Electronic Communication Augmented Mental Health Care

Summary

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Description

Mood and anxiety disorders are among the most common mental health disorder in the United States, and these disorders are associated with significant morbidity, mortality and overall impairment in functioning. These disorders often have an onset in adolescence, and suicide is now the second leading ...

Mood and anxiety disorders are among the most common mental health disorder in the United States, and these disorders are associated with significant morbidity, mortality and overall impairment in functioning. These disorders often have an onset in adolescence, and suicide is now the second leading cause of death among 15-29 year-olds. Furthermore, adolescent mood and anxiety disorders are increasing, with lifetime prevalence of major depressive disorder for adolescents now estimated at 11%. For adolescents and young adults, untreated mood and anxiety disorders can impede normal development and attainment of important milestones (i.e., high school or college graduation, transition to employment), in addition to greatly increasing the risk of suicide. While there are evidence-based treatments for these disorders, 40% of depressed adolescent patients, for example, do not have a substantial response to initial treatment and only a third experience remission of symptoms. Consequently, there is an urgent need to improve upon current treatments and develop novel approaches to care of depression, as well as other mood and anxiety disorders, in adolescents, young adults, and adults in general. Electronic communication is ubiquitous. Given this, it has been hypothesized that monitoring electronic communication, including social media, activity in partnership with patients as part of routine clinical care has the potential to prevent negative outcomes of mood and anxiety disorders and greatly improve care of these conditions. At the individual level, electronic communication activity can reflect the underlying course of these disorders and reveal associated risks for worsening course and negative outcomes such as suicide. Automated technologies (e.g., natural language processing systems) may assist therapists in assessing these conditions and risks, by identifying aspects of language use or other key behavior patterns, such as number of friends or time of electronic communication activity, that correlate with an individual's mental health status. At the population level, analysis of aggregated electronic communications data can illuminate important mental health trends across a range of disorders (e.g., depression, bipolar disorder, anxiety, eating disorders). In this pilot study, the investigators propose to develop and evaluate a dashboard for mental health therapists in alliance with patients to augment the care of patients with mood/anxiety disorders and to improve clinical outcomes. Of note, changes to primary, secondary, and other pre-specified outcomes were made prior to intervention implementation.

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