In an Experience Sampling Method (ESM) based emotion self-report collection study, engaging participants for a long period is challenging due to the repetitiveness of answering self-report probes. This often impacts the self-report collection as participants dropout in between or respond with arbitrary responses. Self-reflection (or commonly known as analyzing past activities to operate more efficiently in the future) has been effectively used to engage participants in logging physical, behavioral, or psychological data for Quantified Self (QS) studies. This motivates us to apply self-reflection to improve the emotion self-report collection procedure. We design, develop, and deploy a self-reflection interface and augment it with a smartphone keyboard-based emotion self-report collection application. The interface provides feedback to the users regarding the relation between typing behavior and self-reported emotions. We validate the proposed approach using a between-subject study, where one group (control group) is not exposed to the self-reflection interface and the other group (study group) is exposed to it. Our initial results demonstrate that using self-reflection it is possible to engage the participants in the long-term and collect more self-reports.

dx.doi.org/10.1145/3334480.3383019
SIGCHI Conference on Human Factors in Computing Systems
Distributed and Interactive Systems

Ghosh, S, Mitra, B, & De, P. (2020). Towards Improving Emotion Self-report Collection using Self-reflection. In CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–8). doi:10.1145/3334480.3383019