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Massachusetts Institute of Technology

Crowdsourcing mental health and emotional well-being

Abstract

dc:description.abstract

More than 30 million adults in the United States suffer from depression. Many more meet the diagnostic criteria for an anxiety disorder. Psychotherapies like cognitive-behavioral therapy can be effective for conditions such as anxiety and depression, but the demand for these treatments exceeds the resources available. To reach the widest possible audience, mental health interventions need to be inexpensive, anonymous, always available, and, ideally, delivered in a way that delights and engages the user. Towards this end, I present Panoply, an online intervention that administers emotion- regulatory support anytime, anywhere. In lieu of direct clinician oversight, Panoply coordinates support from crowd workers and unpaid volunteers, all of whom are trained on demand, as needed. Panoply incorporates recent advances in crowdsourcing and human computation to ensure that feedback is timely and vetted for quality. The therapeutic approach behind this system is inspired by research from the fields of emotion regulation, cognitive neuroscience, and clinical psychology, and hinges primarily on the concept of cognitive reappraisal. Crowds are recruited to help users think more flexibly and objectively about stressful events. A three-week randomized controlled trial with 166 participants compared Panoply to an active control task (online expressive writing). Panoply conferred greater or equal benefits for nearly every therapeutic outcome measure. Statistically significant differences between the treatment and control groups were strongest when baseline depression and reappraisal scores were factored into the analyses. Panoply also significantly outperformed the control task on all measures of engagement (with large effect sizes observed for both behavioral and self-report measures). This dissertation offers a novel approach to computer-based psychotherapy, one that is optimized for accessibility, engagement and therapeutic efficacy.

Degree

thesis:*
Department dc:contributor.department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Morris, Robert (Robert Randall)
Advisor dc:contributor.advisor
  • Rosalind W. Picard.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/97972
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/97972

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Morris, Robert (Robert Randall). Crowdsourcing mental health and emotional well-being. Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/97972