The temporal flows of self-tracking: Checking in,moving on,staying hooked

Abstract

This article conceptualizes the experience of self-tracking as flow, a central technique, utilized by digital media companies to hook their users. We argue the notion of flow is valuable for understanding both the temporal lock-ins of self-tracking practices in sequences and repetition, and the way self-tracking technologies thrive on data sequences for retaining users and creating viable businesses. To substantiate this, we present a qualitative empirical study of how users experience flow when tracking various aspects of their personal lives. Users find self-tracking technology and the metrics they generate to have much more limited relevance and thus guide their attention elsewhere. If they are hooked, they are so in ways different from those projected by the technology. Users find meaning in their self-tracking in moments of registration, allocution, consultation and conversation, but also problematize their attachment to specific temporal tracking regimes.

Keywords

Feedback loops flow meaning-making record keeping self-tracking in everyday life temporality

Introduction: self-tracking as flow

Self-tracking technologies, wearables and apps that assist the user in keeping a record of a specific activity or aspect of life are temporal technologies native to today’s metric culture: they organize, manage, exploit and suspend time with the stated aim of improving our lives. Yet, they also subvert conventional metrical infrastructures and logics in their dynamic layout. Thus, while most self-tracking technologies operate within a logic of quantification, they depart from static measurement cultures, instead allowing for, and catering to, considerable user flexibility. Indeed, self-tracking is rarely only performed to keep a rationalized record (lifelog) of vital stats; rather, self-tracking is also often practiced to experiment with oneself, to work with the dynamic body, rather than against it, and for the simple fun of playing with technological gadgets and the data they produce (Kristensen and Ruckenstein, 2018; Neff and Nafus, 2016; Sharon and Zandbergen, 2017).

The practice of self-tracking is becoming ordinary, perhaps because many of the things self-tracking technologies invite us to log belong to the realm of the everyday: the food we eat, our sleep, how much we exercise, the rhythm of the heart and the work we perform (Didžiokaitė et al., 2017, Pantzar et al., 2016; Ruckenstein, 2014). Self-tracking should therefore be understood as part of everyday living (Lupton et al., 2018; Ruckenstein, 2017). Advancing an agenda of studying ordinary usage practices and experiences of self-tracking against the backdrop of everyday life, Lomborg and Frandsen (2016) have pointed to communication theory as a key trajectory for understanding the meanings self-tracking come to hold for users, the pleasures, competences, and agency it mobilizes as part of experiencing oneself. Self-tracking is fundamentally a communicative phenomenon: as we track ourselves, we communicate with a system, with ourselves, and the social world. This communicative perspective moreover attains a cultural dimension as it unfolds in a logic of flow, where both users and their apparatuses integrate with, and contribute to, socio-technical flows on multiple levels. Not only do data flow from self-trackers to systems and back, users flow, too, using self-tracking techniques to sift through everyday life and extract habitual and meaningful practices. In fact, the very experience of self-tracking may be conceptualized as flow, a central technique, utilized by digital media companies to “hook” their users (Schüll, 2012).

Informed by such perspectives, we couple communication-theory with media theoretical works on flow to explore contemporary self-tracking cultures. One important motivation is to reinvigorate the theoretical framework of flow. We contend that the concept of flow is needed and valuable for understanding both the temporal lock-ins of self-tracking practices in sequences and repetition, and the way self-tracking technologies thrive on data sequences for retaining their users and creating viable businesses. A significant contribution of flow-theory to existing research on everyday self-tracking practices, it to call for special attention to the relations between system affordances and user experiences and the lock-in mechanisms created in the practice of self-tracking across time. In this article, we therefore advance the communicative study of self-tracking by asking how the experiential dimensions of using self-tracking tie in with self-tracking infrastructures at the level of the system.

The aim of the article is twofold: first, to develop a theoretical framework of self-tracking as flow by bringing into dialogue classic theories of flow from media, psychology, and game and design studies; second, to empirically explore and elaborate “self-tracking experiences” of communicating with the system by way of flow-theory. The empirical study we present concerns how users experience flow when tracking various aspects of their personal lives: exercise, mood, menstruation, whereabouts, alcohol intake, and so on. We demonstrate that—from the perspective of self-tracking providers—the logic of flow, interlacing segments to hook the user, is present in the self-tracking applications’ offerings of means to accumulate and aggregate segments and use these to visualize the user’s progress. Yet, this sequencing and aggregation is not fully perceived and animated by the users, who find self-tracking technology and the metrics they generate to have much more limited relevance and thus guide their attention elsewhere. If they are hooked, they are so in ways different from those projected by the technology. Users find meaning in their data flows in specific contexts of their practice, in moments of registration, allocution, consultation and conversation (Bordewijk and Kaam, 1986), but also problematize their attachment to specific (temporal) tracking regimes and applications.

System-user communication: mobilizing theories of flow

In scholarly literature on media and communication technologies, we find numerous theories and studies that employ the notion of flow. One influential strand of thinking we find in television studies, where Raymond Williams (1974) proposed that the cultural form of television is a montage of segments organized strategically to retain audiences in a specific channel (Williams, 1974: 94). Significantly, he noted, televised flow could not be reduced back to each program segment, but was rather characterized by an unfinished and tentative sequence—what Jane Feuer (1983) later called “segmentation without closure.” The sequential impetus of flow in television was, for Williams, what made audiences stick to the television channel. While William’s concept was developed in a media reality, where the emblematic victim of flow was a “couch potato,” the concept of flow in television studies has later been further developed to account for audience agency and choice when stepping into and out of the (television) flow (Jensen, 1995). Jensen distinguished between three levels of flow: channel, viewer and macro, referring to the flow of the individual channel as it tries to maintain its viewer glued to the screen, the flow created by the viewer based on the available content across channels and the super-flow of possible combinations of everything that was available on all channels. Jensen advanced the important point that more channels didn’t necessarily imply a more empowered viewer. Rather, he noted, viewers would still be captured by the cultural constraints of super-flow.

A second strand of research, in part mobilizing Mikhail Csikszentmihalyi (1990), is concerned with the autonomous and pleasurable aspects of immersion in media-related activity, focusing on digital and gamified environments in particular. Csikszentmihalyi’s work on how individuals can attain a highly focused mental state have served as inspiration for game and app-developers, whose ambition resemble the strategic attempts described by Williams to retain users on their platform in an increasingly distracting media environment (Bucher and Fieseler, 2017). Yet it has also served as a baseline for exploring the experience of being “hooked” when using particular media. Jesper Juul’s (2009) work in video game studies, for instance, theorizes how frustration and motivation may be mutually constitutive dynamics in the continuous task of playing. Juul draws on Csikszentmilayi’s idea of optimal flow experiences that engage players through a series (or sequence) of tasks that stretch (neither overmatching nor underutilizing) the person’s existing skills so she experiences that the challenges she is faced with are at an appropriate level, and to set clear proximal goals that, when achieved, are alerted with immediate feedback about the progress that is being made. Anthropologist Natasha Dow Schüll (2012), in her study of machine gambling in Las Vegas, takes a critical approach to analyzing the relationship between technology design and user behavior and experience. Schüll emphasizes flow as a technology-induced temporal state of mind that can be designed with addictive consequences for the user. As Dow Schüll (2012) notes,

Gamblers “forget themselves” and feel carried forward by a choreography not of their own making; much like mountain climbers who describe merging with the rocks they climb, or dancers who report feeling “danced” by music, they feel “played by the machine.”

In her most recent work, Schüll (2016) approaches self-tracking technologies and offers a detailed account of how the market discourse and the inner workings of self-tracking technologies are designed to govern users through real-time “micro-nudging,” thereby addressing the user not as an active, choosing subject, but as a consumer to be molded.

We can infer from these diverse strands of research into flow and media that, conceptually, flow hinges upon a relational entanglement between features of the medium (technological design, organization of content) and experiential potential and engagement at the user end. This relationship is marked with certain logics of attention and temporality, largely based in sequential organizing of “slots” of activity (whether repetitive or developing progressively over time), which—in turn—tie activities at the micro level with macro level infrastructures of the medium in question. “Flow” is thus not only a matter of technique and pleasurable experience, but also raise questions of power, self-surrender, and even addiction.

The above outlined theories on flow provide a valuable analytical guidance toward issues of attention, constructions of temporality and feedback, and nudging. Yet, in the context of self-tracking, an endeavor that relies heavily on user input to become an organized sequence, flow may manifest itself in different ways than in the context of television, machine gambling, or even playing video games, which all rely on a planned script or organization of events. We therefore need to include communication-theoretical insights to detail how these micro–macro linkages between flexible, and often unpredictable, acts of engagement and the development of the system and infrastructure are achieved through cumulative media use.

Our point of departure for adding this communication-centric nuance to the concept of flow in the context of self-tracking is Bordewijk and Kaam (1986), whose theoretical work on the power structures in information flows is particularly useful for sensitizing the embedded power dynamics in the relationship between the user input and technological infrastructures of self-tracking. Bordewijk and Kaam, writing on tele-communication systems, offer a systematic classification scheme based on two distinct dimensions of power in information flows: who provides the information, and who controls the distribution of information?

Combining these dimensions, Bordewijk and Kaam identify four prototypes of information flow: registration, allocution, consultation and conversation. Registration, a basic feature of self-tracking systems, refers to a prototypical communication pattern where users enter their own information in a system or database. Allocution—or transmission—refers to scenarios where a central information provider is the source of information as well as distribution of that information. Some self-tracking apps provide pre-tailored programs or challenges (e.g. for learning to do a daily meditation or run five kilometers in January) that the user can subscribe to and then follow, guided by the system which releases new tasks for the user day by day. This pattern holds great similarity with traditional broadcast, albeit often addressing individuals rather than mass audiences. Consultation denotes a pattern where the system provides the relevant information that the user can access at their convenience. This is the case with accumulated data input from the full user base, which self-tracking apps turn into graphs and visualizations to benchmark the individual user against the community (e.g. segments on Strava) which are then made available to the user on demand. Conversation describes situations where the user owns the information and controls what information is distributed. This is the case in the use of social networking features enabled by many self-tracking services which allow users to connect and discuss their tracking experiences with peers.

Bordewijk and Kaam’s typology of flow is not directed at the user experience, but rather at the different modes of communicating with self-tracking systems and the relative distribution of power between system and user expressed through the communication pattern. We treat their four types of flow as analytical categories that nevertheless helps us sensitizing the analysis of user experience by elaborating on how attention, hookedness, control and agency are perceived in various modes—transmissional, registrative, consultative and conversational—of practicing and experiencing self-tracking. These modes combined allow us to nuance how and to what extent self-tracking practices of repetitive registration into sequences of datafied events at the micro-level become traps of engagement sustaining or challenging specific logics at the macro-level of infrastructures.

Research design and empirical data

We conducted qualitative interviews on people’s experience of different kinds of self-tracking in order to explore what the experience of self-tracking as flow entails for users. An open-ended approach had the advantage of allowing us to explore in rich detail how self-tracking is practiced in context through the process of planning, performing and reflecting on the activity. It also allowed us to probe into the users’ experience of temporal stretching and sequencing of activities enabled by the self-tracking technology’s capacity for linking data from isolated events, aggregating them, and feeding them back to users as a comprehensive plot of their activity over time.

We recruited a purposive sample of 11 users of self-tracking in the context of exercise, mood-tracking and multi-tracking (tracking more than one activity), presuming that different kinds of activity were likely to elicit different types of flow. For instance, tracking a temporally clearly bounded activity such as exercise (e.g. going for a run or spending an hour in the local gym) likely involves a different kind of attention and subsuming than tracking one’s mood, which is always “there,” temporally unbounded, and may be reported and checked at regular intervals by an app. Exercise trackers are more well-represented in the sample, simply because this kind of self-tracking is by far the most common (Fox and Duggan, 2013). The participants used a wide range of devices and apps for their self-tracking, including Garmin sports watches attached to Garmin Connect, Withings Smartwatches, the Endomondo app for running, Clue for menstrual tracking, meditation apps, Goodreads for books, beer tasting apps, and so on.

In our sample, we included “hard-core” self-trackers, who might represent extreme experiences of dedication and flow in self-tracking, and “casual” users with clearly demarcated uses of self-tracking in activities and moments during daily life, to be able to probe variations in terms of how users enter, encounter and escape self-tracking as a flow-experience. The assumption was that casual self-tracking involves a different kind of engagement and “hookedness” to tracking-technology than hard-core self-tracking. There was a mix of men and women in the sample, and the respondents were between 20 and 60 years old. Interviewees were recruited through snowball sampling through self-trackers in our extended networks. All interviews were carried out between March and November 2017, and all participants have been pseudonymized in the analysis below.

The interviews were semi-structured, organized around seven themes which addressed the different dimensions articulated in the theoretical work on flow experiences: awareness of body, technology and data when tracking, immersion, sensations of frustration, mastery and control, feedback through consultation and allocution, attention to temporality and sequencing in tracking, conversations about tracking, and connections made between diverse forms of tracking. The interviews were recorded, transcribed, coded first separately and then jointly by the three authors according to, first, a coding scheme based on pre-developed and emergent codes regarding practices of engagement with technology and data (e.g. the use of data before, during and after tracking events), experiences of engagement (e.g. expressions of addiction, fondness, competence and frustration with self-tracking technology and data), social aspects of tracking, and respondents’ orientation to and valuation of bodily “felt” and metrically “seen” data. The material was then mapped onto Bordewijk and Kaam’s (1986) modes of communication flow to connect experiential qualities of self-tracking to the infrastructures that support them.

Analysis: experiences of flow

In the context of the Quantified Self-movement (Wolf, 2010), Ruckenstein and Pantzar (2017) have documented how the notion of “trust in numbers” remains a very powerful discourse outlining how users understand metrics generated through self-tracking as a production of a more valid and accurate knowledge about the individual self-tracker. Our data, however, do not convey an idea that the respondents simply trust in the numbers and need them to get to know themselves better. Our findings resonate with recent work on meaning-making in the context of self-tracking that points to ongoing tensions between sensory, affective and metric input in and around the activity being tracked (Kristensen and Ruckenstein, 2018; Pink et al., 2017; Ruckenstein, 2017; Sharon and Zandbergen, 2017). As a general pattern across our respondents recount an ongoing struggle or negotiation between their bodily and mental sensing and awareness of oneself, and an understanding of the metrics they produce through self-tracking as reliable cues to evaluating themselves. This tension between sensory-bodily and metric knowledge is reflected in the different communication patterns of encountering the self-tracking technologies and the pleasures and flow experiences derived from these patterns. Acts of registration, consultation, allocution, and conversation are imbued with different logics of attention, meanings, and pleasures which together inform the temporal—sequential and here-and-now—experience of flow in self-tracking.

The pleasures of registration

Our study participants track a wide range of things: from bodily issues such as sleep, movements and locations, menstrual cycle, mood, and calorie intake to personal interests such as wine and beer tasting and books they read. At the very basic level, we found that there is an experiential pleasure associated with the act of registering itself. This pleasure has much to do with keeping a record of bodily measures, moods, whereabouts, food intake, and so on. Several respondents speak of gaining a sense of control by actively deciding to track some aspect of their lives, clearly speaking to Csikszentmihalyi’s tying of flow experiences to a sense of mastery and competence. To be sure, part of this comes down to pleasures of buying and wearing a new gadget or experimenting with a new app (Neff and Nafus, 2016). This is especially so for those of our respondents who track themselves with sports- or smart watches, and who claim to have changed their gear at regular intervals simply to acquire the new and upgraded version of their preferred watch, or wanting to wear something with a certain esthetic value. But there is a value for respondents in the unique acts of registering oneself here-and-now and for future reference—whether the self-tracking involves a specific goal or not.

The pleasures involved in the very act of registration appear to be achieved through both automated and manual tracking. For Kevin (35), for instance, tracking allows him to stop thinking and free his energy to focus on other endeavors, by loading stuff off of his capacity to remember. This is similarly expressed by Richard (50), stating that “when I let go, I do not let go of my tracker, I let go of myself.” The way these respondents express “letting go” suggest they think about their relationship with self-tracking devices not as a relation based in addiction to registration, but rather as a means to free their minds from a huge workload of “keeping track.” Indeed, part of the allure of this offloading amounts to being able to go back and check out past behavior, whereabouts, sleep patterns, and so on, simply because the data are archived, registered. It is not particularly tied to acts of browsing through the archived data (cf. consultation).

Registration is further highlighted as a key motivation for self-tracking in respondents’ assertions that it makes them more aware of the actions and activities they record when they know that information about these activities is registered. The relationship between self-tracking and self-awareness is well-documented in the self-tracking literature (Barta and Neff, 2016; Lupton, 2014; Sharon and Zandbergen, 2017). We contend, what seems to lie here is the idea that registration itself serves as a simple micro-nudge toward certain behavior. This is perhaps particularly so for manual tracking, which implies actively plotting data into the self-tracking device or application, and therefore requires some degree of awareness of the relevant data input. Sandy (34) who has previously suffered from depression tracks her menstrual cycle in combination with mood tracking and explains,

It has made me more aware that I am basically a biological entity […] whose hormones control how I experience the world. Without the possibility to change that. I think that is really interesting. […] and if I can acknowledge that that is why, and not because I haven’t done my best, or am a bad person, or all these things you can beat yourself with, if you don’t perform or feel like you look like a million. It makes me sort of calm. And gives me confidence knowing, ok, it’s not you, it’s your biology.

For Sandy, bodily and mental awareness is tied to accuracy in the registration; if the intended outcome of self-tracking is to know better the relation between one’s activity or state of mind and bodily sensations, then this depends on reporting relatively precise information in the system. She knows what data voids do to a data set, as she puts it. The same is true for those of the respondents who exercise with clear goals in mind: progress in training can only be validly gleaned if they are disciplined with their registration. While in Sandy’s case, registration has enabled her to stop beating herself up about issues outside of her control, for others, such as Becky (24), registration becomes a painful reminder of less than ideal food consumption:

When, after lunch, I choose to eat two chocolate bars, and then an ice cream, and then there was cake, and a beer because it was Friday … Then I come home and register it and then I suddenly sit and think “what the h … am I doing, really.” It is a complete waste to spend half the day being healthy and then spoil it all in the afternoon.

Perhaps it is because of such experiences of sudden awareness that Becky further recognizes that she sometimes manipulates her data input to the system to make herself look better, or avoid negative—that is, not pleasurable—feedback based on accurate data input. Here registration is clearly performative, strategic and the point is not to create correspondence between actual actions (such as intake of a chocolate bar) and the digital record of calorie intake. Rather, the pleasure is in creating positive feedback loops, even if this means cheating the system by taking control over what data gets to count as real. While at first glance, Becky’s self-tracking practice appears as a case of self-indulgence, her interactions with self-tracking-systems arguably could thus also be read as belonging to a more generalized symptomatic tendency in the algorithmic cultural dynamic of social platforms such as Facebook that actively reinforce positive feedback loops¹ to keep users hooked and happy. This corresponds to performing what Pantzar and Ruckenstein (2017) call “situated objectivity,” a selective interpretation and valuation of self-tracking that fits specific contextual self-narrations.

Registration of user data is what keeps self-tracking systems going—the basis of the business model for self-tracking services: data can be used for improving the service itself and be merged with data from other services owned by the company or sold to third-parties. Therefore, users must be motivated to continue producing data—and self-tracking systems have other ways to “hook” the user than simply offering templates for manual or automated registration: personalized feedback based on accumulated data that the user can consult on demand, or the system can push to the user (allocution) at given moments during and between activities.

Allocution: system-initiated feedback as moments of interruption

If the promise of registration draws users to begin using self-tracking systems, the allocative and consultative features of self-tracking tap into the experiential qualities of self-tracking by homing in on data-based feedback provided by the system to the user. Feedback comes in the forms of “push and pull,” suggesting different logics of attention to self-tracking and data analysis, which in various ways draws the user further into the systems, or presents sources of annoyance.

Allocution refers to the ways in which the self-tracking device pushes information to the user in-between tracking sessions, for instance, by reminding the user to register something, and while tracking something, for instance, by reporting running pace or pulse in the moment. It differs from consultation by being system-initiated communication. In the case of our respondents, allocution took the form of guiding a meditation or dictating interval pace and length in a running session. This to some extent corresponds to having a personal coach, and it may be a relief to delegate the responsibility for a specific activity to the system, as suggested by Richard (50) and Max (26). By soliciting and pushing information, the system invites the users’ attention to turn (back) to self-tracking—to get the user back in flow, so to speak. Yet, for the respondents, allocution is often perceived as disruptive.

Tessa (21) asserts about system-initiated feedback during running:

Actually, I like my watch to be as discreet as possible, if you will, so it does not influence me too much but that it is more up to me to decide when I look at it. That the watch does not remind me to look at it.

She further contends that she has customized the screen to show only the values that she wants to know (e.g. pace, time and distance of a run). One might argue that Tessa thereby has tried to take charge—to make the process of allocution mimic consultation so her sports watch provides relevant information that she has selected and only at her convenience. Customization of the what and when of allocution may be seen as users’ carving out small niches of agency in a communication pattern where they are largely left to the constraining control of the system.

In some instances, the pushed feedback during an activity is seen to offer valuable input to the respondents. If feedback is positive, for example, demonstrating that the runners in our sample are keeping a strong pace, receiving this feedback feels motivating, uplifting, and be integrated in a seemingly pleasurable experience, because it confirms a sense of mastery and competence in the situation (as was seen above). But at other times, when providing negative feedback, it appears distractive, even detrimental to the experience of running itself, for instance, by making the workout feel longer and harder. Paula (56) complains,

I’m out having a good time running, and then this voice-thing goes on. If it tells me that I am performing worse than my average, I start thinking “I have run too slowly,” and then it ruins my experience of running.

This is also the case for other types of self-tracking. As Richard (50), who suffered from stressful periods in the past, puts it, “The awareness that my pulse was high MADE it high. It was self-perpetuating, and I did not realize until long after. But in the situation it was actually harmful.”

In the above outlined examples, it becomes clear that while the communication with self-tracking devices can both be used as pleasurable distraction, allocution mechanisms can also serve as a source of frustration and discouragement that turns playful activities into tedious labor (Etkin, 2016; Lupton et al., 2018; Patel and O’Kane, 2015). Elaborating existing work on this, we suggest that it is not self-tracking per se, but allocution as a specific mode of communicating with the system that drives the experience of self-tracking as hard work.

Finally, allocution appears to present instances where participants have most often come to doubt the accuracy of their data, typically when it presents “evidence” that contradicts their bodily sensations. Lauren (28) recalls her Garmin watch predicting a certain half-marathon pace: “it tells you, based on your current pace, you should be able to run it at this and that pace, and that is like twenty minutes too fast.” Others say they doubt on their self-tracker’s ability to measure, for example, steps taken or sleep patterns correctly, and become frustrated when this doubt is confirmed. The system-initiated communications seem to have little resonance as a meaningful reference point for strengthening the engagement with self-tracking and for fuelling curiosity to begin exploring the generated data. While requiring the user’s (partial) attention in the moment, instances of allocution serve best as simple and not too frequent reminders that data on the self are being collected and processed. As such, they become emblematic of the flickering focus and attention to the technology that appears to characterize respondents’ self-tracking practices. It is tempting to connect the respondents’ largely critical responses to allocution to the fact that, allocution is the mode of communication in which the user has the least control.

Consulting the system: checking in to confirm bodily sensations

The story of consultation is somewhat different. Instantaneous feedback during activities, specifically exercise, serves as a point of departure for elaborating consultative communication with self-tracking systems, often with a view to attaining better performances. When the respondents talk about their self-tracking practice during their habitual exercise, they talk about it as a mindful and bodily experience, echoing Csikszentmihalyi’s (1990) description of optimal experiences as creating a state of flow. They refer to ongoing sensing of what they can do during the activity and adjusting their exercise accordingly, and about losing themselves in the running rhythm and the bodily motion. Self-tracking simply serves to keep in check: “do I move at the pace I am feeling” (Emily, 27), or as an add-on before and after training (e.g. how much workout did I actually do/do I have to do, based on the previous sessions?). If the bodily feeling is what matters, this reflects a sense of mastery of the body and thus no need to gain self-control via a digital device. In that sense, metrics become marginal. After all, as one male respondent contends, it is difficult to keep record of the bodily feeling unless you write manual notes. The trust in bodily sensations of mastery or challenge during self-tracking is—not surprisingly—more pronounced among the advanced recreational athletes in our sample. They may be thought of as “elite bodies” who through exercising have achieved a strong bodily awareness which may not be the norm. Previous studies of self-tracking have found that many self-trackers, including, for example, newbies in exercise, lean heavily on technology in order to fulfill their tracking goals (e.g. Lomborg and Frandsen, 2016). In our sample, the only respondent with that kind of closely controlled, technologically backed, self-tracking is Christy (34) who is about to do an iron man.

While for some, the affordances of devices for datafying exercise entail a sense of mastery, for others it entails a sense of unwanted pressure, expressed in active resistance to the allure of consulting the numbers. “I will not let the numbers make me doubt myself” (Lauren, 28). It also involves a sense of obligation, as reflected in one of the male participants contending that “I should reflect more on my data” (Ryan, 26), to make his exercising less based on ad hoc feelings and more based on strict metric control of, for example, his running pace, distance, and so on.

Together, this suggests that respondents have an ambiguous, and multifaceted, relationship with their tracking devices and data: while respondents practice their sports according to a habitual sense of time, metrics impose themselves on this practice, offering no particular extra assets apart from providing documentation for the activity.

Yet, metrics also matter positively in specific contexts; thus, for instance, for the exercising respondents, metrics provided by their running watches have strong, even crucial, value when they participate in a race. Here, the respondents report more active pace-control based on declared goals of finishing times, for which the self-tracking technology becomes indispensable.

Thus, our data suggest that there is a fine line between respondents’ sense that self-tracking technology helps them perform and thus enhances the experience, and disturbs, imposes on the experience, and that this fine line is largely defined by the specific here-and-now context of self-tracking.

If self-tracking tools create value (for users and systems alike) through aggregate—sequenced—tracking data, which may, for instance, be used to optimize some activity or conduct, we were surprised to find that for our respondents, looking and playing with their data was limited. Respondents do not seem to think much about the relationships between individual tracking events through data sequences (e.g. benchmarking a run against the previous one). Specifically, very few report tinkering with their data, using the analysis features of their self-tracking apps, for example, to generate insights into developments in their tracking over time. When respondents do consult their tracking devices to look across events, it is to plan ahead rather than look back. In the context of exercise, some schedule specific types of exercise across sessions when planning the coming week, but simply in the manner of ensuring an appropriate balance between different kinds of exercise and exercise and rest in the week ahead. The women who track their menstrual cycle naturally have some sense of temporality included in their tracking and consult their menstrual tracker to check upcoming fertile periods and bleeding patterns. Kevin, who is particularly interested in craft beer consults his tracked beer tastings to inform the choice of what beer to taste next. Self-tracking devices’ promise of providing tools for optimizing oneself through analysis and reflection of previous behavior is contested by usage practices, which in our case appear very instrumental and directed at coming events. Arguably, respondents’ metrics play a marginal role as a feature to consult for self-reflection; respondents simply keep practicing their habitual ways of doing things.

Patterns of allocution and consultation sensitize us to the push and pull of attention in self-tracking, and how these dynamics of tracking support or disturb the experience of doing a certain activity in the here-and-now. The data suggest a main hook on the users is achieved in the production of positive feedback loop, micro-nudges that come to augment the self-tracking experience. In some instances, the consultative features prolong the experience, but not in the way intended by the design of the self-tracking technology, and specifically the features for data analysis, looking back and learning from past events and tracking patterns. Rather self-tracking prolongs and emphasizes practical awareness of things to plan for, thus serving as organizing tools for the day-to-day tasks and activities of the users.

Peers in conversation, data in conversation

The last communication pattern in Bordewijk and Kaam’s (1986) typology is conversation between users, mediated by a central unit, in our case the self-tracking system. Many such systems enable users to connect with like-minded peers for on-site social networking, data sharing, and support. Few of our respondents make use of these features, notable exceptions being Christina (34) who systematically sends her data to her personal coach who analyses them to optimize Christina’s preparation for an iron man contest, Max (26) and Ryan (26) who share data because they are preparing for a contest together, and Lauren (28) who sometimes shares running data with her ex-boyfriend. He was the reason she began to run in the first place, and they maintain a good relationship through occasional small-talk around her improvement. All these examples testify to specialized, small dyads or communities being facilitated around self-tracking. These social dimensions may enhance the experience as has been documented by Lomborg and Frandsen (2016), but they certainly do not appear a strong driver, a hook, for self-tracking as such. Instead, respondents largely consider self-tracking technologies and data as very close to the personal sphere. Self-tracking is experienced as a relationship between “me,” ‘my data’ and “my device,” whereas the social world and the broader circulation of data in digital networks become secondary or outright irrelevant concerns. If self-tracking is part of a dedicated but—to our users—temporally and contextually delimited and repeated practice this suggests a different form of “hookedness” or flow than promoted by companies.

There is another dimension to conversation that goes beyond Bordewijk and Kaam’s (1986) original idea, namely the notion that data themselves can enter into conversation with other data as they traverse the digital infrastructures in processes of data consolidation. The mutual enrichment of different types of data, cross-tracking, does hold value for some of the “hardcore” self-trackers in the sample, in particular by creating “slots” of activity and for slacking across tracking regimes. Richard (50), wanting to avoid gaining weight, asserts,

The Fitbit app went on par with MyFitnessPal, and then I systematically started measuring everything I ate, counting calories, and then it was fantastic that when I had walked for one and a half hours, I could see that I could eat a whole lot of chocolate if I wanted to.

The quote articulates a sense of pleasure in bringing different data sets into conversation at will. Such “data conversation” may be goal-directed, as in the case of Richard’s, or it may serve as a means to reach plausible explanations of patterns in the data, as seen in the case of Sandy’s (34) combining of menstrual and mood tracking to understand why she sometimes, at regular intervals, feels a little down. Both examples illustrate that cross-tracking, too, is seen to be directed at oneself.

Self-tracking is apparently not considered an activity where users are part of the infrastructuring of a commercial market through having their data repurposed, as described in Lupton’s (2017) work on “lively data.” It is noteworthy that the respondents express no specific interest in or concern for the system, commercial power logics undergirding their tracking practices, which are pointed to as key in the theories of flow above. Commercial logics of sequentiality and data sharing are not part of the vocabulary of these users, supporting Lupton’s (2017) findings about the users’ lack of concern for the commercial value of their data.

The temporalities of flow

Self-tracking apps seek to tap into and enhance user motivation, by offering repositories for monitoring, keeping track of development of one’s own results, sharing them with one’s peers and perhaps using them to optimize behavior or mental states over time. Our study clearly challenges the idea of “hookedness” as something installed or achieved by way of technology itself. The promise of optimization has been documented in analyses of the discourses of the market of self-tracking and in the quantified self-movement that has fuelled much public and scholarly interest in self-tracking (Berg, 2017; Ruckenstein and Pantzar, 2017; Schüll, 2016). The intentions of optimization seemingly inscribed in self-tracking technology differ from respondents’ actual usage practices. Users seem content with their current level of mastery of their activity, more than development, and are happy to validate their sense of competence with metric data. This warrants further discussion of why, then, the respondents keep using self-tracking devices as part of their daily activities. What is it that hooks the user, if anything?

Ongoing validation through metric feedback arguably supports a feeling of confidence in users’ pursuits, but in a sense, what comes across in our study is that the lock-in of users with self-tracking technology evolves around the basic act of registration. Put bluntly, users track themselves because they can, and can do it easily. The pleasure and the motivation to keep going is in the very basic feature of technology, the promise of creating and keeping a repository, a data log of one’s activities, by imprinting a personal history of mood, food intake, sleep pattern, or book reading in a digital system. Regardless of the infrastructures of data collection, aggregation, circulation, and repurposing that lie at the heart of the business model of digital self-tracking technologies, and the timely critical scholarly and other work that has emerged as a response to datafying infrastructures, we also need to understand and acknowledge the agentic pleasure that fuels the choice of tracking and building a personal record of something. If anything, the mode of registration is where the system logics present themselves most discretely: particularly in the case of automated registration the system simply runs in the background and is not invoked beyond being turned on and off, in the case of manual registration, it provides a registration template that organizes the data input but does not “speak back” to the user in the same manner as seen in consultation and allocution.

Referring back to sequential logics of flow, as seen in Williams’s and Dow Schüll’s works in particular, we posit that the idea that sequencing keeps the user “hooked” holds explanatory potential in the study of self-tracking. Basically, the pleasure of continuous registration is undergirded by a sequential logic of communicating data input to the system, which, by extension creates a lock-in between user and system. Flow manifests itself as the interplay between sequenced streams of data and the users’ engagement with the system across extended periods of time. At the same time, however, “flow” also manifests at the level of the individual event of tracking by way of real-time feedback solicited by the user. While in a sense, feedback interrupts the flow of events, the small punctuations of individual events against the horizon of extended data streams may exactly be considered as the series of micro-nudges that keeps the user in data production mode. As Natasha Dow Schüll (2016) shows, many technologies today operates within a gamified logic of flow which is designed to keep users on their platforms through real-time “micro-nudging.” Within this logic, the small punctuations of, for instance, registration function as singular, yet addictive, micro-events that, combined, hook the user in a constant state of data production. As our study show, this continuous, yet sequenced, state of data production often plays an ambiguous, and multifaceted role in the lives of self-trackers. To some, it is experienced as pleasurable and playful practice that can help them enhance autonomy in their practice, while others experience it as a disturbing presence that entraps and controls them, thus threatening their sense of agency.

Experiences of inherent meaningfulness and frustration are constant, and thus the same user can move from annoyance to pleasure depending on the context. Despite these variations, however, the self-trackers’ constant flow of data remains an unequivocal benefit of the data platform, which offers algorithmic technologies not only as functional tools of registration, but also as affect modulators, helping people to manage their moods and anxieties by way of temporalized stimulus responses in recursive loops.

Annoyance and discouragement, especially experienced in the mode of allocution can lead to disengagement and strategies of non-use in the form of active resistance (Lazar et al., 2015). As several scholars of non-use of technology have pointed out, such strategies cannot be interpreted in a void, but are inherently linked to the role a specific technology plays in the broader forms of social engagement (Satchell and Dourish, 2009; Selwyn, 2006). To understand the difficult line allocution mechanisms must tread between motivating and disengaging users, one must therefore also understand the role of the broader social and communicative role of tracking mechanisms and the values they convey in terms of success and failure. Indeed, as Pepita Hesselberth (2017) notes, such inquires not only have to contend with the social structures of the device itself, but also the means by which one interrogates these structures, since the types of inquiry into non-use, qua its primary focus on the role of individual agency, often ends up uncomfortably feeding “into the paradigm of datafication from which the one who disconnects arguably precisely seeks to withdraw.” The coupling of Bordewijk and Kaam’s analytical framework with Dow Schüll’s more structurally oriented perspective on flow mitigates this risk, by lodging the data-driven surveys and taxonomies of self-tracking within a larger critical framework of how platform capitalism, with its constant calls for connectivity, operates today.

Combined, different small-scale dynamics of communicating with the system show how the algorithmic logics of self-tracking both extend traditional forms of flow, but also transform the temporal structures of sociality in new flow dynamics. The flows of self-tracking transform the classic problematic of the temporal rhythms of human versus machine into a much more complex ensemble of temporalized communication flows among intelligent devices, among devices and humans and among humans and humans. In the context of self-tracking this means that any meaningful analysis of flow requires us to take into account not only human experience or material infrastructure, but rather how humans and machines interact and condition each other.

Such an approach offers us the opportunity to challenge the narratives of modernity that pits mechanical and metric time against contingent human time and opens up new ways of exploring how self-tracking is woven into the temporal fabric of our culture. It shows that the temporal flows of self-tracking technologies give rise to fantasies about on the one hand the dispersion and marginalization of human agency; but simultaneously, on the other hand, also produce new investments in what it means to be a sensing human, and new forms of mediated sociality.

Conclusion

Our existence is “technologically textured” not just at the broad-scale level but also in the “rhythms and spaces of everyday life” (Ihde, 1990: 1). The scenes of self-tracking we have just analyzed combined provide us with a succinct sense of their temporal complexity, and how this temporal complexity is both entangled in the monotonous throbs of everyday life and subverts these through the individualized data flows taking place between user and device, between device and device and between user and user.

The notion of “flow” provides an analytic space for exploring, empirically, the intricate relations between agency, pleasure and self-surrender in these temporalized scenes of self-tracking. We have based the analysis in Bordewijk and Kaam’s typology of different modes of acting with and exercising power in the (self-tracking) system and coupled it with theories of flow as developed by Raymond Williams and Natasha Dow Schüll. We contend the framework is specifically productive for articulating the micro-levels of users’ experiences of temporality, feedback and agency in self-tracking practices, while also opening up to the macro-dimensions of these individual experiences in relation to self-tracking communities, self-tracking platforms and other self-tracking apps. We thus see how users find pleasure in the simple acts of registration offered by the self-tracking technologies, but also how these simple acts of registration become entangled in more complex affective processes of machine and social feedback that are experienced by the user interchangeably as disturbing and pleasurable and sometimes both these things at once. Some users not only use the singular acts of registration to create a truthful data mirror of their past behavior, but also manipulate their individual acts of registration, exactly to produce a more “positive” flow through the complex feedback loops sustained by the self-tracking technology.

Finally, flow sensitizes us to different capacities and valuations of agency in the communicative relationship between user and system. Users seem more hooked on self-tracking when they experience a level of control and agency, vis-à-vis the affordances of the system for guiding self-tracking, pushing processed data back, and inviting users to use their data for self-development. If the system pushes its regime of optimization too hard, it fails to connect: optimization may not be the main goal, after all.

Footnotes

Authors’ Note

Nanna Bonde Thylstrup is now affiliated to Aarhus University.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

ORCID iD

Stine Lomborg

Author biographies

Stine Lomborg is an associate professor in communication and IT at the University of Copenhagen. Her research focuses on how people use self-tracking and social media in personal and work life, and the implications of these uses for contemporary datafied living.

Nanna Bonde Thylstrup is an assistant professor in aesthetics and culture at Aarhus University. works on the infrastructures and politics of digitization and the uncertainty of big data. She is the author of The Politics of Mass digitization (with MIT Press).

Julie Schwartz holds an MA in communication and IT from the University of Copenhagen.

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