Supporting Anxiety Patients' Self-Reflection through Visualization of Physiological Data

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Anxiety patients are often constrained in daily life to an extent where they experience severe difficulties in keeping a job or being with family, hereby leading to a decreased quality of life. Self-reflecting on emotional reactions during daily life activities is a critical part of anxiety treatment, and can lead to increased self-awareness and eventually behavior change to cope with the disorders. mHealth technologies have emerged as a means to improve effectiveness of treatment for mental disorders, yet few studies have utilized real-time data from physiological sensors to support self-reflection on emotions. We conducted a study with two anxiety patients and their psychiatrists to explore their experiences of using GSR sensor data as visual cues to support daily self-reflection on anxiety episodes. We contribute with findings indicating that GSR visualization as part of anxiety treatment can support patients in confirming episodes. Furthermore, we present design considerations for such visualizations.

Original languageEnglish
Title of host publication32nd Australian conference on Human-Computer Interaction
PublisherAssociation for Computing Machinery
Publication date10 Dec 2020
Pages742–747
ISBN (Print)9781450389754
DOIs
Publication statusPublished - 10 Dec 2020
EventOzCHI '20: 32nd Australian Conference on Human-Computer Interaction - Sydney, Australia
Duration: 1 Dec 20201 Dec 2020

Conference

ConferenceOzCHI '20: 32nd Australian Conference on Human-Computer Interaction
Country/TerritoryAustralia
CitySydney
Period01/12/202001/12/2020

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