Widespread Third-Party Tracking On Hospital Websites Poses Privacy Risks For Patients And Legal Liability For Hospitals.

Computer code that transfers data to third parties (third-party tracking) is common across the web and is subject to few federal privacy regulations. We determined the presence of potentially privacy-compromising data transfers to third parties on a census of US nonfederal acute care hospital websites, and we used descriptive statistics and regression analyses to determine the hospital characteristics associated with a greater number of third-party data transfers. We found that third-party tracking is present on 98.6 percent of hospital websites, including transfers to large technology companies, social media companies, advertising firms, and data brokers. Hospitals in health systems, hospitals with a medical school affiliation, and hospitals serving more urban patient populations all exposed visitors to higher levels of tracking in adjusted analyses. By including third-party tracking code on their websites, hospitals are facilitating the profiling of their patients by third parties. These practices can lead to dignitary harms, which occur when third parties gain access to sensitive health information that a person would not wish to share. These practices may also lead to increased health-related advertising that targets patients, as well as to legal liability for hospitals.

Prevalence of Third-Party Tracking on Abortion Clinic Web Pages.

This cross-sectional study assesses how often third-party domains use tracking data from visitors to abortion clinic web pages.

What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention.

Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates have become a major issue that prevents these apps from achieving their full potential. In this paper, we present a national-scale survey experiment ( N = 1963 ) in the U.S. to investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions. We found that individual differences such as prosocialness, COVID-19 risk perceptions, general privacy concerns, technology readiness, and demographic factors played a more important role than app design choices such as decentralized design vs. centralized design, location use, app providers, and the presentation of security risks. Certain app designs could exacerbate the different preferences in different sub-populations which may lead to an inequality of acceptance to certain app design choices (e.g., developed by state health authorities vs. a large tech company) among different groups of people (e.g., people living in rural areas vs. people living in urban areas). Our mediation analysis showed that one's perception of the public health benefits offered by the app and the adoption willingness of other people had a larger effect in explaining the observed effects of app design choices and individual differences than one's perception of the app's security and privacy risks. With these findings, we discuss practical implications on the design, marketing, and deployment of COVID-19 contact-tracing apps in the U.S.