Quantifying the Changeable Self: The Role of Self-Tracking in Coming to Terms With and Managing Bipolar Disorder

Abstract

There has been a recent increase in the development of digital self-tracking tools for managing mental illness. Most of these tools originate from clinical practice and are, as a result, largely clinician oriented. As a consequence, little is known about the self-tracking practices and needs of individuals living with mental illness. This understanding is important to guide the design of future tools to enable people to play a greater role in managing their health. In this article, we present a qualitative study focusing on the self-tracking practices of 10 people with bipolar disorder. We seek to understand the role self-tracking has played as they have come to grips with their diagnosis and attempted to self-manage their health. A central motivation for these participants is to identify risky patterns that may be harbingers of mood episodes, as well as positive trends that support recovery. What emerges is a fragmented picture of self-tracking, with no clear delineation between clinician-initiated and self-initiated practices, as well as considerable challenges participants face in making observations of themselves when their sense of self and emotional state is in flux, uncertain, and unreliable. Informed by these observations, we discuss the merits of a new form of self-tracking that combines manual and automated methods, addresses both clinician and individual needs, helps engage people with bipolar disorder in treatment, and seeks to overcome the significant challenges they face in self-monitoring.

View correction statement:

Erratum

Additional information

Funding

Mark Matthews’s work was supported by a Marie Curie Fellowship (Project Number: 302530). Elizabeth Murnane was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE 1144153.

Notes on contributors

Mark Matthews

Mark Matthews ([email protected], www.aplayspace.com) is a computer scientist researcher with an interest in the interplay between technology and mental health; he is jointly a Research Associate in the Department of Information Science and cofounder of HealthRhythms.

Elizabeth Murnane

Elizabeth Murnane ([email protected], http://www.cs.cornell.edu/~elm236/) is a computer scientist with an interest in developing interactive technologies that support self-management of wellness; she is a Postdoctoral Associate, having recently received her PhD from the department of Information Science at Cornell University.

Jaime Snyder

Jaime Snyder ([email protected]) is an information scientist with an interest in visualization practices; she is an Assistant Professor in the Information School at the University of Washington.