"I Just Can't Help But Smile Sometimes": Collaborative Self-Management of Depression

Eleanor R. Burgess, Madhu C. Reddy, David C. Mohr

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Depression is a challenging condition that requires individuals to manage their moods and emotions over time. Within CSCW, there has been an interest in understanding how individuals seek and share support on social media and in online communities. However, less attention has been paid to how collaboration as an aspect of self-management of depression unfolds in people's daily lives. In this paper, we explore the collaborative self-management work of 28 individuals managing depression who live in the United States. Data collection included remote semi-structured interviews with an associated cognitive mapping exercise. Our findings describe who participants turn to for day-to-day collaborative support, how collaborative activities are enacted (across both mood-focused and preventative support practices), and where these often technology-mediated interactions occur across text, phone, video, and picture-based channels. We discuss collaborative self-management in the depression support context, including key characteristics: agency, reciprocity, time, and interaction. We also present a four-step model of how the process occurs over time (awareness, planning, interaction, and reflection). We conclude by discussing how technology ecosystems support individuals' collaborative self-management.

Original languageEnglish (US)
Article number70
JournalProceedings of the ACM on Human-Computer Interaction
Issue numberCSCW1
StatePublished - Apr 7 2022


  • collaborative self-management
  • communication channels
  • depression
  • mental health
  • polymedia
  • roles
  • social network
  • social support
  • technology ecosystems

ASJC Scopus subject areas

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


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