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Recent growth in the use of consumer self-tracking technologies has attracted attention from patients and healthcare providers alike, while researchers have begun to explore its value in the context of chronic health conditions. Sensemaking challenges faced by patients and clinicians have shifted the focus of self-tracking studies towards co-interpretation. Yet workflow constraints and conflicting interests remain barriers to the integration of self-tracking data into clinical conversations. My research aims to address these issues with designs of interactive systems that support the collaborative use of patient self-tracking data.

OBJECTIVES: mHealth tools may support dietary management of type 2 diabetes. However, sustaining user engagement is a challenge. We used mixed methods to explore usage of a motivationally tailored custom smartphone application. METHODS: Platano is a self-determination theory-based app that promotes self-tracking of diet and blood glucose in diabetes. The app has four different interfaces that are tailored to users’ level of extrinsic or intrinsic motivation: monetary reward, registered dietitian feedback on diet goal(s), self-assessment of diet goal(s), or post-meal blood glucose forecast. For PI-TECH, Platano is being evaluated in a pilot Sequential Multiple Assignment Randomized Trial (SMART): participants are sequentially randomized to receive interfaces that match or do not match their level of motivation based on the Treatment Self-Regulation Questionnaire. Here, we report on preliminary results from the initial subset of participants (n = 16, mean age = 54+/−8, 82% female, 94% non-white, 69% household income

Self-tracking can help people understand their medical condition and the factors that influence their symptoms. However, it is unclear how tracking technologies should be tailored to help people cope with the progression of a degenerative disease. To understand how smartphone apps and other tracking technologies can support people in coping with an incurable illness, we interviewed both people with Parkinson's Disease (n=17) and care partners (n=6) who help people with Parkinson's manage their lives. We describe how symptom trackers can help people identify and solve problems to improve their quality of life, the role symptom trackers can play in helping people combat their own tendencies towards avoidance and denial, and the complex role of care partners in defining and tracking ambiguous symptoms. Our findings yield insights that can guide the design of tracking technologies to help people with Parkinson's Disease accept and plan for their condition.

Though some work has looked at the implementation of personal informatics tools with youth and in schools, the approach has been prescriptive; students are pushed toward behaviour change intervention or otherwise use the data for prescribed learning in a particular curriculum area. This has left a gap around how young people may themselves choose to use personal informatics tools in ways relevant to their own concerns. We gave workshops on personal informatics to 13 adolescents at two secondary schools in London, UK. We asked them to use a commercial personal informatics app to track something they chose that they thought might impact their learning. Our participants proved competent and versatile users of personal informatics tools. They tracked their feelings, tech activity, physical activity, and sleep with many using the process as a system for understanding and validating aspects of their own lives, rather than changing them.

A 'data-driven life' has become an established feature of present and future technological visions. This dissertation interrogates the human experience of a data-driven life, by conceptualising, investigating, and speculating about personal informatics tools as new technologies of memory. I argue that the prevalence of quantified data and metrics is creating fundamentally new and distinct records of everyday life: a 'quantified past'. To address this, I conducted qualitative and idiographic fieldwork -- with long-term self-trackers, and subsequently with users of 'smart journals' -- to investigate how this data-driven record mediates the experience of remembering. Further, I undertook a speculative and design-led inquiry to explore the context of a 'quantified wedding'. Adopting a context where remembering is centrally valued, this Research through Design project demonstrated opportunities for the design of data-driven tools for remembering. Crucially, while speculative, this project maintained a central focus on individual experience, and introduced an innovative methodological approach 'Speculative Enactments' for engaging participants meaningfully in speculative inquiry.

This paper introduces an emerging typology of the 'absences' that confound the study of self-tracking. A review of the literature, and the ongoing work of the authors on the long-term value of self-tracking data, is used as a resource to develop descriptions of levels and types of ?gaps' that emerge as part of the activities, behaviors, technologies, and data practices of self-tracking. Such gaps are shown to be both common and insightful, highlighting the economic, social, behavioral, and psychological layers that undergird self-tracking.

Background: Investigations into person-specific predictors of stress have typically taken either a population-level nomothetic approach or an individualized ideographic approach. Nomothetic approaches can quickly identify predictors but can be hindered by the heterogeneity of these predictors across individuals and time. Ideographic approaches may result in more predictive models at the individual level but require a longer period of data collection to identify robust predictors. Objective: Our objectives were to compare predictors of stress identified through nomothetic and ideographic models and to assess whether sequentially combining nomothetic and ideographic models could yield more accurate and actionable predictions of stress than relying on either model. At the same time, we sought to maintain the interpretability necessary to retrieve individual predictors of stress despite using nomothetic models. Methods: Data collected in a 1-year observational study of 79 participants performing low levels of exercise were used. Physical activity was continuously and objectively monitored by actigraphy. Perceived stress was recorded by participants via daily ecological momentary assessments on a mobile app. Environmental variables including daylight time, temperature, and precipitation were retrieved from the public archives. Using these environmental, actigraphy, and mobile assessment data, we built machine learning models to predict individual stress ratings using linear, decision tree, and neural network techniques employing nomothetic and ideographic approaches. The accuracy of the approaches for predicting individual stress ratings was compared based on classification errors. Results: Across the group of patients, an individual’s recent history of stress ratings was most heavily weighted in predicting a future stress rating in the nomothetic recurrent neural network model, whereas environmental factors such as temperature and daylight, as well as duration and frequency of bouts of exercise, were more heavily weighted in the ideographic models. The nomothetic recurrent neural network model was the highest performing nomothetic model and yielded 72% accuracy for an 80%/20% train/test split. Using the same 80/20 split, the ideographic models yielded 75% accuracy. However, restricting ideographic models to participants with more than 50 valid days in the training set, with the same 80/20 split, yielded 85% accuracy. Conclusions: We conclude that for some applications, nomothetic models may be useful for yielding higher initial performance while still surfacing personalized predictors of stress, before switching to ideographic models upon sufficient data collection.

Background The tracking, or logging, of food intake and physical activity is increasing among people, and as a result there is increasing evidence of a link to improvement in health and well-being. Crucial to the effective and safe use of logging is a user’s information literacy. Objective The aim of this study was to analyze food and activity tracking from an information literacy perspective. Methods An online survey was distributed to three communities via parkrun, diabetes.co.uk and the Irritable Bowel Syndrome Network. Results The data showed that there were clear differences in the logging practices of the members of the three different communities, as well as differences in motivations for tracking and the extent of sharing of said tracked data. Respondents showed a good understanding of the importance of information accuracy and were confident in their ability to understand tracked data, however, there were differences in the extent to which food and activity data were shared and also a lack of understanding of the potential reuse and sharing of data by third parties. Conclusions Information literacy in this context involves developing awareness of the issues of accurate information recording, and how tracked information can be applied to support specific health goals. Developing awareness of how and when to share data, as well as of data ownership and privacy, are also important aspects of information literacy.

We consider why and how women track their menstrual cycles, examining their experiences to uncover design opportunities and extend the field's understanding of personal informatics tools. To understand menstrual cycle tracking practices, we collected and analyzed data from three sources: 2,000 reviews of popular menstrual tracking apps, a survey of 687 people, and follow-up interviews with 12 survey respondents. We find that women track their menstrual cycle for varied reasons that include remembering and predicting their period as well as informing conversations with healthcare providers. Participants described six methods of tracking their menstrual cycles, including use of technology, awareness of their premenstrual physiological states, and simply remembering. Although women find apps and calendars helpful, these methods are ineffective when predictions of future menstrual cycles are inaccurate. Designs can create feelings of exclusion for gender and sexual minorities. Existing apps also generally fail to consider life stages that women experience, including young adulthood, pregnancy, and menopause. Our findings encourage expanding the field's conceptions of personal informatics.

Getting enough quality sleep is a key part of a healthy lifestyle. Many people are tracking their sleep through mobile and wearable technology, together with contextual information that may influence sleep quality, like exercise, diet, and stress. However, there is limited support to help people make sense of this wealth of data, i.e., to explore the relationship between sleep data and contextual data. We strive to bridge this gap between sleep-tracking and sense-making through the design of SleepExplorer, a web-based tool that helps individuals understand sleep quality through multi-dimensional sleep structure and explore correlations between sleep data and contextual information. Based on a two-week field study with 12 participants, this paper offers a rich understanding on how technology can support sense-making on personal sleep data: SleepExplorer organizes a flux of sleep data into sleep structure, guides sleep-tracking activities, highlights connections between sleep and contributing factors, and supports individuals in taking actions. We discuss challenges and opportunities to inform the work of researchers and designers creating data-driven health and well-being applications.

The vision of ubiqitous computing is becoming increasingly realized through smart city solutions. With the proliferation of smartphones and smartwatches, alongside the rise of the quantified-self movement, a new technological layer is being added to the urban environment. This framework offers the possibility to capture, track, measure, visualize, and augment our experience of the urban environment. However, to that end, there is a growing need to better understand the triangular relationship between person, place, and technology. Urban HCI studies are increasingly focused on emotion and affect in order to create a better understanding of people's experience of the city, and investigate how technology could potentially play a role in augmenting this lived urban experience. For one example, artist Christian Nold used wearable technology to measure people's arousal levels as they walked freely through the urban environment, identifying locations in the city that evoked an emotional response from people. After these walks, people's arousal levels were superimposed on a map of the city and participants were asked to interpret their own data, resulting in aggregated, fully annotated, and beautifully visualized emotion maps of the city. Based on a systematic review of emotions maps in existing literature, this paper discusses the strengths, limitations and potential of capturing, representing, exploring and sharing this personal, geo-located emotion data with other people using emotion maps. This is part of a PhD project which seeks to understand how people's experiences of places in the urban environment are meaningful to them on a personal level. Although our analysis seems to indicate that emotion maps in their current form are only of limited efficacy in accurately capturing, representing and communicating the profound, complex emotional bond that people have with personally meaningful places in the city, there appears to be potential for the use of emotion maps as a provocation in a speculative design approach.

Consumer sleep tracking devices are known to be inaccurate, but there is a lack of understanding of how user characteristics may affect the accuracy of these devices. This study aims to examine the effect of age, gender, subjective sleep quality, sleep hygiene and sleep structure on the accuracy of two consumer sleep trackers, i.e. Fitbit Charge 2 and Neuroon. Sleep data were collected from 27 healthy participants using consumer devices and a medical device concurrently. Analysis found that age, sleep hygiene and sleep structure were significantly associated to the accuracy of consumer sleep trackers, whereas no association was found on gender and subjective sleep quality. Both consumer devices had improved accuracy on total sleep time and sleep efficiency for participants who had longer, deeper and less interrupted sleep. Our findings suggest that consumer devices may not be suited for young adults and for people with short and fragmented sleep.

Self-tracked health data can help people and their health providers understand and manage chronic conditions. This paper examines personal informatics practices and challenges in migraine, a condition characterized by unpredictable, intermittent, and poorly-understood symptoms. To investigate how people with migraine track and use data related to their condition, we surveyed 279 people with migraine and conducted semi-structured interviews with 13 survey respondents and 6 health providers. We find four distinct goals people bring to tracking and data: 1) answering questions about migraines, 2) predicting and preventing migraines, 3) monitoring and managing migraines over time, and 4) enabling motivation and social recognition. Each goal suggests different needs for the design of tools to support migraine tracking. We also find needs resulting from an individual's goals evolving over time, their varied personal experiences, and their communication and collaboration with providers. We discuss these goals and needs in terms of opportunities for personal informatics tools to facilitate learning to: 1) avoid common pitfalls; 2) support customization and flexibility; 3) account for burden, negativity, and lapsing; and 4) support management with uncertainty.

The hospital setting creates a high-stakes environment where patients' lives depend on accurate tracking of health data. Despite recent work emphasizing the importance of patients' engagement in their own health care, less is known about how patients track their health and care in the hospital. Through interviews and design probes, we investigated hospitalized patients' tracking activity and analyzed our results using the stage-based personal informatics model. We used this model to understand how to support the tracking needs of hospitalized patients at each stage. In this paper, we discuss hospitalized patients' needs for collaboratively tracking their health with their care team. We suggest future extensions of the stage-based model to accommodate collaborative tracking situations, such as hospitals, where data is collected, analyzed, and acted on by multiple people. Our findings uncover new directions for HCI research and highlight ways to support patients in tracking their care and improving patient safety.

Mental wellness is a desirable health outcome for students. However, current personal informatics systems do not adequately support students in creating concrete mental health-related goals and turning them into actionable plans. In this paper, we introduce MindNavigator - a workshop in which groups of college students were invited to generate behavioral change goals to manage daily life stress and practice personalized interventions for two weeks. We describe the manner in which participants identified both stressors and pleasures to create actionable, engaging, and open-ended behavioral plans that aided in stress relief. We found that the social nature of the workshop helped participants understand themselves and execute self-intervention in new ways. Through this practice, we build on prior studies to propose an analytical framework of personal informatics for mental wellness.

Personal Informatics (PI) systems allow their users to collect data from a variety of sources for the purpose of extracting meaningful insights and making positive changes in their lives. Emerging consumer-grade Brain- Computer Interface (BCI)/EEG devices may provide an additional source of data for incorporating into PI systems. To explore users’ expectations for brain- related PI systems we provided participants with a consumer-grade BCI headset and prototype mobile application capable of visualizing and recording their brain waves. Participants were interviewed to assess expectations for this type of technology. Our work contributes an understanding of users’ various motivations for tracking brain activity data within a personal informatics system. We present our findings so far and discuss their implications for the design of a Cognitive Personal Informatics system, which we intend to deploy in a follow-up longitudinal field study.

This paper presents a designerly exploration of the potential values of parent-tracked baby data in interactions between parents and healthcare professionals (HCPs). Where previous work has used parent-tracked data as part of the solution to a problem, we contribute by starting our design exploration from data, using it as creative material in our design process. As we intend to work towards a system that could be viable across different levels of care, we invited three different types of HCPs and five families with newborns, for a five-week situated design exploration. Facilitated by an open and dynamic data collection toolkit, parents and HCPs could together decide what data to collect. In a continuous dialogue, they reflected on the relevance of that data in their interaction. Based on this, we continuously and remotely developed two concepts.

While recent research has emphasized the importance of understanding the lived experience of personal tracking, very little is known about the everyday coordination between tracker use and the surrounding environment. We combine behavioral data from trackers with video recordings from wearable cameras, in an attempt to understand how usage unfolds in daily life and how it is shaped by the context of use. We recorded twelve participants' daily use of activity trackers, collecting and analyzing 244 incidents where activity trackers were used. Among our findings, tracker use was strongly driven by reflection and learning-in action, contrasting the traditional view that learning is one of deep exploration, following the collection of data on behaviors. We leverage on these insights and propose three directions for the design of activity trackers: facilitating learning through glances, providing normative feedback and facilitating micro-plans.

Personal informatics technologies, such as consumer fitness tracking devices, have an enormous potential to transform the self-management of chronic conditions. However, it is unclear how people living with relapsing and progressive illnesses experience personal informatics tools in everyday life: what values and challenges are associated with their use? This research informs the design of future health tracking technologies through an ethnographic design study of the use and experience of personal informatics tools in multiple sclerosis (MS) self-management. Initial findings suggest that future health tracking technologies should acknowledge people's emotional wellbeing and foster flexible and mindful self-tracking, rather than focusing only on tracking primary disease indicators and optimising health behaviours.

We report on the design of ThinkActive - a system to encourage primary aged school children to reflect on their own personal activity data in the classroom. We deployed the system with a cohort of 30 school children, over a six-week period, in partnership with an English Premier League Football club's health and nutrition programme. The system utilizes inexpensive activity trackers and pseudonymous avatars to promote reflection with personal data using an in-situ display within the classroom. Our design explores pseudonymity as an approach to managing privacy and personal data within a public setting. We report on the motivations, challenges, and opportunities for students, teachers, and third-party providers to engage in the collection and sharing of activity data with primary school children.

World of Warcraft (WoW) may be a source of inspiration to enrich the Personal Informatics systems user's experience and, at the same time, improve gamification design. Through the findings of a four-year reflexive ethnography in WoW, I outline how its game design elements support players in making sense of their own data, emphasizing how "game numbers" are turned into meanings. On the basis of the study results, I propose a series of design considerations to be used in the design of self-tracking systems, which recommend to embody data into digital entities, provide different analytical tools depending on the users' expertise through a flexible model, and foster the formation of "communities of practice" in order to support learning processes.

Extended periods of uninterrupted sedentary behavior are detrimental to long-term health. While prolonged sitting is prevalent among information workers, it is difficult for them to break prolonged sedentary behavior due to the nature of their work. This work aims to understand information workers' intentions & practices around standing or moving breaks. We developed Time for Break, a break prompting system that enables people to set their desired work duration and prompts them to stand up or move. We conducted an exploratory field study (N = 25) with Time for Break to collect participants' work & break intentions and behaviors for three weeks, followed by semi-structured interviews. We examined rich contexts affecting participants' receptiveness to standing or moving breaks, and identified how their habit strength and self-regulation are related to their break-taking intentions & practices. We discuss design implications for interventions to break up periods of prolonged sedentary behavior in workplaces.

Digital self-tracking technologies offer many potential benefits over self-tracking with paper notebooks. However, they are often too rigid to support people's practical and emotional needs in everyday settings. To inform the design of more flexible self-tracking tools, we examine bullet journaling: an analogue and customisable approach for logging and reflecting on everyday life. Analysing a corpus of paper bullet journal photos and related conversations on Instagram, we found that individuals extended and adapted bullet journaling systems to their changing practical and emotional needs through: (1) creating and combining personally meaningful visualisations of different types of trackers, such as habit, mood, and symptom trackers; (2) engaging in mindful reflective thinking through design practices and self-reflective strategies; and (3) posting photos of paper journals online to become part of a self-tracking culture of sharing and learning. We outline two interrelated design directions for flexible and mindful self-tracking: digitally extending analogue self-tracking and supporting digital self-tracking as a mindful design practice.

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 [...]

In situ self-report is widely used in human-computer interaction, ubiquitous computing, and for assessment and intervention in health and wellness. Unfortunately, it remains limited by high burdens. We examine unlock journaling as an alternative. Specifically, we build upon recent work to introduce single-slide unlock journaling gestures appropriate for health and wellness measures. We then present the first field study comparing unlock journaling with traditional diaries and notification-based reminders in self-report of health and wellness measures. We find unlock journaling is less intrusive than reminders, dramatically improves frequency of journaling, and can provide equal or better timeliness. Where appropriate to broader design needs, unlock journaling is thus an overall promising method for in situ self-report.

Lockscreen is one of the most frequently encountered interfaces by smartphone users. Although users perform unlocking actions every day, there are no benefits in using lockscreens apart from security and authentication purposes. In this paper, we replace the traditional lockscreen with an application that analyzes facial expressions in order to collect facial expression data and provide real-time feedback to users. To evaluate this concept, we have implemented Quantified Lockscreen application, supporting the following contributions of this paper: 1) an unobtrusive interface for collecting facial expression data and evaluating emotional patterns, 2) an improvement in accuracy of facial expression detection through a personalized machine learning process, and 3) an enhancement of the validity of emotion data through bidirectional, multi-channel and multi-input methodology.

Personal informatics systems are tools that capture, aggregate, and analyze data from distinct facets of their users’ lives. This article adopts a mixed-methods approach to understand the problem of information overload in personal informatics systems. We report findings from a 3-month study in which 20 participants collected multifaceted personal tracking data and used a system called Exist to reveal statistical correlations within their data. We explore the challenges that participants faced in reviewing the information presented by Exist, and we identify characteristics that exemplify “interesting” correlations. Based on these findings, we develop automated filtering mechanisms that aim to prevent information overload and support users in extracting interesting insights. Our approach deals with information overload by reducing the number of correlations shown to users by about 55% on average and increases the percentage of displayed correlations rated as interesting to about 81%, representing a 34 percentage point improvement over filters that only consider statistical significance at p

Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to those of average consumers who tend to be less conscious about health? In this study, we analyze the healthy eating behaviors of active food journalers using data from MyFitnessPal. Surprisingly, our findings show that food journalers do not eat as healthily as they should despite their proclivity to health eating and their food choices resemble those of the general populace. Furthermore, we find that the journaling duration is only a marginal determinant of healthy eating outcomes and sociodemographic factors, such as gender and regions of residence, are much more predictive of healthy food choices., Comment: Published at Digital Health 2018

In recent years, User Modeling (UM) scenery is changing. With the recent advancements in wearable and mobile technologies, the amount and type of data that can be gathered about users and employed to build User Models is rapidly expanding. UM can now be enriched with data regarding different aspects of people's daily lives and is likely to deliver novel personalized services. All these changes bring forth new research questions about the kinds of services which could be improved, which of them would be the most useful, the ways of conveying effectively new forms of recommendations, and how users would perceive them. In this paper the authors tried to find answers to some of these questions by exploiting a novel personalized system to conduct a qualitative user study, with the aim to understand users' needs and expectations w.r.t. personalization enabled by the presence of wearable and mobile technologies.

This study proposes two conceptual products using wearable devices (smartwatches) for the purpose of emotional management. One is designed with Slow Technology, and the other is designed with Personal Informatics. Questionnaire survey method was used in this study. The questionnaire consists of two types, AttrakDiff and INTUI. Subjects filled out the questionnaires after watching two videos of conceptual products. The questionnaire data were analyzed by the independent sample and paired sample t-test in order to find the differences of ideas and user experience (pragmatic quality, hedonic quality, attractiveness, and intuition) about these two kinds of products. It is important to find out that the Slow Technology products are inferior to Personal Informatics products in pragmatic quality and intuition, but superior in hedonic quality and attractiveness.

In this chapter we discuss the use of external sources of data in designing conversational dialogues. We focus on applications in behavior change around physical activity involving dialogues that help users better understand their self-tracking data and motivate healthy behaviors. We start by introducing the areas of behavior change and personal informatics and discussing the importance of self-tracking data in these areas. We then introduce the role of reflective dialogue-based counseling systems in this domain, discuss specific value that self-tracking data can bring, and how it can be used in creating the dialogues. The core of the chapter focuses on six practical examples of design of dialogues involving self-tracking data that we either tested in our research or propose as future directions based on our experiences. We end the chapter by discussing how the design principles for involving external data in conversations can be applied to broader domains. Our goal for this chapter is to share our experiences, outline design principles, highlight several design opportunities in external data-driven computer-based conversations, and encourage the reader to explore creative ways of involving external sources of data in shaping dialogues-based interactions.

Mobilapplikationer har potential till att hjälpa människor förändra vanor och beteenden av olika slag. I Sverige har vi rätt till avgiftsfri tandvård upp till 22 år och i vissa landsting erbjuds fri tandvård i ytterligare några år utöver det. Traditionellt har interventioner bestått av motiverande samtal med patienter för att motivera till bättre munhälsa, vilket gör att det kan skilja sig i hur mycket människor motiveras till att ta hand om sin orala hälsa. Den här studien syftar till att försöka besvara hur ungdomars uppfattning och attityd är om en prototyp till en mobilapplikation som är tänkt att hjälpa ungdomar att förbättra sin munhälsa genom själv-monitorering. Själv-monitorering genom mobilapplikationer kallas ofta för Personal Informatics. Dessa verktyg låter användaren observera och registrera ett eller flera beteende och därefter få informationen presenterat till sig för att förstå ens beteende bättre. En aspekt som är av stor vikt vid utvecklingen av mobilapplikationer är användarupplevelsen med dem. User Experience Design handlar om processen att försöka förbättra användarupplevelsen med produkter. Den här studien har genomförts med metoder som ofta används i en UX-designprocess, såsom skapande av prototyper och intervjuer med målgruppen. Resultatet visar inte bara åsikter från deltagare ur målgruppen, utan även vad som enligt dem ger mervärde i mobilapplikationen samt framtida utmaningar i fortsatta arbetet.

Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comics strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations.

Personal informatics systems, particularly activity trackers, often provide quantified feedback on movement and physical activities. However, current design solutions fail to provide opportunities for reflection on collected data and do not cultivate a holistic picture of one's health. Through literature research we found four actionable design strategies to address reflective design in personal informatics. A review of thirteen commercial activity trackers highlighted that visualization and enabling data sharing on social networks are the most common strategies used to elicit reflection in current products whereas other strategies such as effective playback of data or including journaling features are largely ignored. We conclude that the current industry trends do not adequately address reflective design and do not appreciate the growing interest amongst users in learning about health.

Increasingly people use mobile phones many times daily. This makes the phone's lockscreen almost ambient, part of everyday life. This work explores how to use that valuable ambience of the lock-screen to help people maintain awareness of, and to track an important goal, such as improving nutrition. We describe the design of FIT, a lockscreen app for ultra-lite logging of vegetable serves consumed each day. Our 4-week field study of FIT, with 19 young adults indicates it is quick and easy to use. The 973 log events took an average of 1.03 seconds, compared with 0.72 seconds for the 25,530 unlocks. The study demonstrated that most people found FIT to be an ambient reminder to eat vegetables and track intake. Our contributions are the definition of lock-screen ambience and the design and evaluation of FIT, an app that harnesses lockscreen ambience to raise awareness of, and support ultra-lite logging of, an important nutrition goal.

The aim of this research is to create a simple wearable technology for people engaged in upper limb rehabilitation to track how much they move their arm as well as the activities that the arm is engaged in. This paper describes the design of the `ArmBeta' prototype, which is based on the Microsoft Band 2 device and a mobile app. A lab-based trial study of ArmBeta with four healthy adults showed the accuracy for recognising reach-and-retrieve tasks was 78%, but the accuracy for other tasks (opening doors, eating, stirring a pot) was below 50%. A consecutive two-hour trial in daily life showed that the information generated was easy to understand but that the accuracy and accessibility need to be improved. We discuss the trade-offs between accessibility, accuracy, and the significance of information generated to track arm movement. The paper closes with considerations for future work to refine the system and to engage with patients and clinicians involved in rehabilitation.

We present the design of MyFootCare, a mobile app to support people with diabetic foot ulcers in their self-care. Self-care is a critical component of care for people with a diabetic foot ulcer as most of their ulcer care is provided away from the clinic. To promote better self-care, we designed a mobile application ‘MyFootCare’ that harnesses visual analytics and self-report to provide feedback about the healing process. MyFootCare encourages people to take a photo of their ulcer with their mobile phone each time they change their wound dressing. Based on computer vision techniques, users receive graphical feedback on changes in ulcer size over time to objectively track the healing progress. Additionally, MyFootCare seeks to foster self-care through personal goals, diaries, and reminders to enact care. Feedback from three people with chronic ulcers shows that the app builds on existing practices of taking wound photos and that it is seen as useful to track progress and to facilitate dialogue with clinicians. More work is underway to evaluate the use of MyFootCare in a deeper field study.

Personal informatics data are prevalent in clinical care today. My research builds an understanding patient and provider needs and challenges to advance the design of personal informatics systems and theoretical understandings of patient-provider collaboration. Through studies of patients with Irritable Bowel Syndrome and people who want to eat healthier, I study people's current tracking experiences and their collaborative review practices with providers. Based on these findings, I propose design and theoretical considerations regarding interactions among providers, patients, and patient-tracked data. I design and evaluate systems in situ to understand potential use of lightweight data collection and integration to support collaboration around personal informatics data.

Quantified Self (QS) field needs to start thinking of how situated needs may affect the use of self-tracking technologies. In this workshop we will focus on the idiosyncrasies of specific categories of users.

Despite increasing interests in learning tea mastery, current tea apps lack supports for tracking tea practices done by apprentices in the tea industry and tea aficionados who want to improve their skills. Because many of them practice their tea skills individually, a system is needed to support learners by (1) tracking tea practices in real time, and (2) estimating their improvements over time. This workshop paper analyzes recently released tea apps, suggests QS design sketches that support users' learning by displaying and comparing quantitative data collected from the trials of tea practices, and finally discusses challenges and the future work. This paper aims to provide insight into an understudied user group for future QS studies and suggests a novel design considering the users' needs.