Opportunities for collaborative clinical work: Predicting relapse onset in bipolar disorder from online behavior

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Bipolar disorder (BD) can negatively impact the lives of individuals. Symptoms of BD can manifest not only in their offline behaviors, but online as well. Being able to identify manic and depressive mood episodes early on can lead to more effective interventions. In this work, we focus on understanding the feasibility and acceptance of an early warning system for patients with BD that leverages online behavioral data to infer mood episode onset. For this, we interview three participants with BD to probe how they envision this type of intervention system and might use it to manage BD. Our goal is to uncover the opportunities and constraints of the future of work in BD healthcare that connects intelligent tools and objective data to provide an effective partnership between patients, caregivers, and clinicians. Toward this goal, in this paper, we focused on understanding concerns and gathering design ideas from patients with BD. We present this study as a case for a new type of work, incorporating clinical perspectives from start to finish-both as collaborators and active participants - -to enhance clinical work experiences and provide better care.

Original languageEnglish (US)
Title of host publicationProceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2020
PublisherAssociation for Computing Machinery
Pages234-238
Number of pages5
ISBN (Electronic)9781450375320
DOIs
StatePublished - May 18 2020
Event14th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2020 - Virtual, Online, United States
Duration: Oct 6 2020Oct 8 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference14th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2020
CountryUnited States
CityVirtual, Online
Period10/6/2010/8/20

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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