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Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition
Abstract
Wearable activity trackers hold great potential for facilitating self-regulated health behavior, thereby improving physical fitness and preventing cardiovascular diseases. Unfortunately, many users discontinue tracking after only a few months, mitigating large-scale health effects. To identify usage barriers and psychological mechanisms resulting in tracker abandonment decisions, it is essential to characterize former users regarding their abandonment reasons as well as former tracker usage patterns. Within the present research, we reviewed past literature on wearable activity tracking attrition and developed an online questionnaire for assessing abandonment reasons. Results from 159 former users revealed insights into the relative importance of abandonment reasons, former users’ usage patterns, evaluation of personal quantification, and tracker acceptance. Correlational analyses showed that intensity of tracker usage and data interaction, current physical activity, and tracker acceptance were related to specific abandonment reasons. Moreover, abandonment due to perceived data inaccuracy/uselessness and loss of tracking motivation were linked to negative attitudes towards personal quantification. Furthermore, permanent abandonment decisions were particularly related to loss of tracking motivation. Based on the results, we derived six design guidelines for supporting continued tracker usage.
... Instead, the focus is often on those who use technology (e.g. Kuru 2016;Nuss and Li 2021), and non-users are typically framed as either previous (Attig and Franke 2020;Nuss and Li 2021) or future (Augustin et al. 2021;Chiu and Cho 2020) users. The knowledge interest is particularly technical (see Habermas, 1968) as one of the research tasks is to produce information on how non-users can be turned into users and/or how the use of technology can be increased (Chiu and Cho 2020, p. 820;Fronczek et al. 2022;Mathavan et al. 2022). ...
... Research on the use and non-use of sports technology is often quantitative and aims to explain causal relationships (e.g. Adesida, Papi, and McGregor 2019;Attig and Franke 2020;Camomilla et al. 2018;Chiu and Cho 2020;Janssen et al. 2020;Mathavan et al. 2022;Åkerberg, Söderlund, and Lindén 2017;cf. Esmonde 2020). ...
... socio-cultural, feminist) unacknowledged (Lupton 2020; for concrete examples, see, e.g. Attig and Franke 2020;Nuss and Li 2021;cf. Esmonde 2020). ...
The use of digital sports technology has become more the rule than the exception in digitalized societies. The normativity of technology use is also present in the research literature and there is only a little research on the non-use of technology. We see the non-use of technology as an active and conscious choice, reflecting people's relationship with digital society, with sport, and with themselves. We have limited the research context to recreational running, which, as a popular and highly technologized form of sport, offers a rich environment for research into the non-use of technology. Through an abductive analysis of the qualitative questionnaire data, we identified four partially overlapping themes: 1) Technology, and its use and non-use, are not categorical and binary things; 2) Non-use of technology as freedom; 3) The relationship between technology and the meanings attributed to running ; and 4) The material reasons for non-use of technology.
... However, a study conducted in a lower socioeconomic community indicated that those who adopted a new WT were more likely to already lead a healthier lifestyle [13]. Identified reasons for discontinuing WT use include loss of motivation, perceived measurement issues, poor design, obsessive tracking, and privacy concerns [14]. Privacy concerns seem to be a major issue when potential users even consider WT use [9,11]. ...
... While WT use is common in Finland [30], it is not known who the WT users are. Prior international research has recruited participants from social media or other web-based platforms [8,14,22], examined an otherwise restricted sample [12][13]31], for example consisting only of students and employees with graduate-level education and mid-to-high incomes or the study sample has had a specific age limit [1,3,[31][32][33]. One study did have a large population, but it did not entirely represent the intended population in terms of sex, age, education, and body mass index (BMI) [33]. ...
... On the other hand, older adults do not form a homogenous group and their needs should be assessed individually while at the same time considering possible obstacles to adopting new technology [47]. Providing users customizable tracker designs has been suggested by researchers to be meaningful for the continued use of WT in all ages [14]. ...
The use of wearable technology, which is often acquired to support well-being and a healthy lifestyle, has become popular in Western countries. At the same time, healthcare is gradually taking the first steps to introduce wearable technology into patient care, even though on a large scale the evidence of its' effectiveness is still lacking. The objective of this study was to identify the factors associated with use of wearable technology to support activity, well-being, or a healthy lifestyle in the Finnish adult population (20-99) and among older adults (65-99). The study utilized a cross-sectional population survey of Finnish adults aged 20 and older (n = 6,034) to analyse non-causal relationships between wearable technology use and the users' characteristics. Logistic regression models of wearable technology use were constructed using statistically significant sociodemographic, well-being, health, benefit, and lifestyle variables. Both in the general adult population and among older adults, wearable technology use was associated with getting aerobic physical activity weekly according to national guidelines and with marital status. In the general adult population, wearable technology use was also associated with not sleeping enough and agreeing with the statement that social welfare and healthcare e-services help in taking an active role in looking after one's own health and well-being. Younger age was associated with wearable technology use in the general adult population but for older adults age was not a statistically significant factor. Among older adults, non-use of wearable technology went hand in hand with needing guidance in e-service use, using a proxy, or not using e-services at all. The results support exploration of the effects of wearable technology use on maintaining an active lifestyle among adults of all ages.
... Reasons for usage stops and hesitance to or rejection of app usage may be different in nature and influenced by distinct barriers and should hence be examined independently. Recent investigations on general populations (not age group-specific) have addressed reasons for disrupted and discontinued app usage [77,78], thereby accounting for barriers to sustained usage acceptance. Still, most research on (mHealth) technology usage focuses on the pre-initiation phase, neglecting, for instance, investigations of sustained usage acceptance [73]. ...
... The interview setting itself may hence have functioned as a facilitating condition. Cabrita et al. [55] further revealed their interviewees' wishes and expectations that could facilitate future app adoption and/or continued use, with their findings being consistent with research on younger populations [71,78]. The specific study design used by Cabrita et al. [55] and potentially arising effects such as social desirability may have had an impact on their findings. ...
... Psychological aspects such as motivational processes [cf. 78] have hardly been examined and societal or cultural influences, amongst others, have not yet been considered with respect to our target group. ...
Background
To promote healthy aging, the support of digital mobile health tools such as mobile applications (apps) addressing a healthy diet or physical activity appears promising, particularly when initiated before entering old age. For such tools to be effective, middle-aged and older adults’ acceptance need to be studied in depth.
Objective
The aim of this systematic review was to provide an integrative synthesis of the current state of research regarding the question in how far middle-aged and older adults (people aged 50 years and above) accept mobile nutrition and fitness apps to gain a deeper understanding of the influencing factors shaping this target group’s usage behaviour and needs.
Methods
The review process followed the PRISMA guidelines. The databases Medline, Embase, Web of Science as well as reference lists were systematically searched. Study quality was assessed using the MMAT and AXIS appraisal tools. Data of the included studies were extracted and thereupon narratively synthesized, involving thematic analysis.
Results
Of N = 8823 articles screened, n = 7 studies could be identified–five quantitative, cross-sectional ones and two qualitative studies. Overall, the synthesized findings showed a lower acceptance among middle-aged and older adults compared to younger populations, which was particularly reflected in lower usage rates and more negative attitudes towards such apps (e.g., Perceived usefulness , Ease of use ). The target group’s acceptance of fitness apps was greater compared to nutrition apps. Findings on contextual factors and social determinants were inconsistent (e.g., regarding gender differences).
Conclusion
While cross-study comparability was limited, the synthesized evidence underscores the importance to target mobile nutrition and fitness apps to the distinctive and heterogeneous needs of middle-aged and, particularly, of older adults. The scarcity of the existing body of knowledge highlights the need of further (longitudinal) research.
PROSPERO protocol register number
CRD42020159409.
... By contrast, other reviews may focus on PA but restrict themselves to specific digital technologies. For example, Attig et al [12], focusing on wearable trackers for PA, summarized reported reasons for abandoning their use, such as usability issues and privacy concerns. mHealth is a commonly used innovative solution to deliver health interventions. ...
... Evidence on the topic of adherence or the related concept of engagement was included in 3 previous research studies [11,12,73]; however, all 3 differ from this review in terms of the focus of the interventions. Perski et al [11] developed a conceptual framework to highlight potential influences on engagement with a digital behavior change intervention and relationships between engagement and target behaviors. ...
... In addition, Perski et al [11] considered the engagement of users with a broad range of digital behavior change interventions rather than focusing on mHealth-based PA interventions. Attig et al [12] emphasized the exploration of factors that are related to the abandonment of an activity tracker rather than conceptualizing a framework for abandonment. Attig et al [12] identified less-intensive device use, less device interaction, and amount of PA achieved as important factors that affect abandonment of activity tracker use. ...
Background:
Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.
Objective:
Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.
Methods:
MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.
Results:
In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.
Conclusions:
This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.
... Research on wearable activity tracker abandonment has shown that between 30 and 70% of users discontinue tracking after a few months (e.g., Alley et al., 2016;Hermsen et al., 2017;Lee & Lee, 2017). Reasons for abandoning the device are extensive and cover factors related to the tracker itself (e.g., perceived measurement reliability issues), the user (e.g., changes in life circumstances) or user-tracker interaction outcomes (e.g., obsessive tracking; see Attig & Franke, 2020 for an overview of abandonment factors). However, discontinuation does not necessarily mean abandoning self-tracking altogether (Attig & Franke, 2020;Epstein et al., 2015;Gorm & Shklovski, 2019;Meyer et al., 2017;Trace & Zhang, 2019). ...
... Reasons for abandoning the device are extensive and cover factors related to the tracker itself (e.g., perceived measurement reliability issues), the user (e.g., changes in life circumstances) or user-tracker interaction outcomes (e.g., obsessive tracking; see Attig & Franke, 2020 for an overview of abandonment factors). However, discontinuation does not necessarily mean abandoning self-tracking altogether (Attig & Franke, 2020;Epstein et al., 2015;Gorm & Shklovski, 2019;Meyer et al., 2017;Trace & Zhang, 2019). In fact, episodic use might even be inherent to self-tracking as it might serve as a mechanism for coping with tracker-related stress (Gorm & Shklovski, 2019). ...
... Based on a systematic literature review that condensed the multitude of studies, Attig and Franke (2020) developed a questionnaire for assessing reasons for wearable activity tracker abandonment. Using this questionnaire in a quantitative study with former users of activity trackers, the authors were able to group abandonment reasons based on a factor-analytical approach into six broader factors (Attig & Franke, 2020; see Table 1). Thus, this factor analysis enabled insights into which abandonment reasons likely occur together and condensed these various reasons in preparation for subsequent correlational analyses. ...
Activity trackers are promising tools to increase the motivation to be physically active, thus strengthening users’ physical constitution and potentially preventing cardiovascular diseases. To establish behavioral changes with such beneficial consequences, prolonged continuous use of trackers seems to be necessary. However, the usage behavior of many tracker users is characterized by interruptions or complete discontinuation after only a few months. Which factors determine individual usage trajectories is still unclear. This research sheds light on user diversity to investigate how inter-individual differences are related to reasons for usage interruptions and permanence of abandonment. Results based on a survey of N = 159 former users revealed that usage motives regarding self-determination theory, domain-specific personality traits (affinity for technology interaction), and interaction variables (dependency effect, trust in activity tracker measurement) were related to specific reasons for usage interruptions. Moreover, highly autonomous usage motivation and high trust were linked to more fragile abandonment decisions.
... In general, loss of interest in activity tracking, poor accuracy, technical difficulties, habituation, and discomfort in wearing and charging the device have been identified as the most common reasons for the abandonment of wearable activity trackers among adults. 60 Similar observations were also included in our qualitative findings highlighting areas, where engagement issues may be most likely to occur. However, it should be noted that the reduced engagement over time can also be due to existing physically active habits or successful physical activity habit formation. ...
... However, it should be noted that the reduced engagement over time can also be due to existing physically active habits or successful physical activity habit formation. 60 ...
Objective
Activity trackers appear cost-effective and acceptable intervention tools for promoting physical activity among older adults, particularly in the short-term. However, long-term studies focused on participants’ experiences continue to be scarce. This study evaluated participants’ experiences of a 12-month activity tracker-driven physical activity intervention.
Methods
Participants’ experiences were assessed qualitatively using open-ended questionnaire items ( n = 113) and semi-structured interviews conducted after the 12-month intervention ( n = 27). Quantitative items assessed the perceived ease-of-use and usefulness of the activity tracker during the intervention. Qualitative data was analyzed using thematic analysis and Wilcoxon signed-rank tests were used to examine changes in the perceived ease-of-use and usefulness over time.
Results
The 113 participants completing the 12-month intervention were on average 65.2 ( SD 1.0) years old and 81.4% women with 92.3% providing activity tracker data on at least 2 weeks per each intervention month. In the qualitative analysis, four main themes with 20 subthemes were identified: (a) burdens of participation, (b) affective attitudes of using the activity tracker, (c) perceived effects of using the activity tracker, and (d) no perceived behavioral effects. At 12 months, the participants found activity trackers mainly easy to use (mean 4.6, SD 0.6), reliable (mean 3.6, SD 1.2), motivating (mean 3.9, SD 1.0), and helpful in reducing sitting (mean 3.7, SD 1.0) with no changes observed during the intervention.
Conclusions
The participants’ experiences were highly varied suggesting that tailored intervention designs are likely to be required for effectively using activity trackers to promote long-term changes in daily activity among older adults.
... The results show that users should choose MFAs that provide a complete set of fitness information (Completeness), wellformatted information (Format), correct information (Accuracy), most recent/real-time information (Currency), reliable information (Reliability), easily-accessible information (Accessibility), flexible functions (Flexibility), and integrated data (Integration) because those functions will increase the frequency of using goal setting and goal tracking functions, which, later, significantly assist users to achieve their goal and positively change their habits (physical activities). The findings are consistent with the literature that data inaccuracy or uselessness is one of the reasons for users to stop using a tracking fitness app (Attig & Franke, 2020). These characteristics of system quality and information quality are also a helpful guideline for MFA designers or providers to attract more users and increase frequency of using MFAs. ...
... The results are consistent with other previously published studies (Armitage, 2005;Miller et al., 2002;Sallis et al., 1990), showing that past perceived behavior is an important predictor of physical activity maintenance. Maher et al. (2017) and Attig and Franke (2020) also found the "happy abandonment" achieved when users reached their fitness goals and successfully formed physical activity habits. They no longer needed a fitness app to track their activities, and would more likely stop using the app. ...
Grounded in goal setting theory and other IS models, this study introduces a robust model, that examines the determinants of MFA goal setting and goal tracking use, and their impact on user behavior and achievement. The empirical results show that system quality and information quality are two key determinants of MFA goal setting and goal tracking use, which significantly influence a user’s goal achievement and behavioral change in terms of physical activities.
... Earables are compelling for activity recognition because many people wear ear-based devices, such as earphones or hearing aids, as they perform their everyday activities. In contrast, other wearables are commonly abandoned as activity trackers due to their inability to be incorporated into a person's everyday life (e.g., knee or waist trackers) [30,130]. ...
... The location of the earable presents a relatively stable platform from which to sense a wide range of movements and activities, in turn enabling recognition of exercises, sports, and other daily activities. Despite earables not achieving the best performance when used in isolation, they can support and complement other devices in the wider wearable eco-system [318], and the everyday use of ear-based form factors make them easier to integrate into everyday life than many other devices -an important factor for successful habit formation [30]. Beyond just classication, quantication of sensed phenomena can also support users to self-regulate healthy behaviours in their everyday life, from monitoring their levels of physical activity to tracking what food and drink they consume. ...
Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform.
... However, high thresholds of accuracy, suggested by one of our focus group participants, are unrealistic, particularly because of the uncertainty of the accuracy and reliability of data from commercial devices [23]. The expectation of having an accurate wearable activity tracker is consistent with several other studies [24]. Although no participants in this study directly questioned the accuracy of wearable activity trackers, the algorithms embedded within devices are typically developed using the movement patterns of healthy people, which may lead to higher data inaccuracies when applied to people with HD, who often present with motor symptoms involving their upper limbs and pathological gait characteristics. ...
... Concerns regarding data privacy were also raised in this study. These concerns are echoed in the literature [24,25,33]. Although patients may be open to sharing their personal information for the purpose of clinical benefit, there is a risk of data misuse. ...
Background:
There are early indications that lifestyle behaviors, specifically physical activity and sleep, may be associated with the onset and progression of Huntington disease (HD). Wearable activity trackers offer an exciting opportunity to collect long-term activity data to further investigate the role of lifestyle, physical activity, and sleep in disease modification. Given how wearable devices rely on user acceptance and long-term adoption, it is important to understand users' perspectives on how acceptable any device might be and how users might engage over the longer term.
Objective:
This study aimed to explore the perceptions, motivators, and potential barriers relating to the adoption of wearable activity trackers by people with HD for monitoring and managing their lifestyle and sleep. This information intended to guide the selection of wearable activity trackers for use in a longitudinal observational clinical study.
Methods:
We conducted a mixed methods study; this allowed us to draw on the potential strengths of both quantitative and qualitative methods. Opportunistic participant recruitment occurred at 4 Huntington's Disease Association meetings, including 1 international meeting and 3 United Kingdom-based regional meetings. Individuals with HD, their family members, and carers were invited to complete a user acceptance questionnaire and participate in a focus group discussion. The questionnaire consisted of 35 items across 8 domains using a 0 to 4 Likert scale, along with some additional demographic questions. Average questionnaire responses were recorded as positive (score>2.5), negative (score<1.5), or neutral (score between 1.5 and 2.5) opinions for each domain. Differences owing to demographics were explored using the Kruskal-Wallis and Wilcoxon rank sum tests. Focus group discussions (conducted in English) were driven by a topic guide, a vignette scenario, and an item ranking exercise. The discussions were audio recorded and then analyzed using thematic analysis.
Results:
A total of 105 completed questionnaires were analyzed (47 people with HD and 58 family members or carers). All sections of the questionnaire produced median scores >2.5, indicating a tendency toward positive opinions on wearable activity trackers, such as the devices being advantageous, easy and enjoyable to use, and compatible with lifestyle and users being able to understand the information from trackers and willing to wear them. People with HD reported a more positive attitude toward wearable activity trackers than their family members or caregivers (P=.02). A total of 15 participants participated in 3 focus groups. Device compatibility and accuracy, data security, impact on relationships, and the ability to monitor and self-manage lifestyle behaviors have emerged as important considerations in device use and user preferences.
Conclusions:
Although wearable activity trackers were broadly recognized as acceptable for both monitoring and management, various aspects of device design and functionality must be considered to promote acceptance in this clinical cohort.
... PART II -STATE OF RESEARCH AND STUDY DESIGN 2 SELF-TRACKING IN ACADEMIA -MAPPING THE FIELD Different aspects of the self-tracking phenomenon were researched in various academic disciplines, particularly in the science of human-computer-interaction (HCI) (e.g., Li et al., 2010Li et al., , 2011Rooksby et al. 2014;Swan, 2012), but also in medicine (e.g., Hoy, 2016), cognitive science (e.g., Attig & Franke, 2020), busines administration (Jahn et al., 2020), sociology (e.g. Lupton, 2016, Selke, 2016, cultural studies (e.g., Bernard, 2017;Sanders, 2017), philosophy (Buongiorno, 2019), sport science (e.g., Duttweiler et al., 2016), gamification studies (e.g., Abend & Fuchs, 2016;Whitson, 2013), literature studies (Danter et al., 2016), and led into a growing body of research. ...
... While in some studies participants have been able to reach goals (e.g., Choe et. al., 2014), in other studies they were not (e.g., Rooksby et al., 2014) or gave up after initially trying and facing technical or discipline related problems (e.g., Attig & Franke, 2020). Another facet of self-control in ST that was encountered (and will be substantiated by the results of this study) is not being able to control and in fact being addicted or feeling compelled to use these tools even though the circumstances might be dramatic or tragic (Foss, 2014). ...
This work focuses on the actor perspective and elaborates the relations to the self and the applied technology in self-tracking (ST), expanding critical studies. Based on ethnographic material with ST informants and four years of autoethnography by the author, two complementary but also individually occurring modes of self-relations were synthesized. Interwoven in a duality a co-existence and ambiguity of self-care and self-control, which appear as two sides of the same coin, emerge.
The self-control relation is characterized by increased awareness and complexity-reducing information about oneself, motivation (often occurring as self-challenge), and considering algorithmic recommendations, which summa summarum facilitate orientation and decision making in daily life. However, the self-control relation can go astray on the downside into losing control over the control (and becoming compulsive and addictive) and over the data.
The self-care relation entails placing oneself in the center of attention in a digital medium by increased self-thematization, archiving body diaries, and self-affirmation. Self-concepts are no longer primarily constructed, confirmed, or rejected by the social environment but also by applying digital technologies upon oneself. However, self-care can be undermined on the downside, such as self-doubt, self-deception (maybe narcissism), and self-distraction.
Three different relations to ST technology in technologically mediated self-care and self-control were elaborated: technology as a means, a counterpart (partner, nanny, coach), and a promise of salvation. Here another dialectic becomes visible. In using ST devices, the relationship of the users to technology seems to intensify, with the technology being able to perform a partner-like or even superior role.
Finally, the often-assumed self-optimization in ST emerges as harmonizing and balancing life-maintenance tasks.
... Within the HCI community, and among Quantified Self researchers in particular, attrition of users (or participants in the context of a study) is a well-known phenomenon [1,21,38]. For example, Gouveia et al. found that only 14% of the users of their app-based activity tracker used the application for longer than two weeks, despite implementing a number of literature-based design strategies to promote long-term engagement [16]. ...
While self-report studies are common in Human-Computer Interaction research, few evaluations have assessed their long term use. We present a longitudinal analysis of a web-based workplace application that collects well-being assessments and offers suggestions to improve individual, team, and organisational performance. Our dataset covers 219 users. We assess their first year of application use, focusing on their usage patterns, well-being evaluations, and behaviour towards notifications. Our results highlight that the drop-off in use was the steepest in the first week (-24.2%). However, substantial breaks in usage were common and did not necessarily result in dropout. We found that latency periods of eight days or more predicted a stronger intention to drop out than stay engaged and that reminder notifications did not result in more completed self-reports but significantly prolonged the usage period. Our work strengthens findings related to high drop out rates, but also provides counter-evidence by showing that despite individuals appearing to drop-off in short-term studies, individuals can and do return to self-report applications after extensive breaks. We contribute an analysis of usage behaviour drivers in the area of technology-enabled well-being measurement, responding to the call for longer-term research to extend the growing literature on self-report studies.KeywordsSelf-reportwell-beinglongitudinaldiary studyexperience sampling
... Although measurement inaccuracy is a common reason to abandon self-tracking technologies (Attig & Franke, 2020;Nuss & Li, 2021) data and accuracy mean different things for different runners. Typically, the most interested in technology and data are those for whom running is "serious leisure" (Feng & Agosto, 2019;Kuru, 2016;Stebbins, 2017), which includes goal-oriented training and regular participation in competitions (Qiu et al., 2020;Tainio, 2020). ...
Data literacy is typically described in a decontextualized manner, and many data literacy frameworks are detached from the "messy" realities of everyday life. In the present study, we selected a specific context (recreational running), specific data technology (self-tracking devices), and specific viewpoint (accuracy of data and analyses) to construct a substantial theory of (one form of) contextual data literacy. The research question is: How does recreational runners' everyday data literacy appear in relation to the accuracy of measurements and analyses of self-tracking devices? Through an abductive analysis of qualitative survey data (N ¼ 1057), we identified the data literacy actions that runners engaged with when assessing the accuracy of data in relation to their subjective needs, objectives, and life situations. The first-order data literacy actions (comparison and evaluation) captured how runners assessed and analyzed the accuracy of data, and they took place mainly in the immediate context of running. The second-order data literacy actions (accept-ance, adaptation, and optimization) were the result of the runners' reflections on what they sought from running and how they valued data, as well as their broader life situation.
... Attig and Franke [66] outlined several reasons for using these devices, including accuracy, data usefulness, design and comfort, motivation, privacy and so on. However, the high rate of usage attrition raises the issue of user satisfaction and perceptions of product usefulness for these devices. ...
Technology and its continuous advancement facilitate human beings to get rid of their criticality and limitation. Applied artificial intelligence (AAI) is one of the latest forms that delimited the limitation of human beings. Smartwatch acts as an applied artificial intelligence to assist various patients to check medical care without going to hospital and physicians. This (three) multiple-study research focused on the intention to use, purchase, and their satisfaction and spread positive word of mouth among others in the Ghanaian. To investigate these issues two renowned theories were underpinned- TAM theory and the Stimulus-Organism-Response (S–O-R). Total 550, 320, and 170 respondents were interviewed with Google forms due to COVID-19 using social media. AI-enabled smartwatch considering Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Perceived Credibility (PC), Perceived Self-Efficacy (PSE), and Perceived Financial Cost (PFC) were significant on intention to adoption and adoption intention on actual purchase. The final study showed device quality, its service level, their usage experience, perceived value, and the extent to which the satisfied customers made positive word of mouth to their friends and family, colleagues and followers. This research is significant in understanding the usage of AI-enabled smartwatches as a device doctor or electronic doctor (e-doctor).
... In [229], the authors argue that one might have the false perception that performing HAR using IMUs is already at a perfect state and that no further actions need to be done. On contrary, out of those who are not using their wearable devices sensing: 36% cited that this is due to the measurement accuracy and 34% cited that is because the improper activity tracking [230]. The authors argue that HAR is still far away from being solved due to the following reasons: (1) the difficulty in defining an activity, (2) Heterogeneous benchmarks, (3) Collecting ground-truth data for the HAR systems is expensive and not easy, (4) Various characteristics causes diverse activity profiles, (5) the lack of standardization in storing, processing, and analyzing the data. ...
Human activity recognition (HAR) using inertial motion data has gained a lot of momentum in recent years both in research and industrial applications. From the abstract perspective this has been driven by the rapid dynamics for building intelligent, smart environments, and ubiquitous systems that cover all aspects of human life including healthcare, sports, manufacturing, commerce etc., which necessitate and subsume activity recognition aiming at recognizing the actions, characteristics, and goals of one or more agent(s) from a temporal series of observations streamed from one or more sensors. From a more concrete and seemingly orthogonal perspective such momentum has been driven by the ubiquity of inertial motion sensors (IMUs) on-board mobile and wearable devices including smartphones, smartwatches, etc. In this paper we give an introductory and a comprehensive survey to the subject from a given perspective. We focus on a subset of topics, that we think are major, that will have significant and influential impacts on the future research and industrial-scale deployment of HAR systems. These include: (1) a comprehensive and detailed description of the iner-tial motion benchmark datasets that are publicly available and/or accessible, (2) feature selection and extraction techniques and the corresponding learning methods used to build workable HAR systems; we survey classical handcrafted datasets as well as data-oriented automatic representation learning approach to 1 the subject, (3) transfer learning as a way to overcome many hurdles in actual deployments of HAR systems on a large scale, (4) embedded implementations of HAR systems on mobile and/or wearable devices, and finally (5) we touch on adversarial attacks, a topic that is essentially related to the security and privacy of HAR systems. As the field is very huge and diverse, this article is by no means comprehensive; it is though meant to provide a logically and conceptually rather complete picture to advanced practitioners, as well as to present a readable guided introduction to newcomers. Our logical and conceptual perspectives mimic the typical data science pipeline for state-of-the-art AI-based systems.
... However, while governments and the tech sector highlight the benefits of digital health to improve healthcare services and to give more control to endusers, we argue that these technologies lack end-user input. As increasingly reported in international statistics (Fox et al., 2017;Gartner, 2016), people are no longer using consumer health wearables or they are abandoning health apps at a faster rate (Attig & Franke, 2020;Clawson et al., 2015). Acknowledging the growing number of studies in technology adoption across various disciplines (Jacobs et al., 2019;Li et al., 2019), we argue that a core reason that people turn away from self-health technologies is the design of these technologies: that is, current self-health technologies do not support people engagement. ...
The emergence of self-health technologies such as Fitbits and smart watches has not yet demonstrated success in influencing people's ability to improve their health. The design of self-health technologies must support people's decision making towards their health goals over time. This paper presents a theoretical model describing six stages of people engagement with self-health technologies for personal health goals. Following a Human Centred Design (HCD) approach, the model was applied in the design of new health tech products. Results indicate that the design of self-health technologies require s addressing the dynamic relationship between a personal health goal and the personal use of technology. The model presents a simple to apply strategy for designers and developers of self-health devices.
... A hordható egészségügyi eszközök (pl. fitneszkövetők, okosórák) területén végzett kutatások számos okot mutattak ki az eszközök használatára, tartós használatára és elhagyására, például egészségi állapottal, egészséggel kapcsolatoscélok,(de)motiváció,észlelthasznosság,mérési pontatlanság, használhatóság, kényelem, hozzáférhetőségésmagánélet (Simblettet al.2018,Attig& Franke 2020, Kovács -Várallyai 2021. König et al. (2018)szakirodalomfeldolgozásaalapjánmegállapította, hogy a fitnesz-alkalmazások általában népszerűbbek,mintatáplálkozásialkalmazások.A magyar piacra vonatkozó statisztikai adatok is ezt támasztják alá, legtöbb felhasználó az ingyenesen elérhető fitnesz applikációkat (6,58%) részesítette előnyben a fizetős fitnesz applikációkkal (3,8%) és táplálkozási alkalmazásokkal (1,47%) szemben (Statista2022b). ...
A TANULMÁNY CÉLJA Világszerte számos kutatást végeztek az m-health applikációkkal kapcsolatban, és az eredmények azt mutatják, hogy a jól megtervezett m-health alkalmazások javíthatják a gyógyszeres kezelést, és csökkenthetik az egészségügyi ellátás költségeit. Kutatásunk célja, hogy feltárjuk az m-health applikációk és különös tekintettel az életstílus-alkalmazások használatának elméleti hátterét és tapasztalatait felhasználói szemszögből. ALKALMAZOTT MÓDSZERTAN Az m-health alkalmazások használatát vizsgáló kérdőívek (MAUQ) közül az önálló applikációkra kifejlesztett skálát használtuk. Az applikációk értékelése három dimenzió mentén történt: a használat könnyűsége, az applikáció felületével való elégedettség, és a hasznosság megítélése. A két kutatási kérdés vizsgálatához kísérleti módszert alkalmaztunk, amit 22 hallgató bevonásával bonyolítottunk le, a 2021-es tanév őszi félévében, 14 héten keresztül. Az elemzés során leíró statisztikai mutatókat és páros t próbát alkalmaztunk. LEGFONTOSABB EREDMÉNYEK A vizsgált alanyok összességében 16 különböző applikációt értékeltek, melyek az életstílus applikációk öt területéhez sorolhatók: (1) sport és fitnesz tevékenységmérő, (2) étrend és táplálkozás, (3) stresszoldás és relaxáció, (4) női ciklus figyelés, illetve (5) betegségkezelés. A kísérletben résztvevő alanyok leginkább a könnyű használattal elégedettek és legkevésbé az applikációk felületével, valamint annak hasznosságának megítélésével. A kísérleti alanyok közül többen számoltak be pozitív hatásokról a fizikai és a mentális egészség javulása által. Az észlelt egészségjavulás szignifikáns (t=-4,55; p≦0,00) és a legkedvezőbb változás a diéta és táplálkozási alkalmazások esetében figyelhető meg. Biztató, hogy 17-en tervezik az applikációk további használatát. GYAKORLATI JAVASLATOK Kutatásunk eredményei különösen hasznosak lesznek az egészségtudatosságra és egészségfejlesztésre fókuszáló fogyasztók, alkalmazásfejlesztők és szolgáltatók számára. Az egészségügy esetében hozzájárulhat az ellátórendszer terheinek csökkentéséhez, valamint a telemedicina és a hagyományos egészségügy integrált fejlesztéséhez. Népességi szinten kiemelt szerepe van a megelőzés területén. A fejlesztőknek érdemes lenne nagyobb figyelmet szentelni az appok felületének fejlesztésére, a design-ra, a rendszerezésre, vagyis ergonómiai szempontokra. Ezen kívül, a fejlesztők számára lehetőséget kínál az ingyenesen elérhető szolgáltatások bővítésére, valamint a BigData adatok GDPR előírásainak megfelelő kezelésére, elemzésére. Köszönetnyilvánítás: A kísérleti alanyok toborzását és a kísérelt lefolytatásával kapcsolatos koordinációt ezúton köszönjük Dr. Printz-Markó Erzsébet egyetemi adjunktus asszonynak.
... A meta-review by Attig and Franke [47] shows several reasons for the abandonment of these devices, including usability, accuracy, data usefulness, design and comfort, loss of motivation, privacy and so on. These problems with attrition raise the issue of user satisfaction and perceptions of product usefulness. ...
The study assesses the effect of technology transfers on subjective well-being in 29 African countries. We adopt the GMM and the IV Tobit models and employ the Lifeladder indicator of happiness as a measure of subjective well-being. The findings reveal a positive significant effect of technology transfers on subjective well-being in Africa after accounting for the problems of autocorrelation, endogeneity, and heteroskedasticity. After controlling for the limited range of the subjective well-being indicator, the findings still indicate a positive significant effect of both residents' and abroad patent applications on the Lifeladder index. Employing scientific and technical article publication as an alternative indicator of technology transfers, the findings still indicate that subjective well-being in Africa is significantly improved by technology transfers and investments in academic research. The study suggests African economies should invest more in both human capital and technology infrastructure while developing patentable inventions that allow technology transfers to boost the continent's development and well-being.
... Nevertheless, the user's perspective has not received much attention despite its importance in providing better insight into consumer behaviours. More recently, a handful of prior studies had investigated such issues, and yet their studies were still limited to the topic of adoption intention or intention to use (Jacobs et al., 2019;Lee and Lee, 2018;Naglis and Bhatiasevi, 2019;Park, 2020;Ruup et al., 2018), continuance to use (Bölen, 2020;Dehghani et al., 2018;Nascimento et al., 2018), and abandonment (Attig and Franke, 2020). Meanwhile, post-adoption behaviours, including switching behaviours that play a critical role in customer relationship management and consumer behaviours (particularly customer's loyalty), have not been the focus of many previous studies. ...
... Previous researchers have noted a high rate of attrition in eHealth interventions. Explanations to the problem of the high dropout rate are required to find solutions [33,34]. Few studies have investigated the perspective of individuals living with chronic diseases on the use of eHealth and its integration with person-centered care [35][36][37]. ...
Background:
The trend of an exponential increase in prediabetes and type 2 diabetes (T2D) is projected to continue rising worldwide. Physical activity could help prevent T2D and the progression and complications of the disease. Therefore, we need to create opportunities for individuals to acquire the necessary knowledge and skills to self-manage their chronic condition through physical activity. eHealth is a potential resource that could facilitate self-management and thus improve population health. However, there is limited research on users' perception of eHealth in promoting physical activity in primary care settings.
Objective:
This study aims to explore the perspectives of health care professionals and individuals with prediabetes and T2D on eHealth to promote physical activity in primary care.
Methods:
A qualitative approach was applied using focus group discussions among individuals with prediabetes or T2D (14 participants in four groups) and health care professionals (10 participants in two groups). The discussions were audio-recorded and transcribed verbatim. Qualitative content analysis was used inductively to code the data.
Results:
Three main categories emerged: utility, adoption process, and accountability. The utility of eHealth was described as a motivational, entertaining, and stimulating tool. Registration of daily medical measurements and lifestyle parameters in a cohesive digital platform was recognized as a potential resource for strengthening self-management skills. The adoption process includes eHealth to increase the accessibility of care and personalize the support of physical activity. However, participants stated that digital technology might only suit some and could increase health care providers' administrative burden. Accountability refers to the knowledge and skills to optimize eHealth and ensure data integrity and security.
Conclusions:
People with prediabetes and T2D and health care professionals positively viewed an integration of eHealth technology in primary care to promote physical activity. A cohesive platform using personal metrics, goal-setting, and social support to promote physical activity was suggested. This study identified eHealth illiteracy, inequality, privacy, confidentiality, and an increased workload on health care professionals as factors of concern when integrating eHealth into primary care. Continuous development of eHealth competence was reported as necessary to optimize the implementation of eHealth technology in primary care.
... Our studies shed light on how anthropomorphized tracking devices influence consumer evaluations and motivations over time. Examining self-tracking devices over time offers critical causal insights into consumers' evolving intentions towards and evaluations of self-tracking (Attig & Franke, 2020;Costa Figueiredo et al., 2018;Maltseva & Lutz, 2018). In doing so, we contribute to the nascent marketing literature on self-quantification (e.g., Charitsis et al., 2019;Etkin, 2016;Paluch & Tuzovic, 2019;Pettinico & Milne, 2017). ...
Self-quantification, with the promise of motivating consumers to engage in health behaviors through measuring their performance, is a popular trend amongst consumers. Despite the economic impact of self-tracking technologies, consumers’ experiences with self-tracking devices and corresponding consequences for firms remain understudied. Six studies examine how the popular marketing tactic of anthropomorphization influences (a) consumers’ favorability towards wearable tracking devices, (b) their health motivation, and (c) their health behavior (number of steps taken) over time. The authors uncover a novel dynamic effect of anthropomorphism, such that with use, the initially positive evaluations of anthropomorphized (vs. non-anthropomorphized) devices decrease, and (contrary to prior literature), anthropomorphized devices are not favored. Importantly, health motivation and health behaviors are also reduced over time with the use of an anthropomorphized (vs. non-anthropomorphized) wearable device. This decrease occurs because anthropomorphized devices reduce the wearers’ perceived autonomy, which in turn, reduces their health motivation and health behavior. However, customizing the anthropomorphized device (by setting a customized goal or by monitoring a greater number of health-related indicators) can mitigate its negative effects. These findings provide novel insights to marketing scholars and managers, by suggesting that anthropomorphism can be a successful short-term selling strategy, but over time, it can have unintended consequences for both firms and consumers.
... There is a gap, however, between the potential of mobile technology and its current impacts on public health. Interventions to date that target health-promoting behaviors have small to moderate effects on behavior (53,119); engagement, and the associated health benefits, typically declines over time (7,16,102,103). Previous reviews have shed light on reasons for the untapped potential of mobile technology for promoting health behaviors. A common theme is that integrating knowledge across fields will help close the gap between the potential and impact of mobile technology (38, 67,99). ...
Health behaviors are inextricably linked to health and well-being, yet issues such as physical inactivity and insufficient sleep remain significant global public health problems. Mobile technology—and the unprecedented scope and quantity of data it generates—has a promising but largely untapped potential to promote health behaviors at the individual and population levels. This perspective article provides multidisciplinary recommendations on the design and use of mobile technology, and the concomitant wealth of data, to promote behaviors that support overall health. Using physical activity as an exemplar health behavior, we review emerging strategies for health behavior change interventions. We describe progress on personalizing interventions to an individual and their social, cultural, and built environments, as well as on evaluating relationships between mobile technology data and health to establish evidence-based guidelines. In reviewing these strategies and highlighting directions for future research, we advance the use of theory-based, personalized, and human-centered approaches in promoting health behaviors.
Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
... Our results clearly show that physiolytics' use decreases with time. Even if the disengagement may be temporary -because it is linked to a brief loss of motivation or to external factors [56]it seems critical for public officials to consider additional measures to accompany such digital occupational health initiatives. Since privacy laws prevent the PA to establish a mandated use of physiolytics for most areas of work [13,14], a relevant approach is to draw on positive reinforcements to recognize and reward this effort. ...
... Perceived values: Hedonic value was measured by adopting the three-item scale from Hong et al. (2017). Utilitarian value was measured by three items, including two items adopted from Hwang et al. (2016) Use frequency: The frequency of using wearable devices was assessed on the basis of three items adapted from the scale from Attig and Franke (2020). ...
S
Despite the enormous potential of wearables, the adoption rate of wearables among older people is low. To better understand the aspects influencing the adoption of wearables by older Chinese adults, this study investigates the changes in the usage behaviors, perceptions, and attitudes of older people toward wearables over four weeks. Twenty older people (age > 60 years) were included, and each of them was assigned a device for use at home. Information about features they desired and used, their perceptions of functional (i.e., affordances) and experiential qualities, perceived values, and adoption intention of wearables were collected before actual use and at weekly meetings during use. Results showed that health data monitoring was the most expected use of wearables before actual use and considered the most valued affordance throughout the period, although the less-than-anticipated actual experience reduced the usage. Interestingly, notification/reminders were not considered as important initially; however, the increasing usage increased its importance. Regression analysis showed that perceived utilitarian value was influential throughout the study, while hedonic value influenced the adoption intention only before actual use. These findings facilitate understanding how older people adopt wearables and provide practical design suggestions that could benefit the elderly population.
... However, there seems to be a lack of motivation from most users to keep using these health apps over a long period of time [3]. Attig et al. [4] assessed reasons for physical activity tracker attrition and found that lack of motivation was one of the main reasons for no longer wearing such trackers. For persons with chronic disease, continuous use of physical activity trackers are reported to improve their health management [5]. ...
Patient self-management is vital to improved health outcomes for patients with chronic diseases. The objective of this study was to understand the role of wearable sensors in patients’ self-management. A survey encompassing factors related to motivation in mHealth was conducted. Ease of use and sensory accuracy was found most important when choosing a wearable. Manual registration of most health-related information is unpopular, although some exceptions exist. Respondents valued sensor accuracy and easiness in manual registration and usage of mHealth systems. Further research is needed to pinpoint what ease of use exactly is, and how ease of use can be improved.
... The use of wearable technology for health care service provision is still in its infancy, and evidence to support its implementation is still being developed. Known concerns exist regarding passive data collection, data ownership, data use, user trust, and user attitudes toward wearable technologies, leading to potentially high abandonment rates [44,103]. ...
Background
An anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts.
Objective
This literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment.
Methods
A literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch.
Results
A total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep.
Conclusions
The results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.
... Why feedback is recommended and what actions should do to fix issues are considered to be important information (Li et al. 2011, Feustel et al. 2018. Lastly, uncontrollable using is a widely concerned reason for abandonment (Attig and Franke 2020), since raising awareness of privacy protection. Users like to know what data are collected, what are the purposes of collecting, and who is data shared with. ...
Since the characteristic of the Internet of Medical Things (IoMT) is featured with connectivity, distribution, and context-awareness (Rowland et al., 2015; Chin et al., 2019), it has become a common understanding of constant monitoring from surrounding “Ubiquitous” Environment. Concerning such sensing and monitoring situation for humans, devices, and the context, this study tackles a raising concern of tracking personal health data without an awareness (Sun et al., 2019). The challenge has two folds. On one hand, the amount of health data being collected and transferred continually through the network between different devices in any place and anywhere. Ideally, high convenience should be achieved for supporting reviewing and reflective thinking of end-users’ daily activities and vital health signals through data. However, quantified self-reflection hasn’t been achieved to facilitate human behavioural change to reach various healthy living goals. On the other hand, due to the vital role of visualized data that could effectively sufficient human requirements, the challenges of health data transparency (including data privacy, data security, and data visualization for various stakeholders etc.) are not only demonstrated by scholars but also lead to the negative user experience of connected devices. This study proposes a human-centred approach that aims at ensuring make sense of data transparency to enhance the IoMT experience. For instance, “trust and privacy” are critical issues for IoMT (Haghi Kashani et al., 2021), “access and storage” of health data are obscured and untraceable, “access control of data” (Calvillo-Arbizu et al., 2021), and the opacity of data process and abstraction (Hepworth, 2019) are reasons for losing trust, which users cannot know and modify the decision-making result of their data. The gulf between user expectations and understanding of this emerging technology leads to negative experiences. Despite the market has witnessed a breakthrough in the adoption of IoMT, evidence has shown a large percentage of abandonment (Clawson et al., 2015). User experience (UX) is the significant factor that influences long-term use (Hermsen et al., 2017). Zou et al. (2020) demonstrate the gap between the user’s perception and data interaction. Furthermore, how users make sense of their data is identified as one of the reasons for abandonment and treated as the key design challenge for IoMT stakeholders (Lazar et al., 2015; Ravichandran et al., 2017; Attig & Franke, 2020). As such, a review of existing data transparency and visualization related works for health data is conducted and summarized in this paper, which incorporates the following three aspects:1)The user perception of quantified health data.2)The interconnection of self-reflection and meaningful data representation through data visualization and physicalization.3)The design approach for tracking, accessing, and controlling data.Besides such a review, a ‘data transparency’ based guiding framework is also proposed to contribute and explore the relationship between UX design and health data, which has limited evidence been provided (Hepworth, 2019). Finally, the proposed framework intends to be validated from the user perception identification of existing products and design practice for utilizing the framework to address the data challenges of the IoMT system.
... 2. Prior research and theory 2.1 Prior research Numerous prior academic research in the area of fitness wearables were based on technologyfocused theme, which studies the technology-related issues of fitness wearables (Attig and Franke, 2020;Gonçalves and de Figueiredo, 2022;Gupta et al., 2021). These studies addressed the technical issues such as user's perception, affordances feasibility and quality of fitness wearables (Niknejad et al., 2020b). ...
Purpose
This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).
Design/methodology/approach
Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.
Findings
The findings support some of the hypotheses developed with R ² values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.
Practical implications
This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.
Originality/value
This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.
... Gamification is particularly beneficial in fields where individuals need to display long-term commitment and persistent behaviours, and tend to procrastinate (Koivisto & Hamari, 2019a), such as health and physical exercise. However, despite the initial excitement they feel when using gamified health and fitness apps, many users discontinue using them shortly after they download them (Feng et al., 2020), mainly due to loss of motivation (Attig & Franke, 2020). Therefore, a question arises: in the context of fitness apps, is gamification failing to motivate users and to improve their health? ...
This study analyses how gamification motivates users of gamified mobile exercise apps and enhances their health. Data from 276 Fitbit users were analysed using structural equation modelling. The findings showed that feelings of competence and autonomy arise when exercise apps include achievement and progression-oriented affordances, and that feelings of relatedness arise with social, immersion and achievement and progression-oriented affordances. They also revealed that exercise apps should satisfy the needs for competence and relatedness to develop individuals’ intrinsic motivation, which in turn leads to greater physical, mental and social health. These findings offer insights for managers in this industry.
... Monitoring responses to treatment is known to significantly improve mental health and substance user treatment outcomes (Goodman et al., 2013). Further, Attig and Franke (2020), found that tracking motivation was closely linked to continued engagement with personal fitness and health apps. Yet as our findings indicate, prompts to self-track can act as a negative or a positive reinforcer for engagement. ...
Justice services have begun to integrate the use of mobile applications into treatment, support, and rehabilitative programs for forensic clients. One such application that been adopted to support forensic clients is "eRecovery": a smartphone application that provides clients recovering from a substance addiction with support for managing relapse. In this article, we report on evaluation findings from a trial of eRecovery in an Australian Community Justice Centre, and reflect on several issues relating to fostering and sustaining client engagement with similar applications within forensic and justice settings. We propose the Service Design Engagement Model to organize, visualize, and describe the stages and factors important to adoption, appropriation, and on-going routine use of the software by forensic clients. The model recognizes the role of contextual and environmental factors in supporting users through the early stages of engagement, and the importance of user agency in longer-term engagement with therapeutic apps.
... Thus, although our results are consistent with some prior work that has concluded that concerns about losing privacy are not significant factors for adoption [92], there are possibilities that latent privacy concerns could affect long-term trust. Perceived costs of sharing data, including concerns about privacy, have been identified as a motivation for abandoning technology [9,26]. The number of people who have uninstalled a contact tracing app after having installed one seems to be small [15], so abandonment may not be an immediate concern for adoption rates. ...
COVID-19 has demonstrated the importance of digital contact tracing apps in reducing the spread of disease. Despite people widely expressing interest in using contact tracing apps, actual installation rates have been low in many parts of the world. Prior studies suggest that decisions to use these apps are largely shaped by pandemic beliefs, social influences, perceived benefits and harms, and other factors. However, there is a gap in understanding what factors motivate intention, but not subsequent behavior of actual adoption. Reporting on a survey of 290 U.S. residents, we disentangle the intention-behavior gap by investigating factors associated with installing a contact tracing app from those associated with intending to install, but not actually installing. Our results suggest that social norms can be leveraged to span the intention-behavior gap, and that a privacy paradox may influence people’s adoption decisions. We present recommendations for technologies that enlist individuals to address collective challenges.
... This has been particularly true when the smartwatch market has moved beyond the early adoption stage [6,7]. However, despite its high adoption rate, this highly prized innovation is facing an imminent threat: nearly one-third of users have discontinued using their smartwatch within a year, as they found it to be less useful and interesting [6,8,9]. This undesired behavioural pattern implies that firms cannot efficiently harvest data, which represents the core valuation of the IoT industry, and the development of smartwatches may be impeded [10]. ...
Smartwatch technology advancements have revolutionised a wide array of aspects of human life, ranging from communication to healthcare. As the smartwatch market moves beyond the initial adoption phase, there are questions regarding continued smartwatch usage. This study seeks to extend our understanding of sustained smartwatch usage. We propose and validate a framework that comprises technology-related features (i.e. perceived interactivity and perceived autonomy), fashion-related features (i.e. visual aesthetics and visibility), and psychographic factors (i.e. self-congruence and lifestyle congruence) as antecedents of value perception and smartwatch continuance intention. A quantitative survey was conducted with 275 smartwatch users, and the data were subjected to Partial Least Square-Structural Equation Modelling (PLS-SEM). The standard PLS-SEM findings, combined with importance performance map analysis (IPMA), indicate the relevance of perceived interactivity, perceived autonomy, visual aesthetics, self-congruence, and lifestyle congruence in determining value perception, which in turn positively influences continuance intention. A post-hoc multigroup analysis revealed the moderating effect of gender. These findings offer insights for smartwatch manufacturers and marketers to improve their products and develop more effective strategies to sustain smartwatch usage.
Wearables have seen an increase in popularity as the technology has advanced. Via physiological sensing, these devices allow individuals to easily monitor their daily health, but there are limitations in real-world implementation. One limitation is the ability of end users to properly gauge how well a device fits. Proper fit is often crucial for accurate data collection, as ill-fitting devices can result in poor performance. In this work, we examine the fit of the ring sizes the participants chose at the start of the in-the-wild study and examine the effect it has on sensor data. An analysis of 38 participants shows that only every third participant chooses an optimal ring size. We show that this leads to reduced efficacy of the wearable.Keywordsphysiological sensingfitness trackerin the wildsensor fit
Informal caregivers play an essential role in caring for persons who require assistance and in managing the health of their loved ones. Unfortunately, they need more health, leisure, and relaxation time. Nature interaction is one of many kinds of self-care intervention. It has long been regarded as a refreshing break from stressful routines, and research suggests exposure to nature interventions to improve the quality of life of caregivers. Despite not being the real thing, technology allows us alternatives that can still have some beneficial effects. In this preliminary study, we explore the benefits of natural environment videos on informal caregivers as an alternative to exposure to nature. Specifically, we are interested in the effects of their own choices versus a random video. We found that natural environment videos improve the well-being of informal caregivers in at least three key areas: valence, arousal, and negative affect. Furthermore, the effect increases when they choose the video they want to watch instead of a random video. This effect benefits the studied subjects because they need more time and energy to visit real natural environments.KeywordsInformal caregiversSelf-careWell-beingNature videos
One of the main promises of wearable sensing devices capable of physiological tracking is the potential that users can leverage the technology to make positive life changes. Now that these devices have sufficient accuracy, it is feasible that users could make decisions based on feedback from the device to change their habits and improve their well-being. A potential challenge to this, however, is whether users are able to recognize actual changes in their behavior compared to perceived changes. In this work, we look at participants who used the Oura ring as part of an in-the-wild study. Based on data analysis following 10–12 months of usage, we find that users who had positive perceptions of habit change towards sleep failed to show long-term improvement in their sleep quality, indicating a gap between perceived success and real-world impact. This work is important to informing the future design and implementation of health-tracking wearables.KeywordsWearable devicesIn-the-wildSelf-trackingSelf-reflection
In the last decade, the research interest in self-tracking practices mediated by wearable technologies has risen exponentially. A variety of contributions is focused on examining interaction modalities and user experiences to increase the usability and utility of such systems. However, several scholars are also committed to unveiling the inherent ethical, social and political implications of the self-tracking phenomenon, proposing an alternative perspective. Based on the review of contributions investigating polarities and issues in the landscape of self-tracking technologies, the current work proposes five interrelated tensions at play in the self-tracking domain. The tensions presented are allusion to objectivity and non-neutrality of numbers; trust in data and reliance on subjective experience; reductionism and complexity of lived phenomena; performance and wellbeing; and surveillance and self-surveillance. Rather than researching ways to avoid these tensions, the present contribution discusses the role that design may play in further exploring them. In particular, the paper illustrates studies leveraging speculative and critical design approaches to explore the ethical, political, and social issues of technologically-mediated self-tracking practices, as well as individuals’ relations with data, beyond conscious interaction.KeywordsWearable technologiesself-trackingdata representationstensionsspeculative design
Just-in-time (JIT) intervention aims to proactively detect a user's problematic behaviors and deliver interventions at an opportune moment to facilitate target behaviors. However, prior studies have shown that JIT intervention may suffer from user disengagement, a phenomenon in which a user's level of engagement with intervention apps and target behaviors declines over time. In this study, we aimed to deepen our understanding of disengagement in a mobile JIT intervention system. As a case study, we conducted a user study with college students (n = 54) for eight weeks to understand how disengagement appears over time and what factors influence user disengagement. Our findings reveal that personal traits, such as boredom proneness and self-control issues, are closely related to disengagement, with key factors including 1) boredom and habituation related to repetitive and monotonous JIT interventions, 2) inopportune alarm, 3) distrust for the JIT feedback mechanism, and 4) a lack of motivation due to low rewards. We provide theoretical and practical design guidelines for follow-up studies on JIT intervention system design.
The aim of the study is to provide an analytical overview of the resources and their management ensuring competitiveness of Hungarian family wineries. Family businesses need to be conscious of their various resources and to be able to identify and apply those to maintain competitiveness and to achieve the objectives. The awareness and possession of these resources is not in itself a sufficient basis; an organization-based optimal combination and effective integration are also crucial for success. The aims of the research carried out by the Budapest Business School were to identify and classify the existent and possible resources of Hungarian family business wineries. Furthermore, the research aimed to identify how these resources were integrated into the daily operation. Managing resources in an effective way and integrating them into a strategy is a creative, managerial task requiring meta-skills, experience, and tacit knowledge. This qualitative empirical research proves that familiness can facilitate but also complicate the operation of family businesses. The study demonstrates that resource-based theory can explain the performance of family businesses as well as an optimal combination of resources allows to gain competitiveness, but a real competitive advantage is linked to the goal setting of
Objectives:
Technology has substantial potential to transform and extend care for persons with chronic pain, a burdensome and costly condition. To catalyze the development of impactful applications of technology in this space, we developed the Pain Tech Landscape model (PTL), which integrates pain care needs with characteristics of technological solutions.
Methods:
Our interdisciplinary group representing experts in pain and human factors research developed PTL through iterative discussions. To demonstrate one potential use of the model, we apply data generated from a narrative review of selected pain and technology journals (2000-2020) in the form of heat map overlays, to reveal where pain tech research attention has focused to date.
Results:
The PTL comprises three two-dimensional planes, with pain care needs on each x-axis (measurement to management), and technology applications on the y-axes according to: a) user agency (user- to system-driven), b) usage timeframe (temporary to lifelong), and c) collaboration (single-user to collaborative). Heat maps show that existing applications reside primarily in the "user-driven/management" quadrant (e.g., self-care apps). Examples of less developed areas include artificial intelligence and internet of things (i.e., internet-linked household objects), and collaborative/social tools for pain management.
Conclusion:
Collaborative development between the pain and tech fields in early developmental stages using the PTL as a common language could yield impactful solutions for chronic pain management. The PTL could also be used to track developments in the field over time. We encourage periodic re-assessment and refinement of the PTL model, which can also be adapted to other chronic conditions.
Stories are a core way human beings make meaning and sense of the world and our lived experiences, including our behaviors, desires, and goals. Narrative structures, both visual and textual, help us understand and act on information, while also evoking strong emotions. Focusing on the health context, this research examines the effectiveness of narrative-based feedback in motivating physical activity behaviors and underlying attitudes over longitudinal periods. After collecting two weeks of baseline physical activity levels, N=39 participants installed our smartphone application, WhoIsZuki. The WhoIsZuki app supports goal setting and semi-automated activity tracking, and it provides an ambient display that visually encodes these tracked activities as well as progress toward goals. Half of participants received a version of the interface that supplied behavioral feedback in the form of a multi-chapter episodic narrative, while the other half received a control condition version that provided an aesthetically-similar visualization but without any characterization, episodic structure, dramatic effect, or other narrative elements. After interacting with these versions for four months, our analysis showed that participants receiving the multi-chapter narrative feedback performed more physical activity, achieved more goals, experienced more positive psychological shifts, and overall engaged more meaningfully with the digital intervention.
Background:
Heart failure (HF) is the leading cause of hospitalization among older adults in the United States. There are substantial racial and geographic disparities in HF outcomes, with patients living in southern US states having a mortality rate 69% higher than the national average. Self-management behaviors, particularly daily weight monitoring and physical activity, are extremely important in improving HF outcomes; however, patients typically have particularly low adherence to these behaviors. With the rise of digital technologies to improve health outcomes and motivate health behaviors, sensor-controlled digital games (SCDGs) have become a promising approach. SCDGs, which leverage sensor-connected technologies, offer the benefits of being portable and scalable and allowing for continuous observation and motivation of health behaviors in their real-world contexts. They are also becoming increasingly popular among older adults and offer an immersive and accessible way to measure self-management behaviors and improve adherence. No SCDGs have been designed for older adults or evaluated to test their outcomes.
Objective:
This randomized clinical trial aims to assess the efficacy of a SCDG in integrating the behavioral data of participants with HF from weight scale and activity tracker sensors to activate game progress, rewards, and feedback and, ultimately, to improve adherence to important self-management behaviors.
Methods:
A total of 200 participants with HF, aged ≥45 years, will be recruited and randomized into 2 groups: the SCDG playing group (intervention group) and sensor-only group (control group). Both groups will receive a weight scale, physical activity tracker, and accompanying app, whereas only the intervention group will play the SCDG. This design, thereby, assesses the contributions of the game. All participants will complete a baseline survey as well as posttests at 6 and 12 weeks to assess the immediate effect of the intervention. They will also complete a third posttest at 24 weeks to assess the maintenance of behavioral changes. Efficacy and benefits will be assessed by measuring improvements in HF-related proximal outcomes (self-management behaviors of daily weight monitoring and physical activity) and distal outcomes (HF hospitalization, quality of life, and functional status) between baseline and weeks 6, 12, and 24. The primary outcome measured will be days with weight monitoring, for which this design provides at least 80% power to detect differences between the 2 groups.
Results:
Recruitment began in the fall of 2022, and the first patient was enrolled in the study on November 7, 2022. Recruitment of the last participant is expected in quarter 1 of 2025. Publication of complete results and data from this study is expected in 2026.
Conclusions:
This project will generate insight and guidance for scalable and easy-to-use digital gaming solutions to motivate persistent adherence to HF self-management behaviors and improve health outcomes among individuals with HF.
Trial registration:
ClinicalTrials.gov NCT05056129; https://clinicaltrials.gov/ct2/show/NCT05056129.
International registered report identifier (irrid):
DERR1-10.2196/45801.
The aim of the present study was to explore perceptions of the Digital Twin (a three-dimensional digital representation of an anatomical body) on a mobile health application, and the potential mechanisms that are important for behaviour change, with a focus on health and weight management. An explorative and participant-led approach was taken using semi-structured online interviews to explore the experiences of people, in this case non-users and users wanting to independently manage their health. An opportunity sample of forty participants from the United Kingdom (20 who had not used digitally assistive technology and 20 who had) were recruited from social media platforms (22 females and 18 males; mean age was 30). The interviews were transcribed verbatim and analysed using Thematic Analysis. Two main themes were elicited: Initiators of behaviour change (i.e., autonomous choices, social influences, and personalisation) and Barriers to behaviour change (i.e., adverse reactions, weight management norms and negative attitudes). Overall, it was suggested that the Digital Twin should be representative of a user’s personalised health information and BMI. These results can inform an intervention designed to use the Digital Twin to initiate and maintain lifestyle behaviour change. It can also develop our understanding of how such technology can be applied as a tool for health management.
Promoting behavioral changes through feedback: A systematic literature review
Feedback has been identified as a key ingredient for strengthening social marketing interventions. In this respect, a systematic literature review was conducted based on eighty-four articles in order to understand the effects of a feedback intervention on behavioral change. This research puts into perspective the most frequently manipulated variables and ultimately offers recommendations for all stakeholders.
Background
Emerging evidence suggests that individuals use mHealth apps in multiple disjointed ways in the real-world—individuals, for example, may engage, take breaks, and re-engage with these apps. To our knowledge, very few studies have adopted this ‘multiple-live’ perspective to analyze long-term usage of a physical activity (PA) app. This study aimed to examine the duration of use, as well as the frequency, length, and timing of streaks (uninterrupted periods of use) and breaks (uninterrupted periods of non-use) within a popular commercial PA app called Carrot Rewards over 12 months. We also examined sociodemographic correlates of usage.
Method
This retrospective observational study analyzed data from 41,207 Carrot Rewards users participating in the “Steps” walking program from June/July 2016 to June/July 2017. We measured four usage indicators: duration of use, frequency and length of streaks and breaks, time to first break, and time to resume second streak. We also extracted information regarding participants' age, gender, province, and proxy indicators of socioeconomic status derived from census data. We used descriptive statistics to summarize usage patterns, Kaplan-Meier curves to illustrate the time to first break and time to resume second streak. We used linear regressions and Cox Proportional Hazard regression models to examine sociodemographic correlates of usage.
Results
Over 60% of the participants used Carrot Rewards for ≥6 months and 29% used it for 12 months (mean = 32.59 ± 18.435 weeks). The frequency of streaks and breaks ranged from 1 to 9 (mean = 1.61 ± 1.04 times). The mean streak and break length were 20.22 ± 18.26 and 16.14 ± 15.74 weeks, respectively. The median time to first break was 18 weeks across gender groups and provinces; the median time for participants to resume the second streak was between 12 and 32 weeks. Being female, older, and living in a community with greater post-secondary education levels were associated with increased usage.
Conclusion
This study provides empirical evidence that long-term mHealth app usage is possible. In this context, it was common for users to take breaks and re-engage with Carrot Rewards. When designing and evaluating PA apps, therefore, interventionists should consider the 'multiple-lives' perspective described here, as well as the impact of gender and age.
Physical inactivity is a global public health challenge, and effective, large-scale interventions are needed. We examined the effectiveness of a population-wide mHealth intervention in Singapore, National Steps Challenge Season 3 (NSC3) and two booster challenges (Personal Pledge, Corporate Challenge). The current study includes 411,528 participants. Regression discontinuity design and difference-in-difference with fixed-effects regression examined the association of NSC3 and the additional booster challenges on daily step counts. Participants tended to be female (58.5%), with an average age of 41.5 years (SD = 13.9) and BMI of 23.8 kg/m2 (SD = 4.5). We observed that NSC3 was associated with a mean increase of 1437 steps (95% CI, 1408 to 1467) per day. Enrolment in the Personal Pledge and Corporate Challenge was associated with additional mean increases of 1172 (95% CI, 1123 to 1222) and 896 (95% CI, 862 to 930) steps per day, respectively. For NSC3, the associated mean increase in the step counts across different sex and age groups varied, with greater increases for females and those in the oldest age group. We provide real-world evidence that suggests NSC3 was associated with improvements in participants' step counts. Results suggest NSC3 is an effective and appealing population-wide mHealth physical activity intervention.
A confluence of advances in biosensor technologies, enhancements in health care delivery mechanisms, and improvements in machine learning, together with an increased awareness of remote patient monitoring, has accelerated the impact of digital health across nearly every medical discipline. Medical grade wearables-noninvasive, on-body sensors operating with clinical accuracy-will play an increasingly central role in medicine by providing continuous, cost-effective measurement and interpretation of physiological data relevant to patient status and disease trajectory, both inside and outside of established health care settings. Here, we review current digital health technologies and highlight critical gaps to clinical translation and adoption.
This proceeding presents the papers presented at the 18th Scandinavian Conference on Health Informatics - SHI 2022 in Tromsø, Norway on August 22-24, 2022.
The SHI conference is an annual scientific event attended by scientist and practitioners working in the field of Health Informatics. The area of Health informatics is driven by development in technologies and informatics research that are advancing in parallel and for the integration of information and communication of health and social care. The area includes issues related to EHR, eHealth services and systems, intelligent systems, mobile health applications, telemedicine, assistive technology, artificial intelligence, and Internet of Things.
The field of Health Informatics in this conference is examined from a very broad perspective with participants presenting research outcomes and with focus on eHealth, informatics, Assistive technologies, machine learning, gaming, Internet of the Things, Implementation of eHealth services, EHR, Artificial Intelligence, management and organizational aspects, legal and social issues. More than 40 manuscripts were received with a total of 32 accepted as full papers and 11 as extended abstracts after peer-review. The Editorial Board selected publications with relevance and quality of the field to provide a state-of-the-art of the area. Authors of these communications are researchers of 35 different affiliations, and 13 countries (in alphabetic order: Czech Republic, Denmark, Finland, Germany, India, Italy, Luxembourg, Netherlands, Norway, Pakistan, Sweden, Switzerland, and USA).
All contributions are peer reviewed. The Editorial board expect this proceeding will be of interest for researchers and practitioners working in the field of Health Informatics.
Among many other things, 2022 made us aware of the value of networking. The past years , due to the Covid pandemic, demonstrated the necessity for access to information to improve health and healthcare, and the need for professionals to use and apply that information to transform healthcare. At the same time, the past years made us aware of different approaches and of the importance of Health informatics for renew and innovation of health and social care to improve the delivery of health and social care services to benefit citizens and patients, as we were forces to adapt to a “new normal” in many areas.
The Editors would like to thank the members of the Scientific Program Committee, the Organizing Committee, and all reviewers, who carried out the very professional, through and objective refereeing of the scientific work in order to achieve a high-quality publishing achievement for this scientific event.
The Editors would like to thank Linköpings University press, Sweden for the publication of the processing as an Open access Book. We expect the SHI 2022 provides a forum for research and researchers in Health Informatics, as well as to facilitate scientific discussion, share experiences, and promote collaboration and networking between researchers and practitioners across all countries.
In addition to the delegates presentations, SHI 2022 had the following keynote speakers: Prof. Sabine Koch from Karolinska Institutet (Sweden), Dr. Morten Hasselstrøm Jensen from Aalborg University (Denmark), Prof. and chief physician Audny Anke from the University Hospital of North-Norway (Norway), and research scholar & psychologist Henriette Michalsen, University Hospital of North-Norway (Norway).
Purpose
Online task-oriented check-ins (i.e. OTOCs) are popular means of tracking personal progress in certain fields. This study focused on the use of OTOC platforms and explored the predictors of individuals' continuing usage intention.
Design/methodology/approach
A model was proposed to understand Chinese users' continuous intention of OTOCs based on the UTAUT framework. Perceived social presence was also incorporated as a predictor of continuance intention of OTOC platforms. A survey of 397 users of the OTOC platforms was conducted in Nanjing, China.
Findings
Performance expectancy, hedonic motivation, and habit had direct, positive influence on the continuous use intention, whereas effort expectancy and social influence were not significant predictors of continuance intention of OTOCs. Perceived social presence was a significant, indirect predictor of intention to continuously use the OTOCs, and the relationship was mediated by performance expectancy, hedonic motivation, and habit.
Originality/value
This study distinguished OTOCs from other modes of self-tracking and extended the UTAUT framework by incorporating perceived social presence as a predictor of continuous technology use in the context of OTOCs. This study also provided a deeper understanding of the interrelations between the explanatory variables of the model that have been identified as robust in previous literature on technology use.
Background
Literature shows a litany of health issues disproportionately impacting Black Americans, with physical inactivity as a major risk factor.
Purpose
This study seeks to understand the role of smartwatches in physical activity uptake and subsequent improvement in health outcomes for students at HBCUs (Historically Black Colleges & Universities).
Methods
We administered an electronic survey to undergraduate students (n = 215) about smartwatch ownership, features, competitions, fitness goals and accomplishments, exercise tracking, frequency of exercise, perceptions of weight, and student demographics.
Results
Smartwatch owners who were aware of features such as calorie counting were significantly more likely to exercise at the gym at least once per week. The majority recorded themselves running and competed with other smartwatch users in some fashion. Others were unaware of fitness tracking features. Overall, smartwatch users were not more likely to workout than non-users and were significantly more likely to see themselves as overweight.
Discussion
Many smartwatch users are unaware of exercise tracking features and not using the devices to become more physically active.
Translation to Health Education Practice
Motivations for purchasing smartwatches must be explored, and initiatives to showcase the technology’s fitness promotion potential and encourage competition between users could yield positive health impacts.
Recent market reports have suggested that adoption of the Internet of Things (IoT) does not always lead to long-term use. This paper aims to advance an understanding of the sociological process of the (non-)use of the IoT. To this end, we present results from a mixed-methods study that analyzed survey data from 834 IoT users in the U.S. Many of our participants treated these devices as co-actors for achieving their goals and continued to use them because they had developed a routine or because the devices influenced their social interactions and identity. Participants limited their use of a device when they did not feel in control, when the device failed to understand their intent, or when they did not understand the device's behavior. We also found that excessive information offered by, disappointment due to, and the complexity of the devices led to their abandonment. Lastly, we discuss the implications of our results for understanding technology (non-)use and provide design recommendations.
Wearable activity trackers (WAT) are electronic monitoring devices that enable users to track and monitor their health-related physical fitness metrics including steps taken, level of activity, walking distance, heart rate, and sleep patterns. Despite the proliferation of these devices in various contexts of use and rising research interests, there is limited understanding of the broad research landscape. The purpose of this systematic review is therefore to synthesize the existing wealth of research on WAT, and to provide a comprehensive summary based on common themes and approaches. This article includes academic work published between 2013 and 2017 in PubMed, Embase, Scopus, Web of Science, ACM Digital Library, and Google Scholar. A final list of 463 articles was analyzed for this review. Topic modeling methods were used to identify six key themes (topics) of WAT research, namely: 1) Technology Focus, 2) Patient Treatment and Medical Settings, 3) Behavior Change, 4) Acceptance and Adoption (Abandonment), 5) Self-monitoring Data Centered, and 6) Privacy. We take an interdisciplinary approach to wearable activity trackers to propose several new research questions. The most important research gap we identify is to attempt to understand the rich human-information interaction that is enabled by WAT adoption.
Background
Although smartphone apps might support physical activity (PA), engagement with them tends to be low.
Objective
This study aimed to examine potential users’ needs and preferences regarding their engagement with PA apps during a first exposure to a never-used PA app and after 2 weeks’ usage.
Methods
A longitudinal, one-arm qualitative study was conducted with potential PA app users. At baseline, participants (N=20) were asked to explore 1 of 3 randomly allocated PA apps while thinking aloud. Semistructured interview techniques allowed participants to elaborate on their statements. After 2 weeks, follow-up interviews explored participants’ (n=17) lived experiences of real-world app use. Verbal reports from both time points were analyzed using inductive thematic analysis.
Results
Features that promote a fair and simple user experience, support users’ self-regulation skills, and address users’ exercise motives were considered important for engagement both during a first exposure and after a 2-week use of PA apps. Features that support users’ need for relatedness as well as those that facilitate users to implement their intentions were expected to be important for engagement mainly during a first exposure to PA apps. Proactive and tailored features that integrate behavioral, psychological, and contextual information to provide adaptive exercise plans and just-in-time support were considered relevant to sustain engagement over time.
Conclusions
App features that address users’ exercise motives, promote self-regulation, and fulfill users’ need for relatedness might promote engagement with PA apps. Tailored and proactive features were expected to promote sustained engagement.
Given the large discrepancy between rates at which wearable activity trackers (WATs) are initially adopted and their continued use, the question concerning how sustainable use emerges arises. While IS research has found habit an important driver of sustained use, the mechanisms of habit formation have been left unexplored. To address this research gap, we conducted narrative interviews to investigate the habit-formation mechanisms behind the use of WATs. We identified two drivers of habitual WAT use and constructed five narratives that provide insights into the habit-formation processes of WAT users and possible interrupting factors. Our results provide a valuable basis for both theory and practice in explaining how sustained WAT use develops.
Mobile health (mHealth) technologies have increasingly been used in interventions to promote physical activity (PA), yet, they often have high attrition rates. Integrating social features into mHealth has the potential to engage users; however, little is known about the efficacy and user engagement of such interventions. Thus, the aim of this systematic review was to characterize and evaluate the impact of interventions integrating social features in mHealth interventions to promote PA. During database screening, studies were included if they involved people who were exposed to a mHealth intervention with social features, to promote PA. We conducted a narrative synthesis of included studies and a meta-analysis of randomized controlled trials (RCTs). Nineteen studies were included: 4 RCTs, 10 quasi-experimental, and 5 non-experimental studies. Most experimental studies had retention rates above 80%, except two. Social features were often used to provide social support or comparison. The meta-analysis found a non-significant effect on PA outcomes [standardized difference in means = 0.957, 95% confidence interval −1.09 to 3.00]. Users’ preferences of social features were mixed: some felt more motivated by social support and competition, while others expressed concerns about comparison, indicating that a one-size-fits-all approach is insufficient. In summary, this is an emerging area of research, with limited evidence suggesting that social features may increase user engagement. However, due to the quasi-experimental and multi-component nature of most studies, it is difficult to determine the specific impact of social features, suggesting the need for more robust studies to assess the impact of different intervention components.
Wearable fitness devices (i.e., activity trackers) are increasingly popular for monitoring everyday activity. Research suggests that long-term adherence to activity trackers is relevant for their positive effects on health. Thus, it is essential to understand the factors that foster usage intensity and long-term adherence. Based on first research regarding users’ motives for using activity trackers and self-determination theory, we examined usage motives as predictors for the current and estimated future usage intensity. In addition, we investigated the relation of usage motives and user diversity facets (affinity for technology interaction, geekism, and need for cognition). Results of an online study with N = 58 regular users of activity trackers indicated a substantial variation of users’ intrinsic/extrinsic motivation for using an activity tracker. Further, positive relationships between intrinsic motivation, autonomous regulation and usage intensity were found. Regarding user diversity, affinity for technology interaction and geekism predicted the intrinsic motivation whereas need for cognition did not. Our results imply that, in order to obtain possible beneficial health effects of a more intensive activity tracker usage, users’ intrinsic motivation and autonomy have to be supported.
Technological advances in wearable computing are changing the sports domain. A variety of Personal Informatics (PI) tools are starting to provide support and improve athletes’ performance in many sports. In this article, we interviewed 20 amateur and elite athletes of different disciplines, using an array of PI devices, to explore how sports, as well as athletes’ experience, are affected by such instruments. We discovered that amateur athletes present different patterns of usage compared to elite ones. Moreover, we found that elite athletes make sense of their data by exploiting the knowledge they have about their own body and sports practice. We then proposed four considerations for design that we believe should be explored in the future, to reflect on how self-tracking is changing our perspective on sports, and, by and large, on our everyday life.
Personal quantification is one fundamental mechanism of gamification. Activity trackers constitute a prototypic case for studying the psychological dynamics of this mechanism. Despite their high potential to increase physical activity, health and well-being, the effects of trackers on users’ motivation to be physically active have yet rarely been explored. The present research examines the notion that quantified feedback of gamified systems can create a dependency that can harm motivation, which becomes apparent through activity reduction when the tracker is not available. To generalize findings from experimental studies to a naturalistic setting, we examined motivational effects of activity trackers in 210 actual users through a scenario- and questionnaire-based survey. Moreover, facets of user diversity (i.e., need for cognitive closure, affinity for technology interaction, achievement motivation, and the Big Five personality traits) were taken into account. Results indicated that a decrease of motivation for physical activity in situations when the tracker is not available plays a role in everyday usage. This dependency effect was stronger for participants with high extrinsic motivation for physical activity and tracker usage, high need for cognitive closure, and low hope of success. In contrast, high intrinsic motivation for physical activity was related to a less strong dependency effect.
The potential of things or objects generating and processing data about day-to-day activities of its users has given a new level of popularity to Internet of Things (IoT) among its consumers. Even though the popularity has seen a steady increase, the use of IoT devices has been slow and abandonment rapid. To build on the existing literature and advance our understanding of the sociological processes of use and non-use of these devices, this paper presents results from the survey of 489 IoT users. Our qualitative analysis of open ended questions revealed that the motives for use include multi-functionality of devices that provide control over daily activities, social competitive edge, economic advantage, and habit. The justifications for limiting or stopping the use include privacy concerns, information overload and inaccuracy, demotivation because of the reminders about pending or failed goals, no excitement after satisfying initial curiosity, and maintenance becoming unmanageable in terms of effort, time, and money.
While the number of users sporting fitness trackers is constantly increasing, little is understood about how tracking goals can evolve over time. As recent studies have shown that the long-term health effects of trackers are limited, we need to readdress how trackers engage users. We conducted semi-structured interviews and an online survey to explore how users change their tracking goals. Based on our results, we created the Tracker Goal Evolution Model. The model describes how tracker goals can evolve from internal user needs through qualitative goals to quantitative goals that can be used with trackers. It also includes trust and reflection as key contextual factors contributing to meaningful transitions between goals. We postulate showing how tracker goals relate to other personal fitness goals as key for long-term engagement with trackers. Our model is useful for designers of future trackers as a tool to create evolving and meaningful tracking goals.
Background:
Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion.
Objective:
The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities.
Methods:
A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs).
Results:
Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under the resting state (MAPE of 0.04), whereas Dongdong performed the best for the measurement of the number of steps under the walking state (MAPE of 0.01). Fitbit Surge performed the best for distance measurement under the cycling state (MAPE of 0.04), and Huawei Talk Band B3 performed the best for energy consumption measurement under the walking state (MAPE of 0.17).
Conclusions:
At present, mainstream devices are able to reliably measure heart rate, number of steps, distance, and sleep duration, which can be used as effective health evaluation indicators, but the measurement accuracy of energy consumption is still inadequate. Fitness trackers of different brands vary with regard to measurement of indicators and are all affected by the activity state, which indicates that manufacturers of fitness trackers need to improve their algorithms for different activity states.
Background:
Wearable activity trackers have the potential to be integrated into physical activity interventions, yet little is known about how adolescents use these devices or perceive their acceptability.
Objective:
The aim of this study was to examine the usability and acceptability of a wearable activity tracker among adolescents. A secondary aim was to determine adolescents' awareness and use of the different functions and features in the wearable activity tracker and accompanying app.
Methods:
Sixty adolescents (aged 13-14 years) in year 8 from 3 secondary schools in Melbourne, Australia, were provided with a wrist-worn Fitbit Flex and accompanying app, and were asked to use it for 6 weeks. Demographic data (age, sex) were collected via a Web-based survey completed during week 1 of the study. At the conclusion of the 6-week period, all adolescents participated in focus groups that explored their perceptions of the usability and acceptability of the Fitbit Flex, accompanying app, and Web-based Fitbit profile. Qualitative data were analyzed using pen profiles, which were constructed from verbatim transcripts.
Results:
Adolescents typically found the Fitbit Flex easy to use for activity tracking, though greater difficulties were reported for monitoring sleep. The Fitbit Flex was perceived to be useful for tracking daily activities, and adolescents used a range of features and functions available through the device and the app. Barriers to use included the comfort and design of the Fitbit Flex, a lack of specific feedback about activity levels, and the inability to wear the wearable activity tracker for water-based sports.
Conclusions:
Adolescents reported that the Fitbit Flex was easy to use and that it was a useful tool for tracking daily activities. A number of functions and features were used, including the device's visual display to track and self-monitor activity, goal-setting in the accompanying app, and undertaking challenges against friends. However, several barriers to use were identified, which may impact on sustained use over time. Overall, wearable activity trackers have the potential to be integrated into physical activity interventions targeted at adolescents, but both the functionality and wearability of the monitor should be considered.
Background
Although mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior.
Objective
To establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages.
Methods
Participants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed.
ResultsAnalysis of the 5 behavior adoption stages showed that stage 1 (“unengaged”) was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). “Unengaged” nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already “acting” (stage 4) showed a greater preference for a deliberative decision-making style (F4,1012=21.83, P
Wearable devices introduce many new capabilities to the delivery of healthcare. But wearables also pose grave privacy risks. Furthermore, information overload gets in the way of informed consent by the patient. To better protect American patients in an increasingly digital world, the U.S. Congress passed the Health Insurance Portability and Accountability Act of 1996 (HIPAA). This article examines the adequacy of HIPAA vis-à-vis issues raised by wearable technologies in the Internet of Things environment and identifies policy gaps and factors that drive health data exposure. It presents a 2 × 2 Partnership-Identity Exposure Matrix, illustrates implications in four different contexts, and provides recommendations for improving privacy protection.
A large number of activity-tracking devices have recently dominated the fitness world. These devices typically track different forms of activities and are argued to encourage more active lifestyles. The devices encourage and incentivize change in behavior through mechanisms including personal goals, gratifying representations, and social features. However, both current research and anecdotal evidence about the real impacts of these devices point to mixed outcomes. Many users enjoy positive experiences, while others are reported to have abandoned these devices without generating lasting value for themselves. Through a qualitative study of 29 users of Fitbit activity-tracking devices, we explore how different types of pre-existing motivation shaped people’s perception and adoption of the device. Building from the affordance perspective, our findings suggest that users’ pre-existing motivations, derived from unique life priorities, personal situations, and personalities, may interact with different aspects of the tool, and result in disparate outcomes. Two primary conclusions of this research are (1) the motivational features of activity-tracking devices may only complement already existing motivations of the users but do not create incentive for more physical activities on their own. (2) The value of informational affordances of activity trackers diminishes over time for most users (except the quantified selfers), and without motivational affordances, informational affordances do not sustain long-term use of the device.
Background
Wearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users’ experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use. MethodsA cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests. ResultsParticipants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18–74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5–7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51–81%) more commonly than they had their diet (14–40%) or sleep (11–24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties. Conclusions
Results suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.
Background:
A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time.
Objective:
The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience-related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity.
Methods:
A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique.
Results:
The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience-related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn.
Conclusions:
This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience-related aspects of activity trackers.
Despite numerous health advantages wearable health trackers could offer, tracker users often abandon their devices after a short period of time. One reason for abandonment is users' lack of identification of their trackers as an accurate reflection of who and what they are (i.e., sense of identity). In this study, we examine the role of cosmetic customization (i.e., a modification of a given product's presentation) of a wearable health tracker in increasing one's sense of identity. Furthermore, we explore if one's sense of identity can explain the relationship between cosmetic customization and user engagement (assessed by attitude, exercise intention, and sense of attachment) with a wearable tracker. We conducted a between-subjects online experiment and found that individuals presented with a high level of cosmetic customization features experienced a higher sense of identity with a wearable health tracker, which in turn was associated with more favorable attitude, higher exercise intention, and greater sense of attachment towards the tracker than individuals presented with a low level of cosmetic customization features. Based on the study results, we recommend the designers of wearable health trackers to provide users with salient and recognizable cosmetic customization features so that users can establish a good "identity fit" with their tracker.
Background
As commercially available activity trackers are being utilized in clinical trials, the research community remains uncertain about reliability of the trackers, particularly in studies that involve walking aids and low-intensity activities. While these trackers have been tested for reliability during walking and running activities, there has been limited research on validating them during low-intensity activities and walking with assistive tools.
Objective
The aim of this study was to (1) determine the accuracy of 3 Fitbit devices (ie, Zip, One, and Flex) at different wearing positions (ie, pants pocket, chest, and wrist) during walking at 3 different speeds, 2.5, 5, and 8 km/h, performed by healthy adults on a treadmill; (2) determine the accuracy of the mentioned trackers worn at different sites during activities of daily living; and (3) examine whether intensity of physical activity (PA) impacts the choice of optimal wearing site of the tracker.
Methods
We recruited 15 healthy young adults to perform 6 PAs while wearing 3 Fitbit devices (ie, Zip, One, and Flex) on their chest, pants pocket, and wrist. The activities include walking at 2.5, 5, and 8 km/h, pushing a shopping cart, walking with aid of a walker, and eating while sitting. We compared the number of steps counted by each tracker with gold standard numbers. We performed multiple statistical analyses to compute descriptive statistics (ie, ANOVA test), intraclass correlation coefficient (ICC), mean absolute error rate, and correlation by comparing the tracker-recorded data with that of the gold standard.
ResultsAll the 3 trackers demonstrated good-to-excellent (ICC>0.75) correlation with the gold standard step counts during treadmill experiments. The correlation was poor (ICC
This study identifies and explores evolving concepts of trust and privacy in the context of user-generated health data. We define “user-generated health data” as data captured through devices or software (whether purpose built or commercially available) and used outside of traditional clinical settings for tracking personal health data. The investigators conducted qualitative research through semistructured interviews (n = 32) with researchers, health technology start-up companies, and members of the general public to inquire why and how they interact with and understand the value of user-generated health data. We found significant results concerning new attitudes toward trust, privacy, and sharing of health data outside of clinical settings that conflict with regulations governing health data within clinical settings. Members of the general public expressed little concern about sharing health data with the companies that sold the devices or apps they used, and indicated that they rarely read the “terms and conditions” detailing how their data may be exploited by the company or third-party affiliates before consenting to them. In contrast, interviews with researchers revealed significant resistance among potential research participants to sharing their user-generated health data for purposes of scientific study. The widespread rhetoric of personalization and social sharing in “user-generated culture” appears to facilitate an understanding of user-generated health data that deemphasizes the risk of exploitation in favor of loosely defined benefits to individual and social well-being. We recommend clarification and greater transparency of regulations governing data sharing related to health.
Background
Although many wearable devices for monitoring and tracking physical activity are available to consumers, relatively few research studies have been conducted to determine their efficacy in promoting health.
Methods
In this article, data on the use of consumer wearable devices in promoting healthy behaviors are summarized based upon bibliographic searches in PubMed and Psychology and Behavioral Sciences Collection with relevant search terms through September 2016.
Results
A total of 274 articles were identified in the bibliographic searches. By screening abstracts or full-text articles, six pre/post test trials and seven randomized controlled trials were identified. In initial trials, consumer wearable devices have been shown to increase physical activity and help users lose weight. However, the number of studies completed to date is small and limited by small sample sizes, short study durations, and uncertain generalizability of the findings.
Conclusions
Future studies should utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better establish the efficacy of wearable devices in promoting physical activity. Additional research is needed to determine the feasibility and effectiveness of wearable devices in promoting physical activity and weight loss in community settings including communities affected by health disparities. Studies focusing on children and adolescents are also needed.
Although Personal Informatics stresses the importance of “self”-awareness and “self”-knowledge in collecting personal data, a description of the “self”, to which all these knowledge endeavors are addressed, is missing in the current debate. In this article we first review how the different theoretical assumptions that currently inform the design of Personal Informatics tools lack to convey a convincing image of the self which ought to be quantified by these technologies. We then move on to the outline of a theory of the self that may ground the current discourse in Personal Informatics. Building on this theoretical framework, we propose a set of design guidelines as its implications, which may drive the design of future self-tracking technologies. Finally, we outline a research agenda, organized around such guidelines, in the form of research questions to be addressed in the future.
Abstract: Wearable fitness trackers have gained a new level of popularity due to their ambient data
gathering and analysis. This has signalled a trend toward self-efficacy and increased motivation
among users of these devices. For consumers looking to improve their health, fitness trackers offer a
way to more readily gain motivation via the personal data-based insights the devices offer. However,
the user experience (UX) that accompanies wearables is critical to helping users interpret, understand,
gain motivation and act on their data. Despite this, there is little evidence as to specific aspects of
fitness tracker user engagement and long-term motivation. We report on a 4-week situated diary study
and Healthcare Technology Self-efficacy (HTSE) questionnaire assessment of 34 users of two popular
American fitness trackers: JawBone and FitBit. The study results illustrate design implications and
requirements for fitness trackers and other self-efficacy mobile healthcare applications.
Physical activity is closely linked with health and well-being; however, many Americans do not engage in regular exercise. Older adults and those with low socioeconomic status are especially at risk for poor health, largely due to their sedentary lifestyles. Fitness technology, including trackers and smartphone applications (apps), has become increasingly popular for measuring and encouraging physical activity in recent years. However, many questions remain regarding the effectiveness of this technology for promoting behavior change. Behavior change techniques such as goal setting, feedback, rewards, and social factors are often included in fitness technology. However, it is not clear which components are most effective and which are actually being used by consumers. We discuss additional strategies not typically included in fitness technology devices or apps that are promising for engaging inactive, vulnerable populations. These include action planning, restructuring negative attitudes, enhancing environmental conditions, and identifying other barriers to regular physical activity. We consider which strategies are most conducive to motivating behavior change among sedentary adults. Overall, fitness technology has the potential to significantly impact public health, research, and policies. We suggest ways in which app developers and behavior change experts can collaborate to develop successful apps. Advances are still needed to help inactive individuals determine how, when, where, and with whom they can increase their physical activity.
Personal health-tracking technologies have become a part of mainstream culture. Their growing popularity and widespread adoption present an opportunity for the design of new interventions to improve wellness and health. However, there is an increasing concern that these technologies are failing to inspire long-term adoption. In order to understand why users abandon personal health-tracking technologies, we analyzed advertisements of secondary sales of such technologies on Craigslist. We conducted iterative inductive and deductive analyses of approximately 1600 advertisements of personal health-tracking technologies posted over the course of one month across the US. We identify health motivations and rationales for abandonment and present a set of design implications. We call for improved theories that help translate between existing theories designed to explain psychological effects of health behavior change and the technologies that help people make those changes.
The Internet of Things (IoT) and, particularly, wearable products have changed the focus of the healthcare industry to prevention programmes that enable people to become active and take responsibility for their own health. These benefits will only materialise, however, if users adopt and continue to use these products, as opposed to abandoning them shortly after purchase. Our study investigates how the characteristics of the device, the context and the user can support the adoption and the sustained use of health and fitness wearables. We find that the factors that support the former differ from those that support the latter. For instance, features that signal the device’s ability to collect activity data are essential for adoption, whereas device portability and resilience are key for sustained use.
Background:
Wearable activity trackers have become a viable business opportunity. Nevertheless, research has raised concerns over their potentially detrimental effects on wellbeing. For example, a recent study found that while counting steps with a pedometer increased steps taken throughout the day, at the same time it decreased the enjoyment people derived from walking. This poses a serious threat to the incorporation of healthy routines into everyday life. Most studies aim at proving the effectiveness of activity trackers. In contrast, a wellbeing-oriented perspective calls for a deeper understanding of how trackers create and mediate meaningful experiences in everyday life.
Methods:
We present a study of real life experiences with three wearable activity trackers: Fitbit, Jawbone Up and Nike + Fuelband. Using need fulfillment as a theoretical lens, we study recent, memorable experiences submitted by 133 users of activity trackers.
Results:
We reveal a two-dimensional structure of users' experience driven by the needs of physical thriving or relatedness. Our qualitative findings further show a nuanced picture of the adoption of activity trackers and their impact on wellbeing. For instance, while reflection about own exercising practices lost its relevance over time, users continued to wear the tracker to document and collect their runs. More than just supporting behavioral change, we find trackers to provide multiple psychological benefits. For instance, they enhance feelings of autonomy as people gain more control about their exercising regime. Others experience relatedness, when family members purchase a tracker for relatives and join them in their efforts towards a better, healthier self.
Conclusions:
The study highlights that activity trackers can be more than "tools" to change behavior. Through incorporation in daily life, they offer new social experiences, new ways of boosting our self-esteem and getting closer to our ideal selves.
The spreading of devices and applications allowing people to collect personal information opens new opportunities for Personal Informatics. Although many of these tools are already effectively used by motivated people to gain self-knowledge and produce change in their behaviors, there is a great number of users that are potentially interested in Personal Informatics but do not know of its potentialities and criticalities. In order to investigate how users perceive and use self-tracking tools in everyday life, we conducted a diary study, requiring fourteen participants with no previous experience in Personal Informatics to use a variety of trackers. We discovered that they use and perceive these technologies differently from the ones experienced in self-tracking. Participants considered the act of collecting personal information burdensome, with no beneficial reward. We also uncovered a series of problems that they experienced while tracking, managing, visualizing, and using their data. Among them we found that the lack of suggestions on using data and the excess of abstract visualization in the apps prevented users to gain useful insights. As a result, their interest in self-tracking soon faded, despite their initial curiosity in exploring and “playing” with their data. Starting from the findings of this study, we identified seven design strategies to better Personal Informatics tools, supported by literature and examples that draw from different research fields, from tangible interfaces, to virtual environments and video games. These strategies are primarily addressed to satisfy the inexperienced users’ needs, but their applicability can be reasonably extended to all the individuals curious and interested in Personal Informatics.