Self-Reports in the Field Using Smartwatches: An Open-Source Firmware Solution

Selina Volsa,Bernad Batinic,Stefan Stieger

doi:10.3390/s22051980

Selina Volsa, Bernad Batinic + Show 1 more

Open Access

https://doi.org/10.3390/s22051980

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Abstract

In situ self-reports are a useful tool in the social sciences to supplement laboratory experiments. Smartwatches are a promising form factor to realize these methods. However, to date, no user-friendly, general-purpose solution has been available. This article therefore presents a newly developed, free and open-source firmware that facilitates the Experience Sampling Method and other self-report methods on a commercially-available, programmable smartwatch based on the ESP32 microcontroller. In a small-scale pilot study comparing this smartwatch and firmware to an equivalent design on smartphones, participants using the smartwatch showed increased compliance. The presented project demonstrates a useful tool for complementary tools like smartphones for self-reports.

Highlights

Compared to laboratory studies, field research offers high ecological validity, i.e., high generalizability of results in everyday life situations
A total of 245 notifications were scheduled across all participants in the smartwatch condition and 210 were scheduled across all participants in the smartphone condition
Log files showed that 240 notifications were triggered in the smartwatch condition (98.0%) and 203 notifications were triggered in the smartphone condition (96.7%; see Table 1)

Summary

Introduction

Field research offers high ecological validity, i.e., high generalizability of results in everyday life situations. This is important in sciences like psychology, sociology, and other social sciences that make claims about real-life experience and behavior. In situ self-reports are a valuable tool for the realization of field research but can be burdensome for participants. Smartwatches are a promising form factor to reduce this burden, as they are relatively unobtrusive. No easy-to-use general purpose software solution for realizing studies with these methods has been available so far. Our intent is to present such a solution

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