The chapter uses the self-monitoring of menstrual cycles via an app as an example for an exploration of the ways in which people engage with data and its ambivalences in their daily lives. Period-tracking apps allow for the tracking and visualising of all kinds of personal data and offer a digitised, ‘smart’ version of the well-known menstruation calendar. In addition to insecurities emerging from ‘taming’ the uncertainties of (menstruating) bodies via quantification and algorithms, the unanticipated collection of user data by private companies and the potential surveillance raise issues of privacy and data security. This chapter will address these two forms of insecurity by drawing on material from an ongoing empirical study into the everyday use and discussion of period-tracking apps in Germany. For those interviewed, the negotiation of data insecurities can encompass an increased body competence, idiosyncratic interpretations of data or ignoring predictive deficiencies just as attempts of sidestepping dubious data collection or impositions of an algorithmic understanding of menstrual normalcy. Hence, the chapter gives insight into the multi-faceted ways people live with datafication and contributes to everyday perspectives in critical data studies.
- Mobile apps
- Quantification of the self
- Menstruation/menstrual cycle
- Data privacy
- Everyday life
Application software for mobile computing devices forms part of the numerous digital technologies that pervade and mediate everyday life. Given the normalisation of the use of mobile apps to support, extend, delegate, or reorganise all kinds of mundane tasks and routines over the last ten years, daily life has been increasingly “appified” (Morris & Murray, 2018). Out of the multitude of available mobile apps, period trackers provide the exemplary case considered in this chapter on everyday data practices around the use of apps. Besides being an integral part of everyday communication and everyday life, mobile apps, in conjunction with smartphones take part in the ongoing creation of data (sets) by and about people, their devices, and interactions. Voluntarily or involuntarily, app or smartphone users leave data traces and participate in the generation of data or data profiles about themselves in different ways. Whereas providers of mobile apps rely on such data as a valuable resource and prized commodity, the unanticipated collection, distribution, and utilisation of user data by private corporations (and states) have become the subject of public debates on privacy issues and data ownership. Overall, mobile apps and devices can be understood as mundane tools of “datafication” (Cukier & Mayer-Schoenberger, 2013: 35) and are elements of the socio-technical systems or “data assemblages” (Kitchin, 2014: 24–26) that organise contemporary data practices and are a principal subject for critical data studies.
Within critical data studies’ heterogeneous examination of the impact and challenges of data and its power in society (see Iliadis & Russo, 2016) calls have been made to pay more attention to the everyday experience of (big) data (see Michael & Lupton, 2016; Ruckenstein & Schüll, 2017; Kennedy, 2018). Scholars studying the wide array of digitised self-tracking practices underpin this focus empirically and complicate the picture of datafication, data power, and dataveillance on the level of the everyday by pointing to the ambivalent effects and appropriation of data technologies and dataflows (e.g. Weiner et al., 2020; Pantzar & Ruckenstein, 2017; Fiore-Gartland & Neff, 2015). In addition, Helen Kennedy links the importance of research on how people engage and live with data to the endeavours of data activism: “One of the main purposes of exploring how ordinary people experience datafication in their everyday lives is to develop understanding of their perspectives on how they might live better with data” (Kennedy, 2018: 21, emphasis in original). I join this literature’s concern to take a closer look at datafication and “its agential possibilities” (Ruckenstein & Schüll, 2017: 268) from an everyday perspective, and thus broadening perspectives in critical data studies, by using a genre of mobile apps as an entry point for examining mundane data practices.
Drawing on empirical material, in particular interviews with app users, I will explore how people encounter menstruation with and through data. App-supported period tracking provides an interesting example because of its commonness, its non-digital precursors and its banality (not triviality) in terms of self-tracking. Further, it is insightful regarding typical data traces produced through mobile app usage and regarding its enmeshment with the sociocultural circumstances and the gendered politics of birth control—turning the question of safe use in a twofold matter. To illustrate, I will begin with situating the app-genre of period trackers, the motives of users, and the promises of app-providers by outlining the sociotechnical constellations in which app-mediated menstrual self-observation as an everyday engagement with data unfolds. Then, I will discuss two critiques that regularly come up in public discussions about period trackers, which address two forms of data insecurity.
The first kind of insecurity concerns the promises and failures of measuring and ‘taming’ bodily processes with self-tracked data, quantification, and predictive algorithms. It addresses the reliability of bodies as data repositories (Lupton, 2013), the accuracy of algorithms just as the confidence of app users interpreting data and aligning their embodied selves with their data(fied) bodies. The second kind of insecurity concerns the question of what data apps reveal to whom and who can use the data entered into the app for what purpose. It brings the ambiguities of dataflows, commercial data collection, and issues of privacy to the fore and addresses the ways app users deal with the accompanying “intimate surveillance” (Levy, 2015) or “dataveillance” (van Dijck, 2014). Both insecurities do not pertain to period trackers alone. The first applies in particular to mobile apps that allow the monitoring of bodily processes and support self-tracking practices but ties in with wider discussions of the calculability of the body and the self. The second is a central subject in considerations of mass data collection and consumer tracking for commercial purposes (be it via mobile apps or web cookies).
Exploring how interviewed app users in Germany make use and sense of period trackers and menstruation data while negotiating the two insecurities involved, this chapter will show the multi-faceted ways people with periods engage with data in everyday life. Their narratives point to ambivalences resulting from the tension that app-related data present both a source of insecurity and security. Moreover, their accounts of becoming entangled with, while pragmatically tackling, datafication and its challenges in the field of appified menstruation indicate a reflexive (data) practice. In this way, this chapter aims at contributing to new perspectives in critical data studies that pay more attention to the contingencies and contradictions of people’s daily involvement with and understanding of data. Such an approach encourages the reframing of dominant narratives about the data(fied) worlds we live in and to envision alternative forms of living with data.
Material and Methods
The analysis presented here draws on an ongoing case study of digitised period tracking that is part of a broader ethnographic study, in which I explore the cultural dimension of software, data, and algorithms, especially with respect to body-technology relations. The empirical material has been created in the process of my “polymorphous engagement” (Gusterson, 1997: 116) with period trackers since 2017. It consists primarily of conversations with menstruating people in Germany, with a focus on those who track their period and use an app to do so. Further, it includes a mix of online app reviews and discussions of period trackers in different (social) media, my (self-)testing of apps,Footnote 1 and the participation in events of/with actors involved in the education and counselling of sexual and reproductive health and rights. For this chapter, I focus on the manifold conversations I had with app users. Of these, six were formal interviews of 1–2 hours that were audio recorded and, to a varying degree, included an engagement with the participant’s respective app/smartphone. Yet, most of these ongoing conversations about experiences with menstruation and period trackers took place in a less formalised manner and occurred rather impromptu in diverse social settings and interactions as part of my daily (private and academic) life. These informal ethnographic interviews range from a vast number of brief exchanges of a few minutes to, by now, 23 more focused conversations of 15–30 minutes, which I recorded via memory logs or notes on the spot. In terms of demographics, participants were between 18 and 44 years old, identified themselves as women, mostly as heterosexuals, and are—due to the bias of recruiting through personal networks and snowball sampling—largely educated, middle class, and white. To take into account the diversity of forms and experiences of app-supported period tracking, I did not limit recruitment to a specific purpose—like the use of fertility tracking apps in trying to conceive (e.g. Hamper, 2020) or of period trackers supporting the symptom-thermal method in order to prevent pregnancy (e.g. Rotthaus, 2020). Despite the dissemination of period trackers, it is important to remember that not all people with periods track their cycles, nor do those who track their periods use an app to do so.
Situating Period Trackers and Period Tracking
Period trackers, also known as menstrual cycle apps, ovulation trackers or fertility tracking apps, help to record, monitor, and forecast menstrual cycles. They have names like Ava, Clue, Cycles, Eve., Flo, Glow, Kindara, Magic Girl, Maybe Baby, My Calendar, Natural Cycles, Ooops!, Ovy, Period Calendar, or Women’s Log and are considered part of the booming field of health and wellness apps, which promise to coach healthy users in their self-care. Increasingly launched since 2012,Footnote 2 they also filled a biased gap: fitness and health trackers of the time allowed collecting all kinds of body data but left out menstruation. Period trackers range from simple calendar programmes to more advanced applications that support fertility awareness methods. They draw on long-established practices of monitoring menstruation and a familiar tool—the menstruation calendar, of which the apps represent a digitised and extended version. Based on a user’s self-observation and logged data the apps calculate and predict the onset of period, estimated ovulation and fertile window, and (pre)menstrual symptoms. To a differing degree, these apps include user community features, additional information on menstrual health, and the possibility of sharing period data with ones’ intimates or to connect with wearables. They all edit and visualise a user’s menstrual data by means of colourful icons and charts and above all offer a broad variety of tracking categories that cover, besides bleeding, numerous symptoms and complaints associated (more or less) with menstruation as well as information on sexual behaviour, mood, fitness, health, or lifestyle. In terms of business-models, some period trackers are part of a larger company, others rely on venture capital (Rizk & Othman, 2016), and most of those that are for free are heavily supported by advertising however, subscriptions models seem to be on the rise.
Situating Period Trackers as Gendered Technology
When one takes a window shopping tour at one of the app stores, one can be overwhelmed as much by the number of available period trackers as by the quantities of pink, flowery-lovely-girly-cute design. The colour scheme of period-tracking apps has been a source of amusement or annoyance in some of my interviews, has been mocked in many reviews, news and social media pieces, and has even been taken up in the tagline “reliable, scientifically based and definitely not pink” with which the app Clue was introduced in 2013. Yet, the feminised design is only one aspect illustrating menstrual cycle apps as a gendered technology that reflects and reproduces gender stereotypes and social norms.Footnote 3 The “gender scripts” (Rommes et al., 1999) or inscribed designers’ imaginations of (potential) uses and users entail the ways theses apps address and judge users as well as socio-cultural ideas of menstruating people, which might correspond with some users, their experiences, or aims of period-tracking but marginalise, exclude, or simply annoy others.Footnote 4 Built-in gender assumptions are reflected as much in the apps’ focus on fertility, pregnancy, family planning and heterosexuality as in the vocabulary and symbols that are used to present tracking categories, menstrual information, or remind users via push notification. Obviously, there are more binary systems at work in these apps than binary code.
Although several research participants stated that they have decided for a specific period tracker “for aesthetic reasons” and app creators inevitably react to gender stereotypes by carelessly reproducing, playfully appropriating, or deliberately avoiding them (see also Klein, 2020), choosing a period-tracking app is about more than an individual consumer decision based on personal preferences of design. As one interviewee explains: “I don’t mind the pink or sometimes silly icons, which certainly do not meet everyone’s sense of humour, right […] as long as the app does what it is supposed to do. […] help me to keep an eye on my menstruation, to know where I am in my cycle and to be somewhat in control” [ptiv5]. Regardless of why research participants pay attention to their menstrual cycles, the subject of control or lack thereof came up in almost all conversations eventually. For this 27-year-old (and other interlocutors), controlling one’s period is about being able to handle bodily processes, which are recurring yet tend to be or are perceived to be unreliable and raise questions about what is considered normal. For her, control also means being able to deal responsibly with sex: “Of course, period tracking is first of all about understanding your cycle and body. But in the end it is quite often about the dread of potential pregnancy, isn’t it?” [ptiv5]. In line with the dominant marketing of period trackers as an aid to control one’s fertility the practice of period tracking becomes part of the interviewee’s (contraceptive) “fertility work” (Bertotti, 2013; Kimport, 2018). The individual wish to keep an eye on one’s cycle and the apps’ offer to get to know one’s body with the help of data must hence be placed in the wider socio-technical arrangements and gendered politics of period tracking and sexual reproduction—period trackers are enmeshed in both, body and data politics.
Resonances in Observing and Measuring Menstrual Cycles
In addition to offering fertility monitoring to achieve or avoid pregnancy, app providers invite users to get to know their bodies better. While the idea of learning about one’s body (self) conjures up memories of the feminist legacies of the women’s health movement of the 1970s,Footnote 5 the idea of perhaps not having numbers but data as a (superior) form of self-knowledge resonates with contemporary promises of quantified self-measurement. That the idea of measuring and knowing (and often improving) oneself is older than the public discourse around the recent Quantified Self movement suggests, as Crawford et al. demonstrate (2015), by juxtaposing the introduction of the domestic weight scale at the early twentieth century and current wrist-worn fitness trackers. Schmechel, who discusses self-measuring from a gender perspective, even views menstrual self-observation shaped by the development of the menstruation calendar as a precursor to today’s quantified self-tracking (2016: 148–150). Although such comparisons are instructive, there are differences in terms of measuring menstrual cycles.
Two of my interlocutors firmly distinguished period tracking from fitness-related self-tracking, which would be aimed more at optimisation or self-improvement: “The wish for better apprehending and feeling more in control of one’s body is perhaps similar. But you cannot improve your cycle” [ptiv4]; instead, period tracking can help you to “feel less at the mercy of menstruation” [ptst17]. Moreover, in contrast to sensor-equipped self-tracking devices, which make invisible bodily processes visible and render them into digital data (Lupton, 2018: 2), period trackers cannot rely on a continuous recording of physical conditions and body activities.Footnote 6 Rather, users estimate qualities (e.g. how strong is the bleeding, how is my skin, hair and mood) or check boxes (e.g. had [unprotected] sex, headaches, voracious appetite) in order to log their observations and activities before those can be processed and quantified by the app. While the apps’ tracking categories surely preconfigure what users should observe, log, and how it should be classified, users have to enter metrics (values of self-measurement) manually. This extra effort creates uncertainty, but also more opportunities to tinker with (Mol et al., 2010) or “curate” (Weiner et al., 2020) the self-generated data records—in the spirit of self-care.
Motives, Benefits, and Promises of App-Based Period Tracking
The reasons research participants expressed about their wishes to track their menstrual cycles via app vary and can change over time. In the following, I outline some of the typical reasons they provided. I present what interviewees appreciate about period trackers and their app-mediated engagement with menstrual cycles. Finally, I discuss the role of tracking data and apps as hubs.
Reasons for Tracking Menstrual Cycles
The most frequent reasons given for period tracking were getting to know one’s body and getting “a better picture” of one’s cycle. Meaning to “recognise more clearly how the menstrual cycle works” [ptst5] and to understand how one’s own body is responding to menstrual processes. Comparable to other forms of self-tracking, gaining body knowledge through data was for many research participants about identifying patterns and understanding co/relationsFootnote 7—for example, concerning their fertility, well-being, or troubles in specific phases of their menstrual cycles. Interestingly, they described their app-based learning about their body equally often as a purpose and a side benefit of using a period tracker. For several, this included realising how much they actually do not know about menstruation.
In addition to the motive of learning and the above-mentioned concerns of controlling fertility, interviewees emphasised the possibility that they could “check quickly the cycle in between”. For example, one interlocutor used a period tracker “to have less random sex to get pregnant” [ptst8]; checking the app/cycle daily was essential for her to realise her goal. More common was a “glimpse in between”, in order to not be surprised when the period starts, “whether tampons or condoms should be taken on a weekend-trip” [ptiv3], “when to better not schedule a visit to a sauna or the beach” [ptst11], to know “everything is okay, nice and regular” [ptst20] or that one is not pregnant. These reasons for tracking menstrual cycles concur with the outcomes of a study in the U.S. (Epstein et al., 2017). Also mentioned was the motive to answer the standard question of gynaecologists (When was the first day of your last period?) without having to think twice. Although this was a statement regularly made tongue-in-cheek, it points to period tracking as an established everyday practice that is entrenched in gendered medical regimes of knowing and controlling menstrual cycles and menstruating bodies/people.
Benefits of Using an App
Among my research participants were those for whom period tracking was a routine before they used an app and those who only began regular period tracking through one. Some started out with recording “the typical information” (first and last day of period, strength of bleeding), yet were encouraged to log further details by the app’s diverse tracking categories and frequency of prompts to insert more data. Others depicted the first few months with the app as playful exploration before deciding what to monitor—often after realising “the amount of work all the tracking means” [ptst14]. Over time, quite a few reduced their logging to a few aspects or “decided to restrict data entry to the bloody days and 2–3 PMS-days prior to that” [ptiv6]. Except for those who use the symptom-thermal method and, therefore, must be disciplined self-trackers, research participants described tracking routines of varying discipline when reflecting on their app-related data practices. In these descriptions, comparisons with other (non-digital) forms of menstrual observation were common.
According to interviewees, period trackers are “more fun but also more sophisticated than the good old paper version” [ptiv4]. An app allows them to “record all that actually happens” and offers information “with a few swipes”, “in nice graphs”, or “in the form of a neat overview”. Besides increasing the calendar’s availability through the smartphone, the app does the calculating and predicting, is perceived as “less schematic”, often includes a glossary, encyclopaedia, explanatory articles or “even scientific reference”, and, last but not least, “involves you differently” in dealing with the menstrual cycle. As to the different involvement through the app, two points regularly came up: the data visualisations and the push notifications. All interviewees welcomed (and were often fascinated by) the functions of processing tracking data, making it visible in charts or diagrams, and showing forecasts and connections. This would help them to become more aware of their menstrual cycle as a cycle and of patterns, which they may have only imagined or never considered. There was more disagreement regarding the push notifications. While some appreciated these reminders as an occasion for self-observation and for “getting more involved” with their cycle, others stated that notifications that especially prompted log entry can “turn into an obligation one is kind of dragged into” [ptiv4]. The “tone of the app” perceived as either supportive, intrusive, or disciplinary also appeared in various images or ambivalent roles interlocutors attributed to their period trackers—for example as a daily companion, advisor or backup, as fusspot or “clever calendar, which for better or worse speaks back” [ptst1].Footnote 8 Regardless of the app-user relationship, research participants highlighted their app-mediated engagement with data as a positive, notably “new way” of dealing with menstruation.
The Promise of Data and Smart Algorithms: To Be on the Safe Side
The helpfulness of data is, according to taglines and self-representations, exactly what providers of period-tracking apps promise. To illustrate, I quote four popular period trackers:Footnote 9 The above-mentioned Clue invites you to “Find the unique pattern in your cycle” and offers “an algorithm that learns from the data that you enter. The more you use it, the more intelligent it gets” as well as period, PMS and fertile window “predictions, you can trust”. Glow presents a data-driven ovulation calculator that “helps women take control of their fertility” and “predications that become smarter over time”. It asks potential users if they “[W]ant a period tracker or a woman’s health app you can rely on for detail and accuracy?” to confirm, “We’ve got you covered.” Natural Cycles summons potential users to “take birth control in your own hands” by “track[ing] your cycle naturally and effectively” with “the only birth control app that is cleared by the FDA in the US and CE-marked in Europe as a medical device”. Finally, Flo advertises that users can “log over 70 menstrual symptoms and activities to get the most precise AI-based period and ovulation predictions”. Self-observation paired with personalised calculations and data-driven accuracy, self-knowledge through aggregated data and ‘learning’ algorithms—this sounds promising and fits in well with what research participants expect from or value in period trackers.
Overall, app users consider (their) period-tracking apps to be valuable as both a tool to find out more about themselves (thus creating or adding to self-knowledge) and a more graspable and formalised form of self-observation. Referring to the often felt waywardness of the human body in general and menstrual cycles in particular, some described the app and the insights gained as assuring support or as a backup of self-perception. Several felt better informed since using the app and stated that the calculations and visuals of data (i.e. displays of PMS clouds, typical cycles summarised in numbers or that “today is your calculated ovulation”) would particularly help them to feel more certain and confident. As one of them put it, it is “like an insurance against failure” [ptst9]—failure understood in the sense of “getting it [her body or interpretation of hormonal processes] wrong”. Very often, interviewees used in this context, the German phrase sicherheitshalber [for good measure, just to be on the safe side], a word regularly used in everyday life for all kinds of precaution that contains the German word for security in its root word. By contrast, insecurities were associated with menstruating bodies rather than data.
The idea that data provide a better access to bodies than other forms of self-knowledge or self-observation (Lupton, 2013; Berson, 2015) ties in with cultural beliefs of what counts as secure or accurate information. Participants’ reliance on data points less to the alleged data fetishism commonly associated with self-trackers than to the historically established appeal of quantification in modern societies (Porter, 1995) or to the medical model of knowing and its “medical gaze” (Foucault, 2012). The notion of the body as something that is measurable, understandable, and manageable through data or assessable and judgeable in comparison with norms has a long history intertwined with biomedicine as well as its critique (Lock & Nguyen, 2010). It might not be surprising, therefore, that participants’ narratives echo understandings of the body as a source or depot of data, which technology helps to read, visualise, and make sense of. In contrast to the “reading” of their bodies through self-perception, interviewees often considered data provided by their period tracker to be more “reliable”, “objective”, and “credible” (see also Ruckenstein, 2014: 10). Some used this approved credibility of (visualised) data for their own purpose, such as to support their subjective claims or actions towards a doctor or a sexual partner. The view that menstrual data is not only useful but also gives a sense of confidence and security is where the wishes of users and the advertising of app providers meet. The promise of period trackers is one of self-knowledge and security through accuracy and, as a result, self-empowerment by enabling users to take control over assumed chaotic bodily processes with the help of up-to-date science and technology. In other words, it is a story that once again tells of either the utopian character of or the mythically charged belief in (big) data and datafication (boyd & Crawford, 2012). So what is the problem, when apps provide what users ask for?
Critiques of Period Trackers’ Smartness: Two Safety Concerns or Data Insecurities
With its rising popularity,Footnote 10 menstrual cycle apps have increasingly become the subject of warnings in the media. Both the apps’ smartness and the privacy of the data entered gave rise to criticism. In Germany, the results of a test of 23 popular period trackers by the state-funded German Foundation of Product Testing received a lot of attention. They had rated most of the tested apps as “faulty” because of their predictive deficiencies and, in addition, had classified many of them as “critical” regarding privacy (Stiftung Warentest, 2017).
Unwise Algorithms and Old Methods Repackaged
Dealing with the question of how reliable period trackers are in predicting ovulation and fertility (and, therefore, how good they are for achieving conception or contraception), medical studies detected that the apps’ algorithms are in most cases neither particularly smart nor precise (e.g. Duane et al., 2016; Moglia et al., 2016). Most apps not only lack independent, scientific studies proving their efficacy but also base their predictions primarily on the average data of previous cycles while ignoring information on the current one (Freis et al., 2018). These tests call into question the extent to which most period tackers actually present an improvement (ibid.). To understand what went wrong with the smart determination of fertility, one should go back to the pen-and-paper version of period tracking. Schlünder (2005) has convincingly shown that today’s well-known menstruation calendar resulted from a medical dispute in the 1920s over the question of how to calculate “female natures” and eventuated in the calendar-based contraception method by Knauss and Ongino in the 1950s. The method demands the recording of at least 12 menstrual cycles and applies the retrospectively gained data of the longest and shortest cycle in order to estimate the length of the pre-ovulatory infertile phase, the fertile days, and the start of the post-ovulatory infertile phase. In other words, the method is about recognising a pattern in retrospect and draws on menstrual data from the past to forecast the next ovulation and fertile window. A rough estimation, though, does not count as a safe method of birth control. Considering normal menstrual cycles varying between 21 and 35 days, (inter)individual variability of cycle length, normal fluctuations and diverse activities influencing ovulation (e.g. travelling, illness, sport, lack of sleep, alcohol—simply life as it is lived), predicting distinct fertile windows with retrospective data and mathematics or statistics is a rather risky business—regardless of whether a human or an app calculates.
Various professionals in the fields of gynaecological care, family planning, and sex education, who I met during my research, viewed period trackers as an old method repackaged in shiny new clothing and their use (especially among young people) with concern. Albeit controversial, the German Professional Association of Gynaecologists even attributed an increase in the number of abortions in 2017 to the use of menstrual cycle apps (BVF, 2018). In a similar vein, the app Natural Cycles, marketed as an effective hormone-free contraceptive method, hit the headlines in 2018: In Sweden, a large hospital reported that 37 of 668 women, who sought an abortion in the last quarter of 2017, claimed that they had been relying on the Natural Cycles app for birth control (Wong, 2018). The app includes the basal body temperature, measured and entered by users in the morning, and informs users whether it is safe to have unprotected sex. Yet, despite this extension of data, again the app only considers previous cycles for predictions (Freis et al., 2018: 5).Footnote 11 Not all period trackers employ calendar methods. In the test carried out by the German Foundation of Product Testing, the three apps judged best (“good”) were those based on the symptom-thermal method. What is also known as Natural Family Planning (NFP) employs parameters of the current cycle (self-observation of bodily signs such as temperature and cervical mucus changes) to determine fertile days. If applied correctly, it is considered a safe (albeit marginalised) method of birth control—which works well for some people but requires daily, disciplined, and differentiated self-observation/-analysis and requires knowledge, instruction, effort put into learning, and regularity.Footnote 12 The key benefit of an NFP-app is that it analyses the data for the user. Among research participants, only a very few employed this method in conjunction with their app.
Critical Dataflows of Intimate Data
In addition to failing to deliver on their promises of predictive power, apps are just as often, if not more so, criticised for their problematic data collection and sharing practices. For instance, Burke (2018) warned “Your Menstrual App Is Probably Selling Data about Your Body!” and drew on insights by a project of the Brazil-based feminist digital rights organisation codingrights.org on “How to turn your period into money (for others)” (Felizi & Varon, n.d.). Likewise, other NGOs advocating for digital rights, privacy, and data protection (e.g. the Tactical Tech Collective, the Electronic Frontier Foundation or Privacy International) have analysed the data-sending and security properties of period trackers in more detail and detected flaws in several of them, such as invasion of privacy and data protection issues. Most period trackers collect an enormous quantity of data and meta-data, share parts of this data without specifying with whom, or allow extensive third-party requests (Rizk & Othman, 2016; Quintin, 2017); some were even exposed as having automatically transferred data to Facebook or other third-party services (Privacy International, 2019). It is for reasons like these that period trackers have been in the limelight recently: as vampiric violators of privacy that profit from sensitive user data (Kresge et al., 2019). Subsequently, in response to this bad press, several app providers updated their privacy policies and some made changes to their data-sharing practices. However, machine learning-based systems can access an increasingly larger database of intimate data. It seems to be the case the creators of these apps would rather develop algorithms that process period-tracking data for commercial purposes (such as targeted advertising, data brokering, and analytics) than to improve those that predict fertility.
Negotiating Data Insecurities—Pitfalls, Lessons Learned, and New Competences
Nonetheless, my interlocutors are among the many people who do use period-tracking apps. In view of the criticisms, one could easily sketch out a story of passive users delegating tasks to their apps and relying against better knowledge or judgement on false promises of security. Yet, this would neither do justice to the thoughts and practices of research participants nor help us in understanding why users tolerate app-related data insecurities, participate in sharing data, or find period trackers valuable (see also, Sharon & Zandbergen, 2017). So how do the interviewed app users encounter the two outlined forms of app-related data insecurities?
Data Insecurities 1: Understanding Menstruating Bodies with and Through Data
While interviewees changed their period tracker when they disliked changes to app features after an update or got annoyed with the way the app addressed them (“I am 29, I am not an Ovy-girl!”), they expressed hardly any concern with the ways in which the app actually arrives at its calculations. Just as in other cases of mundane technology, many simply trusted or assumed that their app would work properly. As mentioned above, interlocutors view period trackers not merely as calculators to which users delegate tasks but as “a new way” or as an additional instrument to deal with the insecurities of their menstruating bodies and feel more knowledgeable and certain about it. As an instrument of sorting, evaluating, and makings sense of individual bodily experiences, which guides participants in “having everything in black and white” and to help “sharpen” or “underpin” self-perception, the value of its use enfolds between the poles of self-empowerment and normalisation (see also Rotthaus, 2020) and the poles of security gained by self-awareness or by misguided certainty. Some interviewees reflect quite critically about the persuasive and normative power of data and its visualisation through the app: In particular, the constant display of the cycle (three months in advance) would easily eclipse inherent uncertainties of calculated probabilities. Yet in the accounts of research participants, insecurities are neither only caused by bodies nor simply resolved by data.
Rather, insecurities arise when participants align their embodied selves with their data(fied) bodies, that is, when they match their self-perception and own interpretations of tracking data with the predictions and the analysis of their apps. This process of “continuous synchronisation” [ptst7], to put it technically, is not a smooth process. Some took potential or occurring discrepancies lightly and the apps’ output as a “rough orientation to think with”, others found it “hugely unsettling”. The expressed insecurities indicated and depended on a varying distance or proximity to the app/data-based mediation of one’s body through default tracking categories. Nonetheless, and as already mentioned, all interviewees emphasised that their experience of the menstrual cycle has changed through app-based period tracking and generated learning processes, which resulted in an increased or new body competence.
Ironically, for several participants, this very competence included the possibility of emancipating themselves from the app to a certain extent. Moments of questioning the app’s translation of intimate experiences into quantified data points were underpinned by self-awareness, everyday empiricism (e.g. when the app’s predictions were implausible or repeatedly wrong), and newly acquired self-knowledge. For instance, one 20-year-old interviewee learned through her app and became interested in the variable nature of cervix mucus during the cycle. While she finds the symptom-thermal method “too much effort and inapplicable” for her, she started self-observing and logging cervix mucus shifts as well as searching for further information. As we met, she stated proudly that (now after a year) she would confidently assess the app’s calculation of her ovulation. “It’s like a game: does the app get me right?” she says. The fact that the app’s prediction is not always correct according to the interviewee’s self-observations has not yet caused her to change the app or to stop engaging with its calculations: “Do I get my cycle right, is [or remains] an important question, too.” This and other examples in my material show that while period trackers cannot shake off all the insecurities involved in the taming or the making sense of menstruating bodies/selves, they include for some users the opportunity to move with the app beyond the app. Several participants decide on a case-to-case basis if they give more or less weight to the app’s interpretation, while others simply ignore its estimations or recommendations.
One the one hand, interviewees find their period trackers convenient, helpful, and trust technical solutions, on the other hand do not passively place blind faith in mobile apps. For most of them, delegating tasks such as fertility calculations to an app does not mean to delegate personal responsibility, such as contraception, for example. At this point it should be noted that the accusation of a naïve or irresponsible behaviour (here the use of technology such as period trackers) is by no means new, especially in the culturally and politically charged area of contraception, and is once again directed solely at menstruating people (here users of period trackers). In sum, period trackers are another tool for research participants to get to know themselves and better live with menstruation, nothing more, and nothing less. What is new is that this tool makes users more knowledgeable through data but also “more knowable to an emerging set of data-driven interests” (Crawford et al., 2015: 495).
Data Insecurities 2: Sidestepping the Vague Privacy of Logged Data
While the non-users I met more often criticised or suspected privacy issues in sharing intimate data with period trackers, the app-using interviewees rarely brought up the issue themselves. Some noted that they made use of the option to password protect access to their app/data but did so without considering the cloud storage of these data, even though they all know, their “private dialogue” with the app is not limited to their mobile phone. Their attitudes and actions can be characterised by the “‘privacy paradox’ where intentions and behaviours around information disclosure often radically differ” (Shklovski et al., 2014: 2347). Quite a few waved off or shrugged their shoulders when asked about uncertainties emerging from sharing menstrual data and said this is neither a specific problem with period trackers, nor an occasion for them to worry. With more or less regret, they framed such privacy risks to be “part and parcel” of using mobile apps and devices. In regard to this tendency to normalise unanticipated data collection, use, and surveillance, Levy (2015) and Lupton (2015) have elaborately problematised the extraction of data on bodies, sexuality, and intimate relationships. It remains a central challenge in retaining and reclaiming privacy and autonomy in times of the databased commodification of users (see Véliz, 2020).
It was only when I followed up on the subject during our conversation that participants started to reflect on what they actually know or want to know about the whereabouts of their data, why it matters to them, or whether they should be more concerned. Lately, though, there seems to be slightly greater awareness. This also became apparent when I recently asked someone whether we could continue our talk in an interview and immediately got the response, “Ah, I bet you want to talk to me about data protection problems, don’t you?” [ptsm24]. Like some others, this interlocutor was attentive to insecurities regarding privacy but was not too concerned as she “doesn’t share everything” with her period tracker. To clarify her attitude, she remarked on occasions where it became obvious through the app’s prompts and recommendations that the app “doesn’t capture me completely correctly” and that it was “in some areas, in the dark”. Like her, some decide with caution which information they share, omit, or enter incorrectly, “Why should I tell my period tracker about my hours of sleep, party life or libido?” [ptst21]. Yet, these forms of intentional non-disclosure were rare. More frequent were less intentional data gaps that resulted from irregular or partial tracking or from simply forgetting to enter personal data. Some pointed out these gaps when explaining that they do not view their random data points as particularly valuable to companies that try to make sense of their fragmented data doubles—distinguishing: “this is my data, but it’s not me” [ptst13].
The most data-conscious interviewee I have met so far had distinctly looked for an “uncritical” period tracker. She chose one of the few that allows for the use of the app without a personal account (a precondition for cloud data storage, which others appreciated as backup of their data). Storing period data only locally on her phone meant for her that she was able to maintain a certain sense of control of her data. Albeit, though, once her phone had broken and made her feel quite insecure: “I was really crushed, I can tell you… I lost my menstrual history! Three years of properly documenting my cycle, [snaps her fingers] just gone” [ptiv2]. Starting over with a new phone and a “blank” app, she worried about the accuracy of predictions of an algorithm that would not yet know or, rather, had forgotten to know her. She almost regretted opting-out from cloud storage, but after a while realised that having a long record of cycles was less important than she thought—both for herself and for the app’s calculations. Instead, the data loss led her to question the personalisation of the predictions she received from the app as well as the personal values of a “menstrual data history”. “[Mostly] it’s something the app suggests, [speaks in different voice]: ‘give us data, [app name] is getting smarter…’ I rarely use the app to look back. Thanks to my regular cycle, the averages displayed are not that surprising after all. I didn’t keep my paper menstrual calendars either.” With respect to addressing and approaching the second kind of app-related data insecurity, this interviewee was an exception. In contrast to the first form of data insecurity, research participants appeared to be less interested in gaining knowledge in this (ambivalent) aspect of their period trackers.
This chapter took period-tracking apps and menstrual self-observation as an entry point for exploring everyday data practices and the ways app users engage with insecurities of and through data. In juxtaposing the critical public discussion of period trackers with evaluations by my research participants, the chapter discussed two forms of insecurity with respect to period-tracking data and apps. These insecurities concern for one, the datafication of menstruating bodies, and for the other, the risks involved in sharing intimate data with an app and making it available to unknown others. In comparison, the former generates more agential possibilities and moments of confidence for users than the latter. The first form of data insecurity emerges where bodies are incalculable or where embodied selves and datafied bodies mismatch. It addresses the limits of period trackers’ offer to counter the lack of control over the body with data and help users feel, if not in control of, at least less dependent on menstrual processes based on these data. The second form of data insecurity arises from the fact that what happens to data entered into the app is mostly beyond app users’ control. The two kinds of data insecurities put emphasis on different app-related data practices—either, on data practices with mobile apps such as the ways in which users engage with apps and data to obtain their aims, or on the data practices ofmobile apps, such as the ways apps allow app providers (or third parties) to gather and distribute data. In terms of both insecurities, the overall verdict on period trackers is that most of them are in a twofold way, not safe to use. This, however, does not stop users from using them. As far as the two insecurities are concerned, for my interviewees, the experienced benefits of period trackers outweigh their experienced or perceived harm. As I have shown, users deal with the ambivalences of data and app-related insecurities in their own way.
Such forms of engagement with data provide a good starting point for everyday perspectives in critical data studies. Examining how app users experience app-mediated menstrual cycles and negotiate the uncertainties of data-driven predictions and untrustworthy dataflows allows for the problematising of overly simplistic stories about processes of datafication. Surely, participants’ gained body competence, their moving beyond the app’s predictions, their evasion of sharing data, and even their deliberate ignoring of it cannot stand in for a counternarrative of subversive app users resisting the quantification of bodies, the persuasiveness of data (visualisation), or the flipside of using an app’s cloud storage facility. What I told instead, based on my empirical material, was not a story of gullible users but of pragmatic uses. The accounts of interviewees’ equally carefree, wayward, and reflexive use of period trackers tell of their being empowered and caught up through data as well as their enmeshment with and participation in the sociotechnical constellations of app-based data use. My findings show how people in their daily lives embrace data technologies such as apps while tackling the possibilities and imponderabilities of datafication but also point to the powerful arrangements and conditions in which their data encounters take place.
The practices, with which research participants put up with the deficiencies of period trackers in terms of data insecurities (in particular the second form), do not seem to leave much room for optimism. For this reason, I would like to end on a positive note. In 2019, the Bloody Health Collective, a feminist open-source project based in Berlin, launched the beta version of drip to provide a more secure, transparent, and non-commercial alternative to available period trackers. In January 2021, they released a redesigned and the first stable version of the app. Underlined by slogans like “your data, your choice” or “your body is not a black-box” the app only stores data locally on one’s phone and is based on the symptom-thermal method. It invites users to look into the workings of its algorithm/calculations and reminds them that they do not need an app to understand their cycle. Regarding the two data insecurities, this, indeed, seems to be an app that is safe for users. I cannot predict how successful this app will be, or whether it will have any impact on the period tracker genre. Although such an intervention may only provide a safe period tracker for users actively seeking one, such new forms of feminist data activism also provide a possible alternative for imagining how life with data and its power could be otherwise. Everyday perspectives in critical data studies can contribute to such efforts of data activism by exploring people’s experiences of and practices with and through data in order to understand how people live and could better live with data (to return to Kennedy’s proposal quoted in the beginning of this chapter). Engaging with the mélange of the datafied everyday, life can not only empirically expand critical data studies, but also help reshape the circumstances in which data is used.
In order to better understand, compare, and get a feeling for different period trackers, their features, functions, and ways of addressing or guiding users, I tested several popular period trackers [on an Android device] and those my interlocutors mentioned, each for about 3–5 months. In the course of the process, I came across the “walk-through method” proposed by Light et al. (2018), which provides a good systematic for what I was doing in the wild and helps with assessing the embedded meanings, norms, scripts, and ideal use(r)s of apps.
Despite earlier examples, e.g. Period Tracker (launched 2009) or Maybe Baby (2010), there was a boom of period-tracking apps in 2012/2013. Moreover, several share a similar foundation narrative (Fluhrer, 2018: 48–53, 59–65).
See Faulkner (2001: 83–84) for an overview of how technological objects are gendered symbolically or materially to varying degrees.
This applies not only but particularly to queer, non-binary, and Trans people with periods or to those who are infertile or not interested in procreation. In 2013, the crowdfunding campaign for mcalc (iOS), a “gender neutral menstruation calculator”, which “can be used by almost everyone regardless of their gender identity” and “is inclusive with the LGBTQA community” failed. Apparently, the project and existing beta version for Android got shelved (https://www.indiegogo.com/projects/mcalc-for-iphone#/).
The women’s health movement also opposed the objectification of female bodies by patriarchal medical authority (we are our bodies) and considered self-knowledge as a way to gain control over “our bodies/ourselves” and medical technologies. Becoming knowledgeable rested upon the collective compilation of scientific information but also on sharing personal experiences (see Boston Women’s Health Collective, 1970). Ford (2019) discusses in what way period-tracking apps take up this feminist legacy by offering self-knowledge via technology.
There are period trackers that include sensors or measuring systems that record the basal body temperature or hormones in the urine. I do not consider these apps/systems in my research or this chapter.
Differentiations between types of self-trackers, e.g. “pragmatic and enthusiastic self-trackers” (Gerhard & Hepp, 2018), provide an interesting template for comparison but they need to consider the socio-cultural specificities of documenting menstrual cycles.
A more detailed analysis of the app-user relationship captured in these images would take me in this chapter too far afield. Ambivalent feelings towards period trackers were common; see also Hamper (2020: 11).
The quotes are from the blurbs used on websites and app-store presentations of the respective apps.
It is necessary to note that apart from the high download numbers displayed in app-stores, public figures on the actual user-base or regular uses of period-tracking apps are lacking.
Later that year, Swedish authorities cleared the app because they could confirm the indicated failure rate of 7 per cent but asked the company to state the risk of unwanted pregnancy more clearly (Leonard, 2018). Since then, some other period trackers also notify users that they should not use the app as a contraceptive method.
Against the background of growing criticism of (the side effects of) hormonal contraception in Germany, there seems to be a new interest in the method. Rotthaus (2020) studied German users of NFP-apps, who turned to the method as a liberating alternative to the pill because it is hormone-free. For details on NFP, its reconfiguration of bodies, technologies, and gender relations in the 1980s as well as the involved mode of knowledge production see DeNora (1996).
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Amelang, K. (2022). (Not) Safe to Use: Insecurities in Everyday Data Practices with Period-Tracking Apps. In: Hepp, A., Jarke, J., Kramp, L. (eds) New Perspectives in Critical Data Studies. Transforming Communications – Studies in Cross-Media Research. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-96180-0_13
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