Personal informatics for everyday life: How users without prior self-tracking experience engage with personal data

Rapp, Amon; Cena, Federica

doi:10.1016/j.ijhcs.2016.05.006

Cited by 161 publications

(106 citation statements)

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“…In these lines of research, body monitoring devices are regarded in this process as neutral observers that keep track of bodily activity, and the 'problem' of users not being able to, or not being interested in, interpreting personal data is addressed with a technology-centred approach. The solution is framed as a matter of providing the best and the most user-friendly human-technology interface (Li et al 2010;Rapp and Cena 2016). The kinds of pedagogies built into the devices are evident in, for instance, Li et al's (2010) five-stage model of how to understand how people make sense and meaning of life-tracking.…”

Section: Personal Data Epistemologiesmentioning

confidence: 99%

Pedagogy as Possibility: Health Interventions as Digital Openness

Fors

Pink

2017

Social Sciences

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In this article we propose an approach to digital health tracking technologies that draws on design anthropology. This entails re-thinking the pedagogical importance of personal data as lying in how they participate in the constitution of new possibilities that enable people to learn about, and configure, their everyday health in new ways. There have been two dominant strands in traditional debates in the field of pedagogy: one that refers to processes of teaching people to do things in particular ways; and another that seeks to enable learning. The first of these corresponds with existing understandings of self-tracking technologies as either unsuccessful behavioural change devices, or as providing solutions to problems that do not necessarily exist. When seen as such, self-tracking technologies inevitably fail as forms of intervention towards better health. In this article we investigate what happens when we take the second strand-the notion of enabling learning as an incremental and emergent process-seriously as a mode of intervention towards health through self-tracking technologies. We show how such a shift in pedagogical understanding of the routes to knowing these technologies offer creates opportunities to move beyond simplistic ideas of behavioural change as the main application of digital body monitoring in everyday life. In what follows, we first demonstrate how the disjunctures that arise from this context emerge. We then outline a critical response to how learning through life-tracking has been conceptualised in research in health and human-computer interaction research. We offer an alternative response by drawing on a processual theory of learning and recent and emerging research in sociology, media studies, anthropology, and cognate disciplines. Then, drawing on ethnographic research, we argue for understanding learning through the production of personal data as involving emplaced and non-representational routes to knowing. This, we propose, requires a corresponding rethinking of the epistemological status of personal data and what kind of knowledge it can be claimed to produce. Finally, we take up the implications of this and advance the discussion through a design anthropological approach, through which we refigure the interventional potential of such technologies as lying in their capacity to create possibilities for experiential, and often unspoken, ways of embodied and emplaced knowing.

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Section: Personal Data Epistemologiesmentioning

confidence: 99%

Pedagogy as Possibility: Health Interventions as Digital Openness

Fors

Pink

2017

Social Sciences

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“…Moreover, the currently available technologies permit an automatic detection of emotions only by using cumbersome and/or intrusive means for the user, since she has to be equipped with a set of invasive devices (such as sensors or wearable devices, like bracelets, helmets, belts, etc.). This makes the gathering of parameters very awkward, not natural and, above all, not easily applicable to everyday life [12,27]. For these reasons, we think that the tracking of people's emotions can be done only with the direct participation of the user, using introspective reports.…”

Section: Emotions and Moodmentioning

confidence: 99%

“…However, some other factors still remain difficult to track. The increasing popularity of PI systems among "inexperienced users" [11,12], who track for enjoyment and wellness (e.g., by using commercial devices like the FitBit), has led researchers to explore new ways for collecting [13], structuring [14,15], visualizing [16,17], prompting [18,19], and using [20] personal data.…”

Section: Introductionmentioning

confidence: 99%

“…We think that such users need novel interaction modalities to make the self-reporting of data more engaging, and thus motivate the use of self-tracking instruments over time. Otherwise, after an initial engagement, they will soon abandon the use of their trackers, as recent research has highlighted [12]. In this article we will explore novel possibilities for collecting mood and emotional data by means of a tangible interface.…”

Section: Introductionmentioning

confidence: 99%

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Self-Monitoring of Emotions and Mood Using a Tangible Approach

Sarzotti

2018

Computers

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Nowadays Personal Informatics (PI) devices are used for sensing and saving personal data, everywhere and at any time, helping people improve their lives by highlighting areas of good and bad performances and providing a general awareness of different levels of conduct. However, not all these data are suitable to be automatically collected. This is especially true for emotions and mood. Moreover, users without experience in self-tracking may have a misperception of PI applications' limits and potentialities. We believe that current PI tools are not designed with enough understanding of such users' needs, desires, and problems they may encounter in their everyday lives. We designed and prototype the Mood TUI (Tangible User Interface), a PI tool that supports the self-reporting of mood data using a tangible interface. The platform is able to gather six different mood states and it was tested through several participatory design sessions in a secondary/high school. The solution proposed allows gathering mood values in an amusing, simple, and appealing way. Users appreciated the prototypes, suggesting several possible improvements as well as ideas on how to use the prototype in similar or totally different contexts, and giving us hints for future research.

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“…Data "curation" is burdensome demanding efforts and time to be accomplished. This task cannot be easily managed without strong motivation and compliance over time, so that many users fail to report their data, making the use of self-tracking tools quite useless [4]. It is paramount, therefore, to find new ways for engaging users in actively collecting their data, making this activity more enjoyable and sustainable in their daily living [5].…”

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confidence: 99%

Editorial of the Special Issue on Quantified Self and Personal Informatics

Rapp

Cena

Marcengo³

2018

Computers

Self Cite

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In recent years, we witnessed the spreading of a plethora of wearable and mobile technologies allowing for a continuous and "transparent" gathering of personal data. People are increasingly visualizing information about physical activity, health, everyday movements, and mood to monitor their routines, increase their performance, or change their behavior.Two decades ago, lifelogging research, which originated in research labs, attempted to make everyday recording effortless [1,2], aiming at creating a sort of "total" repository of an individual's life. In more recent years, however, the idea of endlessly hoarding personal information for archiving purposes made way for the ambition of using such information to increase users' self-awareness, highlighting the need to make data useful for their situated purposes. The so-called Quantified Self (QS) movement first foresaw a future when individuals could manage their own data to raise their self-knowledge. Quantified selfers enact practices of self-experimentation in which data are used to understanding the factors that may influence a (problematic) behavior or condition (e.g., a chronic diseases) [3].In this vein, personal informatics (PI) research attempted to explore novel forms for collecting and displaying personal information. PI researchers aimed to go beyond the quantified selfers' specialized practices, supporting the "use" of personal data in individuals' daily living. There are a variety of domains, such as health, sports, fitness, and transportation, that might benefit from the increased availability of personal information. By making such data actionable, PI research aims at supporting people in understanding the richness of their own digital traces, thus increasing the meaningfulness and value of data.However, a variety of challenges still need to be addressed in order to achieve such a goal. For example, despite the recent advancements in automation for recognizing and mining emotional, cognitive, and behavioral information, an active role of the user through self-reporting is still required. Data "curation" is burdensome demanding efforts and time to be accomplished. This task cannot be easily managed without strong motivation and compliance over time, so that many users fail to report their data, making the use of self-tracking tools quite useless [4]. It is paramount, therefore, to find new ways for engaging users in actively collecting their data, making this activity more enjoyable and sustainable in their daily living [5].Moreover, numbers, per se, are not meaningful, and data need to be "narrated" [6] and integrated in the users' personal histories and system of meanings in order to really develop their self-knowledge [7]. Although PI research strived for designing visualizations going beyond stats and analytical representations, for example by using natural language [8], glanceable displays [9], metaphoric depictions [10], and multiple visual cuts [11], there is room for the exploration of radically novel modalities for managing and feeding info...

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Personal informatics for everyday life: How users without prior self-tracking experience engage with personal data

Cited by 161 publications

References 60 publications

Pedagogy as Possibility: Health Interventions as Digital Openness

Pedagogy as Possibility: Health Interventions as Digital Openness

Self-Monitoring of Emotions and Mood Using a Tangible Approach

Editorial of the Special Issue on Quantified Self and Personal Informatics

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