fitness app research paper

A Systematic Review of Fitness Apps and Their Potential Clinical and Sports Utility for Objective and Remote Assessment of Cardiorespiratory Fitness

Affiliations.

• 1 GICAFE "Physical Activity and Exercise Sciences Research Group", University of Balearic Islands, Balearic Islands, Spain. [email protected].
• 2 PROFITH "PROmoting FITness and Health through physical activity" Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain. [email protected].
• 3 Chronobiology Research Group, Department of Physiology, Faculty of Biology, University of Murcia, Campus Mare Nostrum, IUIE, IMIB-Arrixaca, Murcia, Spain.
• 4 Ciber Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.
• 5 Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School, The University of Queensland School of Medicine in New Orleans, New Orleans, LA, USA.
• 6 Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
• 7 School of Kinesiology and Health Studies, Queen's University, Kingston, ON, Canada.
• 8 Department of Physical Therapy, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, USA.
• 9 PROFITH "PROmoting FITness and Health through physical activity" Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain.
• 10 Department of Biosciences and Nutrition at NOVUM, Karolinska Institutet, Huddinge, Sweden.
• PMID: 30825094
• PMCID: PMC6422959
• DOI: 10.1007/s40279-019-01084-y

Background: Cardiorespiratory fitness (CRF) assessment provides key information regarding general health status that has high clinical utility. In addition, in the sports setting, CRF testing is needed to establish a baseline level, prescribe an individualized training program and monitor improvement in athletic performance. As such, the assessment of CRF has both clinical and sports utility. Technological advancements have led to increased digitization within healthcare and athletics. Nevertheless, further investigation is needed to enhance the validity and reliability of existing fitness apps for CRF assessment in both contexts.

Objectives: The present review aimed to (1) systematically review the scientific literature, examining the validity and reliability of apps designed for CRF assessment; and (2) systematically review and qualitatively score available fitness apps in the two main app markets. Lastly, this systematic review outlines evidence-based practical recommendations for developing future apps that measure CRF.

Data sources: The following sources were searched for relevant studies: PubMed, Web of Science ® , ScopusTM, and SPORTDiscus, and data was also found within app markets (Google Play and the App Store).

Study eligibility criteria: Eligible scientific studies examined the validity and/or reliability of apps for assessing CRF through a field-based fitness test. Criteria for the app markets involved apps that estimated CRF.

Study appraisal and synthesis methods: The scientific literature search included four major electronic databases and the timeframe was set between 01 January 2000 and 31 October 2018. A total of 2796 articles were identified using a set of fitness-related terms, of which five articles were finally selected and included in this review. The app market search was undertaken by introducing keywords into the search engine of each app market without specified search categories. A total of 691 apps were identified using a set of fitness-related terms, of which 88 apps were finally included in the quantitative and qualitative synthesis.

Results: Five studies focused on the scientific validity of fitness tests with apps, while only two of these focused on reliability. Four studies used a sub-maximal fitness test via apps. Out of the scientific apps reviewed, the SA-6MWTapp showed the best validity against a criterion measure (r = 0.88), whilst the InterWalk app showed the highest test-retest reliability (ICC range 0.85-0.86).

Limitations: Levels of evidence based on scientific validity/reliability of apps and on commercial apps could not be robustly determined due to the limited number of studies identified in the literature and the low-to-moderate quality of commercial apps.

Conclusions: The results from this scientific review showed that few apps have been empirically tested, and among those that have, not all were valid or reliable. In addition, commercial apps were of low-to-moderate quality, suggesting that their potential for assessing CRF has yet to be realized. Lastly, this manuscript has identified evidence-based practical recommendations that apps might potentially offer to objectively and remotely assess CRF as a complementary tool to traditional methods in the clinical and sports settings.

Publication types

• Systematic Review
• Cardiorespiratory Fitness*
• Cardiovascular Diseases / diagnosis
• Exercise Test
• Mobile Applications / standards*
• Monitoring, Physiologic / instrumentation
• Reproducibility of Results
• Risk Factors

Grants and funding

• MINECO/FEDER DEP2016-79512-R/Spanish Ministry of Economy and Competitiveness
• 667302/European Union?s Horizon 2020 research and innovation programme
• DEP2005-00046/ACTI/EXERNET Research Network on Exercise and Health in Special Populations
• PN I+D+I 2017-2021/SAMID III network, RETICS,
• RD16/002/ISCIII- Sub-Directorate General for Research Assessment and Promotion, the European Regional Development Fund
• CB16/10/00239/Ministry of Economy and Competitiveness and the Instituto de Salud Carlos III
• 19899/GERM/15/Seneca Foundation

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• v.1(8); 2022 Aug

The use of mobile apps and fitness trackers to promote healthy behaviors during COVID-19: A cross-sectional survey

Huong Ly Tong

1 Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia

Carol Maher

2 Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, Adelaide, Australia

Kate Parker

3 Deakin University, Geelong, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences

Tien Dung Pham

4 Royal Melbourne Hospital, School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

Ana Luisa Neves

5 NIHR Imperial Patient Safety Translational Research Centre, Imperial College of London, London, United Kingdom

6 Centre for Health Technology and Services Research, Department of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, Porto, Portugal

Benjamin Riordan

7 Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia

Clara K. Chow

8 Department of Cardiology, Westmead Hospital, Sydney, Australia

Liliana Laranjo

9 Western Sydney Primary Health Network, Sydney, Australia

Juan C. Quiroz

10 Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia

11 Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia

Associated Data

The data that support the findings of this study are openly available at https://osf.io/wa5p8/?view_only=06a70c1321114dfc8f45bd4e1affca4b .

To examine i) the use of mobile apps and fitness trackers in adults during the COVID-19 pandemic to support health behaviors; ii) the use of COVID-19 apps; iii) associations between using mobile apps and fitness trackers, and health behaviors; iv) differences in usage amongst population subgroups.

An online cross-sectional survey was conducted during June–September 2020. The survey was developed and reviewed independently by co-authors to establish face validity. Associations between using mobile apps and fitness trackers and health behaviors were examined using multivariate logistic regression models. Subgroup analyses were conducted using Chi-square and Fisher’s exact tests. Three open-ended questions were included to elicit participants’ views; thematic analysis was conducted.

Participants included 552 adults (76.7% women; mean age: 38±13.6 years); 59.9% used mobile apps for health, 38.2% used fitness trackers, and 46.3% used COVID-19 apps. Users of mobile apps or fitness trackers had almost two times the odds of meeting aerobic physical activity guidelines compared to non-users (odds ratio = 1.91, 95% confidence interval 1.07 to 3.46, P = .03). More women used health apps than men (64.0% vs 46.8%, P = .004). Compared to people aged 18–44 (46.1%), more people aged 60+ (74.5%) and more people aged 45–60 (57.6%) used a COVID-19 related app ( P < .001). Qualitative data suggest people viewed technologies (especially social media) as a ‘double-edged sword’: helping with maintaining a sense of normalcy and staying active and socially connected, but also having a negative emotional effect stemming from seeing COVID-related news. People also found that mobile apps did not adapt quickly enough to the circumstances caused by COVID-19.

Conclusions

Use of mobile apps and fitness trackers during the pandemic was associated with higher levels of physical activity, in a sample of educated and likely health-conscious individuals. Future research is needed to understand whether the association between using mobile devices and physical activity is maintained in the long-term.

Author summary

Technologies such as mobile apps or fitness trackers may play a key role in supporting healthy behaviors and deliver public health interventions during the COVID-19 pandemic. We conducted an international survey that asked people about their health behaviors, and their use of technologies before and during the pandemic. Sixty percent reported using a mobile app for health purposes; 38% used a fitness tracker. People who used mobile apps and fitness trackers during the pandemic were more active than people who did not. Women were more likely to use health apps than men, and people aged 45+ were more likely to use COVID-19 apps than people under 45. Differences in app usage based on sex and age indicate that tailored technologies are needed to support different groups. Participants revealed that they had to adapt their use of mobile apps to fit their needs during the highly restricted circumstances caused by COVID-19. Altogether, our findings provide new insights into how mobile apps and devices can deliver health support remotely during a pandemic, and highlight the need for these technologies to adapt to support people’s changing needs.

Introduction

Coronavirus disease 2019 (COVID-19) and subsequent public health measures have drastically impacted lifestyles worldwide and have had adverse effects on health behaviors [ 1 – 6 ]. Several cross-sectional surveys of adults in Australia, the US and UK have reported negative changes in health behaviors and mental health during the pandemic, including reduced physical activity [ 3 , 4 ], unhealthy eating habits and lower diet quality [ 3 , 4 ], increased alcohol consumption [ 1 ], and higher prevalence of anxiety and depression symptoms [ 1 , 2 , 6 ]. In addition to self-reported changes, studies using objective smartphone-based data also showed a decline in daily step count worldwide [ 5 , 7 ]. During the pandemic, the World Health Organization highlighted the importance of maintaining healthy behaviors in the fight against COVID-19 [ 8 ]. With restrictions on face-to-face clinical consultations and the strain on health care systems in delivering patient care, mobile devices were increasingly harnessed to remotely deliver health care support [ 9 , 10 ].

Mobile devices such as mobile apps and fitness trackers [ 11 ] can be leveraged to deliver behavior change interventions and might play a role in supporting healthy behaviors during the pandemic. Specifically, mobile apps and fitness trackers can incorporate behavior change techniques (i.e., the active component of an intervention designed to regulate behavior change [ 12 ]) that are known to be effective in changing behaviors. Systematic reviews have found that behavior change techniques such as goal setting and self-monitoring of behavior are effective at improving physical activity and diet outcomes [ 13 , 14 ]. Mobile apps or fitness trackers can deliver these behavior change techniques, such as by enabling users to set their own goals, or to self-monitor some behaviors, as demonstrated in prior reviews [ 15 , 16 ]. During the pandemic, mobile apps and fitness trackers can offer unique benefits, by allowing people to access health support remotely and engage in virtual activities (e.g., livestreamed exercise class), in replacement of disrupted in-person activities. Evidence from systematic reviews suggests that under pre-pandemic or ‘normal’ conditions, mobile apps and fitness trackers can improve physical activity [ 17 – 21 ], diet [ 17 , 22 ], sleep [ 23 ], reduce smoking and alcohol intake [ 22 , 24 , 25 ], and help manage mental health [ 17 , 26 ]. However, little is known about the use of these technologies for health behaviors during the COVID-19 pandemic, and the association between using mobile apps and fitness trackers, and healthy behaviors.

A few studies have examined the use of digital technologies for physical activity and mental health during the pandemic. Specifically, a study of Google Trends showed an increase in searches for physical activity and exercise in Australia, the US and the UK [ 27 ]. An analysis of App store data in the US showed an increase in downloads of mental health apps [ 28 ]. Cross-sectional surveys found that the use of digital platforms (e.g., streaming services, mobile apps) was associated with higher physical activity levels [ 29 – 31 ]. While this evidence is promising, the scope was limited to physical activity and mental health and did not explore other behaviors (e.g., diet, smoking, alcohol intake) that are important to maintain good health during the pandemic. Moreover, existing research has not examined the use of fitness trackers, which have been known to have a positive impact on health behaviors [ 18 , 20 , 21 ]. Thus, there remain gaps in understanding how a range of mobile devices were being used for physical and mental wellbeing during the pandemic, and the association between usage and health behaviors.

In addition to supporting healthy behaviors, mobile devices have also been leveraged to deliver public health interventions during the pandemic. Specifically, mobile apps have been developed for COVID-19 purposes, such as to support contact tracing [ 9 ], self-management of symptoms, or home monitoring [ 32 – 34 ]. Despite rapid growth in the number of COVID-19 mobile apps, little is known about their adoption, with preliminary evidence suggesting that specific subgroups (e.g., older people) are more likely to adopt such apps [ 35 ]. It is important to better understand how different subgroups might adopt COVID-19 apps, to inform public health strategies and policy makers in their response to the pandemic.

To address these gaps, we conducted a cross-sectional survey to examine use of mobile apps and fitness trackers to support health behaviors (i.e., self-reported physical activity, diet, sleep, smoking, alcohol consumption), mental wellbeing, and public health interventions (e.g., COVID-19 apps) during the pandemic.

The secondary aims of the study were to examine:

• Whether using mobile apps and/or fitness trackers was associated with healthy behaviors,
• What was the adoption of COVID-19 related apps (i.e., mobile apps designed specifically for COVID-19), and
• Whether specific subgroups showed a higher use of COVID-19 related apps and mobile apps and fitness trackers for health-related purposes.

Study design

This study is a cross-sectional survey that examined the use of mobile apps and fitness trackers for health behaviors and public health interventions during the COVID-19 pandemic. The reporting adheres to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guideline for cross-sectional studies [ 36 ] ( S1 Appendix ). Ethical approval was granted by Macquarie University’s Human Research Ethics Committee (Approval number: 52020674017063). All participants provided electronic written consent prior to participation ( S2 Appendix ).

Settings and participants

An anonymous online survey was hosted on the Qualtrics platform [ 37 ]. The study was advertised via various channels, including social media (Facebook, Twitter, LinkedIn, Instagram, Reddit), public posters (e.g., at parks, libraries, university campus), and research institute networks (e.g., email lists, university website). In our social media advertisements, we also asked people to share the study with their networks (e.g., re-tweet on Twitter), in order to expand the geographical scope of the study. Study recruitment was self-selected, i.e., interested individuals could click on the survey link, upon which they were provided with the study information and provided an electronic written consent prior to participation. Eligible study participants were adults aged over 18 years who were proficient in English. We followed published heuristics for sampling for behavioral research and aimed to recruit at least 500 participants into the study [ 38 ]. The survey was open from start of June to end of September 2020 to achieve the targeted sample size.

During the data collection period (June–September 2020), the World Health Organization assessed the global risk of COVID-19 to be very high [ 39 ]. The number of infected cases globally increased from over 10 million [ 40 ] to 32.7 million [ 41 ] during this period, with vastly different infection rates amongst countries. Public health policies across countries varied considerably with respect to lifestyle restrictions such as lockdown measures, travel restrictions, and mask mandates [ 42 , 43 ]. It is worth noting that during June–September 2020, a few countries had started to ease lifestyle restrictions (e.g., Australia, UK, Canada) [ 43 ].

Survey development and measures

Existing COVID-19 surveys [ 44 – 46 ] were reviewed to inform the wording and structure of the present survey. Subsequently, a draft survey was prepared and reviewed independently in three rounds to establish face validity. Specifically, in round one, a draft survey was prepared by the first author and reviewed by a clinician and a computer science expert, with revisions made accordingly. In round two, the survey was sent out to three experts in digital health and behavioral research for feedback, and revised accordingly. Finally, the revision made in round two was reviewed again by a clinician prior to being finalized. A copy of the Qualtrics survey can be found in S2 Appendix .

Demographic characteristics

Participants reported their age (years), gender (female, male, other, prefer not to say), highest level of education completed (primary school, high school, vocational training, bachelor’s degree, postgraduate degree), country of residence, and whether they had medical conditions that required regular medical care or medication (yes, no).

Health behaviors

Health behaviors including physical activity, diet, smoking and alcohol consumption during the pandemic were self-reported. Participants were asked how many minutes of moderate-to-vigorous physical activity they completed each week. Participants were considered to have adhered to the recommended levels of aerobic physical activity if they self-reported at least 150 minutes of moderate-to-vigorous physical activity in a week, based on the World Health Organization’s guidelines [ 47 ].

Participants self-reported daily servings of vegetables and fruits. Participants were considered to have adhered the recommended intake of vegetables and fruits if they self-reported consuming at least five servings of vegetables and fruits in a day, based on the World Health Organization’s recommendation [ 48 ]. Participants also reported the number of standard drinks they typically have in a week, their smoking status (yes, no) and number of cigarettes smoked in a day. Examples of moderate-to-vigorous physical activity, fruit and vegetable servings, and standard alcoholic drink servings were provided.

The use of mobile apps and fitness trackers for health behaviors

The survey contained 20 questions about participants’ usage of mobile apps (including health apps, general apps, and social media apps) and fitness trackers to support health-related purposes before and during the COVID-19 pandemic. In the survey, health-related purposes were defined as staying active, eating healthily, sleeping better, reducing/stopping smoking and alcohol drinking, and managing mental wellbeing, and it was specified that the focus was not on chronic disease management (e.g., monitor blood glucose, medication reminders). Usage status during the pandemic was classified into three groups: current users, past users and never-users, based on existing literature [ 30 , 31 , 49 ]. The definition of usage status is provided in Box 1 . Additionally, participants were asked to indicate the extent to which they agreed with the usefulness of technologies in supporting different health behaviors. These items were measured using a five-point Likert scale, ranging from strongly disagree to strongly agree. The survey also contained three optional, open-ended questions to collect qualitative data on how participants used mobile apps, fitness trackers, and other technologies to support health behaviors and mental wellbeing during the COVID-19 pandemic.

Box 1: Classification based on technology usage during the pandemic*

Note: Classification based on [ 30 , 31 , 49 ]. [ 30 , 31 ] classified participants into users and non-users. We modified this classification to include current users, and broke non-users into past and never-users based on [ 49 ] to provide more granularity in usage patterns.

COVID-19 related apps

The survey included two questions about whether people used COVID-19 related apps (i.e., mobile apps created specifically for use during the COVID-19 pandemic), and for what purposes (e.g., for contact tracing, symptom checking).

Data analysis

Quantitative data were analyzed using R version 4.0.4 [ 50 – 52 ]. Descriptive statistics, including frequencies and percentages, were generated for categorical variables; means and standard deviations (SD) were generated for continuous variables. Two logistic regression models were used to examine the association between 1) the use of mobile apps and fitness trackers and adherence to aerobic physical activity guidelines, and 2) the use of mobile apps and adherence to fruit and vegetable consumption guidelines. Specifically, one logistic regression model included adherence to aerobic physical activity guidelines as the outcome variable, and the independent variables were current use of mobile apps or fitness trackers, whether participants used an app or tracker before COVID-19 (as a proxy for interest in technology before COVID-19), and whether participants started using a new app or tracker since COVID-19. Another model included adherence to fruit and vegetable consumption guidelines as the outcome variable, and the independent variables were current use of mobile apps, whether participants used a mobile app before COVID-19, and whether participants started using a new app since COVID-19. Both models were adjusted for factors selected a priori, including age, gender, education, and the existence of current medical conditions. Odds ratios (OR) and 95% confidence intervals (CI) were reported. Post-hoc sensitivity analyses were conducted to include only Australia-based participants, given the large proportion of this group in the sample.

Subgroup analyses were conducted to explore to explore whether age and gender subgroups were more likely to use mobile apps for health-related purposes or COVID-19 related apps. These subgroups were chosen based on the literature, as previous cross-sectional surveys have found that app usage might differ by age and gender [ 30 , 35 ]. Specifically, Thomas et al found that COVID-19 app downloads appeared to increase with age, with the 65+ age group having the highest proportion of downloads [ 35 ]. Additionally, Parker et al also found that more women than men used digital platforms for their physical activity during the pandemic [ 30 ]. Chi-square tests were used for categorical data. When the assumption of chi-square test was violated, Fisher’s exact test was used instead. The significance level for all statistical tests was set at P < .05, two-tailed.

Qualitative data (from free-text responses) were analyzed using thematic analysis [ 53 ] in NVivo 12 [ 54 ] to explore the different ways people used technologies to maintain health and wellbeing during the pandemic. Integration of results was conducted after quantitative and qualitative analyses were completed, through embedding of the data. Integration is presented throughout the Discussion section.

Sample description

While 554 people consented to participation, two were under 18, and thus, were not eligible. In total, 552 participants (mean age 38±13.6 years, 76.6% women) were included in data analysis. Responses were recorded from 32 countries, with most participants (382/549, 69.6%) living in Australia. The majority (359/552, 65%) had completed a postgraduate degree, and 71.1% (385/541) reported having no current medical condition requiring regular care or medication. The self-reported average weekly time spent in moderate-to-vigorous physical activity was 164 (SD 152) minutes. The average vegetable and fruit consumption reported by participants were 2.7 and 1.7 daily servings, respectively. Most of the sample (525/541, 97%) were non-smokers. The average alcohol consumption was reported as 3 drinks per week. The sociodemographic and health characteristics of the study sample are presented in Table 1 .

a Total number in each row might not add up to 554 due to missing responses

b Sums may not equate to 100% due to rounding

c S3 Appendix includes a detailed breakdown of country of residence

d Self-reported data

e One extreme value 6450 was excluded.

Technology use for health behaviors and mental wellbeing during COVID-19

Mobile apps.

Regarding participants’ app usage habits, 59.9% (302/504) were currently using apps for health purposes during the pandemic (i.e., current users) ( Table 2 ). Amongst the current app users, 77.8% (235/302) consistently used mobile apps for their health before COVID-19. A greater proportion of women were current app users than men (64.0% vs 46.8%, P = .004, S4 Appendix provides more details on subgroup analyses). The most popular apps used for health purposes during the pandemic were general and social media apps (e.g., Zoom, Facebook, Youtube), which were not purposedly built to promote health behavior change ( Table 2 ).

a People who used apps consistently (e.g., use an app more than 5 times) for health purposes in the past, but were not currently using them during the pandemic

b People who never used app for health purposes

c New apps adopted for health purposes during COVID-19

Compared to pre-pandemic times, nearly half (192/401, 47.8%) used mobile apps more frequently for health purposes during the COVID-19 pandemic ( Table 2 ). Forty percent (164/401, 40.9%) started using a new mobile app for health-related purposes since the outbreak of COVID-19.

During the COVID-19 pandemic, the most reported health purpose of app usage was to stay active (248/298, 83%) ( Table 2 ). Amongst those who used apps for physical activity, the majority used them to track activity levels (196/246, 79.7%), or to follow an exercise video (148/246, 60.1%) ( Table 2 ). Over two-third of participants (203/298, 68.1%) used mobile apps for more than one health purpose during the COVID-19 pandemic. Compared to men, a greater proportion of women used mobile apps to stay active (48% vs 36.7%, P = .02) and to connect with other people (22.7% vs 9.2%, P = .004, S4 Appendix ).

Regarding the perceived usefulness of mobile apps for health, 59.4% (232/390) of participants agreed that mobile apps helped them incorporate more activity in their days; 43.5% (167/384) agreed that mobile apps helped them manage their mental wellbeing. Compared to men, a greater proportion of women found mobile apps helpful for managing their mental wellbeing (80.6% vs 63.2%, P = .04, S4 Appendix ).

Fitness trackers

Over a third of participants (188/492, 38.2%) were current users of fitness trackers, 19.3% (95/492) were past users, and 42.7% (210/492) had never used fitness trackers for their health. The median length of usage for current and past users was 2 years (range 1 month—10 years). Forty-eight percent of responders (237/492, 48.1%) mentioned that they had used fitness trackers before the pandemic. Amongst those who used trackers before the pandemic, the most popular trackers used pre-COVID were Fitbit, and Apple Watch. Since the COVID-19 outbreak, 5.1% of respondents (25/492) started using a new fitness tracker.

During the pandemic, the most common reasons for using fitness trackers were to track different measurements (e.g., distance run or walked, heart rate), and to receive reminders to move. Over half (147/274, 53.6%) agreed that fitness trackers helped them incorporate more activity in their daily lives.

The association between technology usage and healthy behaviors

People who currently used a mobile app or fitness tracker during the pandemic had almost two times the odds of meeting aerobic physical activity guidelines (OR = 1.91, 95% CI 1.07 to 3.46) compared to non-users ( Table 3 ). Whether participants used mobile apps or fitness trackers before COVID-19, and whether participants started using a new app or tracker since COVID-19 were also statistically associated with meeting aerobic physical activity guidelines. Specifically, people who started using a new app or tracker since COVID-19 had 1.7 times the odds of meeting aerobic physical activity guidelines than people who did not (OR = 1.66, 95% CI 1.06 to 2.61) ( Table 3 ). People who had used mobile apps or trackers before COVID-19 had more than 2 times the odds of meeting aerobic physical activity guidelines than non-users (OR = 2.32, 95% CI 1.36 to 4.02). Mobile app usage was not associated with meeting fruit and vegetables consumption guidelines (OR = 0.97, 95% CI 0.53 to 1.76) ( Table 3 ).

a Participants were considered to have adhered to aerobic physical activity guideline if they self-reported doing at least 150 minutes of moderate to vigorous physical activity in a week

b Participants were considered to have adhered to fruit and vegetable consumption guideline if they self-reported having at least 5 servings of fruits and vegetables in a day

c The model exploring the link between technologies and fruit and vegetable consumption only considered app usage, not fitness trackers.

Given the large proportion of Australia-based participants in our sample, we conducted a sensitivity analysis with this subgroup ( S5 Appendix ). The sensitivity analysis showed that current app or tracker usage was no longer statistically associated with meeting aerobic physical activity guidelines (OR = 1.63, 95% CI 0.79 to 3.43). Age, whether participants used an app or tracker before COVID-19, and whether participants started using a new app or tracker since COVID-19 were statistically associated with meeting aerobic physical activity guidelines. Mobile app usage was also not associated with meeting fruit and vegetable consumption guidelines in this subgroup (OR = 1.08, 95% CI 0.52 to 2.27).

Less than half of the participants (235/508, 46.3%) used a COVID-19 related app. Of those that used COVID-19 related apps, most used country-specific apps (e.g., COVIDSafe in Australia). The main purpose of using COVID-19 related apps was to support contact tracing. Twelve percent (59/508, 11.6%) used COVID-19 related apps for more than one purpose, most often to support contact tracing and get COVID-19 information.

Use of COVID-19 related apps differed by age and whether they were currently using mobile apps for their health. Compared to people aged 18–44, a larger proportion of people aged 60+ (74.5% versus 46.1%) and a larger proportion of people aged 45–60 (57.6% versus 46.1%) used a COVID-19 related app ( P < .001, S4 Appendix ). Compared to never-users, a greater proportion of current users (50.3% vs 35.3%) and past users (47.6% vs 35.3%) of mobile apps for health used COVID-19 related apps ( P = .034, S4 Appendix ).

Qualitative results

The most common and central themes from the responses to open-ended questions are described below and comprised: maintaining a sense of normalcy and social connections; technologies as a double-edged sword; desired features of technology. S6 Appendix includes demographic details of the subset of participants who answered each of the open-ended questions.

Maintaining a sense of normalcy and social connections

Participants mentioned that during the pandemic, mobile devices has allowed them to maintain a routine despite the disruption caused by COVID-19, and maintain a sense of normalcy, which in turn gave them motivation to exercise ( Table 4 , quotes 1–2). Additionally, most participants mentioned that technologies helped them stay socially connected with their family and friends, which alleviated some emotional stress and allowed them to share their fitness progress ( Table 4 , quote 3–4).

Notes: The bracket provides gender, age, and country of residence. F: female, M: male.

Technologies as a double-edged sword

Participants cited both positive and negative effects from the use of technologies, especially social media, during the COVID-19 pandemic. On one hand, social media allowed people to stay updated with COVID-19 news ( Table 4 , quote 5). On the other hand, participants also mentioned that the high volume of COVID-19 news could cause information overload and emotional stress ( Table 4 , quote 6). Similarly, when talking about fitness trackers, some participants indicated negative emotions associated with self-monitoring, as their physical activity had declined due to COVID-19 circumstances ( Table 4 , quote 7).

Desired features of technology

There were two subthemes within the area of desired features of technology: adaptability and gamification. Participants mentioned that while technologies had been helpful, one key thing missing was the adaptability of technologies to the unprecedented circumstances caused by COVID-19 ( Table 4 , quote 8). Consequently, several mentioned that they took the initiative to repurpose existing health apps to serve their needs during COVID-19 pandemic ( Table 4 , quotes 9–10). Many participants across different ages also valued gamification features of technologies (e.g., competition, exercise challenges, exercise role-playing games), which helped them to incorporate fitness into their life with an element of fun and enjoyment ( Table 4 , quotes 11–12).

Principal results

Our study found that 60% of participants used mobile apps and 38% used fitness trackers for health behaviors during June–September 2020. People who used mobile apps or fitness trackers during the pandemic were more likely to self-report meeting recommended levels of aerobic physical activity than non-users. A greater proportion of women used apps for their health during the pandemic than men. Additionally, 46% of respondents self-reported using COVID-19 apps. Specific subgroups such as people aged 45+ and current or past users of mobile apps for health purposes were more likely to use COVID-19 related apps. We note that these subgroup analyses based on age and gender are exploratory in nature and should be confirmed in future research. The generalizability of our quantitative findings is limited, given our sample of highly educated individuals who might have been more health-conscious, and had better access and more inclined to use technologies. Qualitative findings complemented quantitative findings by showing while mobile devices helped maintain a sense of normalcy, there were potential negative effects of using technologies (e.g., stress and information overload from seeing COVID-19 information on social media, guilt when seeing low activity levels), which might have impacted users’ motivation and continued use of mobile devices. Our participants highlighted the need for technologies to adapt to changing circumstances.

Impact of mobile devices on health behaviors

Our results are consistent with existing literature showing that users of mobile apps and other digital technologies seem to be more active than non-users during the pandemic [ 29 – 31 , 55 ]. Uniquely, by adjusting our model to variables related to ‘previous use of mobile devices before COVID’ and ‘adoption of new apps or trackers during the outbreak’, we found these were associated with adherence to physical activity guidelines. It is possible that the physical activity benefits observed in our study are influenced by an overrepresentation in our sample of health-conscious and tech-adopting people. Future research is needed to understand how mobile devices can extend its reach and benefit other groups beyond the typical highly motivated and ‘worried-well’ adopters [ 56 ]. A sensitivity analysis including only Australia-based participants found that current mobile app or tracker usage was not associated with adherence to physical activity guidelines. It is possible that the smaller sample size made it difficult to detect the difference. Given the inconsistency between the primary and sensitivity analyses, the potential physical activity benefits associated with mobile devices observed in our findings should be interpreted with caution, and future research is needed to ascertain the potential impact of mobile devices on health behaviors.

Our qualitative data highlight the need for mobile apps and fitness trackers to adapt quickly to the changing circumstances of human lives, especially in health crises like COVID-19. Given the disruption to normal routines and closure of exercise and health facilities, people might need additional, or different types of support to maintain healthy behaviors, which is difficult to accommodate by mobile apps and devices based on static algorithms. With recent development in artificial intelligence and machine learning, mobile apps and devices can collect information about its users (including users’ behaviors, context or preferences) to continuously adapt their content, timing and delivery, and personalize their support to suit the person’s needs [ 57 , 58 ].

Differences in app usage between genders

Findings suggested that a greater proportion of women used mobile apps during the pandemic than men. Specifically, women were more likely to use apps to support physical activity and to connect with others, and more likely to report apps as useful for mental health. It is worth noting that this gender difference is based on a subgroup analysis and is exploratory in nature. However, we also note that our finding is in line with previous research reporting higher use of digital platforms for physical activity amongst women [ 30 ]. There are several possible explanations for this observed gender difference. Research has shown that during the pandemic, women reported increased overeating [ 4 ] and less physical activity than men [ 59 ], and heightened stress from taking on more caring or home-schooling responsibilities [ 1 , 59 – 62 ]. Thus, women might have needed additional support and turned to mobile devices to support their wellbeing. Another possible explanation is linked to the type of health activities that can be accommodated in health apps. Research has suggested that women were more likely to engage in directed activities (e.g., exercise classes [ 63 , 64 ]), which could be delivered online more easily, compared to competitive sports usually done by men [ 63 ]. Future research is needed to explore how the adoption of mobile devices might differ by gender and how to design health interventions to reduce the existing gender differences in adoption.

Adoption and usage of COVID-19 related apps

Only 46.3% of our participants used a COVID-19 related app. Previous research has reported uptake ranging from 20% [ 65 , 66 ] to 40% [ 35 , 67 ] amongst European countries and Australia. Given that the most common purpose is contact tracing, this low uptake is concerning as digital tracing apps rely on a high adoption rate to work effectively [ 9 ]. Research has suggested that the reasons for low uptake are mainly privacy and functionality concerns (e.g., battery drain, apps not working as intended) [ 35 ]. This indicates the need to improve the functionality of digital tracing apps, as well as public health communication regarding the privacy protections of tracking technologies [ 68 ]. Our study found a greater proportion of people aged 60+, and people aged 45–60 used COVID-19 related apps compared to those less than 45 years. This is in line with previous research which suggests that the higher uptake in older adults might be related to concerns about their vulnerability to COVID-19 [ 35 ]. This trend highlights the need for public health communication to also target younger populations to ensure a high adoption rate in this subgroup. It is worth noting that since 2021, some countries (e.g., Australia) have made ‘signing-into’ venues mandatory, usually through a ‘check-in’ function in government apps to support contact tracing. Thus, since the completion of this study, it is likely that the use of these government apps for COVID-19 purposes have increased. Furthermore, given the exploratory nature of this subgroup analysis, future research is needed to confirm potential age differences in COVID-19 app uptake.

Strengths and limitations

A strength of our study is the mixed-methods design, including qualitative, open-ended questions, which allowed us to acquire a deeper exploration of users’ perspectives. However, the results must be interpreted considering some limitations. While face validity was established through multiple co-authors independently reviewing the survey draft, the survey questions were not formally assessed for criterion or content validity, and the survey was not pilot tested. Health behaviors were assessed through self-report. We assessed the impact of technologies on only aerobic physical activity and the intake of fruits and vegetables. To enable a more comprehensive analysis on the link between technologies and physical activity and diet, future research should collect data on other types of activity (e.g., muscle strengthening exercises) and food groups (e.g., salt or sugar intake). We were not able to examine the link between technologies usage and alcohol intake and smoking because only a small percentage of our sample used technologies for these purposes. While our sampling was worldwide, the majority of participants resided in Australia. As a large proportion of participants were women, and had high level of education, this might bias our findings and affect the generalizability to other population groups. Previous surveys have reported a similarly high participation rate from women and people with higher education levels [ 1 , 3 , 4 , 30 ]. The survey was conducted online and proficiency in English was required, which might have precluded participation from non-English speaking individuals and those lacking access to the Internet. Finally, our findings are also impacted by common limitations of survey research—self-reported answers and self-selection sampling method. This might have led to sampling bias, social desirability bias, or recall bias, which affect the generalizability of the findings and the reliability of the responses.

Implications

Mobile apps and fitness trackers seem promising in promoting physical activity during the COVID-19 outbreak. Potential improvements on these technologies from users’ perspectives should focus on personalization and adaptability, such as allowing for higher customization of content delivered and a better ability to support people’s changing needs. This is in line with previous research which suggests that personalization can increase user engagement with mobile devices [ 69 ]. By leveraging recent advances in big data and artificial intelligence [ 58 ], mobile devices may be able to provide more in-time, personalized support to users. Future research is needed to investigate whether the engagement with health apps and devices is sustained post-COVID, and robust clinical trials are needed to ascertain their objective benefits for preventative health, including physical activity and other health behaviors.

Our findings may be influenced by the large proportion of highly educated individuals who might be more health-conscious and have access to technologies more easily than other population groups. Previous research has described this phenomenon as the “digital divide” [ 70 , 71 ], which can widen existing social inequalities. The benefits of mobile apps and devices would be limited if they can only reach high socioeconomic status groups. Thus, efforts must be made to bridge this gap in technology adoption, such as through increasing access, promoting collaborative and inclusive design, and improving digital literacy [ 70 , 71 ].

Our study found a positive impact of mobile apps and fitness trackers on physical activity during the pandemic, in a sample of likely health-conscious and technology-inclined individuals. Qualitative data revealed the lack of flexibility of mobile apps and devices and highlighted the need for these technologies to adapt quickly to changes in life circumstances. Future research should assess the use of mobile apps and fitness trackers post-COVID, and whether these technologies provide objective benefits to health behaviors.

Supporting information

S1 appendix, s2 appendix, s3 appendix, s4 appendix, s5 appendix, s6 appendix, funding statement.

HLT was supported by the International Macquarie University Research Excellence Scholarship (iMQRES) (Macquarie University funded Scholarship – No. 2018148) and the Australian Government Research Training Program Scholarship. CM is supported by a Medical Research Future Fund Investigator Grant (APP1193862). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability

• PLOS Digit Health. 2022 Aug; 1(8): e0000087.

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PDIG-D-21-00140

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

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Reviewer #1: This is an interesting research.

I have highlighted a few comments to improve the manuscript.

1. Was the survey items/questions validated?

2. Line 146: What is the rationale for the study duration?

3. Why was snowball sampling explicitly used?

4. Line 153: specify the period (date) rather than "during this time."

5. Line 189: 5-point Likert scale?

6. Line 249: What is the frequency of Mobile App usage (e.g., once a week, daily, monthly)?

7. Suggest putting survey items/questions in a table for easy understanding.

8. Define the current, past, and never users categories (include references). Some studies use light or heavy users.

9. Did you identify the gamification features that users were interested in?

10. Line 362-363: Suggest to detail the negative effects.

11. Important to highlight the negative and positive effects on user motivation and adherence?

12. Can gamification positively affect the adoption and post-adoption of the COVID-19 apps?

13. Interested in knowing if these apps were theory-based and their relevance to the present of future study.

14. The results can be expanded to compare with similar studies. An interesting study to consider is:

User Engagement and Abandonment of mHealth: A Cross-Sectional Survey (2022). In Healthcare (Vol. 10, No. 2, p. 221). MDPI.

Reviewer #2: - The self-selection bias in this sample is so significant that I have to question the added value for research. But this is not limited to sociodemographic patterns. How valid are statements about subgroups of different usage behavior in a sample that seem to be strongly overrepresented by participants with higher health and fitness orientation?

- Another substantial issue is the inclusion of participants from such diverse national backgrounds. Covid 19 incidences and distancing rules varied massively around the globe within the corresponing survey period. Amongst other reasons, this was obvious, at least because of the seasonal variation in pandemic events in the northern vs. southern hemisphere and completely different policy measures (e.g., USA vs. Australia). Therefore, I would strongly recommend limiting the analyses to the Australian subpopulation.

- Furthermore, I would recommend not to focus the analyses of so-called “subgroups” only on differential frequencies of app usage depending on sociodemographic characteristics. The authors should consider applying methods for exploring subgroups within the sample instead, e.g., cluster analysis or latent class analyses.

- I think using an app tracker before the pandemic is a strongly confounded proxy for interest in technology, as this may also indicate increased health and fitness orientation of the participants in particular. (For example, only 3% reported being smokers , with an average of 0.2 cigarettes a week!).

Reviewer #3: Thank you for this interesting manuscript describing technology usage and healthy behaviors during COVID-19.Please find below my comments:

Major comments:

1) I would like to know if you pilot-tested the survey. If not, could you please describe the methodology that you followed in order to create a validated survey?

2) "Diet was assessed by self-report of daily servings of vegetables and fruits."

Why did you assess only those two food categories? I would appreciate it if you could provide data on the rest of the food groups.

3) In Table 2, how did you define "more or less" in the usage of the app?

4)"Mobile app usage was not associated with meeting fruit 296 and vegetables consumption guidelines (OR = 0.97, 95% CI 0.53 to 1.76) (Table 3)"

Since you are including data from people coming from different countries and those ones have different guidelines, how did you end up with adherence or no to fruit and vegetable guidelines?

5)Could you maybe group the qualitative data? To my opinion, the quotations do not add a lot to the manuscript.

Minor comments:

Please check Table 1 to ensure that all categories reach 100%

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Reviewer #1: Yes: Abdulsalam Salihu Mustafa

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Decision Letter 1

14 Jul 2022

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Dear Ms Tong,

We are pleased to inform you that your manuscript 'The use of mobile apps and fitness trackers to promote healthy behaviors during COVID-19: A cross-sectional survey' has been provisionally accepted for publication in PLOS Digital Health.

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Reviewer #1: All comments have been addressed

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2. Does this manuscript meet PLOS Digital Health’s publication criteria ? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

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Reviewer #2: Yes

3. Has the statistical analysis been performed appropriately and rigorously?

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

5. Is the manuscript presented in an intelligible fashion and written in standard English?

6. Review Comments to the Author

Reviewer #1: I am happy with all the responses from the Authors. The quality of the manuscript has been enhanced.

Reviewer #2: I would like to thank the authors for their efforts related to the revision of the manusciprt and the additional analysis undertaken to address the issues highlighted in my previous review. I have no further comments to add.

7. PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.

Reviewer #1:  Yes:  Abdulsalam Salihu Mustafa

Reviewer #2: No

Interpreting fitness: self-tracking with fitness apps through a postphenomenology lens

• Original Article
• Published: 07 February 2021
• Volume 38 , pages 2255–2266, ( 2023 )

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• Elise Li Zheng 1  

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Fitness apps on mobile devices are gaining popularity, as more people are engaging in self-tracking activities to record their status of fitness and exercise routines. These technologies also evolved from simply recording steps and offering exercise suggestions to an integrated lifestyle guide for physical wellbeing, thus exemplify a new era of "quantified self" in the context of health as individual responsibility. There is a considerable amount of literature in science, technology and society (STS) studies looking at this phenomenon from different perspectives, linking it with the sociology of self-surveillance and neoliberal regimes of health. However, the human-technology interface, through which the micro- (behavioral) and macro- (social) aspects converge, still calls for extensive examination. This paper approaches this topic from the postphenomenological perspective, in combination with empirical studies of design analysis and interviews of fitness apps, to reveal the human-technology link between the design elements and people's perception through the direct experiences and interpretations of technology. It argues that the intentionality of self-tracking fitness app designs mediates the human-technology relations by "guiding" people into a quantified knowledge regime. It shapes the perceptions of fitness and health with representations of meanings about a "good life" of individual success and management. This paper also gives a critique of current individual, performance-oriented fitness app designs and offers the possibility of seeking alternatives through the multistable nature of human-technology relations—how altering interpretation and meaning of the design with a cultural or social context could change the form of technological embodiment.

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Avoid common mistakes on your manuscript.

1 Introduction

The spring of 2020 is certainly not the best time to take exercises—the global pandemic COVID-19 has trapped millions of people across the world at home (especially those told to self-quarantine). Gyms are closed; running or walking outside is not encouraged; there is certainly no team sports due to social distancing; Those who would like to stay active have to turn to in-door alternatives like fitness apps. "Making your home your own gym," claimed a popular Chinese fitness app "Keep" on one of their campaigns during the coronavirus outbreak. Footnote 1 However, for those who desperately want to keep their shape tuned during a difficult time, another well-known slogan from "Keep" is much more needed to progress during isolation when everyone is trapped indoors—"Self-discipline brings freedom." Footnote 2

Fitness apps have gained popularity with widely available mobile personal technology like smartphones and wristbands, years before the COVID-19 outbreak. These "gig-economy" innovations focus on the consumer's market and correspond with self-tracking and self-management trends, promoting extensive engagement through interactive design elements. With these innovations, fitness apps have revealed various intriguing façades of health and fitness in our daily life. For those who want to exercise everywhere and keep track of their fitness status, fitness apps can easily help users be physically active anywhere and everywhere. The apps help manage their daily physical exercise, movement or even dieting regiment, summarizing one's fitness status with quantified data charts (such as the MyFitnessPal in the US, "Keep" in China). Alongside these "at-home," convenient exercise guides and features, there is also a sense of dedication: one should always count on the tracking records of calories and exercising time to keep fit. Besides, fitness apps also gamify fitness exercise, orienting the way of using it into a "fun" setting (e.g., Nintendo "Ring-Fit," released in 2019, which turns exercise into adventure games). They sometimes turn everyday actions like walking into a numerical competition with your friends (e.g. "WeChat Exercises" in China, see Gui et al. 2017 ), adding social network elements into the management of health.

Emerging technologies have changed the way people exercise. But do these new trends change the way people see health and fitness? More importantly, as the trending technologies incorporate new elements of self-exercising and self-management, how do they correspond with the concepts and understandings of personal responsibility and personal health? If so, what is the role of technology in this process of persuading people to do certain things or to subscribe to certain knowledge regimes? What is the technical and social mechanism behind those changes? Most importantly, as more studies start to examine the social implications of various gadgets, how are the social messages embedded in technological designs and delivered through interactions?

In this paper, I will use some concepts from the philosophical perspective of postphenomenology to explain the technologically mediated relationships between fitness app users and health/fitness practice. Based on the empirical case analysis of a Chinese fitness app, I argue that the technological intentionality embedded in the interface design gives users a normalized view of fitness and guides them to perform an extensive engagement with personal data they have generated during exercise. The design elements also help users to create the hermeneutic interpretation of achievement as the core elements of "keeping fit." However, the social and cultural context of fitness allows different users to develop a "multistable" relationship with the app.

2 Monitoring health as a "self-centered" practice

A growing body of literature has paid attention to fitness apps and self-tracking. The studies range from the socio-political analysis that draws upon Foucauldian theories of self-surveillance and governmentality, socio-psychological and behavioral studies that focus on the effectiveness of health promotion, to Science, Technology and Society (STS) studies that focus on human-tech interactions. Sociologists criticize this "quantified self" trend as a neoliberal form of self-governance, which has reduced the social context of health to a bunch of numbers with an increasing focus on individual responsibility and self-surveillance (Ajana 2013 ; Lupton 2012 and 2016 ; Neff and Nafus 2016 ; Ruffino 2018 ). Some of them raise questions about the politics of bodily control in public and private life (Lupton 2016 ) and the value, agency, and expression of identity (Ajana 2018 ). As Foucault (Foucault 1988 and 1990 ) has argued, technology is the manifestation of the materialized, normalized surveillance power, which works through the internalization of certain values and ethics onto the discipline of self. It perpetuates through everyday engagement with technology. In this way, the status of health and fitness, constructed through a series of numbers with tracking data, reflects the way people see themselves: as "objective self-fashioning" (Dumit 2003 ) or "technoscientific identity" (Clarke et al. 2003 ; Rabinow 2010 ; Rowse 2015 ). The digital data circulates as a new form of knowledge and shapes the meaning of a socially accepted "self" (Lupton 2016 )—in this case, a healthy, well-disciplined self.

Looking from the socioeconomic perspective, the prevalence of self-surveillance technology not only puts the responsibility on individuals but also interprets fitness as commodities (Clarke et al. 2003 ; Millington 2016 ; Alam 2016 ). The "datafication of everything" process is based on collecting and valuing personal data, which generates business opportunities (Millington and Millington 2015 ; Millington 2016 ). Thus the automated fitness trend unifies self-identity, commerciality and neoliberal healthism at the same time with problems of data privacy and ownership controversies (Ajana 2017 ).

On the other hand, the micro-perspective of human-technological interactions opens channels of new observations on the behavioral side. The nonhuman elements mediate the dynamic and experience of using technology. Research shows that self-tracking technology can facilitate learning insights about one's body and mind (Choe et al. 2014 ); function as triggers for action (Ajana 2017 ); give a "nudge;" (Lupton 2014 ) or play the role of an authority that shows the persuasive effect (Fogg 2002 ). Users also divert themselves from the projection of technology, finding meanings or engaging in negotiations (Ruckenstein and Schüll 2017 ; Lomborg et al. 2018 ; Didžiokaitė et al. 2018 ).

The nuances in the textual contents and designs of fitness apps call for further investigation—how they are connected with the wider social, cultural and political pictures via an individual's interactions and experiences, where the socially constructed "self" is embodied. This paper aims at explaining the link between personal technology and constructed perception of health at the level of technological interface—What does this process look like? How do people experience, feel and perceive the technological design and subsequently build meanings and understandings of fitness and health in a social context? How can this connection have implications for engagement and design? Most current sociological studies are falling short of revealing the interactive mechanisms where the conversations between people and technology occur. Technologies are treated as something static and "external." As Lupton ( 2019 ) recently calls for a "more-than-human" perspective between technology and users, the interactions need to be examined in a more dynamic and "internal" Footnote 3 way, and a closer investigation on the phenomenal of human-technology connections is needed. Thus, a postphenomenological perspective of technology is introduced.

3 Postphenomenology: a way of closer investigation

In the fields of STS, a philosophical theory of postphenomenology has offered enlightening perspectives. This empirical-rich, versatile theory that combines phenomenology and American pragmatism has been widely adopted in the studies of human-technology relationships. According to Rosenberger and Verbeek ( 2015 ), these studies focus on the various ways in which technology helps to shape the relations between humans and the world via its "mediation," which plays not only an instrumental role but is closely intertwined with human experiences and practices. Researchers have closely examined human actions and ideas about technological incorporation by analyzing technology-related experiences and meanings, revealing the shaping power of such technology, especially the interface upon which the technology and human connect and interact (such as designs, visualization image, etc.).

In this paper, I will use a few terms and concepts that postphenomenologists have coined and applied in delineating the interactive process between human and technology Footnote 4 :

The " intentionality " of artifacts, which is embedded in the technological interfaces that "tend to" guide, interrupt or form behavioral habits of humans (Verbeek 2005 ). It studies how the appearances of technology (such as interactive interfaces) bridge the subjects (human) and objects (technology) during the interactions. It can indicate how technologies can be directed at particular aspects of reality and the "purposiveness" that technologies can embody (Verbeek 2011 ). The relationship of human and technology shapes itself in the joint interaction between technology and human, "adding technological intentionality to human intentionality." (Ibid: 145)

The " hermeneutic" relations. In this way, technology "explains" the world through interactive designs and experiences, which helps to form the perceptions of the world. Meanwhile, the materiality of technology provides a representation of the world to the human, and the human develops an interpretation of it (Verbeek 2005 ). Certain forms of technological intentionality would direct people into certain hermeneutic interpretations.

" Multistability ." The term "multistability" refers to the way users may interpret different meanings during technological interactions or create different bodily experiences under different scenarios and contexts. Footnote 5 Also, the interaction between artifacts and humans is not intrinsic nor deterministic. It bears different forms in different contexts, against a totalizing narrative. The process of forming multistable relations—even for the most mundane objects—uncovers new information or re-interprets cases in productive ways (Rosenberger and Verbeek 2015 ; Rosenberger 2017a ) and calls for a more flexible and contextual approach to studying the technology. For example, according to Tripathi ( 2017 ), technologies are culturally multistable and open to a culturally embedded "hermeneutic act" during human interaction.

3.1 Technological mediation, self-tracking and fitness

Several postphenomenology scholars have researched self-tracking, focusing on both theoretical implications (Ihde 2002 ; Kristensen and Prigge 2018 ; Kristensen and Ruckenstein 2018 ) and empirical investigations (Van Den Eede 2015 ; Secomandi 2017 and 2018 ). The self-tracking practices have contributed to a constructed, culturally relevant image of the health and fitness of human bodies (Van Den Eede 2015 ). All this research has shown the role of design to be an important nonhuman factor in technological mediations, and the " intentionality " of technology offers the possibility to interfere, intervene or even interrupt our life. Meanwhile, the mediation takes many forms (" multistability ") that call for further investigations.

The " embodiment " aspect of self-tracking devices has altered the user's bodily perceptions. The experiences and practices of "bodily skills" count as a form of "human technique," guiding and shaping our actions from the "bodies in technologies." (Ihde 2002 ) For example, the tracking results have rendered our physical health and fitness status visible and intelligible with numbers and metrics, which are easily connected with an academic-based knowledge regime and transfer the sense of a somatic self from "Body One (our own, physical body)" to "Body Two (A socially and culturally intelligible construction)." (Ihde 2002 ) The use of electronic health records can reinforce the embodiment by "fading into the background, becoming a means of experience." (Moerenhout et al. 2019 ) Besides, the " hermeneutic " mediations of tracking devices translate bodily performances and shape the user's perception of health and fitness status. The making of "body image" (Ihde 2009 ) here represents the knowledge production process.

Secomandi ( 2018 ) analyzes the technological mediation of a commercial tracking device (DirectLife) as a "service interface," where the human-technology interaction reveals a "reference and translation issue." (Ibid: 88) The process includes not only the users but also the maker's design dynamics, which also shapes the entire technological experience (Secomandi 2017 ). Self-tracking devices make present the objective body as a site for hermeneutic inquiry, creating the link between subjective and objective body (de Boer 2020 ) as we read numbers, reflect and interact with them.

The postphenomenology perspective is not only rich in theoretical constructions but also methodological implications. It bounds the micro-and macro- aspects of technological design, accounting for cultural and social factors in the direct phenomenon of the user's interaction with the interface. It offers possibilities of connecting neoliberal health regimes and culture of self-surveillance with design elements in a market-driven network. For sociologists, it is another way to address the Foucauldian thoughts: a materiality-based power structure casting upon a self-practice (Verbeek 2011 ). The approach can better articulate human experiences with a sense that the technologies comprise a critical part of how people feel, sense and comprehend the world, thus building human-technology connections more dynamically and organically. Moreover, the philosophy-rich fields need to be combined with more case studies on the connection between technology and people's health in daily life.

4 Case study: interviewing fitness app users in China

To examine the empirical implications of postphenomenology on the fitness apps, I will use the case study of the most popular fitness app in China, "Keep," It was first released in 2015. Since then, it has gained notable popularity among the urban, middle-class population in China. It claims to have over 100 million installations across the Chinese smartphone market, with monthly active users totaling over several million. It offers home training sessions and tutorials that people can follow and can help users keep track of their activity levels, lengths of time and calories burnt, among many other features that users could engage in. The product description addresses its convenience and accessibility of the training sessions and various options to fulfill needs from beginners to an advanced fitness level. It would walk the users through the process with extensive, everyday engagement—almost free (unless you're lured into buying their premium services). At the same time, it tries to motivate users with its inspirational slogans of self-discipline (such as "self-discipline brings freedom") and virtual rewards from continuous tracking, monitoring, reflecting and sharing of their fitness status.

But how is the self-tracked fitness ideal carried out among users, and how do users consume the messages that the App provides? Do they self-identify as self-disciplined, motivated individuals during the interaction with the technology user-friendly design? To investigate the experience of using the App, I have collected a sample of 20 users online from social media platforms as well as my personal social network (which is not a very hard task thanks to its popularity) and conducted semi-structured interviews. Footnote 6 They were between 20 and 45 years old and consisted of 9 males and 11 females, all from urban areas in China. Their frequency of use and level of engagement of the App ranged from occasional or casual users to dedicated or long-term trackers. The interviews covered questions of habits, preferences, behaviors and "feelings" (such as "how do you feel when you use certain features" and "how do you like its interface") with the App. The interviews asked their understanding of fitness and health through digesting the messages and contents of the App. The analysis is built on a thematic basis—to generate meanings and interpretations by coding and categorization with the help of social theories (Mayring 2004 ; Charmaz 2006 ). In this paper, I will focus on the user's interpretation of meanings about health, personal life and achievements associated with technological designs and then apply and develop theoretical insight according to the analysis of these empirical materials.

4.1 "Flow" and "follow": intentionality behind normalization and engagement

Upon registration with the App, the user will enter his/her (biological) sex, age and body measurements (such as weight and height), then run through a self-evaluation of "fitness level" before getting a "personalized" plan for everyday exercises. It will determine the "need" for different levels and types of workouts, such as "losing weight," "keeping fit," or "toning up muscles." The App will then recommend the user a series of exercise routines or give the user a monthly workout plan based on the "fitness level" and goals. The entire process specifies each exercise routines, length of time, purpose (e.g., which part of body one set of routine is supposed to work on), and the calories it will burn. The user is supposed to follow the recommendations and to earn progress toward the goal.

As sociological critics indicate, the user's "body" here is supposed to meet a standardized norm and be placed onto a linear diagram of fitness (the "fitness level") and decontextualized in a way that objectifies body parts as targets for intervention. It serves as the "embodiment of quantification of self" (Lupton 2016 ) and the initial intention of one to monitor the status of fitness to comply with a specific standard, complying with the belief that universality of science could contribute to the health of bodies corresponds with Foucault's view of surveillance and norms (Foucault 2012 ).

However, the intentionality of the interactive design gives the user a different impression of normalization. As Ihde ( 1990 ) proposes, the intentionality of technology bridges up the human-technology—world arch and mediates the relations into certain forms and trajectories, Footnote 7 and the specific ways in which specific technologies can be directed at specific aspects of reality (Verbeek 2008 ). Here, technology interferes with the user's life by offering "guidance" through this process and selects certain information for a simple, user-friendly display. As Ihde ( 1990 ) and Verbeek ( 2005 ) identify as an "innate trajectory," the intentionality becomes visible through the promotion of the designed "flow." It is shared by other user-centered fitness apps and games apps and games which tend to make "immersive" and "effortless" experiences tailored for specific users (Maloney et al. 2015 ; Martin and Kluckner 2014 ). Users follow the designed process as a proper, "scientific" guidance. It will develop a positive feedback loop when the users meet the norms and standards by getting rewarded or upgraded, and in this way, they comply with the norms of regulating the bodies.

To the users, the initial process—a series of clicks and filling in blanks that lead to a visualized display—makes intelligible communications of "which level am I at?" "How fit am I?" and "What should I do to improve?" Much of the information about "what to do" (such as time of exercise, intensity, and exercise goals) is easily accessible in a conversational style and mostly visible throughout the experiences. Users connect themselves with the numbers they need to achieve, according to which level they are assigned and which three goals they choose. The intentionality of the "flow" prioritizes accessibility and simplifies decisions, while a majority of users describe their experiences as "easy" and "clear." For this reason, although packed with information and numbers, the design style of the App is sleek and simple to serve many fitness beginners for intentionality towards easy use and simple comprehension, and which "directs" users into thinking fitness in the same way with the design languages. For example, one user stated,

"I think [the evaluation] is quite appropriate. I would feel challenging when I finish about 2/3 length of the exercise, but I think it is normal [to feel that way] …it makes an evaluation based on this, you have to put yourself into it to get an accurate outcome." (#2, female, in her 20 s). "It is convenient…not so many steps, and loads of recommendations…(The exercise tips) show up timely before and after exercise, and I'll click on to read, sort of a 'no-brainer' reading without a hitch." (#19, female, in her 20 s).

Also, the notification system with sound effects enhances the intentionality, giving the app the impression of some kind of "guidance." Thus, it is also easy to subject oneself to the App's framework of evaluating "standard" human bodies. Users take in the information without much of the impediments of fitness-related jargon.

"[When I follow the exercise instruction during exercise, the video guide] will shout out to 'keep up' just the right time when I feel tired." (#4, female, in her 30 s.) "I've switched off all the notification on my phone other than Keep. It'll send a notification to me to remind me to exercise; I hope it could work." (#4, female, in her 30 s.)

The intentionality of design is meant to be "followed." The users are supposed to be consuming the App’s information when needing assistance, instructions and reminders to keep fit. Users respond to the intentionality of design with simpler, routinely choreographed patterns, such as following notifications and personalized plans (which include just a few exercises). Users generally embrace the "no-brainer" of design and information display. However, during this process, more subtle personal needs are sacrificed for a pre-determined, easily applicable setting that a popular app needs to develop a wider user base. Other social determinants of health, such as access to healthy food, built environment and socioeconomic status and mental status, are ignored in the initial design and narrow the scope of equating "healthy-life" to self-disciplined practices that could be translated into numbers. The idea that a "healthy life" must be quantified to count has reduced health and fitness onto a thin layer of workouts and engagements.

4.2 Engagement and achievement: intentionality and hermeneutic relations

Another design component that bears intentionality is the emphasis on engagement. The App gives considerable emphasis on "discipline" and "management"—exercising every day, monitoring every movement, sharing with friends and families, and increasing overall activity levels so that one could be rewarded with a virtual upgrade of his/her user status. All of these are to prompt engagement with various functions within the App. For a commercially available app, the aim is to expand the user base as well as to boost the engagement level. The MAU (monthly active users) and DAU (daily active users) are two of the most important metrics for evaluating the success of mobile apps and its potential of gaining profits.

To fulfill these aims, the App recommends the users a series of exercise routines or gives the user a monthly plan based on the "fitness level" and goals. It specifies each exercise routine, length of time, purpose (e.g., which part of body one set of routine is supposed to work on), and the calories it will burn. Once the user finishes a day's exercise (or any other exercise), the achievement will show up in various visual forms—numbers, diagrams, circles, and accumulated levels/grades (See Fig.  1 ). This makes one of the central features of this app: a display of aggregated, quantified data that breaks down and visualizes the user's progress, thus help him/her "understand" what's going on with frequent self-reflection. For users, this form of presentation is clear, number-driven (by offering an "objective" knowledge of a subjective experience of fitness) and visually pleasing. Still, in this way, it leads to the scheme of self-surveillance in a nicely designed outfit.

"I pay a lot of attention to the numbers… I'll take my weight twice a day. I'll pay attention to the exercise time, 40 min per day…When I take a big meal, then I feel guilty about it, I'll take the most' intensive', calorie-burning exercise on the App…Yes, I feel better afterward." (#11, female, in her 20 s).

Diagrams of fitness achievement. The left shows the daily/weekly/monthly summary of exercising time. It shows that the user (the author) has done 36 min of exercise in two routines on this particular day, burning 110 cal. In the middle, it shows "My Data," with a myriad of different types of exercise (Starting from the left blue box counterclockwise): total time, fitness routines, Yoga, walking, running, cycling. On the right, it continues with a weekly chart—if you have exercised, a circle will be filled, followed by the walk steps (the green box, where the number is 0), fitness score (the purple box, linked to Fig.  1 if the user clicks on it) and bodily metrics (here shows body weight, BMI and height)

A personalized "plan" encourages daily and constant interactions from the users (See Fig.  2 ). The newest update in the fall of 2019 has set the "check-in" Footnote 8 as one of the most visible features displayed on the user's home screen and during the interaction. It encourages users to participate in some daily activities for a certain goal while marking their participation with a "streak" on a calendar that shows continuous engagement.

Exercise plan. The left shows the "personalized plan" in a week's span and one routine for the day. For any routine, it shows an introduction, equipment, and how popular it is among users. The time and calories are the core elements, while there's a description of the "purpose" of this workout routine. However, terminologies are there; users do not have to understand them, and some are confusing due to bad translation. The right is how the training plan looks like in the Chinese version. The day-to-day routines are at the bottom, while the overall length (5 weeks, four days per week, 27 min per day) and goals, running and intensity are briefly displayed. The diagram shows how this plan enhances specific parts/capacity of the body (upper limb, lower limb, whole body, core, and cardiovascular)

The overall design is quantified and categorized based on one's performance and level of engagement. It translates into one's fitness status and encourages users to practice on a daily basis. The intentionality of this part of the design encourages constant "attention" and subsequent self-reflection in the form of "self-management" based on those evaluations and feedback. The intentionality channels the way the attention is given,

Through the intentionality of the design, the App creates and directs the user's experience of exercises ("feel better" when numbers are fulfilled), and even shapes one's perception of fitness (fitness or health is directly connected with body metrics and fitness performances, presented in graphs). The design quantifies fitness levels and status, and at the same time, quantifies and interprets engagement as closely connected with fitness. Users interact with this part of the design with a sense of achievement by associating numbers to their life events. The majority of interviewees showed some form of these hermeneutic relations of meaning-making: fitness means to achieve and to excel to be the more motivated and active self, when this "self" could be monitored, quantified and displayed—a "transformation of perception." (Verbeek 2005 : 130).

"It is a great incentive [to look at the numbers] … I'll set my goal, and see how much I should do every day to achieve that. I can discipline and supervise myself." (#9, male, in his 30 s). "I make summary every week and month…It shows me exercise time in each week and each month…last year it generated a picture of your annual achievement." (#16, female, in her 30 s)

This hermeneutic relation mediates their experience and perception in a cultural context of "selfhood." As Lupton has argued, this presentation reflects the creation of a "data assemblage" (Lupton 2016 ). Designs and algorithms play a part in structuring the interaction and information on our devices, affecting our understandings of measurable health—encouraging the perfection of a specific body part by displaying numbers and achievements. Footnote 9 Users interact with the visual and numerical display and presentation by a conscious meaning-making of self-tracking: recording, checking-back, and sharing on social media, expanding the realm of the so-called "dataveillance" of mundane life (van Dijck 2014 ). In this way, the App builds hermeneutic relation with the users, which co-shapes the perceptions of self-governed, self-surveilled health with extensive engagement. Also, The hermeneutic relations are gradually built-in and reinforced in some patterns of interactions. Users take a clear message from the App's contents and how the contents are displayed. For example, opening the app means checking with today's "duty" (plan) and seeing the current status of one's physical body—whether one has reached a goal, finished a commitment, or made progress. It will show visual progress as one starts and finishes each day's routine by filling out a circle. The hermeneutic relations between the users and the App automize the perceptual processes (as a "gestalt") and compose a version of reality for the users to take.

"It automatically notifies you your physical activity. It will tell you which day you exercise or walk less in the past week which you could reflect on." (#7, male, in his 40 s) "I will 'check-in' after each exercise. It is a record of achievement; it makes me feel good, as I've accomplished something." (#2, female, in her 20 s) "(the automatically generated) running track is awesome, amazing. I'll save it and occasionally look back and reflect on it." (#16, female, in her 30 s)

As I have written earlier, some users do "feel" better when they recognize what they have done, but this "feeling" comes more or less from the interpretation of achievement (hermeneutics). Footnote 10 The seemingly mindless interactions with design features are built on these meanings. By designs such as giving user audio instruction during exercise (a female voice saying "come on!"), notifying daily plans with "push notifications," and pop-outs with sound and visual effects, the App provides a "nudge" (Lupton 2014 ) to user's self-surveillance behaviors as a "persuasive technology" (Fogg 2002 ). But only when the context of selfhood—a "better self" and "improvement" of self—are culturally and socially embedded in the user's perception are such persuasive designs persuasive rather than disturbing. As a form of personal "performing data" (Gill 2017 ), the numbers generated and logged in this technology reveals not only one's fitness status of a user but also a hermeneutically interpreted self in various material and embodied ways. It corresponds with the "biocultural discourse" (Rail 2012 ) in self-management and the making of selfhood that one relates to their own bodies in instrumentalist and economic vocabularies, in which better numbers are more desirable. Technology helps to record and regulate the user's practices in a quantified, user-friendly manner so that one could reach the ideal of being healthy and fit with the help of quantified, "objective" knowledge about bodily fitness. This knowledge, in turn, shapes user's subjective feelings and experiences.

Technologies and users help to shape each other in myriad ways, and such "intentionality" needs to be located in human-technology associations, as Verbeek ( 2011 ) argues as "hybrid character of humans and technologies." A broader concept of "hermeneutic strategy" (Rosenberger 2011 ) an interpretive framework in a certain social setting that certain meanings are more likely to be addressed and reinforced. It relates to the culturally historically sedimented procedures that bear upon the interpretation of a technological artifact. This framework can sometimes be co-constructed through both the design and use, a process of "intersubjectivity" (Secomandi 2018 ), which is culturally situated.

Therefore, the intentionality cannot always be reduced to what was explicitly delegated to the technology by its designers or users—a wider meaning-generating context should be taken into account as "multistable" relationships between technology and humans are simultaneously formed during interactions.

4.3 Your health, my life: the multistability of technology

You need to become self-disciplined and become part of the knowledge scheme in which fitness and health are measured by numbers on the mobile screen—however, not everyone buys into the scheme. There are constant negotiations between an ideal of "healthy-lifestyle" and real-life situations, sometimes with tension.

"I was looking for a way to get out of [a bad] situation while doing fitness was kind of easy. Just 10–15 min of exercise could boost myself up a bit." (#11, regular tracker, female, in her 20 s). "Exercise for me is like tidying up the room…if I'm upset today, but I still have some energy left, then I'll spend 30 min to make me feel like achieving something." (#20, casual user, female, in her 20 s).

People feel like they were not achieving their potential—in their jobs, school, social life, or life situations that are not as quantifiable as doing a 30-min workout. The App offers immediate results and, over time, physical results as well. The mental aspect of exercise is not addressed in the App (at least in an apparent way). Nevertheless, users still make meaning from the quantifiable numbers for themselves.

Some users only view the App as a simple tool and reference point of fitness, but not as well-rounded lifestyle guidance (which the App pictures for them). Nevertheless, they could still interpret and associate the technology with their own context of life. As Verbeek ( 2005 ) addresses, the "multistability" of technology allows different interpretations to form during a user's interaction with the technology, and those interpretations and meanings should stand in the social context of technological experiences. Footnote 11 The design features of the technology and intentionality wrapped in the experiencing trajectories might indicate some form of stability here, but multiple "stabilities" should be seen with not only the design features of technology (or the designer's intention) but the cultural and social tendencies of interpretation—and this can occur to other fitness technologies with different visual designs.

The reasons for not closely managing fitness activities might vary. Still, nearly all of the users would agree that a better, healthier life should be well-managed and quantified, and the barrier to that is one's lack of determination, which the App could not offer. Again, this interpretation is out of the user's own context, not the App's agenda.

"Make apps are marketed as 'bite-size' exercise…but many people say that even you do not need a lot of time doing exercise, you still need motivation, or you should be very self-disciplined." (#12, regular tracker, male, in his 30 s).

A lot of variation comes from the "reading" of information and numbers. Even if the numbers are decorated with narratives of fitness, some other meanings can also be associated in another context. Postphenomenologists have analyzed scientific images (Ihde 1986 and 2009 ; Rosenberger 2011 ), medical data (Moerenhout et al. 2019 ) and medical images (Forss 2012 ), which can be read in different ways or even generating conflicts. It is part of instrumentally mediated perception regardless of the claim of "objective knowledge." It involves sensory and hermeneutic perception and interrelations between the two, and the process is "too tangible" for a fixed, abstract concept (Forss 2012 ).

Although nearly half of the interviewees see the App more or less "like a tool" for references when they need some exercise in the absence of gyms or outdoor activities (as is also the case during covid-19), it does not mean that the App is "just a tool." It still bears meanings and knowledge regimes by quantifying certain aspects of fitness and interpreting it into values such as self-discipline and self-surveillance, but the meanings reach users via technological mediation. The multistability noted here allows users with their own social and cultural context to act differently, constituting their own subjectivity with material objectivity. As Lupton and Smith ( 2018 ) argue, users can express their "agential capacities," where self-improvement and control can be translated while they enact their own tracking practices.

Previous STS scholars use the term "interpretive flexibility" such as Bijker and Pinch ( 1984 ) to describe the stage that different people interpret the attributes of the technological design before the final design is agreed upon and closed. Similarly, multistability indicates an extent of flexibility, but instead of a sociological process of conflicting, shaping and settling, there isn't a final closure of any kind. The design itself indicates a certain degree or form of flexibility and will be potentially exploited by different groups according to their social and cultural context.

In this study, the casual users (who exercise less often and take the App more as a reference tool than a self-management companion) showed different interpretation from the frequent users (who engage with their plans and goals daily)—the interplay between their own life course and the design elements went differently. For an app that covers a wide range of users, its interface design would certainly play out differently in different users. The interactions between design elements and various cultural assumptions call for further investigation.

In sum, the App sets the ideal of health and marches to it by self-surveillance, imposing the virtue of "self-discipline"—this aligns with most of the users' perceptions about keeping fit. The extent of achieving that ideal varies among users who combine their own source of motivation with the convenience and accessibility that the App offers. The users bring their "hermeneutic strategy" that involves approaching the app through their own value, not only through the engagement expected by the app designers. People would take things they deem useful from the App, and receive health-related information in "bite-sizes," but can still be skeptical about some aspects of it. They negotiate a "better version of me" that is shaped by the designs, creating their own narratives with the help of technology, compromising the ideal and the reality.

5 Conclusion, discussion and future research

The popularity of fitness apps has changed the way people exercise and understand exercise—into something manageable and trackable, as well as a healthy "lifestyle," This change happens during the contextualized interaction between people and technological designs. In this paper, I have examined the use of fitness apps and its connections with the understandings and practices of fitness/health during the engagement with technological designs. The intentionality of the "flow" of interface design creates an experience in which users are being guided through or subscribed to a normalized body scheme. Through the hermeneutic mediations of technological designs, the concepts of health and fitness are interpreted as "achievements" and associated with meanings that connect self-improvement and self-discipline with health and fitness. The findings correspond with the sociological analysis of the "quantified self" and the trends of self-surveillance, but are in finer details and connect with the cognitive and behavioral aspects of user experiences with the technology.

The quantificational management of self is implemented through the users' interaction with design elements and technological mediations of hermeneutics, or even further with aspirations towards embodiment (with extensive use of wearable gadgets in the future). However, the multistability of technological mediation creates opportunities for the users to re-interpret the context and meanings of fitness and exercises even within the design framework, showing that the designed path is far from determined. The understanding of fitness and health with personal technologies gadgets is a mutual (or even collective, if the users are to be connected into a social network) process.

The changing concepts of fitness and personal health—with the unprecedented detailed personal informatics and numbers available through various gadgets and services—highlight the challenge of traditional methodologies and theories of sociological and behavioral studies in revealing the relationship between technological artifacts and health-related practices. The nuance of direct experiences—through which users recognize the significance and form understandings—is crucial in studying the impact of technology on personal matters such as health and fitness. The introduction of postphenomenology into the analysis of fitness apps and self-quantification behaviors provides a distinctive way of investigating the process of technological interactions, which gives weight to the design elements and interfaces on the shaping of our understandings, behaviors and practices. It casts light on both the materiality (technologies, designs, interfaces, or even systematic schemes) and perception (contents, messages, cultures) and mediating processes that connect both parts. As Latour ( 2005 , see also Mol 2010 ) proposes, the phenomenon should be placed in a network of actors (actants), both human and nonhuman, to delineate a comprehensive picture of human-technology relations and to see the mutual impact of technologies and ideas. Postphenomenology offers a tool, a knife sharp enough to open the hard surface of a phenomenon and to make sound explanations.

This paper has limitations that most case studies share: a tension between internal and external validity. For future sociological examinations, an extensive analysis should be made on a variety of population groups, not limited to the typical app users (young, urban, highly educated). It will show a wide range of engagements and diverse perceptions, raising more questions about personalized health technologies and their social implications. The postphenomenology approach can also lead to investigations on other health-related technologies, including wearables, monitoring devices and services like "virtual helpers." It will bring helpful tools and useful perspectives to such interdisciplinary studies that further reveal the technologically mediated connections of human and health systems. Besides, there should also be conversations between the design and use, which is on-going through data-collecting, user observation, and engagement in the fitness market. The design process would reveal priorities and values from the App makers and how that will have an impact on the experiences and outcomes of fitness apps.

Finally, the approaches in this study could shed lights on the fluid context of health in times of turbulence and change (like in a global pandemic), and how the change in the political economy would trickle down to daily life—what does fitness and health means to a quarantined life? Would the urge of working out indoors converge with the technological intentionality that embraces and encourages the urge? The new questions call for innovative perspectives and new methodological tools to observe and dissect these unprecedented changes and further interrogate what kind of health we want and what technology could do for us.

Data availability

All data and materials support the published claims and comply with field standards and ethical requirements.

Promotional message retrieved in the “Discovery” and “Community” section (where users can find online campaigns or exercise challenges to complete) of “Keep” Fitness App, February 2020.

This message shows up every time a user opens the Keep App.

By saying “internal,” I don’t mean that the technology is part of our somatic bodies (although in some cases, the technology cannot be separated from it, such as a cardiac pacemaker). Humans are increasingly utilize technologies as a way of seeing/understanding the world and reflecting on themselves, whether or not a certain technology is attached to them at all times.

There are some other forms of mediating relations, namely “ embodiment” relations, in which technology broadening human’s sensitivity and human look “through” them to recognize and connect with the material world (Verbeek 2005 : 125). Also, there are two other mediating relations that I will not elaborate in this paper: alterity (technology as a quasi-other, such as robot) and background (not consciously experienced but shaping the environment). See Rosenberger and Verbeek 2015 .

“Stability” or “variation”, see Rosenberger and Verbeek 2015 : 25–26.

The interviews were conducted in the summer of 2019, and some following-ups in the spring of 2020.

This can also be traced back to Heidegger’s “Instrumental Intentionality” that something’s “in-order-to” feature becomes the context of the thing that “could be done.” See Verbeek 2001 .

In Chinese, the term “check-in” is fashioned as “打卡”, originating from the action that one goes to work and inserts the punchcard for recording the presence. It derives a broader meaning of doing something compulsory, or signifying “something has been done” without describing further engagement, e.g. travelling to a tourist spot and taking a picture at the most famous place.

For example, a set of exercise usually consists of a series of routines (such as push-ups, squats, or running distance), each specifically emphasizing the training of a body part or an aspect of fitness (e.g. endurance, strength, etc.).

However, as the wearable technology moves forward, users are envisioning such as future when the inner, physical “self” would be bounded through more numbers and metrics on display; as seeing those numbers becomes a way of reading one’s health and fitness without realizing the existence of technology. It is not yet mediating an embodiment relationship, but would march towards that.

There are some nuances regarding to the term “multistability.” Rosenberger and Verbeek ( 2015 ) pointed mainly to the various versions of use and interpretations from the user’s side, and the divergence from the designing ends to the various perceptual ends, such as the case of fire hydrants (See Rosenberger 2017a ) and “anti-homeless design.” (See Rosenberger 2017b ) However, when Ihde ( 1999 ) uses this for the analysis of imaging technology in the sciences, he argues that a “converge” of variations can also occur—different technologies can hold on to certain imagery artefact from various channels. Whyte ( 2015 ) echoes with the idea of “pivot.”.

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The author thanks Dr. Robert Rosenberger and Dr. Jennifer Singh from Georgia Tech for their advice and contributions towards this paper.

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Zheng, E.L. Interpreting fitness: self-tracking with fitness apps through a postphenomenology lens. AI & Soc 38 , 2255–2266 (2023). https://doi.org/10.1007/s00146-021-01146-8

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Received : 06 August 2020

Accepted : 12 January 2021

Published : 07 February 2021

Issue Date : December 2023

DOI : https://doi.org/10.1007/s00146-021-01146-8

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