More Like this

1. Americans’ willingness to adopt a COVID-19 tracking app

   https://doi.org/10.5210/fm.v25i11.11095  

   Hargittai, Eszter; Redmiles, Elissa M.; Vitak, Jessica; Zimmer, Michael (October 2020, First Monday)

   null (Ed.)

   The COVID-19 global pandemic led governments, health agencies, and technology companies to work on solutions to minimize the spread of the disease. One such solution concerns contact-tracing apps whose utility is tied to widespread adoption. Using survey data collected a few weeks into lockdown measures in the United States, we explore Americans’ willingness to install a COVID-19 tracking app. Specifically, we evaluate how the distributor of such an app (e.g., government, health-protection agency, technology company) affects people’s willingness to adopt the tool. While we find that 67 percent of respondents are willing to install an app from at least one of the eight providers included, the factors that predict one’s willingness to adopt differ. Using Nissenbaum’s theory of privacy as contextual integrity, we explore differences in responses across distributors and discuss why some distributors may be viewed as less appropriate than others in the context of providing health-related apps during a global pandemic. We conclude the paper by providing policy recommendations for wide-scale data collection that minimizes the likelihood that such tools violate the norms of appropriate information flows. 

   more » « less
2. Digital exposure tools: Design for privacy, efficacy, and equity

   https://doi.org/10.1126/science.abi9852  

   Landau, Susan (September 2021, Science)

   Use of smartphone-based digital contact- tracing apps has shown promise in responding to the COVID-19 pandemic. But such apps can reveal very personal information; thus, their use raises important societal questions, not just during the current pandemic but as we learn and prepare for other inevitable outbreaks ahead. Can privacy-protective versions of such apps work? Are they efficacious? Because the apps influence who is notified of exposure and who gets tested—and possibly treated—we need to consider the apps in the context of health care equity. Exposure-notification apps are predicated on the assumption that if someone is informed of exposure, they will follow instructions to isolate. Such an expectation fails to take into account that isolation—and sometimes even seeking care when ill—is much harder for some populations than others. If apps are to work for all, and not make this worse for disadvantaged populations, there needs to be basic social infrastructure that supports testing, contact tracing, and isolation. 

   more » « less
3. A Study of Users' Privacy Preferences for Data Sharing on Symptoms-Tracking/Health App

   https://doi.org/10.1145/3559613.3563202  

   Asif, Hafiz; Vaidya, Jaideep (November 2022, Proceedings of the 21st Workshop on Privacy in the Electronic Society)

   Symptoms-tracking applications allow crowdsensing of health and location related data from individuals to track the spread and outbreaks of infectious diseases. During the COVID-19 pandemic, for the first time in history, these apps were widely adopted across the world to combat the pandemic. However, due to the sensitive nature of the data collected by these apps, serious privacy concerns were raised and apps were critiqued for their insufficient privacy safeguards. The Covid Nearby project was launched to develop a privacy-focused symptoms-tracking app and to understand the privacy preferences of users in health emergencies. In this work, we draw on the insights from the Covid Nearby users' data, and present an analysis of the significantly varying trends in users' privacy preferences with respect to demographics, attitude towards information sharing, and health concerns, e.g. after being possibly exposed to COVID-19. These results and insights can inform health informatics researchers and policy designers in developing more socially acceptable health apps in the future. 

   more » « less
4. Predicting smartphone location-sharing decisions through self-reflection on past privacy behavior

   https://doi.org/10.1093/cybsec/tyaa014  

   Wisniewski, Pamela; Safi, Muhammad Irtaza; Patil, Sameer; Page, Xinru (January 2020, Journal of Cybersecurity)

   null (Ed.)

   Abstract Smartphone location sharing is a particularly sensitive type of information disclosure that has implications for users’ digital privacy and security as well as their physical safety. To understand and predict location disclosure behavior, we developed an Android app that scraped metadata from users’ phones, asked them to grant the location-sharing permission to the app, and administered a survey. We compared the effectiveness of using self-report measures commonly used in the social sciences, behavioral data collected from users’ mobile phones, and a new type of measure that we developed, representing a hybrid of self-report and behavioral data to contextualize users’ attitudes toward their past location-sharing behaviors. This new type of measure is based on a reflective learning paradigm where individuals reflect on past behavior to inform future behavior. Based on data from 380 Android smartphone users, we found that the best predictors of whether participants granted the location-sharing permission to our app were: behavioral intention to share information with apps, the “FYI” communication style, and one of our new hybrid measures asking users whether they were comfortable sharing location with apps currently installed on their smartphones. Our novel, hybrid construct of self-reflection on past behavior significantly improves predictive power and shows the importance of combining social science and computational science approaches for improving the prediction of users’ privacy behaviors. Further, when assessing the construct validity of the Behavioral Intention construct drawn from previous location-sharing research, our data showed a clear distinction between two different types of Behavioral Intention: self-reported intention to use mobile apps versus the intention to share information with these apps. This finding suggests that users desire the ability to use mobile apps without being required to share sensitive information, such as their location. These results have important implications for cybersecurity research and system design to meet users’ location-sharing privacy needs. 

   more » « less
5. Health-related Misinformation Harm during the COVID- 19 Pandemic: An Investigation of Non-comparative and Comparative Harm Perceptions

   Tran, Thi; Valecha, Rohit; Rao, Raghav (February 2022, AIS Transactions on Human-Computer Interaction)

   Nah, Fiona (Ed.)

   Misinformation about the coronavirus disease of 2019 (COVID-19) health crisis has been widespread on social media and caused various types of harms in society. While some researchers have investigated the way in which people perceive misinformation harm in crises, little research has systematically examined harms from health-related misinformation. In order to address this gap, we focus on non-comparative and comparative harm perceptions of the affected community in the COVID-19 pandemic context. We examine non-comparative harms (which component harms and contextual harms reflect) and comparative harms (which counter-contextual harms reflect) in order to understand harm perceptions. We also investigate how harm perception varies based on COVID-19 victimization experience. We used a professional survey company named Cint to collect data using a scenario-based survey with 343 participants. We extract various findings such as how contextual features shape perceived harms and reveal the scenarios in which COVID-19 victims perceive higher contextual harms but lower counter-contextual harms. We also examine how corrective actions of social media shape harm perceptions. 

   more » « less