Evaluating the Potential of Data-Driven Surveys for Fitness-Tracking Research

Online surveys are used extensively in fitness-tracking research. One common limitation is that researchers cannot assess the veracity of participants' self-reported physical activity data. One promising response to this limitation is using data-driven surveys that integrate participants' online account data (e.g., Fitbit). In this paper, we evaluate using data-driven surveys for fitness-tracking research by examining how participants perceive them, how participants' self-reported data compares to their Fitbit data, and what monetary incentives could motivate participation. To this end, we integrated the participants' Fitbit data in a survey and conducted a three-group study with N = 300 participants. We discuss the two main findings: First, although participants were receptive to data-driven surveys, the groups that had to share their data had lower completion rates. Second, there was a large discrepancy between the self-reported data and the data in the participants' Fitbit accounts (e.g., only 38% self-reported a consistent typical weekly exercise-time). We provide suggestions for researchers who conduct online surveys, including data-driven ones, that collect online-account data.

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Publication Details

Journal
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Published
2025-12-02
DOI
https://doi.org/10.1145/3770665
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluating the Potential of Data-Driven Surveys for Fitness-Tracking Research

Lev Velykoivanenko, Kavous Salehzadeh Niksirat, Kévin Huguenin, Amro Abdrabo
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Innovative Human-Technology Interaction
article

Evaluating the Potential of Data-Driven Surveys for Fitness-Tracking Research

Lev Velykoivanenko, Kavous Salehzadeh Niksirat, Kévin Huguenin, Amro Abdrabo
article en

Abstract

Online surveys are used extensively in fitness-tracking research. One common limitation is that researchers cannot assess the veracity of participants' self-reported physical activity data. One promising response to this limitation is using data-driven surveys that integrate participants' online account data (e.g., Fitbit). In this paper, we evaluate using data-driven surveys for fitness-tracking research by examining how participants perceive them, how participants' self-reported data compares to their Fitbit data, and what monetary incentives could motivate participation. To this end, we integrated the participants' Fitbit data in a survey and conducted a three-group study with N = 300 participants. We discuss the two main findings: First, although participants were receptive to data-driven surveys, the groups that had to share their data had lower completion rates. Second, there was a large discrepancy between the self-reported data and the data in the participants' Fitbit accounts (e.g., only 38% self-reported a consistent typical weekly exercise-time). We provide suggestions for researchers who conduct online surveys, including data-driven ones, that collect online-account data.

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesVol. 9(4)
Max Planck Institute for Security and Privacy (DE), University of Lausanne (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 60%
Innovative Human-Technology Interaction
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