Involving Crowdworkers with Lived Experience in Content-Development for Push-Based Digital Mental Health Tools: Lessons Learned from Crowdsourcing Mental Health Messages

Rachel Kornfield, David C. Mohr, Rachel Ranney, Emily G. Lattie, Jonah Meyerhoff, Joseph J. Williams, Madhusudhana C Reddy

Research output: Contribution to journalArticlepeer-review

Abstract

Digital tools can support individuals managing mental health concerns, but delivering sufficiently engaging content is challenging. This paper seeks to clarify how individuals with mental health concerns can contribute content to improve push-based mental health messaging tools. We recruited crowdworkers with mental health symptoms to evaluate and revise expert-composed content for an automated messaging tool, and to generate new topics and messages. A second wave of crowdworkers evaluated expert and crowdsourced content. Crowdworkers generated topics for messages that had not been prioritized by experts, including self-care, positive thinking, inspiration, relaxation, and reassurance. Peer evaluators rated messages written by experts and peers similarly. Our findings also suggest the importance of personalization, particularly when content adaptation occurs over time as users interact with example messages. These findings demonstrate the potential of crowdsourcing for generating diverse and engaging content for push-based tools, and suggest the need to support users in meaningful content customization.

Original languageEnglish (US)
Article number99
JournalProceedings of the ACM on Human-Computer Interaction
Volume6
Issue numberCSCW1
DOIs
StatePublished - Apr 7 2022

Keywords

  • crowdsourcing
  • digital health interventions
  • mental health
  • mixed-methods research
  • peer-to-peer support
  • personalization

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Human-Computer Interaction
  • Computer Networks and Communications

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