Open AccessInvolving Crowdworkers with Lived Experience in Content-Development for Push-Based Digital Mental Health Tools: Lessons Learned from Crowdsourcing Mental Health Messages
Author(s) -
Rachel Kornfield,
David C. Mohr,
Rachel M. Ranney,
Emily G. Lattie,
Jonah Meyerhoff,
Joseph Jay Williams,
Madhu Reddy
Publication year - 2022
Publication title -
proceedings of the acm on human-computer interaction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.379
H-Index - 27
ISSN - 2573-0142
DOI - 10.1145/3512946
Subject(s) - crowdsourcing , personalization , mental health , digital content , adaptation (eye) , content (measure theory) , computer science , world wide web , content analysis , internet privacy , psychology , knowledge management , sociology , psychiatry , mathematical analysis , social science , mathematics , neuroscience
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.