@inproceedings{49ae27a661c34ee394f6986c01fb3d50,
title = "Participant Driven Photo Elicitation for Understanding Activity Tracking: Benefits and Limitations",
abstract = "Studying in-situ technology use over time can be difficult and this is especially so when considering technologies such as activity tracking devices explicitly designed to be unobtrusive. Yet understanding activity tracking in practice is crucial, as tracking technologies become important tools for health promotion and health insurance programs. In this paper, we describe a method for a longitudinal participant-driven photo elicitation study of activity tracking. During the five-month long study, our drop-out rates were low and we observed idiosyncratic practices with lapses and particular use patterns among participants along with significant self-reflection on activity tracking as a practice. We describe our method in detail, discussing the necessary adaptations for the study of activity tracking practices. We offer our experiences of benefits and challenges of this process, and suggest points for consideration for future studies in the area.",
keywords = "qualitative methods, methodology, self tracking, wearable computing, methodology, qualitative research, wearable computing, self tracking",
author = "Jensen, \{Nanna Gorm\} and Irina Shklovski",
year = "2017",
doi = "10.1145/2998181.2998214",
language = "English",
isbn = "978-1-4503-4335-0",
series = "Computer Supported Cooperative Work",
publisher = "Association for Computing Machinery",
pages = "1350--1361",
booktitle = "CSCW '17 Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing",
address = "United States",
}