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Journal Article

Citation

Smith CE, Lane W, Miller Hillberg H, Kluver D, Terveen L, Yarosh S. Proc. ACM Hum. Comput. Interact. 2021; 5(CSCW2).

Copyright

(Copyright © 2021, Association for Computing Machinery)

DOI

10.1145/3479561

PMID

unavailable

Abstract

Online technologies offer great promise to expand models of delivery for therapeutic interventions to help users cope with increasingly common mental illnesses like anxiety and depression. For example, "cognitive reappraisal"is a skill that involves changing one's perspective on negative thoughts in order to improve one's emotional state. In this work, we present Flip∗Doubt, a novel crowd-powered web application that provides users with cognitive reappraisals ("reframes") of negative thoughts. A one-month field deployment of Flip∗Doubt with 13 graduate students yielded a data set of negative thoughts paired with positive reframes, as well as rich interview data about how participants interacted with the system. Through this deployment, our work contributes: (1) an in-depth qualitative understanding of how participants used a crowd-powered cognitive reappraisal system in the wild; and (2) detailed codebooks that capture informative context about negative input thoughts and reframes. Our results surface data-derived hypotheses that may help to explain what types of reframes are helpful for users, while also providing guidance to future researchers and developers interested in building collaborative systems for mental health. In our discussion, we outline implications for systems research to leverage peer training and support, as well as opportunities to integrate AI/ML-based algorithms to support the cognitive reappraisal task. (Note: This paper includes potentially triggering mentions of mental health issues and suicide.) © 2021 ACM.


Language: en

Keywords

Students; mental health; Mental health; social support; Social support; Peer support; Diseases; Online systems; Cognitive systems; peer support; WEB application; cognitive reappraisal; amazon mechanical turk; Amazon's mechanical turks; Cognitive reappraisal; crowdsourcing; Crowdsourcing; Field deployment; human-centered machine learning; Human-centered machine learning; online health communities; Online health communities; Web applications

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