Depression imposes a very high societal burden in terms of cost, morbidity, suffering, and mortality. It is the leading cause of disability in the Unted States and the fourth leading cause worldwide. Current methods of treatment are insufficient to combat such a widespread health problem. Therefore, addressing this mental health epidemic requires significant changes in intervention strategies. A growing body of research is examining the use of behavioral intervention technologies (BITs), such as mobile phones to deliver behavioral and mental health interventions. The delivery of interventions via mobile phones offers the potential to provide a near continuous connection between a care system and the patient. However, currently available mobile applications (apps) for depression lack evidence regarding their efficacy. App stores currently offer apps for depression that are designed based on cognitive therapy (CT) interventions, some with behavioral activation (BA), some with mood monitoring only, and many with no discernable psychological approach. Even when based on psychological theory, there is no evidence that the translation of these theories, developed for face- to-face treatment, work the same way for people with depression when delivered through an app. Given the quickly evolving nature of mobile apps, conducting research on every available app will never be possible, nor very useful. The proposed research plan takes an innovative approach to investigating BITs for depression by incorporating principles from psychology, engineering, and design to examine two primary psychological principles, CT and BA, delivered by mobile apps. The project will include two stages. First, the most usable elements of existing apps will be identified to create two apps, one using CT and the other BA, targeting depressive symptoms. This usability process will use a clear, model-driven approach to identify the most usable and useful characteristics for three app elements: information delivery, tools, and visual feedback. Following usability testing and improvements, the two apps will be subjected to a small comparative trial. Secondary aims will include an examination of usage of the apps, defined as how many times the apps are opened on the mobile devices. Results will provide information that can be broadly used by developers of apps for depression and may also have implications for apps aimed at treating other mental health disorders.
Twelve-month prevalence rates indicate that 21-30 million Americans will require treatment for depression each year, needs that will never be able to be met with standard one-on-one intensive treatments. The proposed research takes an innovative approach to extending care capacity and informing design of future interventions though usability testing on existing mobile application (app) features and evaluating the comparative outcomes of two treatments for depression delivered via mobile apps. Knowledge gained from this project has immense potential to extend care capacity to millions of individuals with empirically supported treatment.