The Experience Sampling Method on Mobile Devices

Abstract

The Experience Sampling Method (ESM) is used by scientists from various disciplines to gather insights into the intra-psychic elements of human life. Researchers have used the ESM in a wide variety of studies, with the method seeing increased popularity. Mobile technologies have enabled new possibilities for the use of the ESM, while simultaneously leading to new conceptual, methodological, and technological challenges. In this survey, we provide an overview of the history of the ESM, usage of this methodology in the computer science discipline, as well as its evolution over time. Next, we identify and discuss important considerations for ESM studies on mobile devices, and analyse the particular methodological parameters scientists should consider in their study design. We reflect on the existing tools that support the ESM methodology and discuss the future development of such tools. Finally, we discuss the effect of future technological developments on the use of the ESM and identify areas requiring further investigation.

Supporting Real‐Time Contextual Inquiry through Sensor Data

“…Of particular importance to our work is contingent experience sampling, which furthers the methodological exploration of contextually capturing grounded experiences through the collection of thick data alongside sensor data and standardised survey responses (Berkel, Ferreira, and Kostakos 2017;Evans 2016;Smets and Lievens 2018;Zhang, Zhao, and Ventrella 2018). Here the sampling is initiated algorithmically based on a variety of factors, including completion events, change in sensor readings, events on the device, and events external to the device (Berkel, Ferreira, and Kostakos 2017). While these methods offer compelling new ways to gather ethnographic and design insights, they often take ethnographers out of the real-time research.…”

Engagement with Mental Health Screening on Mobile Devices

“…Recent HCI research has drawn attention to the challenges of long-term engagement [56,71,77], and some have expressed doubt with respect to the possibility of gathering self-reported data in daily life for periods longer than "2-4 weeks, " after which "the quality of ESM responses is known to deteriorate" [87]. A recent review of experience sampling studies within Computer Science reported a median study length of 14 days and a median population group of 19 participants [11]. Although pregnancy entails a highly diverse patient group and demands a longitudinal perspective, little research has examined the feasibility of self-report technologies in the perinatal context.…”

EmoKey: An Emotion-aware Smartphone Keyboard for Mental Health Monitoring

“…Self-reportCollector collects the emotion self-report from the user at the end of every session. It collects the emotion self-reports based on Experience Sampling Method (ESM), the most common approach for collecting self-reports in behavioral studies [11], [12]. It probes the user as soon as the user completes typing in a session and changes the application.…”