaging in chit-chat about our morning. Agnes has her insulin pump and her cell phone in her hands. She doesn’t listen to our conversation but is busy typing on her cell phone and sighs, “Ohh, why don’t I have a connection now? I need to check how that is going.” Paul leans forward and says to me with a laugh: “That’s also looping, if sometimes something doesn’t quite work, you are temporarily in the zone.”
Going beyond the technology received from healthcare providers and engaging in an unregulated open-source endeavor mean loopers begin to cultivate technical knowledge practices. The epistemology of the setup, maintenance, and repair work of the open-source systems shares similarities with the conceptual points made by Pols and Mol. Yet a looper’s way of knowing is far less “know-now” (Pols 2014, 82). Out of necessity, individuals who want to loop become proficient in knowing how their self-care technologies work to a degree that not even trained healthcare professionals have. These systems moved from the open-source and innovation sphere to the homes of individuals, and this is reflected in the ways loopers know.
Recursive: Collectively Building and Maintaining Structures for Care
You’ll have to build your implementation yourself (no one can/will do it for you!), but…[t]here are users in the community around the world, so there is usually someone online…who can help answer questions and point you to resources. (OpenAPS 2020)
With the lack of “costumer support service” (as there is no commercial company behind looping setups) and healthcare professionals’ limited familiarity, loopers had to build their own support system (Crocket 2019). Although loopers still rely on the established healthcare system, for example, to access insulin prescriptions, they build adjunct structures of care. Markus, an IT (Information Technology) specialist in his thirties, explains: The community is just people who get involved. There are people who can’t program, who can’t do anything, but they can speak [more than one] language. For example, that means they can help with translating or supporting newer members, so the developers and the more experienced members don’t have to answer the standard questions. So, it’s better than some service you can’t get in contact with or one that can’t help because the people aren’t so deeply involved. Because those in the community usually have diabetes themselves or their children do. And they are so involved in the subject, and they have so much knowledge and I find that extremely important. And I have never received so many tips and help from any manufacturer. You only get so many tips and help from someone who is also affected and truly understands.
I interpret the knowledge practices of loopers as recursive. Recursion in programming refers to a function calling on itself during its execution. Knowledge practices in the open-source sphere are recursive in the sense that the software is available for everyone to use without restrictions, as is the source codes that created the software. This means that everyone can modify the code to fit their individual needs and can redistribute those changes within the same infrastructures (Kelty 2008, 15). Hannes, a sales representative in his thirties, explains the open-source aspect of looping as follows: And open source simply means that you can adapt the algorithm yourself, if you know what you’re doing. I played around with it a bit, but I’m not a programmer myself. That means I don’t change much, but theoretically—open source—you can make any modifications you want and then make it available to the group again.
Loopers’ knowledge practices constantly move between customization/personalization of the technical system and collectively building/maintaining adjunct structures of care in healthcare settings where there are no established support structures. This distance to the clinic reveals how knowledge practices can be defined by a constant “(shifting, dynamic, temporal) assemblage of multiple places, people, and resources” (Trnka 2021, 8). How patients engage with their bodies, self-care technologies, and care infrastructures cannot only be understood “through the inter-relation of home and clinic” (Trnka 2021, 8). What makes the knowledge practices of loopers unique is “that code, data, and (digital) devices are their shared concern and the means through which loopers engage individually and collectively” (Jansky and Langstrup 2022, 6). Looping is an inherent individual-in-community knowledge practice that situates the person in feedback loops that involve interacting with peers in an online community, making code and resources available within this open-source community, and ultimately creating adjunct structures of care as part of a broader innovative process in health care.
Methodological: Scientistic Forms of Experimentations for Self-Care Improvement and Epistemic Legitimacy
Looping entails practices of experimenting with bodies, self-care technologies, pharmaceutical aids, and self-care arrangements. My research documents individual loopers explaining their approaches and reconstructing the aspiration of the looper community for epistemic legitimacy, which reveals knowledge practices as methodological and scientistic forms of experimenting for both self-care improvement and epistemic legitimacy.
Jacob, a father of a young child with T1D, explains his experimental approach as follows: Unfortunately, we do not have a second dummy child on which we can test and then see if it will work and then we test. What we have is a second pump, but no one is attached to the second hardware. So, we can’t test the whole algorithm; we can only test how it behaves under certain conditions. But we can’t see what happens if a lot of insulin is suddenly given or not. Or any interaction errors are difficult to test.
Looping is a practice of constantly optimizing and improving the system and codes, adjusting variables for a personalized and customizable system, and testing and tweaking code, often against the instructions of regulatory authorities and taking the risk on oneself. While not every looper is programming, most of the people I met during my fieldwork did share Jacob’s methodological and scientistic approach: using, testing, and modifying the system for personal use, and then if something works, sharing it with the community.
Some of the loopers were deeply involved in the developing and programming aspect, intending to make these efforts available for everyone. Alex, an electrical engineer who started long before the German looper community became as large as it is now, speaks of his involvement in development: And then I was one of the first in Germany who soldered the xDrip hardware and implemented it, and that was super, super exciting. Then through that, I met Sebastian…. He programmed; I tested like crazy. You get up and check the chat channel and then there are questions, and you start to answer them and then you sit there thinking: “I’ve been sitting here answering questions for another hour.”
Loopers’ efforts led to the OPEN-Project, a research project initiated by loopers and funded by the European Union (O’Donnell 2019). Here, “n = 1” refers to unifying knowledge practices that each of these individually setup systems contributes to the common goal, advancing and challenging the seemingly slow innovation cycle in T1D technology development.
Toni, a diabetologist and looper, retraces the relation between knowledge she gained through looping and established diabetology knowledge from her professional training: I would say [looping] changed my understanding of diabetology for the better. I now understand the human organism much better; I think much more dynamically. Before, it was always so that one has a blood-glucose level and takes a dose of insulin. Diabetology for most is still measuring one’s blood glucose and injecting, even though this is a therapy that is actually already decades old, but that is our reality. But still, for that, I have developed a better understanding through my closed loop. Apart from that, if patients talk to me about it, I am, of course, open to dialogue but cannot help practically with setting up the loop, even though I have one myself.
At the time of my fieldwork, concerns were raised by health professionals, legal scholars, ethicists, and regulatory bodies about the risks and safety of using the unauthorized system. In 2019, the US Food and Drug Administration even issued a safety warning: Today, the US Food and Drug Administration is warning patients and health care professionals of risks associated with the use of unapproved or unauthorized devices for diabetes management…. [T]he agency noted that the use of unapproved or unauthorized devices could result in inaccurate blood glucose (sugar) measurements or unsafe insulin dosing, which can lead to injury requiring medical intervention or even death. (FDA 2019) From a medical point of view this is the worst thing you can do…. That’s my opinion from my medical metabolic point of view. It’s completely wrong and I don’t know if a lawyer can even give…therapeutic recommendations.
The literature on patient knowledge is quite clear that care always entails practices of experimenting and tinkering with bodies, technical devices, medication, and human and technical arrangements. Loopers’ knowledge practices aim to improve everyday life for people with a chronic health condition and can be personalized. However, looping goes beyond patient knowledge because it is a more deliberate approach to changing variables and code analytically, often with the goal of improving the system for all. This methodological way of knowing in the looper community points to health-political goals. Loopers know by creating a knowledge base where evidence is produced, with the possibility of formalizing what loopers know, for example, through the establishment of the OPEN project.
Discussion: Elaborative Tinkering
In this article, I empirically mapped out three patient knowledge practices (technical, recursive, and methodological) that emerge when people with T1D use and develop an unauthorized automated system for their illness-related repetitive data work. The epistemologies of going beyond commercial self-care technologies and venturing into this open-source endeavor highlight an entanglement of different forms of (patient) knowledge practices that have not yet been addressed in the literature about patient knowledge.
Pols (2013, 2014), Mol (2006), and others working in their tradition note that what patients do and how they bring together different sources, techniques, and knowledges to live with a disease should be respected as knowledge among other forms of knowledge in the biomedical sphere. On the other hand, Epstein (1995) and Rabeharisoa, Moreira, and Akrich (2014) focus on how patients know in activist ways. They documented affected people self-organizing, being vocal in their demands and criticism of established healthcare structures/actors, and challenging and influencing (medical) understanding of their health condition.
These different concepts from STS are a lens to look at loopers’ knowledge practices, which have elements of tinkering, as described by Mol (2006) and others, as well as practical “know-now” (Pols 2014, 82) and can also include more activist forms of knowing with a health-political aim. Looping is firmly situated in the realm of open-source innovation. The fact that loopers are experimenting with their bodies in creative, critical, and vocal ways—stressing the importance of personal health data—brings their knowledge practices close to the QS movement. These accounts of how patients know add nuance to descriptions of patient knowledge.
Yet developing and using life-saving self-care technologies while being involved in open-source innovation and activism go beyond tinkering and know-now. With loopers, we are somewhere in between these notions of patient knowledge: loopers are demanding, they want to be recognized, they are vocal, and managed to create “actually existing alternatives” (Kelty 2008, 3) to the commercial systems. Loopers’ knowledge practices are technically advanced to a degree that is not conceived of in the current literature on patient knowledge. They know about technical details that even people trained in T1D technologies do not necessarily know. Data repair work (Pink et al. 2018); maintaining devices on, in, and with bodies; keeping data flowing; or navigating the open-source platforms are some of loopers’ common knowledge practices, even though they are not part of the established care structures of living with T1D. Loopers experiment with their bodies and self-care technologies, and they engage in innovative ways in a community outside of the clinic, on social media and in the open-source sphere. In the context of looping, knowing becomes a recursive practice of methodologically experimenting with bodies, self-care technology, algorithms, and digital infrastructures—all while staying in feedback loops with others in the community. The focus of the looper community is always directed at establishing a knowledge base and epistemic legitimacy. Looping becomes a continuous moving between deeply individual practices and inherently communal challenges that cannot be undertaken alone. It connects self-care practices with broader negotiations and tensions in the healthcare sphere regarding expertise, credibility, and knowledge legitimation. Similar to the QS movement, loopers do not see technologies and health programs provided by the “traditional” and standard healthcare regime as fitting or good enough, so they take matters into their own hands (Sharon 2017, 109). They push device manufacturers and pharmaceutical companies like Epstein’s (1995) “treatment activists.” However, with the establishment of the OPEN project, loopers are beginning to enter (clinical) academic spaces, not invited as “citizen scientists,” but by using their diverse professional backgrounds. Evidence is produced within a research project, with the possibility of formalizing what loopers know. Unlike other forms of patient activism, loopers do not stay in the biomedical and healthcare realm, instead moving in and out of healthcare/clinical and open-source innovation spaces, challenging received ideas about patients’ knowledge practices.
Loopers’ knowledge practices are complex and multifaceted and, I suggest, best understood as forms of elaborative tinkering. Downloading instructions, maintaining a technical system that immediately can improve one’s own “chronic living” (Wahlberg et al. 2021), or the engagement in online and offline peer communities for support are all practical ways of knowing and tinkering with self-care arrangements. Loopers’ knowledge practices are closely related to pushing and criticizing commercial device manufacturers and regulatory bodies, deliberate scientistic self-experimenting for “the greater good,” and being engaged in building a knowledge base for epistemic legitimacy. Loopers are engaging within the open-source innovation sphere and using and developing this automated system with the aim to improve one’s personal life with the chronic health condition while at the same time having in mind that they need to generate evidence that these automated systems are efficient.
Loopers create complex knowledge and make it explicit by sharing it with others in methodological, organized, and scientistic ways. Their emerging knowledge practices reveal loopers radically changing their own treatment, while also challenging “the political economy of health device innovation” (Jansky and Langstrup 2022, 18). If we stay only within the literature about how patients know in practical ways, or if we only see the emerging knowledge practices of the looper community through the prism of activist ways of knowing as patient, or as niche self-experimenting as patient innovators in the realm of the QS movement, we lose sight of the nuanced entanglement of these ways of knowing in practice. Focusing on elaborative tinkering captures how knowing as a patient in these spaces of innovation, activism, and digitized (chronic) self-care can and is a constantly moving between and combining different ways of knowing. Understanding that patient knowledge practices in the looper community and similar health communities are made up of different ways of knowing offers a way not to lose sight of the fact that intimate practices of tinkering with self-care arrangements and “know-now” (Pols 2014, 82) can also be entangled with activist and innovative ways of knowing, and how both might be interrelated. With an increase of digitized, personalized, and data-driven healthcare settings, where technologies do not only “travel…from the clinic to the home” (Langstrup 2005), but from open-source innovation spaces to the home (and later to the clinical context), we will see more and more that patients can know in technically advanced, recursive, and methodological and scientistic ways. Turning the gaze toward elaborative tinkering allows us to carefully explore when and how different patient knowledge practices might come together and when they are kept apart.
Conclusion
Although the case presented in this article is rather specific, from a history of high involvement in one’s care in T1D to the uniqueness of the technology and community, similar technologically advanced, recursive, and methodological ways of engaging with technologies can be observed in other healthcare settings, such as sleep apnea (Schultz 2019), epilepsy (Bogataj et al. 2021), and hearing loss (O’Kane et al. 2019). These communities might not be as organized as the looper community currently is—yet the proposed notion of elaborative tinkering may help other researchers to gain a deeper understanding of the complexities of knowing as a patient at these intersections of digitized and personalized health care, open-source innovation, and patient activism. The empirical reports above show that patients can have highly complex and sophisticated technical knowledge about an innovation that far exceeds current commercial self-care technologies. I have also illustrated that healthcare professionals can draw upon their own illness-related experiential knowledge, combined with biomedical knowledge. How this can unfold in other areas of increasingly digitized, data-driven, and personalized healthcare settings calls for more empirical exploration.
Footnotes
Acknowledgments
Firstly, I want to thank the looper community, the regular meetup group, and the participants I interviewed for sharing their experiences and lived expertise with me. I am sincerely grateful for all of it. I also want to thank my PhD supervisors Paula-Irene Villa Braslavsky and Henriette Langstrup for their feedback and comments on my manuscript and their continuous encouragement. In addition, I want to thank Verina Wild, Tereza Hendl, Jasmine Schipp, Ayush Shukla, the two anonymous reviewers, and the Science, Technology, & Human Values editorial team for their helpful comments on earlier versions of the manuscript. For editorial help, I want to thank Fabian Linder. This article is part of my PhD in sociology at the Ludwig-Maximilians-University, Munich.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This article is funded by the German Federal Ministry of Education and Research (grant number 01GP1791).
