μEMA: Microinteraction-based Ecological Momentary Assessment (EMA) Using a Smartwatch

Abstract

Ecological Momentary Assessment (EMA) is a method of in situ data collection for assessment of behaviors, states, and contexts. Questions are prompted during everyday life using an individual’s mobile device, thereby reducing recall bias and increasing validity over other self-report methods such as retrospective recall. We describe a microinteraction-based EMA method (“micro” EMA, or μEMA) using smartwatches, where all EMA questions can be answered with a quick glance and a tap – nearly as quickly as checking the time on a watch. A between-subjects, 4-week pilot study was conducted where μEMA on a smartwatch (n=19) was compared with EMA on a phone (n=14). Despite an ≈8 times increase in the number of interruptions, μEMA had a significantly higher compliance rate, completion rate, and first prompt response rate, and μEMA was perceived as less distracting. The temporal density of data collection possible with μEMA could prove useful in ubiquitous computing studies.

Ramesh Kumar Sah

Research Assistant

I am a Computer Science PhD student in the Embedded Machine Intelligence Laboratory (EMIL) at Washington State University, Pullman.