An Analysis of Privacy Language in the Scholarly Literature on Mental Health Apps

This chapter charts the language of privacy in published scholarship on mental health apps. What definition of privacy is assumed? What meanings of privacy are deployed in the research about mental health apps? Using a qualitative thematic approach, this analysis shows that privacy language can be understood as occurring in three phases: Phase 1: Discourse of Technological Possibility; Phase 2: Discourse of Privacy Challenges and Threats; and Phase 3: Discourse of Advocacy. The authors discuss each of these phases and propose a more critical discourse of privacy by identifying the issues inherent in understanding privacy as security.

Exploitation of Health on Instagram

This chapter focuses on the exploitative nature of Instagram as a community-based platform. Individual users build, maintain, and participate in communities as a way to connect with experiences and insights that resonate with them. Because users are motivated by different gratifications and are met with social support along the way, brands can use influencers to exploit the community-based practices (i.e., liking, sharing, and curating content) to access a variety of data points from users. Ultimately, users' data is routinely at risk as a byproduct of this subversive use of the platform.

How Do Mobile Applications for Cancer Communicate About Their Privacy Practices?

No previous research on cancer mobile applications (apps) has investigated issues associated with the data privacy of its consumers. The current chapter addressed this gap in the literature by assessing the content of online privacy policies of selected cancer mobile apps through applying a checklist and performing an in-depth critical analysis to determine how the apps communicated their privacy practices to end users. The results revealed that the privacy policies were mostly ambiguous, with content often presented in a complex manner and inadequate information on the ownership, use, disclosure, retention, and collection of end users' personal data. These results highlight the importance of improving the transparency of privacy practices in health and fitness cancer mobile apps to clearly and effectively communicate how end users' personal data are collected, stored, and shared. The chapter concludes with recommendations and discussion on practical implications for stakeholders like cancer app users, developers, policymakers, and clinicians.

Role of Wearable Technology and Fitness Apps in Obesity and Diabetes

Rapid economic growth, industrialization, mechanization, sedentary lifestyle, high calorie diets, and processed foods have led to increased incidence of obesity in the United States of America. Prominently affected by the obesity epidemic are the most vulnerable such as the rural poor and those who have less access to nutritious and healthy foods due to barriers such as socioeconomic, infrastructural, and organizational. Wearable technology (WT) and health fitness applications (apps) have the potential to address some of the health disparities associated with obesity. Monitoring health parameters through WT and Apps using remote sensing technology generates personal health data which can be captured, analyzed, and shared with healthcare providers and others in social support network. Because captured data include protected health information, and breaches can occur, the concerns about health data privacy, personal ownership, and portability are addressed in this chapter.

What Can Fitness Apps Teach Us About Group Privacy?

This chapter begins with a case study of Strava, a fitness app that inadvertently exposed sensitive military information even while protecting individual users' information privacy. The case study is analyzed as an example of how recent advances in algorithmic group inference technologies threaten privacy, both for individuals and for groups. It then argues that while individual privacy from big data analytics is well understood, group privacy is not. Results of an experiment to better understand group privacy are presented. Findings show that group and individual privacy are psychologically distinct and uniquely affect people's evaluations, use, and tolerance for a fictitious fitness app. The chapter concludes with a discussion of group-inference technologies ethics and offers recommendations for fitness app designers.

Data Ownership

This chapter explores legal issues concerning ownership of data collected, shared, used, and transmitted via wearable technologies. Such widespread information sharing raises privacy concerns that existing legal protections do not address. The author analyzes prevailing legal regulatory climate surrounding data privacy, such as health laws and privacy policies. Next, the author highlights the inadequacy of these legal instruments and explicate the legal framework of intellectual property laws to determine ways to provide individuals with more control over their personal data.

“Sensitive but Essential Information”

As fitness trackers and applications grow popular, many actors involved in the development, use, and regulation of these devices expressed concerns of privacy and control of data gathered through these platforms. This chapter explores how government representatives, industry leaders, regulators, and politicians discursively constructed and critiqued data privacy in fitness applications in congressional contexts. Findings indicate the following discourses: (1) fitness trackers as indicative of larger data collection issues, (2) weighing the pros and cons of use, (3) military implications for fitness application data security, (4) consumers as responsible for their own data privacy, (5) organizations failing to keep pace with cyber security threats, and (6) the misuse of data collected in fitness applications for promotion/strategic communication uses.

Governmentality, Playbor, and Peak Performance

Gamification—the use of video game elements in non-gaming environments—is an effective and lucrative method of compelling individuals to engage with behaviors normally found aversive or uninteresting. Gamified applications are found in myriad areas, from education and social justice to health and wellness. A preponderance of evidence suggests that gamified health applications can have a positive effect on mental and physical health, but these benefits are often not balanced against the unanticipated or unknown consequences to individuals that come with coercing or “governing” players towards activities that might not be for the players' benefit. The chapter describes and explains gamification, discusses various health and wellness gamification programs, and then highlights existing and speculates on potential exploitative interactions stemming from uncritical engagement with health and wellness gamification. This critique is offered through Foucault's lens of “governmentality.”

Case Study

Under Armour purchased a fitness app, MyFitnessPal, that suffered a data breach shortly after Under Armour acquired the app. This breach made customers usernames, emails, and passwords available and for sale on the dark web. Under Armour informed its users of the breach and handled the crisis in the way they saw fit. During the investigation, it was found that Under Armour used a weaker encryption algorithm than it should have to encrypt customers' sensitive information. The company is currently in a lawsuit over the breach with one MyFitnessPal user.

Wearable Devices and Privacy Concerns

Wearable devices have evolved over the years and shown significant increase in popularity. With the advances in sensor technologies, data collection capabilities, and data analytics, wearable devices now enable interaction among users, devices, and their environment seamlessly. Multifunctional nature of this technology enables users to track their daily physical activities, engage with other users through social networking capabilities, and log their lifestyle habits. In this chapter, the authors discuss the types of sensor technologies embedded in wearable devices and how the data collected through such devices can be further interpreted by data analytics. In parallel with abundance of personal data that can be collected via wearable devices, they also discuss issues related to data privacy, suggestions for users, developers, and policymakers regarding how to protect data privacy are also discussed.