10.6092/issn.2038-3460/17442
Self-tracking technology is considered a critical learning and motivational resource that at best helps people self-reflect, thereby promoting attempts to make changes to lifestyle routines. This study examines how people incorporate this technology into their daily practices and the routines that self-tracking technology produces. The study is based on an indepth empirical analysis of a sample of interviews of volunteer participants of a pilot study aiming to promote health and wellness. The interviews took place in two phases: first, after three months of self-tracking (in total 27 interviewees) and second, at the end of the pilot study after ten months of self-tracking (in total 21 interviewees). The analysis focused on the participants’ reflections on their user experiences of a self-tracking device, the data that this produced and the resulting routines. The results suggest that people’s self-tracking routines are often related to the maintenance of a visible and continuous data flow in self-tracking applications. Routines for wearing, tending to and communicating with self-tracking devices play an important role. These routines are either only remotely related or not necessarily at all related to making changes to lifestyle routines that affect health and wellness. The development of routines through novel artefacts involve much invisible work and can even lead to unintended consequences. During self-tracking, the focus may remain on the technology alone and on attempts to develop routines for maintaining a continuous, accurate flow of data, rather than on actually making lifestyle changes.
application/pdf
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Sari Yli-Kauhaluoma
https://creativecommons.org/licenses/by-nc-sa/2.5/
Tecnoscienza – Italian Journal of Science & Technology Studies
self-tracking
Reflections on Self-tracking Routines: Conducting Maintenance of Digital Data
Text.Serial.Journal
https://tecnoscienza.unibo.it/
10
Essays
2020-01-30
2023-06-26
2020-01-30
2023-10-09
53-78
TS
Sari Yli-Kauhaluoma
2019
10.6092/issn.2038-3460/17442
53
Aalto University
2038-3460
2
self-tracking
en
78
Reflections on Self-tracking Routines: Conducting Maintenance of Digital Data
https://tecnoscienza.unibo.it/article/download/17442/16292
10
                                                                                Essay
Reflections on Self-tracking Routines:
Conducting Maintenance of Digital Data

Sari Yli-Kauhaluoma
Aalto University


     Abstract: Self-tracking technology is considered a critical learning and mo-
     tivational resource that at best helps people self-reflect, thereby promoting
     attempts to make changes to lifestyle routines. This study examines how
     people incorporate this technology into their daily practices and the rou-
     tines that self-tracking technology produces. The study is based on an in-
     depth empirical analysis of a sample of interviews of volunteer participants
     of a pilot study aiming to promote health and wellness. The interviews took
     place in two phases: first, after three months of self-tracking (in total 27 in-
     terviewees) and second, at the end of the pilot study after ten months of
     self-tracking (in total 21 interviewees). The analysis focused on the partici-
     pants’ reflections on their user experiences of a self-tracking device, the da-
     ta that this produced and the resulting routines. The results suggest that
     people’s self-tracking routines are often related to the maintenance of a vis-
     ible and continuous data flow in self-tracking applications. Routines for
     wearing, tending to and communicating with self-tracking devices play an
     important role. These routines are either only remotely related or not
     necessarily at all related to making changes to lifestyle routines that affect
     health and wellness. The development of routines through novel artefacts
     involve much invisible work and can even lead to unintended consequences.
     During self-tracking, the focus may remain on the technology alone and on
     attempts to develop routines for maintaining a continuous, accurate flow of
     data, rather than on actually making lifestyle changes.

     Keywords: routines; artefacts; health and wellness promotion; pilot study;
     self-tracking.

     Submitted: December 19, 2018 – Accepted: October 8, 2019
     Corresponding author: Sari Yli-Kauhaluoma, Aalto University, School of
     Business, Department of Management Studies, P.O. Box 21210, FI-00076
     Aalto, Finland. Email: sari.yli-kauhaluoma@aalto.fi




TECNOSCIENZA
Italian Journal of Science & Technology Studies
10 (2) pp. 53-78 - ISSN 2038-3460
www.tecnoscienza.net                              2019
54                                                           Tecnoscienza – 10 (2)

1. Introduction

     Health care settings are hoping for an overall shift in emphasis from
routines of reactive treatment to routines of the proactive prevention of
diseases and the maximization of people’s wellness. These hopes are ma-
terialized in, for instance, emerging P4 medicine, which stresses the role
of individuals’ health data as predictive, preventive, personalized and par-
ticipatory (Hood and Friend 2011). P4 medicine aims for behavioural
changes to lifestyles that at best result in routines that add to health and
wellness. People today are encouraged to actively collect their personal
data because these are considered the “best (yet often ‘untapped’) re-
source for information” on themselves in general, and their own states of
health and illness in particular (Wyatt et al. 2013, 132). Here, self-
tracking devices that enable real-time tracking are considered important
artefacts that support monitoring, documenting and analysing various as-
pects of daily life, such as activity and sleep, which affect health and well-
ness (e.g. Swan 2012). Self-tracking devices thus allow datafication, that
is, the transformation of social action into online quantified data (Mayer-
Schönberger 2013). The resulting personal data can act as a critical learn-
ing and motivational resource that at best may help people self-reflect and
thereby improve their attempts to make changes to their lifestyle routines,
in turn contributing to better health and wellness.
     This study recognizes routines as patterns of action and refers to
Feldman and Pentland (2003), who note that in addition to the routine in
principle, i.e. the generalized idea of a routine, there is the routine in
practice, i.e. the enactment that brings the routine to life. The role of arte-
facts is considered essential in the production and reproduction of rou-
tines (D’Adderio 2011). This is because they are seen to offer an ‘invita-
tion’ for action simply by being there and being available (Callon and
Muniesa 2005). At the same time, artefacts may act as important media-
tors or intermediaries in routines while organizing or even transforming
the knowledge, skills and capabilities of their users (Latour 2005). As
D’Adderio (2011, 210) points out, “the actor’s knowledge, skills, and
competences depend on – and are at the same time configured by – the
tools and artefacts they encounter or involve into their routine perfor-
mances”. This does not mean that artefacts completely determine actions;
instead, artefacts may act as an enabling or constraining source, making it
easy and possible to do some things or difficult and impossible to do oth-
ers, including the creation of particular routines (e.g. Orlikowski 1992).
     The deployment of novel artefacts that support particular routines or
even routine change is not, however, easy. The designers and promoters
of behaviour change technologies face challenging questions not only re-
garding usability (can the users use the technology?) and user engagement
(does the technology meet the users’ needs?) but also on the long-term
effects of the technology (Stawarz and Cox 2015). Thus, one of the key
questions in terms of routines is whether the technology supports the de-
Yli-Kauhaluoma                                                             55
sired routines or routine change, in other words does the technology ac-
tually work for its user?
    The existing literature has noted that self-tracking technology pro-
vides an infrastructure that “allows for both reflexivity and a creation of
flexible routines” in a personalized manner (Lomborg and Frandsen
2016, 1019). At the same time, recent studies have acknowledged a lack
of understanding of how people generate and interpret their self-tracking
data, as well as of how they incorporate it into their daily routines (Pink
et al. 2017; Lupton et al. 2018). Moreover, it is important to recognize
that digital data may well be broken (Pink et al. 2018). This means that
incomplete, inaccurate, contingent, fractured, or dispersed self-tracking
data may affect the type of routines that self-tracking technology produc-
es.
    This study aims to contribute to the discussion on self-tracking rou-
tines through an empirical investigation of how the users of self-tracking
devices reflect on their routines related to this technology. The context of
the study is a large pilot initiative aiming to promote health and wellness.
In the pilot initiative, the advancement of individuals’ lifestyle changes
played an important role, and to support the volunteers’ attempts to rec-
ord and potentially change their health- and wellness-related routines, in
particular activity and sleep, they received an activity wristwatch, the
Withings Activité Pop, which is a self-tracking device with a connected
smartphone application (Withings Health Mate). This study is based on
an in-depth analysis of a sample of interviews of the pilot study partici-
pants. The analysis focused on the participants’ reflections on their user
experiences of the self-tracking device, the data that it produced and the
resulting routines. To obtain an understanding of how the participants
incorporated this technology into their daily practices and the routines
that the self-tracking technology produced, the interviews had two phas-
es; first after three months of self-tracking, and second at the end of the
pilot study after ten months of self-tracking. The interviewees consisted
of three different types of pilot participants: those with no previous expe-
rience of self-tracking, those with extensive prior experience, and those
who were extreme in their self-tracking.
    The results show how in the interviews, the pilot study participants
mainly reflected on the self-tracking routines that were related to main-
taining a visible, continuous data flow in their smartphone applications.
Some participants were also concerned about the accuracy of their data
and tried to invent ways in which to gain more reliable data. The routines
for wearing, tending to and communicating with their self-tracking devic-
es played an important role in the participants’ reflections. Interestingly,
these routines were either only remotely related or not necessarily at all
related to the original aims of the application of the self-tracking device in
the pilot initiative, i.e. the improvement of activity and sleep routines con-
tributing to health and wellness. The results thus suggest that developing
routines through novel artefacts involves much invisible work and can
56                                                           Tecnoscienza – 10 (2)

even lead to unintended consequences. Instead of promoting lifestyle
changes, the focus may remain on the technology alone and the aim may
be the development of routines for maintaining a continuous, accurate
flow of data.


2. Self-tracking Routines

    There are several disciple-specific literatures on routines. This study
addresses the literature developed in organization theory, which recog-
nizes routines as patterns of action. Feldman and Pentland (2003) have
emphasized three interrelated and important aspects of routines; the os-
tensive and performative aspects of routines and the related artefacts.
They define (2003, 101) the ostensive aspect of a routine as “the abstract,
generalized idea of the routine, or the routine in principle”. These can be
taken-for-granted norms, normative goals, or may exist as codifications in
various forms of artefacts consisting of guidelines, rules or templates for
behaviour. Importantly, however, they remind us that such codifications
are not unified objects; instead, people always have their own subjective
interpretations and understandings of the ostensive aspect of a routine.
Health and wellness promoters, for example, may consider self-tracking
devices artefacts that contain a template for data collection routines that
allows self-reflection and thereby potentially also the improvement of
changes to lifestyle routines (see Lupton 2014). The subjective interpreta-
tions of device users, however, can vary from seeing self-tracking devices
not only as a tutor helping in the formation of routines, but also as a tool
to build statistical records, for instance, or simply a toy that is fun to play
with (Lyall and Robards 2018).
    The performative aspect of a routine, defined by Feldman and Pent-
land (2003, 101) “consists of specific actions, by specific people, in specif-
ic places and times. It is the routine in practice”. They note that the per-
formative aspect of a routine is inherently improvisational, as it can be
adjusted to changing contexts. People may choose to use self-tracking de-
vices in different ways in different situations. Studies show that people
use self-tracking devices for various purposes; for example, to document
their activities, to reach various goals ranging from behaviour change to
effective training, to gain support for self-reflection and self-care, or to
detect patterns and causal relationships in various health-related matters
(e.g. Li et al. 2011; Rooksby et al. 2014). Artefacts that only contain os-
tensive aspects of routines become meaningless if the routines have no
performative aspect. If people are indifferent to self-tracking data and do
not find the use of the device meaningful at all, they may even abandon
the device completely (Ledger and McCaffrey 2014; Nafus 2014).
    Importantly, routines also contain internal dynamics. Feldman et al.
(2016) note that in routines, action is always situated. This means that
routines are always enacted at specific times and in places in particular
Yli-Kauhaluoma                                                             57
sociomaterial contexts. Pink et al. (2017), for instance, have shown how
people appropriate their self-tracking practices into their cycling routines.
Feldman et al. (2016) stress, however, that situated action requires a great
deal of effort, and people need to be knowledgeable and often also reflec-
tive while accomplishing routines. It is not easy to generate the same pat-
terns of action time after time. Instead, there is a constant struggle to deal
with simultaneous pressures of replication (to copy exactly) and innova-
tion (to make variations or changes) (D’Adderio 2014). Thus, as Feldman
et al. (2016, 508) point out, “stability in routines is both a matter of per-
spective and a matter of time”. They emphasize that stability is always an
accomplishment, and at best, routines can only be stable at a given time.
Ledger and McCaffrey (2014) have noted that many users completely
stop using devices for self-tracking routines after a few months, which
means that the devices do not necessarily succeed to drive long-term rou-
tine engagement.
    Intentional routine change has been at the centre of many practition-
ers’ attempts and is also the interest of research (e.g. Dittrich et al. 2017;
Glaser 2017; März et al. 2017). Guidelines for healthy living, which are
seen as advice for managing our bodies and lifestyle changes, are plenti-
ful, and people often falsely consider changing everyday routines to in-
volve simply, straightforwardly and easily putting knowledge into practice
(Lindsey 2010). Routines change as a result of “people doing things, re-
flecting on what they are doing, and doing different things (or doing the
same thing differently) as a result of the reflection” (Feldman 2000, 625).
Reflective talk has shown to support routine change through envisaging
and evaluating alternative patterns of possible actions as well as alterna-
tive ways of enacting a routine (Dittrich et al. 2017). The role of artefacts
has also proved important in intentional routine change (e.g. Iannacci
2014; Glaser 2017; März et al. 2017). As Pentland and Feldman (2008)
have shown, however, shaping routines through the design or implemen-
tation of novel artefacts is not easy, nor necessarily successful. As they
note, the risk of failure is particularly high when artefacts are developed
by those who do not participate in the routines themselves, and when the
perspectives of those who enact the routines are completely ignored. As
an example, technological artefacts are often designed only for particular
versions of the human body: the action options of the same technological
artefacts can be quite different, for instance, for a disabled body (see
Scarry 1985; Bloomfield et al. 2010). The adaptation and customization of
technological artefacts for better support of routines or routine change
can also be difficult due to the ‘power of default’ of such artefacts (Koch
1999; Pollock and Cornford 2004; D’Adderio 2011).
    To develop self-tracking routines, it is essential that people gain data
that are ‘lively’, something that they can reflect on and consider somehow
meaningful in their daily lives (e.g. Lury 2012; Lupton 2016). It is im-
portant to note that users of self-tracking devices do not perceive their
data as uniquely objective and true, and self-tracking can produce a varie-
58                                                         Tecnoscienza – 10 (2)

ty of meanings and values of data for people, from mindfulness and re-
sistance to digital storytelling (Sharon and Zandbergen 2017). Similarly,
self-tracking devices do not necessarily operate in a straightforward man-
ner in health and wellness promotion: they may serve as conversation fa-
cilitators through the production of situated data that become meaningful
through people’s reflection on them in the context of their everyday lives
(Pantzar and Ruckenstein 2017).
     While using self-tracking devices, both experienced and inexperi-
enced users may, however, experience serious difficulties in their at-
tempts to track and reflect their personal data (e.g. Rapp and Cena 2016;
Yli-Kauhaluoma and Pantzar 2018). Data collection and recognition of
behaviour patterns and trends can be burdensome and time consuming
(Li et al. 2011). Data interpretation, i.e. extracting meaningful infor-
mation from self-tracking data, is not necessarily easy and may require
clear tracking strategies or even various material workarounds (Choe et
al. 2014). The users of self-tracking devices may even encounter data that
are broken, i.e. inaccurate, incomplete, or dispersed across different digi-
tal platforms (Pink et al. 2018). This means that self-tracking devices and
the data that they produce may require continuous maintenance and even
repair routines. As long as the artefacts work, however, maintenance and
repair routines often remain invisible (e.g. Shapin 1989).
     Jackson (2014, 221) has noted that we ought to “take erosion, break-
down, and decay, rather than novelty, growth, and progress, as our start-
ing points in thinking through the nature, use, and effects” of the arte-
facts around us in everyday life. The artefacts around us can be fragile
(Connolly 2013) and they usually collect traces of consumption (Gregson
et al. 2009). Object maintenance requires care tasks that entail both con-
stant watchfulness (Denis and Pontille 2015) and user competences
(Gregson et al. 2009). When breakdowns and malfunctions occur, they
are not necessarily easily fixed (Graham and Thrift 2007); repair often
involves situated interaction between the social world and material possi-
bilities, which need to be examined carefully (see Jarzabkowski and Pinch
2013; Mitrea 2015). The digitality of objects complicates things even fur-
ther and undoes professional boundaries not only between making and
using (Suchman 2014), but also between making, using and repairing
(Denis et al. 2015). Tanweer et al. (2016) have shown that the mainte-
nance and repair of digital data is ordinary work for those who are pro-
fessionally involved with complex data sets. They show how working with
digital data requires data manipulation, improvisation and even innova-
tion for dealing with and repairing continuous data breakdowns.
Yli-Kauhaluoma                                                            59
3. A Study of Self-Trackers’ Accounts of Routines in a
Health and Wellness Pilot Initiative

    The design and implementation of various types of health interven-
tions in the form of pilot studies or trials (e.g. Hood et al. 2015; Lynch
and Cohn 2015) has attracted great interest in recent years, to find solu-
tions for increasing the levels of people’s physical activity and to more
generally promote healthy ways of living in modern society. At the same
time, people are eager to learn more about themselves, their state of
health and health risks, their connection to others, and even to contribute
to research (e.g. Turrini and Prainsack, 2016). The empirical setting of
this study is a health and wellness pilot initiative1 in which the promotion
of individuals’ lifestyle changes played an important role. To obtain
knowledge of the participants’ state of health, various types of data, such
as genomic, metabolomic, microbiome and comprehensive lifestyle moni-
toring data were collected in the pilot initiative from roughly one hun-
dred healthy volunteer participants (see Neiman et al. 2019). The pilot
organizer recruited the participants from the clientele of a private occupa-
tional health service provider. They were employees from four different
large organizations. All the participants signed an informed and voluntary
consent form for the study. The pilot initiative ran for sixteen months
from October 2015 to January 2017.
    To support the volunteers’ attempts to record and potentially change
their health- and wellness-related routines, particularly activity and sleep,
the participants were ‘pushed’ into a self-tracking mode (see Lupton
2014). This means that self-tracking was taken up voluntarily but encour-
aged as part of the pilot initiative. The participants received an activity
wristwatch, the Withings Activité Pop, which is a self-tracking device
with a connected smartphone application (Withings Health Mate). Ac-
cording to the pilot organizers, the selected self-tracking device was cho-
sen in the pilot initiative because it was considered relatively affordable,
easy to use (according to the manual, it has an estimated battery life of up
to eight months, which means the battery does not have to be charged
often), and discreet (it resembles a wristwatch). Most importantly, how-
ever, the chosen device allowed participants to collect data on their eve-
ryday activity (mainly number of steps) and sleep (amount of sleep time),
thus helping them record and make their daily activity and sleep routines
visible, potentially helping them change these.

3.1 Key affordances and maintenance and repair of device

    The installation and operating instruction manual of the chosen self-
tracking device, Withings Activité Pop, emphasizes ease of use. The
tracking of walking, running and swimming as well as sleep is said to be
automatic, mainly only requiring the person to wear the device. As a re-
sult, the user can see their total number of steps taken during the day, the
60                                                         Tecnoscienza – 10 (2)

percentage of their achieved daily step goal and the estimated calories
burned during the day. After swimming, the user is informed of the
length of the swim session and the calories burned. Regarding sleep, the
user gains data on their total time spent sleeping and the duration of their
light and deep sleep cycles as well as waking hours. The percentage of the
daily sleep goal is also visible. The collected data are shown in the con-
nected smartphone application (Withings Health Mate) in multiple ways:
as graphs, numbers, and percentages and in different colours.
    The manual has guidelines for both the maintenance of the device it-
self as well as the data flow it produces. For maintaining the functioning
of the device, the manual tells the user what kind of materials to use for
cleaning (e.g. lint-free cloth to clean the glass and casing) and how to
clean the device (instructions for glass, casing and wristband). In addi-
tion, the manual has instructions for when and how to replace the batter-
ies or the wristband of the device (when the hands have stopped moving
and the watch no longer vibrates when the reset button is pressed).
    The key issue of the production and maintenance of data flow is data
synchronization. The installation and operating instruction manual prom-
ises that the synchronization of data continues in the background as long
as the Bluetooth wireless technology is enabled. Automatic synchroniza-
tion is triggered when the user has collected a certain number of steps,
reached the daily steps objective, when enough time (over six hours) has
passed since the last synchronization, or if the time zone changes or day-
light saving begins (p. 29). However, the user also has the option of syn-
chronizing their data manually: for this they must open the connected
smartphone application and keep it close enough to the device itself. The
importance of synchronizing data is emphasized in the following text,
which is highlighted, bolded and marked with a warning sign: “Your
Withings ActivitéTM Pop/Withings ActivitéTM can only store your data for
38 hours. Make sure you open the app regularly so that you do not lose
any of your data” (p. 29). Updating the software of the device is consid-
ered an important part of its maintenance. The manual emphasizes the
importance of data synchronization before updating the versions, as oth-
erwise data might be lost.
    The main advice regarding the repair of the device is that users should
not try to repair or modify the device themselves and should leave this to
a professional technician. If the user feels that the time displayed on the
device is incorrect, the manual advises recalibrating the device. The man-
ual provides no other instructions for the repair of data.

     3.2 Methods

    The participants received their activity wristwatches in February 2016.
After approximately three months, they were asked about their experi-
ences of using the self-tracking device and the data that it produced. The
interviewees were selected on the basis of two criteria. First, whether they
Yli-Kauhaluoma                                                            61
had any previous experience of using a self-tracking device and second,
whether they expected to learn to use the device easily or not. According
to these two criteria, three different groups of participants were identified
for this study. The inexperienced self-trackers had no previous experi-
ence of using any self-tracking devices, nor did they expect it to be easy to
learn to use the device. The opposite applied to the experienced self-
trackers. The extreme self-trackers were already using either two to three
other self-tracking devices or had been using one device for at least two
years and expected no difficulties in learning to use a new device. The
underlying assumption regarding the identification and selection of the
different types of participants was that the experiences of the inexperi-
enced, experienced and extreme self-trackers would differ, and that the
analysis would result in the identification of the different types of self-
tracking routines that participants develop to improve their activity and
sleep.
    Twenty-seven out of approximately one hundred participants were in-
terviewed in May and June 2016. Nine interviewees were inexperienced,
nine experienced and nine extreme self-trackers (nine male, eighteen fe-
male). After roughly six to seven months, twenty-one of these agreed to
the second interview at the end of the pilot study in December 2016 or
January 2017 (eight male, thirteen female). The time period for both in-
terview rounds was aligned with the schedule of the whole pilot initiative.
The first round of interviews was held after three months of using the ac-
tivity wristwatch, as the assumption was that by then the participants
would have become acquainted with the device and that they would have
developed some related self-tracking routines. It is important to note that
the pilot participants were in principle committed to the use of the select-
ed self-tracking device from when they received it to the end of the pilot
study. As the second round of interviews took place at the end of the pi-
lot study, it was possible to examine any changes in use routines.
    All the interviewees were well educated. Eighteen had a university de-
gree (from either a university or a university of applied sciences). One in-
terviewee even had a doctoral degree. Seven interviewees had a vocational
qualification and one interviewee had completed general upper secondary
school. The age of the interviewees ranged from 28 to 57. All the partici-
pants gave their signed informed and voluntary consent for the pilot
study. The shortest interview lasted 13 minutes in the first round and 9
minutes in the second round, whereas the longest was 80 minutes in the
first round and 45 minutes in the second round. The interview questions
had received ethical approval2 and focused on the use of the self-tracking
application (Withings Activité Pop) in the pilot initiative. More specifical-
ly, the participants were asked how they used the application, how they
experienced the use of the application and whether they had any difficul-
ties or problems when using it. They were also asked whether they used
any other self-tracking devices, and if so, what their experiences of these
applications were. All the interviews were recorded and later transcribed
62                                                                   Tecnoscienza – 10 (2)

verbatim, resulting in a total of approximately twenty-five hours of inter-
view material. The anonymity of the interviewees was guaranteed
throughout and after the interview process.
    Careful reading and systematic coding (see Eriksson and Kovalainen
2008) of the interview material first revealed that not all, but many partic-
ipants and all the types of self-trackers (inexperienced, experienced and
extreme) had connectivity difficulties when encountering and trying to
engage with their data. This means that some participants had problems
with invisible or inaccurate data, which led to feelings of indifference.
Therefore, the next step was to focus on how the participants attempted
to deal with the difficulties they faced. This resulted in an analysis of the
self-tracking routines that the participants talked about in their inter-
views. Their attempts to maintain the functioning of the self-tracking de-
vice and to produce a continuous, correct data flow were at the centre of
their reflections.


4. Maintenance and Repair Routines in Self-tracking Con-
text

    The pilot study participants talked a great deal about their methods and
attempts to follow their daily activity and sleep patterns through self-
tracking. Interestingly, however, many of the self-tracking routines that the
participants reflected upon in the interviews were related to the use of the
self-tracking technology itself. They talked about the ways in which they
tried to maintain and sometimes even fix the data flow showing either ac-
tivity or sleep.

     4.1 Wearing the device: rigid patterns and improvisations

    The interviewed pilot participants were dedicated to self-tracking in
the pilot initiative. The primary requirement for producing self-tracking
data was wearing the device. The interviewees described how they wore
their devices and checked the data that they produced on a regular basis.
Many followed the number of steps they accumulated during the day and
in the mornings checked their time spent sleeping as well as the duration
of their light and deep sleep cycles at night. Many considered wearing the
self-tracking device and the resulting data exciting and engaging, particu-
larly at the beginning of the pilot initiative.

     Ten thousand [steps] is the goal. You can see at one glance where you are.
     If it starts to get late and it’s about time to go to bed and I notice that I’ve
     not reached ten thousand [steps] it begins to worry me. Or, if I already
     know during the day that this is not a very active day, I may walk a longer
     route and take additional steps or something. It’s become a positive incen-
     tive. (Female, 42, experienced self-tracker) (Interview: 1st round)
Yli-Kauhaluoma                                                                        63


    The excitement of the novel device did not necessarily last long. The
routine wearing of the device was no longer motivating when the data
stopped producing new learning insights or the device seemed to mal-
function. The participant quoted above said in the second interview that
after roughly six to eight months, wearing the activity wristwatch felt like
having handcuffs. It was not easy to take it off.

    Before the battery change the watch kept time accurately. But it produced
    silly data as if I’d gone to bed at four, even though it was ten o’clock. Or it
    showed no data, even though I knew that I had run for seven kilome-
    tres.… This [malfunction] lasted roughly 1.5 months. I began to think I
    wouldn’t be bothered if it couldn’t be fixed. There was no novelty value
    for me anymore and as [the data] were a bit unreliable I started to think
    whether I should wear it at all. I would have liked to wear my own watch
    again. … I think that I gained the benefits of the device during the first six
    to eight months of use. I should perhaps try to better remember those in-
    sights and live accordingly even if I don’t wear these handcuffs all the
    time. (Female, 42, experienced self-tracker) (Interview: 2nd round)

    The same interviewee reflected on her dedication to wearing the self-
tracking device in the course of the pilot project. She described her devo-
tion to the routine wearing of the device as obsessive for a long time, even
in situations when wearing it broke a dress code or it did not suit certain
special festivities. She said that she no longer kept up the routine of wear-
ing the device on all occasions.

    At the end of the summer, a friend of mine had a birthday party… As my
    hair and makeup were done, my hairdresser wondered whether I would
    wear the activity watch during the party. I told her that I collected data
    every day and that [people] won’t notice the watch much under my lace
    gloves. Today, this would be out of the question. I would leave Withings
    lying on the table if I was invited [to a party like that]. (Female, 42, expe-
    rienced self-tracker) (Interview: 2nd round)

    Some of the participants who felt that the device did not register all
the data that it should have were eager to experiment with different ways
of wearing the device. These participants were particularly concerned
about their activity data as they felt that the device seemed to register only
some types of activity, particularly steps, and only when the circumstanc-
es for data registration were favourable, for example, when their hands
were not still. The problem of lacking activity data mostly bothered the
participants who were active cyclists, as the device did not register cycling
at all, but also many participants who actively took part in different types
of sports. Therefore, some of them tried to think of new ways of routinely
wearing the device that would allow them to maintain a data flow of their
activity that they considered more realistic.
64                                                                  Tecnoscienza – 10 (2)

     I’ve had the Withings from the beginning [of the pilot study] and I use it
     and follow [the data]… We were instructed to wear it in our wrists all the
     time. But, let’s say you cycle on an exercise bike for two hours. This means
     that you hold on to the handlebars for two hours and [the device] thinks
     that you’ve being lying on the sofa for two hours… Well, I did some tests
     and put it on my foot… It worked to some extent. It did recognize some
     activities. I noticed that in many cases it was better that I had it on my foot
     instead of my wrist. But, this isn’t really the idea. (Male, 43, extreme self-
     tracker) (Interview: 1st round)

    The above-quoted participant’s dissatisfaction with the functionality of
the device made him experiment with wearing the device in a way that it
measured the different kinds of sports that he took part in more accurately,
in a more versatile way. The experiment soon turned into routine use. In-
stead of wearing the device on his wrist, the participant wore it on his an-
kle.

     Since the last meeting in the spring I’ve worn it as an ankle monitor. This
     is where it has least hindered my daily activities. But I quit using it as I
     didn’t gain anything from it anymore… [This was] after the summer,
     sometime in the autumn. (Male, 43, extreme self-tracker) (Interview: 2nd
     round)

    The participant quoted above felt that the device selected for the pilot
participants was not designed for people like him who were active in
sports. According to his experience, it did not recognize many of the ac-
tivities that he conducted regularly, such as skiing. He also feared that it
guided people to routinely do sports in an unbalanced way, as people
wanted to demonstrate their activity through data, but the sensors meas-
ured only particular types of activities (mainly number of steps). The de-
vice was designed to be worn on the wrist, and although he felt that the
device did not function properly when worn on the ankle, it collected da-
ta for him much more effectively than when he wore it on his wrist.
Therefore, he kept the device on his ankle instead of his wrist until the
watch strap of the device broke. This made him quit using the device
completely, as he considered the data useless.
    Another participant who was also extremely active in both sports and
self-tracking tried to wear the pilot study device on her other wrist, as one
wrist already held her own self-tracking device. This was because she
feared potential connection disturbances between the devices. However,
she felt that it did not help her collect accurate activity data.

     The intensity of my workout in the gym, well, I was completely dead. It
     was terrible. there was no way I could have done anything else… Well, it
     showed that I had burned 127 calories and that was it. No calories
     burned! While my own device showed the recovery time [needs] to be at
     least 12 hours… I didn’t wear [the two different devices] on the same arm
     because I thought that they [may] connect with each other and there
Yli-Kauhaluoma                                                                    65
    might even be interference or something. I wore the one on one hand and
    the other on the other hand. (Female, 52, extreme self-tracker) (Interview:
    1st round)

    The participant quoted above needed the self-tracking device most
importantly to remind her of the importance of recovery time. Being mo-
tivated to be active and do sports was not a problem for her. Instead, she
wanted the device to remind her that she also needed to remember to
rest. The device used in the pilot study did not recognize all the sports
activities that she did. This worried her and therefore, she tried to think
of new ways to wear the device to help her collect data. She wore the de-
vice either on her ankle or on a different arm to her other self-tracking
device. She was frustrated as she did not succeed in obtaining data that
she could consider correct.

4.2 Tending to the device: automatic settings and manual tasks

    Many participants mentioned that every day they routinely checked
both the number of steps achieved during the day and the amount of
sleep they got at night. Monitoring sleep seemed to be particularly inter-
esting for most participants, many of whom were either in management or
expert positions and suffering from high stress levels. Some participants
mentioned having only four to five hours of sleep per night, which is well
below the recommended eight hours of sleep. Obtaining and seeing the
data required not only data collection but also regular data synchroniza-
tion, either automatically or manually.

    I wear the device practically all the time… It’s easy in the sense that you
    just turn it on once a day. And, the phone reminds you to turn it on to
    synchronize the day’s data… I do check the number of steps every day… I
    don’t think I could do more in a day. My job, hobbies, and the hobbies of
    my children make it a 16-hour day. An evening walk after all that, no way!
    (Male, 40, inexperienced self-tracker) (Interview: 1st round)

    Despite their stressful lives, many participants kept collecting, syn-
chronizing and monitoring their activity (number of steps) and sleep data.
However, being constantly reminded of goals that are hard to reach was
trying.

    I had it until around Christmas. But, I got bored somehow… I had a
    tough year. It didn’t add to my well-being that the device told me I didn’t
    sleep well. (Male, 40, inexperienced self-tracker) (Interview: 2nd round)

    The participant quoted above held a high-level management position
in a large organization. He used to do sport regularly but now found it
difficult to find time for exercise. His heavy workload and stressful job
left him sometimes only a couple of hours of sleep at night. The partici-
66                                                                  Tecnoscienza – 10 (2)

pant revealed that he had considered participation in the pilot study in
order to slowly reactivate his sports routines. The result was, however,
frustrating for him. He was only able to build up a routine of maintaining
and monitoring a continuous data flow in his self-tracking device. He
wore the device and synchronized the data devotedly every day. Howev-
er, he claimed that seeing his constant failure to recreate the regular train-
ing routines he desired, or to increase his amount of daily sleep made him
finally abandon the device completely.
    Another participant compared the maintenance of the device to the
care of a virtual pet, a Tamagotchi, which needs constant care and nur-
ture. In the first interview round, the participant talked about her at-
tempts to maintain a beautiful flower in the interface of her smartphone
application. She emphasized the importance of caring for the four petals
that represented her levels of activity, sleep, weight and blood pressure in
proportion to the pre-defined optimal levels of these health and wellness
areas.

     It has a visual incentive system containing all four different areas [activity,
     sleep, blood pressure and weight], so it’s a bit like a Tamagotchi. You
     need to keep it happy… It turns into a beautiful flower when all these
     four areas are in balance. (Female, 39, experienced self-tracker) (Inter-
     view: 1st round)

    Taking care of a pet, even if it is virtual, can be hard work that re-
quires persistence. For the participant quoted above, taking care of her
Tamagotchi meant not only taking enough steps or having enough sleep
every day; she had also developed weight and pulse measurement rou-
tines, the results of which she needed to record manually.

     I’m clearly not as enthusiastic [as in the beginning]. I used to check [the
     number of] my steps every day, but now I haven’t monitored them so ac-
     tively. Instead, I’ve tracked my sleep every day. This is where I’ve had
     problems and therefore, it’s been useful. It has increased my self-
     knowledge of my own sleep a lot. Monitoring sleep has clearly become a
     positive routine… My steps on the other hand, after my initial excitement
     I haven’t walked as much [as in the beginning]. Then I’ve felt a bit bad,
     had a guilty conscience and been annoyed because I’ve cycled a lot but
     [the device] doesn’t show cycling at all… I’ve [started] to think I might
     need a break from monitoring my steps, because there’s no reason to feel
     guilty as I do exercise a lot. (Female, 39, experienced self-tracker) (Inter-
     view: 2nd round)

    In the second interview, it became clear that keeping to the routines
of caring for the Tamagotchi or maintaining the beautiful flower in the
interface of the smartphone application had been too much work for the
participant. She had given up measuring her weight and pulse as well as
recording the resulting data of her device. She only followed her amount
Yli-Kauhaluoma                                                                      67
of daily activity irregularly as cycling did not add to the numbers. Instead,
she kept monitoring her sleep actively, as she had successfully overcome
her sleep problems and had even been able to give up her sleep medica-
tion. The flawed numbers showing her activity, however, bothered her a
great deal.
    The users of the activity wristwatch were also able to share their data
with others. Some participants in the pilot initiative who were colleagues
at work teamed up to share their activity data (number of steps) and to
compete in activity. Many of those who participated in this type of com-
petition reported that it was motivating, fun or at least somehow stimulat-
ing.

    We can challenge each other. Now, [two of my co-workers] have chal-
    lenged me. I can see their weekly [steps]. I happen to be in the lead now.
    For some reason, [the other co-worker] has not been able to update [her
    data]. That’s why she has zero steps. I know she exercises a lot though.
    (Female, 48, inexperienced self-tracker) (1st interview)

    The participant quoted above found the competition with her co-
workers motivating. At the same time, she pondered the functionality of
her own device and even that of her co-worker’s device, as well as the vis-
ibility problems of the activity data. According to her, the problems with
the functionality of her own device and the visibility of activity data con-
tinued and even increased in the course of the pilot initiative, which re-
duced her motivation to be more active in exercising.

    I’m not involved anymore because I always get so little steps. … Some-
    times we talked during our coffee break about [who] had beat [the oth-
    ers]. I sometimes noticed that [a co-worker] had an evening walk around
    11 pm and beat me. It was fun, but nobody talks about this anymore. … I
    wonder whether [one co-worker] has some problems too because I no-
    ticed a couple of weeks ago that that she only had 23 000 steps a week. In
    a whole week! She exercises outdoors a lot, goes hiking and does all kinds
    of things. How is it possible that she has only 23 000 steps? I don’t believe
    it. Last week, zero steps. This week, zero steps. Most likely her device is
    acting up. At one point, she disappeared completely [from my screen]. I
    don’t know what happened. She said that all her friends disappeared from
    her screen. (Female, 48, inexperienced self-tracker) (2nd interview)

    The above-quoted participant quit the activity competition. She felt
that some of her activity data remained unregistered and reflected on the
possible causes of her device’s functionality problems, such as the lack of
memory space in her smartphone. She claimed that the problems contin-
ued despite switching her activity wristwatch for a new one and changing
its batteries. It seems that the functionality of hers and her co-worker’s
device troubled her quite a lot and that she focused her attention on the
technical issues of data recording.
68                                                                  Tecnoscienza – 10 (2)

4.3 Communicating with the device: Data synchronization and
   repair

    Data synchronization was essential for the maintenance and visibility
of continuous data flow in the connected smartphone application. De-
spite the operating instruction manual promising that the user “should
never have to worry about syncing” (p. 29) their data, as this would take
place in the background automatically as long as the Bluetooth wireless
technology was enabled and when some specific milestones, such as a cer-
tain number of steps, were reached, some participants still had to syn-
chronize their data manually. Data synchronization was thus not com-
pletely unproblematic for all the participants. Problems in data synchro-
nization emerged when, for example, data were missing or data sets were
broken. Some participants had developed peculiar routines for conduct-
ing manual data synchronization to ensure continuous data sets.

     I have a brand-new phone, but still, it doesn’t always [synchronize the da-
     ta]. You have to put the phone really close [to the activity wristwatch]… I
     don’t know if it’s because of the phone case or what… Sometimes there
     are days that show no activity, because I haven’t remembered to put it
     right. Then you have to keep it [close to the activity wrist] for quite a long
     time before it starts importing [the data]… I usually try to do this once a
     day so that it begins to synchronize. Or, I put the watch on top [of my
     phone] and go and do something else… Otherwise it’s easy to use, but if
     you don’t always remember to hold your phone close enough to the
     [wrist] then it might not register [your data… It’s all about routine, of
     course… but I don’t always remember to do this in the morning. (Female,
     49, experienced self-tracker) (Interview: 1st round)

    The participant quoted above had a brand-new smartphone, but still
felt that the phone did not always synchronize the data easily. Her at-
tempt to solve the problem was to put the phone close enough to the ac-
tivity wristwatch and let the synchronization take all the time that it need-
ed. She had days that showed no activity (number of steps), and believed
that this was because she had not remembered to position the activity
wristwatch and the smartphone in the correct way for synchronization to
take place. Although the operating instructions manual emphasized the
importance of the activity wristwatch and the smartphone being close
enough to each other while synchronizing data, the participant wondered
whether the data synchronization problem may originate from her phone
case. For her, data synchronization was burdensome. She stressed that
remembering to synchronize the data required routines and thus tried to
do it once a day in the morning. She did not always succeed, and some-
times forgot to do the manual synchronization, which resulted in missing
data. As she felt that importing the data took a great deal of time, she
sometimes just left the activity wristwatch on the top of her phone and
Yli-Kauhaluoma                                                                      69
went to do something else. She left the self-tracking wristwatch to ‘com-
municate’ alone with the connected smartphone application.
    It was important for the pilot participants that self-tracking produced
continuous, visible data flows. This required them to ensure data syn-
chronization and that the activity wristwatch ‘communicated’ correctly
with the connected smartphone application. Some participants also
brought up the issue of the reliability of data. For example, one of the pi-
lot participants compared the data produced by the activity wristwatch
with the data produced by a pedometer application, Moves, which could
be uploaded for free onto his smartphone.

    Sometimes when I activate Moves, it shows some numbers. But, if I im-
    mediately restart Withings and then go back to Moves… it may add 1000-
    2000 steps. I don’t know how it collects the data. From its own logs? Does
    it somehow spy on the logs in Withings? Is it a coincidence, depending on
    how I use it at specific times?… I haven’t been able to figure out its logic.
    For example, why does it sometimes cut down my number of steps? Is it
    somehow connected to location information?… I don’t know whether
    Withings works in the same way. Maybe it does, maybe it doesn’t. I don’t
    feel like synchronizing it so often because it’s such a slow process. That’s
    why I can’t figure out if it works in the same way. (Male, 41, inexperi-
    enced self-tracker) (1st interview)

    The participant quoted above said that he considered the activity data
produced by the activity wristwatch more reliable than the data produced
by the free pedometer application. At the same time, he felt that the data
synchronization took too long in Withings and therefore, preferred to
check the number of steps in Moves as it seemed to produce numbers in
real time. He complained, however, that the free pedometer application
sometimes either added or reduced his number of steps, which made him
reflect on the possible causes for this. Uncertainty in the functioning of
one piece of technology seemed to lead to concerns about the functioning
of the activity wrist device.
    Some participants in the pilot initiative felt that some of the data that
the device registered were unreliable, even false, and tried to invent ways
in which to guarantee accurate data that did not involve paying attention
to wearing the activity wristwatch. Some participants were unsatisfied
with the reliability of their activity data (number of steps), and others did
not consider even the sleep data reliable.

    It annoys me that the device thinks I’m fast asleep even though I am
    100% sure that I’m awake and watching television… Of course I don’t
    move a lot when I watch television. I suppose if you don’t move at all it
    considers that you’re fast asleep… Every now and then I’ve tried to wave
    my hand like this in some direction so that it understands I’m awake. But,
    I don’t feel like doing this all the time… It should be possible to correct
    [the data] myself. I could do this myself and [change the data] to show
70                                                                  Tecnoscienza – 10 (2)

     that this is not sleep. (Female, 47, experienced self-tracker) (Interview: 1st
     round)

    Inaccurate data may annoy self-trackers so much that they are pre-
pared to do a great deal of additional work and invent routines that may
seem odd to others, such as waving their hands to show the device that its
owner is awake. The participant quoted above was persistent in her sev-
eral attempts to develop self-tacking routines that would result in reliable
data.

     I wear it on my wrist all the time, but I’m extremely disappointed because
     the numbers are so flawed. It gives way too few steps and it thinks that I
     keep sleeping all the time even although I’m just still… I’ve not figured
     out [how to fix it] because when I watch television, I don’t feel like mov-
     ing all the time… But I do see the times here. I can make comparisons and
     then I save my real sleep times in my [other smartphone app]. I check that
     ok, this is when I went to bed. I know that I watched the television for an
     hour. It may look like I woke up in the middle of the night but I know
     that this is when I went to bed from the sofa… I have tried to calibrate
     [=the different devices]. (Female, 47, experienced self-tracker) (Interview:
     2nd round)

    The participant quoted above was annoyed that the device interpreted
that she was fast asleep even though she knew she had been awake and
watching television. The participant came to the conclusion that the
problem could be that she stayed too still while watching television. The
inaccurate data annoyed her so much that she would even have been
ready to correct the data afterwards through changing them manually
from asleep to awake. Although this was not possible in the application,
she tried to fix the problem by communicating with the device through
waving her hands while watching television to tell the device that she was
indeed awake. Waving her hands routinely or remembering to change her
position constantly while watching television was, however, frustrating.
Therefore, her next effort to obtain accurate data was to start using an-
other smartphone application. She collected her sleep data via both de-
vices, compared the data with each other, and modified the data to reflect
how she remembered her sleep and waking hours. She recorded the cor-
rected data in her new self-tracking application and thereby tried to cali-
brate the devices. We can conclude that she was ready to do a considera-
ble amount of additional work in exchange for accurate data flow. One
reason could be that she did shift work and had several animals at home
to take care of and therefore wanted to make sure that she gained enough
sleep every day.
Yli-Kauhaluoma                                                            71
5. Discussion

    Self-tracking devices are considered examples of technological arte-
facts that offer possibilities for promoting lifestyle changes. This is be-
cause they help people collect personal data and thus invite them to de-
velop everyday routines for monitoring, documenting and analysing vari-
ous aspects of daily life that affect health and wellness, such as activity
and sleep (e.g. Swan 2012). At best, the knowledge produced by self-
tracking devices may result in the development of daily routines that fos-
ter and maintain people’s healthy living and thereby also support the
overall shift in health care from treatment to the prevention of diseases.
Self-tracking technology can be considered an infrastructure which, due
to its communicative affordances, allows people to create personalized,
flexible routines as well as reflect upon them (Lomborg and Frandsen
2016). So far, however, an understanding of how people generate and in-
terpret their self-tracking data, and how they incorporate it into their dai-
ly routines, has been lacking (Pink et al. 2017; Lupton et al. 2018). This
study contributes to this critical stream of research through the empirical
examination of reflections on the self-tracking routines of pilot partici-
pants in a large health and wellness pilot initiative.
    In the studied pilot initiative, the promotion of individuals’ lifestyle
changes played an important role. Different types of health and lifestyle
data were collected and returned to the pilot participants, who also re-
ceived an activity wristwatch to collect their activity (mainly number of
steps) and sleep data themselves. The underlying normative goal or the
ostensive aspect of self-tracking in the pilot initiative was that the self-
tracking device would not only allow the participants to document their
data but also possibly inspire them to change their activity and sleep rou-
tines and thereby affect their health and wellness.
    The results of this study emphasize the subjective interpretations and
understandings of self-tracking device usage. Many of the interviewed pi-
lot participants developed routines for monitoring and documenting their
everyday activity and sleep data. In the evening, many of them checked
the number of their daily steps, and in the morning they looked at how
they had slept in the night. Some were even attracted by the elements of
gamification or the possibility to use the self-tracking device as a toy or a
tool for competing with others. Other participants mentioned that self-
tracking data indeed acted as motivation to change their activity or sleep
patterns. However, when reflecting on the data, many of the participants
in this study did not mainly focus on how to produce better activity or
sleep data, i.e. how to change daily routines to gain data that show an in-
creased amount of daily activity or sleep. Instead, they primarily reflected
on the routines that were related to the use of the technology itself. One
of the reasons for this could be connectivity problems (Yli-Kauhaluoma
and Pantzar 2018), when the data remained broken and were thus inac-
curate or incomplete (see Pink et al. 2018). Therefore, they described
72                                                         Tecnoscienza – 10 (2)

their attempts to create routines that would help them collect reliable da-
ta and synchronize the data between different technologies, i.e. the activi-
ty wristwatch and the smartphone application. For example, they experi-
mented with how to wear the device, on which wrist or even on their an-
kles. They applied elements of gamification while tending to the device.
They communicated with the device by, for instance, waving their hands
to tell the device they were not asleep. They organized time for data syn-
chronization to allow the smartphone application to connect with the de-
vice itself. They even tried to calibrate the device with their other self-
tracking applications. It seems that a close, even dialectical relationship
developed between the users of the self-tracking device and the technolo-
gy itself. Importantly, however, the practices that the participants devel-
oped did not necessarily have anything to do with the original aims of the
use of the self-tracking device in the pilot, i.e. the development of rou-
tines that improve activity or sleep thus contributing to health and well-
ness. Instead, in practice these routines emphasized the maintenance of
the digital flow of data.
    The results of the study are based on a sample of pilot participant in-
terviews in two phases. The first round was held after approximately
three months of self-tracking (twenty-seven interviewees) and the second
round after roughly ten months of self-tracking in the pilot study (twenty-
one interviewees). Although the study protocol was strictly controlled and
focused on the use of the self-tracking device and the related service ap-
plication, the pilot participants gave rich descriptions of their technology
use routines. The advancement of individuals’ lifestyle changes played an
important role in the studied pilot initiative. Therefore, it was surprising
that many of the participants’ reflections mainly emphasized their every-
day tasks with the self-tracking technology instead of how the technology
had supported their activity and sleep routines or more generally, their
health and wellness. One reason could be that the interviews were not
conducted by a health or wellness professional, nurse, physician or per-
sonal trainer. Nevertheless, during the interviews, many participants were
eager to show their everyday activity (number of steps) and sleep data in
great detail. The need to reflect on routines for wearing, tending to and
communicating with the device might originate from frustration with the
‘power of default’ of technological artefacts, which makes their adapta-
tion and customization for better support of routines or routine change
difficult (see Koch 1999; Pollock and Cornford 2004; D’Adderio 2011).
This means that the deployment of novel artefacts that support particular
routines or even routine change is not easy.
    The study shows that self-tracking requires users to do more than just
wear a device, as claimed by user manuals. Accomplishing self-tracking
routines calls for a great deal of effort (see Feldman et al. 2016) that in-
volves not only maintenance but sometimes even repairing the digital data
produced. This study shows that the maintenance and repair of digital
data are everyday tasks, not only for professionals involved with complex
Yli-Kauhaluoma                                                             73
data sets (Tanweer et al. 2016), but also for the ordinary people involved
with different artefacts or consumer technologies such as self-tracking de-
vices. The study suggests that the stability of routines is related to the
meanings that technologies or artefacts produce, as well as to the affects
that they have on their users. Among the pilot participants, the routines
for maintaining the digital data flow often ceased if the users no longer
found self-tracking data meaningful in their lives or when they constantly
faced feelings such as boredom or frustration when confronting their per-
sonal data. As Ledger and McCaffrey (2014) have noted, self-tracking de-
vices do not necessarily succeed in encouraging the long-term routine en-
gagement their users. The constant maintenance work effort is not re-
warding if it results in data that remain invisible, inaccurate, self-evident
or frustrating.


6. Concluding Remarks

    The study shows that self-tracking devices and the data that they pro-
duce may require continuous maintenance and even repair routines.
Here, the device users had to exercise persistence, creativity, improvisa-
tion and even care in their attempts to produce complete data. The study
suggests that users of self-tracking devices may develop even peculiar rou-
tines in their communication with self-tracking devices and data synchro-
nization. Such routines may result in a close relationship between the user
of the self-tracking device and the technology itself. The analysis of eve-
ryday routines thus helps expand the literature on self-tracking by reveal-
ing patterns in the users’ application of their devices at specific times and
places in their lives. More research on these everyday routines is needed
to gain a better understanding of the spectrum of the invisible work of
users, as device maintenance is often considered straightforward, and da-
ta synchronization, for instance, is regularly assumed to take place auto-
matically or without much effort. Future research would be particularly
valuable in cases when self-tracking devices or other novel technologies
are introduced into people’s everyday lives with the aim of helping them
make changes to lifestyle routines that affect their health and wellness.
The results could eventually contribute to the better design of technolo-
gies and more understanding of the type of additional support that peo-
ple need when using such technologies in their everyday lives.
    The study also suggests a need for more longitudinal research on rou-
tines and the related artefacts in general, and self-tracking routines in par-
ticular. The obvious challenge and premise of this study was long-term
routine engagement with interesting technological artefacts such as self-
tracking devices. Even the relatively small sample of interviews in two
phases at six- to seven-month intervals revealed changes in people’s re-
flections on their routine practices and the related affectual atmospheres.
A focus on how changing patterns of action relate to changing affectual
74                                                                Tecnoscienza – 10 (2)

atmospheres in self-tracking offers an interesting avenue for future re-
search.
    One important practical implication of the study concerns health and
wellness interventions that are organized in the form of, for instance, pilot
studies and trials. The study suggests that participants of such interven-
tions are deeply dedicated to data production and their contribution to
research: in this case, through self-tracking. However, the committed use
of technologies such as self-tracking devices in organized health and well-
ness projects may simultaneously have unintended consequences. Con-
stant recognition of failure to reach the desired activity or sleep data may
lead to frustration rather than motivation in attempts to make lifestyle
changes. Therefore, the design of pilot initiatives that apply novel arte-
facts for routine change and consolidation should caution users about the
possible negative or unintended consequences of following routines and
offer participants strong technological and social support.


Acknowledgements

    This research was carried out at the Centre for Consumer Society Research in
the University of Helsinki. I would like to thank the organizer of the ‘Digital
Health Revolution’ (DHR) health and wellness pilot initiative, the Institute for
Molecular Medicine Finland (FIMM), HiLIFE, the University of Helsinki and
particularly Riitta Sallinen & Anu Karhu for all their help and collaboration. I also
thank Mika Pantzar and Minna Ruckenstein for useful discussions on digital
health. In addition, I would like to thank all the interviewees who participated in
this study. The comments and suggestions by the editor and three anonymous re-
viewers are also gratefully acknowledged.
    This research was supported by a grant from Tekes – the Finnish Funding
Agency for Innovation – as part of the Digital Health Revolution programme. The
multi-disciplinary programme was coordinated and managed by the Centre for
Health and Technology, University of Oulu, Finland.


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Yli-Kauhaluoma                                                                   75
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    1
      The Digital Health Revolution (DHR) health and wellness pilot initiative was
organized by the Institute for Molecular Medicine Finland (FIMM), HiLIFE,
University of Helsinki.
    2
      The DHR Pilot Study was conducted according to the guidelines of the Dec-
laration of Helsinki. The study protocol was approved by the Coordinating Ethics
Committee of the HUS Hospital District (51/13/03/00/15).
