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DOSE: An open-source, iOS watch-based tool for experience sampling
Ian Kim1,2,3, Sahiti Kunchay4, Saeed Abdullah5
1Department of Kinesiology, Penn State University, University Park, Pennsylvania, United States of America.
None:
Smartwatches facilitate low-burden rapid-access micro-interactions, making them ideal for Experience Sampling Methods (ESMs). Despite the Apple Watch being the most popular smartwatch in the U.S., its broad use in ESM studies has been limited by a lack of accessible frameworks that enable deployment without technical expertise. We developed DOSE, an open-source ESM framework tailored for the Apple Watch. It includes tools and documentation that allow researchers to configure surveys, build custom apps, deploy studies, and stream data to servers with minimal familiarity with Xcode and iOS development workflows. We evaluated the framework's feasibility in a 28-day field study with 18 participants (mean age = 55.3 ± 9.2). Results showed reliable prompt delivery; middle-aged and older adults achieved median survey completion rates of 69% and 88% during watch wear periods, median device access times of 9 and 9.5 seconds, and median total response times of 22 and 29 seconds, respectively. Participants generally demonstrated increasing efficiency in responses over time. These findings establish the DOSE framework as a practical, feasible solution for Apple Watch-based ESMs and a foundation for future smartwatch research.

