Document Type
Article
Language
eng
Publication Date
10-2017
Publisher
Elsevier
Source Publication
Computers in Human Behavior
Source ISSN
0747-5632
Abstract
Human behavior is increasingly reflected or acted out through technology. This is of particular salience when it comes to changes in behavior associated with serious mental illnesses including schizophrenia and bipolar disorder. Early detection is crucial for these conditions but presently very challenging to achieve. Potentially, characteristics of these conditions' traits and symptoms, at both idiosyncratic and collective levels, may be detectable through technology use patterns. In bipolar disorder specifically, initial evidence associates changes in mood with changes in technology-mediated communication patterns. However much less is known about how people with bipolar disorder use technology more generally in their lives, how they view their technology use in relation to their illness, and, perhaps most crucially, the causal relationship (if any exists) between their technology use and their disease. To address these uncertainties, we conducted a survey of people with bipolar disorder (N = 84). Our results indicate that technology use varies markedly with changes in mood and that technology use broadly may have potential as an early warning signal of mood episodes. We also find that technology for many of these participants is a double-edged sword: acting as both a culprit that can trigger or exacerbate symptoms as well as a support mechanism for recovery. These findings have implications for the design of both early warning systems and technology-mediated interventions.
Recommended Citation
Matthews, Mark; Murnane, Elizabeth; Snyder, Jaime; Guha, Shion; Chang, Pamara; Doherty, Gavin; and Gay, Geri K., "The Double-edged Sword: A Mixed Methods Study of the Interplay between Bipolar Disorder and Technology Use" (2017). Mathematics, Statistics and Computer Science Faculty Research and Publications. 561.
https://epublications.marquette.edu/mscs_fac/561
Comments
Accepted version. Computers in Human Behavior, Vol. 75 (October 2017): 288-300. DOI. © 2017 Elsevier B.V. Used with permission.