From Options to Action: Evaluating Adoption of Privacy Features in Fitness - Tracking Platforms

Fitness-tracking platforms, such as Strava and Garmin Connect, are increasingly popular and are reshaping how people monitor and share their physical activity. Given the sensitive nature of the data users share, these platforms implement a series of privacy features, including controls for profile visibility, activity sharing, and the specification of sensitive locations. In this paper, we present the first large-scale study aiming to quantify user adoption of privacy features on fitness-tracking platforms and to shed light on the reasoning behind identified trends. We apply a mixed-method. First, we provide a systematic categorization of the privacy features implemented across major fitness-tracking platforms. We then quantify their adoption, using the Strava and Garmin Connect platforms as our case studies, by analyzing 197,873 public activity records, revealing a gap between available controls and actual adoption. We complement our empirical evaluation by surveying 182 participants, confirming low adoption and identifying barriers. Our findings highlight limited use of privacy features and provide insights into the reasons for this trend, including a lack of awareness, perceived low necessity, concerns about functionality, and difficulties adjusting settings. We also discuss potential strategies to overcome these challenges.