Assessing the Influence of Physical Activity Upon the Experience Sampling Response Rate on Wrist-Worn Devices

Alireza Khanshan, Pieter Van Gorp, Raoul Nuijten and Panos Markopoulos
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Alireza Khanshan: Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
Pieter Van Gorp: Department of Industrial Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
Raoul Nuijten: Department of Industrial Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
Panos Markopoulos: Department of Industrial Design, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands

IJERPH, 2021, vol. 18, issue 20, 1-13

Abstract: The Experience Sampling Method (ESM) is gaining ground for collecting self-reported data from human participants during daily routines. An important methodological challenge is to sustain sufficient response rates, especially when studies last longer than a few days. An obvious strategy is to deliver the experiential questions on a device that study participants can access easily at different times and contexts (e.g., a smartwatch). However, responses may still be hampered if the prompts are delivered at an inconvenient moment. Advances in context sensing create new opportunities for improving the timing of ESM prompts. Specifically, we explore how physiological sensing on commodity-level smartwatches can be utilized in triggering ESM prompts. We have created Experiencer, a novel ESM smartwatch platform that allows studying different prompting strategies. We ran a controlled experiment ( N = 71 ) on Experiencer to study the strengths and weaknesses of two sampling regimes. One group ( N = 34 ) received incoming notifications while resting (e.g., sedentary), and another group ( N = 37 ) received similar notifications while being active (e.g., running). We hypothesized that response rates would be higher when experiential questions are delivered during lower levels of physical activity. Contrary to our hypothesis, the response rates were found significantly higher in the active group, which demonstrates the relevance of studying dynamic forms of experience sampling that leverage better context-sensitive sampling regimes. Future research will seek to identify more refined strategies for context-sensitive ESM using smartwatches and further develop mechanisms that will enable researchers to easily adapt their prompting strategy to different contextual factors.

Keywords: experience sampling method; ecological momentary assessment; context sensing; response rate; compliance; personalization; smartwatch application; wearables; physical activity (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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