Tracking Apps Research Articles

Fit with Faith: An Exploratory Study Examining a Behavior Change Intervention for African-American Clergy and Their Spouses.

Fit with Faith is a 10-week, diet, physical activity, and stress reduction intervention for African-American clergy and spouses, which included: meetings, phone calls, a behavior tracking app. Survey, 24-h recall, accelerometer, anthropometric, and blood pressure data were collected. Wilcoxon signed ranked tests were used for analyses. In this one-arm study, clergy and spouses (n = 20) attended most meetings and calls, but only half posted daily goals or tracked behaviors using the app. Spouses' body mass index (BMI) decreased and physical activity self-regulation cognitive scores increased pre-post intervention. Statistically significant changes in BMI, systolic blood pressure, and self-regulations scores also were seen among younger (< 51years) participants (n = 8). As positive changes were seen mostly among women and younger participants, more research is needed on how to engage all clergy in behavior change programs.

University students' opinions towards mobile sensing data collection: A qualitative analysis.

mHealth researchers can now collect a wealth of data using "life tracking apps" (LTAs), which are smartphone applications that use mobile sensing to capture and summarise a multitude of data channels (e.g., location, movement, keyword use, sleep, exercise, and so on). The combined wealth of information can create digital signatures of individuals, which hold immense promise for mental health research and interventions by allowing new insights into moment-to-moment changes in behaviour and mental states. However, little is known about what a common research demographic (university students) thinks about these apps and what might factor into their decisions to participate in research using a LTA. This qualitative study ran five focus group sessions (21 students in total) to explore students' experiences, beliefs, and opinions about LTAs to generate insights into what would make them more or less likely to participate in research involving LTAs. Transcripts were coded and examined for categories using qualitative content analysis. Important categories that emerged were privacy (although this varied based on the individual and data being collected), data security, inconvenience, intrusiveness, financial compensation, and the perceived nature of the research team responsible. On the basis of these categories, we derived seven key insights to increase student participation in research using LTAs: strengthen and communicate privacy and data security, design the app to be as convenient as possible to users, maximise passive data collection, think cautiously before tracking data perceived as "creepy" such as messages, offer suitable financial compensation, be transparent about goals and justification for data being collection to build trust, and attract participants by highlighting how the app can help them achieve their goals. With these insights, mHealth researchers can maximise their participant pool and improve this nascent and promising field.

More than blood: app-tracking reveals variability in heavy menstrual bleeding construct

BackgroundHeavy menstrual bleeding (HMB) is associated with impaired quality of life and may signal serious health problems. Unresolved challenges in measuring menstrual bleeding and identifying HMB have hampered research and clinical care. Self-reported bleeding histories are commonly used but these may be influenced by recall bias, personal beliefs regarding “normal” flow volume, and the experience of other physical symptoms or disruptions to daily life. The potential usefulness of menstrual-tracking mobile applications, which allow real-time user-entered data recording, for assessing HMB has not been studied. We evaluated recall bias in reported period duration, the relationship of tracked period duration and daily flow volume to subsequently reported period heaviness, variation in quality of life associated with increasing period heaviness, and the advantages and limitations of using app-tracked data for clinical and research purposes.MethodsAn online questionnaire was distributed to current users of Clue, a commercially available menstrual health tracking app, asking them to characterize their last period. We compared responses to the user’s corresponding Clue app-tracked data. The study sample comprised 6546 U.S.-based users (aged 18–45 years).ResultsIncreasing reported heaviness was associated with increasing app-tracked period length and days of heavy flow, impaired quality-of-life (especially body pain severity), and disrupted activities. Of those reporting having had a heavy/very heavy period, ~ 18% had not tracked any heavy flow, but their period length and quality-of-life indicators were similar to those who had tracked heavy flow. Sexual/romantic activities were the most affected across all flow volumes. Compared to app-tracked data, 44% recalled their exact period length; 83% recalled within ± 1 day. Overestimation was more common than underestimation. However, those with longer app-tracked periods were more likely to underestimate period length by ≥ 2 days, a pattern which could contribute to under-diagnosis of HMB.ConclusionPeriod heaviness is a complex construct that encapsulates flow volume and, for many, several other bleeding-associated experiences (period length, bodily impairments, disruptions of daily activities). Even very precise flow volume assessments cannot capture the multi-faceted nature of HMB as experienced by the individual. Real-time app-tracking facilitates quick daily recording of several aspects of bleeding-associated experiences. This more reliable and detailed characterization of bleeding patterns and experiences can potentially increase understanding of menstrual bleeding variability and, if needed, help to guide treatment.

Sex tech, sexual data and materiality

ABSTRACT In its consummate materiality, the sexual body is vital to the current discourse in digital health studies, disability studies and critical, feminist and postcolonial data studies, and broader theoretical trends in new materialism that insist on the embodied status of data production. This sexual body is a vital element in understanding the materiality at the heart of data production. This article explores how datafication becomes inscribed into sexual culture, influencing norms and expectations of sexual behaviours and culturally dominant ways in which the body is conceptualized. The article considers Pornhub, the AI RealDoll, two smart sex toys and a number of dating, intimacy and sex tracking apps, in order to explore the increasingly significant relationship between sex and data. This article considers the datafication of culture to describe the pervasion into culture of imperatives of quantification and categorization and binary and definitive epistemologies. The rhetoric, aesthetics, design and affordances of datafying technologies, and users' engagement with the data are considered here in relation to their impact on contemporary sexual culture.

A Questionnaire Survey of the Mental Health of Japanese Expatriates in China During the COVID-19 Epidemic in 2021

This study examined the impact of coronavirus disease 2019 (COVID-19) on Japanese expatriates living in China. The survey period was from March 30 to July 31, 2021; responses were received via an online survey. An online survey gathered responses from 236 participants about the impact of COVID-19 on their work and life. While 80% of the participants responded that COVID-19 had impacted their work and life, 60% said that it had a physical or mental impact. Kruskal–Wallis test and Mann–Whitney U test were conducted to compare the effects of COVID-19 on job performance, including personal attributes. The impact of COVID-19 was associated with gender (p = .007), age (p = .010), occupation (p = .005), job title (p = .009), and living arrangements with or without a partner (p = .005). The impact was also correlated with age (p = .030), job position (p = .014), number of times the respondent had lived in Japan (p = .003), and number of years in Japan (p = .015). The most significant effect on mental and physical health was correlated with job position (p = .016). Thus, Japanese expatriates living in China were substantially affected by the COVID-19 epidemic; although, 60% of them said their region was easy to live in. Further, despite the Chinese government’s strict isolation orders, they found the thorough testing and use of the coronavirus tracking app reassuring. This suggests the importance of providing not only mental care for expatriates during the COVID-19 epidemic but also prompt decision-making based on an accurate understanding of the local situation.

DIGITAL TRACES, SOCIAL RESIDUES: USAGE AS SELF-REPRESENTATION ON LIFESTYLE APPS

Self-representation is ubiquitous in digital spaces, but much of the existing literature discussing it is focused on social media contexts. Self-representation involves the creation of media traces that record users’ presence and existence through media, but these traces and the platforms that circulate them do not have to be explicitly or directly social. We study self-representation in alternative digital contexts: lifestyle apps focused on ambient usage behaviors that are generally private, personal, or invisible in online spaces. These apps incorporate social features based on displays of user data—streams repurposing users’ engagement with the platform as social displays to networked friends. The three apps of interest include the payment app Venmo, music streaming app Spotify, and fitness tracking app Strava. We study these apps through a combination of “walkthroughs” of each of the platforms and interviews with users. Our findings suggest that these platforms repurpose individual user behaviors as digital residues in social streams, transforming them into networked self-representations. Within this process, we expect that some users intentionally mobilize their engagement with the apps as social performances. Ultimately, this study raises questions about digital self-making, commodification, and platform sanctioned sociality beyond social media.

A Comparison of Two Hormonal Fertility Monitoring Systems for Ovulation Detection: A Pilot Study.

Background and Objectives: Accuracy in detecting ovulation and estimating the fertile window in the menstrual cycle is essential for women to avoid or achieve pregnancy. There has been a rapid growth in fertility apps and home ovulation testing kits in recent years. Nevertheless, there lacks information on how well these apps perform in helping users understand their fertility in the menstrual cycle. This pilot study aimed to evaluate and compare the beginning, peak, and length of the fertile window as determined by a new luteinizing hormone (LH) fertility tracking app with the Clearblue Fertility Monitor (CBFM). Materials and Methods: A total of 30 women were randomized into either a quantitative Premom or a qualitative Easy@Home (EAH) LH testing system. The results of the two testing systems were compared with the results from the CBFM over three menstrual cycles of use. Potential LH levels for estimating the beginning of the fertile window were calculated along with user acceptability and satisfaction. Results: The estimates of peak fertility by the Premom and EAH LH testing were highly correlated with the CBFM peak results (R = 0.99, p < 0.001). The participants had higher satisfaction and ease-of-use ratings with the CBFM compared to the Premom and EAH LH testing systems. LH 95% confidence levels for estimating the beginning of the fertile window were provided for both the Premom and EAH LH testing results. Conclusions: Our pilot study findings suggest that the Premom and EAH LH fertility testing app can accurately detect impending ovulation for women and are easy to use at home. However, successful utilization of these low-cost LH testing tools and apps for fertility self-monitoring and family planning needs further evaluation with a large and more diverse population.

Perceived vs. observed mHealth behavior: A naturalistic investigation of tracking apps and daily movement

Research on mHealth apps provides mixed evidence regarding their effectiveness for behavior change, including physical activity. Synthesizing prior perspectives, we test predictors of tracking app and physical activity intentions (Study 1; n = 658) and their links to everyday mobility (Study 2; n = 418; n = 27,617,440 observations). Study 1 showed that individuals have overlapping perceptions of tracking apps and physical activity. Taking a naturalistic mobile sensing approach, Study 2 found that tracking app and physical activity intentions predicted self-reported physical activity – but not logged movement (i.e., walking, cycling, or running). Tracking app use was not related to the level of logged movement in daily life. However, participants who regularly used tracking apps were more likely to view them as impactful, suggesting that daily mHealth app use is related to perceived (vs. observed) behavior change. Together, our studies illuminate how perceptions of mobility and mobile media – and their effects – can become intertwined in users’ minds.

The role of menstrual apps in healthcare: provider and patient perspectives.

This study aimed to understand the role that menstrual apps ("period tracking apps" or "fertility apps") could perform in healthcare. Expert stakeholders including healthcare providers, app users, and patients offered perspectives on potential benefits, concerns, and role of apps in healthcare. Responses from an online qualitative survey (N=144) and three online focus groups (N=10) were analysed using reflexive thematic analysis. The role of menstrual apps in healthcare could include keeping a record of cycle dates and symptoms and assisting in the management of menstrual disorders, diseases and conditions linked to the menstrual cycle such as endometriosis, PCOS, infertility, and perimenopause. Respondents are using app calendars and symptom tracking to improve communication between healthcare providers and patients, while also expressing concerns about inaccuracies and other uses of data. Respondents wished for assistance in managing their health, while noting that apps currently are limited and suggesting that apps need to be better suited to Aotearoa New Zealand specific menstrual disorders, diseases and life stages. Menstrual apps may have a role in healthcare, but further research needs to develop and evaluate app functions and accuracy as well as providing education and guidelines for whether and when apps are appropriate for healthcare.

Acceptance of Digital Sports: A Study Showing the Rising Acceptance of Digital Health Activities

Digital sports and health activities are rapidly gaining acceptance as viable alternatives to traditional physical activities. With the widespread adoption of digital technologies, people are turning to digital sports and health activities to maintain their physical fitness and well-being. This abstract explores the rising acceptance of digital health activities, particularly in the field of sports. The study highlights the various digital health activities available to consumers, such as fitness tracking apps, virtual coaching, and online exercise classes. The study reviews the benefits of digital health activities, such as increased accessibility, flexibility, and personalization. The study examines the factors that influence the acceptance of digital health activities, such as ease of use, perceived usefulness, and social influence. The study also discusses the challenges of implementing digital health activities, such as data privacy and security concerns, and the need for adequate technological infrastructure. The study concludes that the rising acceptance of digital health activities in the field of sports is indicative of a broader trend towards the adoption of digital technologies in healthcare. As the technology continues to advance, digital health activities are poised to play an increasingly important role in healthcare, providing accessible and personalized solutions to promote physical fitness and well-being.

Perspectives of Patients With Orthopedic Trauma on Fully Automated Digital Physical Activity Measurement at Home: Cross-sectional Survey Study.

The automated digital surveillance of physical activity at home after surgical procedures could facilitate the monitoring of postoperative follow-up, reduce costs, and enhance patients' satisfaction. Data on the willingness of patients with orthopedic trauma to undergo automated home surveillance postoperatively are lacking. The aims of this study were to assess whether patients with orthopedic trauma would be generally willing to use the proposed automated digital home surveillance system and determine what advantages and disadvantages the system could bring with it. Between June 2021 and October 2021, a survey among outpatients with orthopedic trauma who were treated at a European level 1 trauma center was conducted. The only inclusion criterion was an age of at least 16 years. The paper questionnaire first described the possibility of fully automated movement and motion detection (via cameras or sensors) at home without any action required from the patient. The questionnaire then asked for the participants' demographics and presented 6 specific questions on the study topic. In total, we included 201 patients whose mean age was 46.9 (SD 18.6) years. Most of the assessed patients (124/201, 61.7%) were male. Almost half of the patients (83/201, 41.3%) were aged between 30 and 55 years. The most stated occupation was a nine-to-five job (62/199, 30.8%). The majority of the participants (120/201, 59.7%) could imagine using the proposed measurement system, with no significant differences among the genders. An insignificant higher number of younger patients stated that they would use the automated surveillance system. No significant difference was seen among different occupations (P=.41). Significantly more young patients were using smartphones (P=.004) or electronic devices with a camera (P=.008). Less than half of the surveyed patients (95/201, 47.3%) stated that they were using tracking apps. The most stated advantages were fewer physician visits (110/201, 54.7%) and less effort (102/201, 50.7%), whereas the most prevalent disadvantage was the missing physician-patient contact (144/201, 71.6%). Significantly more patients with a part-time job or a nine-to-five job stated that data analysis contributes to medical progress (P=.047). Most of the assessed participants (120/201, 59.7%) stated that they would use the automated digital measurement system to observe their postoperative follow-up and recovery. The proposed system could be used to reduce costs and ease hospital capacity issues. In order to successfully implement such systems, patients' concerns must be addressed, and further studies on the feasibility of these systems are needed.

Ethics of sleep tracking: techno-ethical particularities of consumer-led sleep-tracking with a focus on medicalization, vulnerability, and relationality

Consumer-targeted sleep tracking applications (STA) that run on mobile devices (e.g., smartphones) promise to be useful tools for the individual user. Assisted by built-in and/or external sensors, these apps can analyze sleep data and generate assessment reports for the user on their sleep duration and quality. However, STA also raise ethical questions, for example, on the autonomy of the sleeping person, or potential effects on third parties. Nevertheless, a specific ethical analysis of the use of these technologies is still missing so far. The aim of the current analysis is to identify the characteristics of sleep tracking apps and to explore the specific ethical aspects associated with this form of self-tracking. Firstly, the field of mobile health applications was screened for STA to explore their typical functions and target user groups. Secondly, an ethical analysis was conducted focusing on the three ethical dimensions: (1) medicalization, (2) vulnerability, and (3) relationality. The analysis indicates that these three normative dimensions are decisive for assessing STA and that the ethical profile of this technology varies greatly depending on the respective user group. As the three dimensions medicalization, vulnerability, and relationality play a distinguishing role in the use of STA, they should be especially addressed in responsible development and implementation of STA. In addition, the analysis helps to evaluate the use of STA, in terms of different risks for specific user groups, the sensitive contexts of usage, and potential interference with the intimacy of third parties.

A Sampling of Sleep Apps and Their Benefits

Librarians, clinicians, and library patrons would benefit from exploring the potential of applying mobile technology to help improve their overall health and wellness. One of the most common problems experienced by many children, adolescents, and adults is sleeplessness, poor sleep quality, and inadequate sleep hygiene. A popular and emerging trend in mobile technology is the development of sleep improvement and tracking apps. These apps have infiltrated the market, making it difficult for users to discern which apps will appeal to them without downloading and testing each of them. This article aims to introduce users to 10 popular sleeping apps and their benefits.

Meu corpo é meu: aplicativos menstruais e a normalização sócio-técnica do gênero

Abstract The use of mobile applications to track menstrual cycles is becoming more widespread. The proliferation of applications raises concerns about the normalization of the binary construction of gender identities by means of technological innovation and its impact on human rights. Some of these issues include an opaque treatment of users’ personal data, the reproduction of gender stereotypes in design, and algorithmic biases. This study adopts a qualitative approach to examine those implications in the lives of menstruating people in Mexico City. The qualitative study included 32 in-depth interviews with young adult users aged 18 to 25 to learn about their experiences with various menstrual tracking apps. The analysis revealed that users were dissatisfied with the gender bias in the design, with the inadequate treatment of personal data by the apps, regarded as an invasion of privacy, and with app performance, which contributes to standardizing experiences and normalizing binary conceptions of gender by techno-social means. This study suggests that the design of period tracking apps should consider the experiences and needs of menstruating persons in their diversity, based on a non-binary definition of gender. Fair design should begin by engaging with menstruating people in order to improve their experience and quality of life, with their rights at the forefront.

Comparing the accuracy of estimated time of arrival in mobile navigation applications

Accuracy of estimated time of arrival (ETA) for mobile vehicle tracking applications (apps) remains as a key issue to be discussed. Most of the mobile vehicle tracking apps such as WAZE is using GPS to track the current location of the vehicles. However, the accuracy of data provided by the mobile apps and factors affecting the accuracy remain as an unexplored area. This study examines the ETA accuracy by comparing ETA of a self-developed vehicle tracking app namely UCSITravel and a popular navigation app namely WAZE. The comparison test is performed by using t-test to determine if there is a statistically significant difference between the means of the datasets. Factors affecting ETA accuracy are determined in this study. The comparison results show that UCSITravel, which uses mean-value calculation (MAP), produces as accurate ETA as WAZE, which calculates ETA based on historic and real-time crowdsourced traffic data. The results shed light to mobile application developers to explore and understand more options of prediction models in developing mobile vehicle tracking app. In addition, this study has demonstrated several factors that were found to affect the accuracy of ETA in both apps as in line with literature. The results yield theoretical and practical implications.

The Impact of Apple's App Tracking Transparency Framework on the App Ecosystem

The Impact of Apple's App Tracking Transparency Framework on the App Ecosystem

The Impact of Apple's App Tracking Transparency Framework on the App Ecosystem

The Impact of Apple's App Tracking Transparency Framework on the App Ecosystem

Vehicle Detection Using Machine Learning Model with the Gaussian Mixture Model (GMM)

Motion tracking apps are used for a lot of different things, like finding traffic jams and counting the number of cars going through a traffic light. The datasets come from many places on the internet, like YouTube and public dataset archives. There are about 20 videos that are tagged with the words "traffic" and "traffic camera video" and run for 10 to 30 seconds. The Gaussian Mixture Models (GMM) method is the proposed model. It separates the background from the tracked object, which is needed to do motion tracking. Then, the GMM method groups pixel data based on the background color of each pixel. After the cluster is made, the input is matched as a distribution, with the most common distribution used as the background. The analysis was done using MATLAB2019B. The results of this study show that the GMM method can adapt to the background. This is shown by the fact that testing of some of the given conditions went well.

ERRATUM to “Quantifying sex. Sex tracking apps and users’ practices”

ERRATUM to “Quantifying sex. Sex tracking apps and users’ practices”

Gendered morphologies and walking: Evidence from smartphone tracking data among young adults in Barcelona

AbstractIt is well established that urban form can encourage or hinder daily walking activity. Consequently, urban form has a direct impact on both spatial accessibility and the ability of achieving daily physical activity recommendations. However, the relationship between urban form and walking patterns may present relevant differences among different population subgroups, for instance in terms of gender. In order to analyse how the relationship between urban form and daily walking time might be modulated by gender, the present study aims to explore walking patterns of men and women living in different neighbourhood types in Barcelona Metropolitan Region (Spain). For this purpose, the study uses data extracted from a smartphone tracking app among a rather specific population group: young adults who commute daily to the same destination. The findings show that compact urban forms promote gender equality. The study especially sheds light on the disadvantaged position of young women living in small towns and suburbs, who walk much less than other women and any men.