Investigating User Perceptions to Mitigate Dropout in Longitudinal Passive Sensing Studies

Abstract

This paper presents a pilot study exploring user perceptions and engagement in longitudinal passive-sensing systems to provide insights and future directions for dropout prevention research. Leveraging structural equation modeling, we analyzed behavioral intention and use behavior within a mobile sensing app, focusing on privacy and constructs from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. Privacy, hedonic motivation, and facilitating conditions were identified as significant factors influencing behavioral intention, which, in turn, directly impacted use behavior. These findings highlight the importance of trust-building, user-centered design, and support systems to mitigate dropout and advance passive sensing research.