Collaborative Self-Management of Depression

Burgess, Eleanor R.

doi:https://doi.org/10.21985/n2-9cwm-4b22

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Collaborative Self-Management of Depression

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Depression is a challenging mental illness that requires individuals to manage their moods and emotions over time. While past mental health literature describes how individuals seek and share support on social media and within online communities, the ways that offline and one-on-one supportive interactions unfold is less clear. To address this literature gap, in this dissertation, I explore the collaborative self-management work of individuals managing depression across two studies using semi-structured interviews and visual elicitation techniques. I focus on how these interactions are mediated by technologies across individuals’ technology ecosystems. In Chapter 1 (Introduction), I present the three research questions guiding this dissertation. In Chapter 2 (Related Work), I provide an overview of relevant literature on self-management, collaborative self-management, sociality, and social support. In Chapter 3 (Methodology), I discuss my methodological approach to the studies in this dissertation, utilizing interview and visual elicitation procedures as well as Braun and Clarke’s thematic analysis process [30]. In Chapter 4 (Preliminary Study), I present an analysis of my preliminary interview and visual elicitation study (n=30), showing the key importance of sociality for self-management of depression. I describe how individuals connect with specific others to achieve expected support and how these interactions are mediated through locations and communication channels. I discuss how factors including roles, culture, and locations influence participant collaboration. Next, in Chapter 5 (Main Study), I share my remote interview and cognitive mapping elicitation study (n=28). Through this main study I present a deeper understanding of the collaborative self-management practices of individuals managing depression. I describe who participants turn to for day-to-day collaborative support, how collaborative self-management activities occur (across both ‘mood-focused’ and ‘preventative’ practices), and where these often technology-mediated interactions take place. I discuss the technology ecosystems utilized in collaborative self-management, highlighting factors influencing channel selection and periods of engagement with support technologies. In Chapter 6 (Discussion: Collaborative Self-Management), I extend the concept of collaborative self-management from the chronic disease domain to mental health. In doing so, I discuss key characteristics — agency, reciprocity, time, and interaction, present a four-step model of collaborative self-management, and discus implications of the COVID-19 pandemic on participant collaborative interactions. In Chapter 7 (Discussion: Implications for Design) I share approaches to future design from an assets-based perspective, describe key technology features that enable collaborative self-management, and consider future technology solutions. Chapter 8 (Limitations) discusses the limitations of the dissertation studies. Finally, Chapter 9 (Conclusion) reiterates the contributions of my research. The findings from this dissertation make several novel contributions. First, I extend the concept of collaborative self-management from the chronic disease clinical literature to the mental health domain in Human-Computer Interaction. In doing so, I provide deeper conceptual understanding about the characteristics, processes, and roles involved in this critical work from the perspectives of individuals managing depression. Second, I contribute a detailed understanding of the breadth of everyday technology tools and services used to support collaborative self-management. I describe beneficial features, contexts of use, and challenges. Finally, looking across current support technologies and practices, I contribute an understanding of opportunities for designing technology improvements and future collaborative interactions that are sensitive to the needs of individuals managing depression.

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