Electronic Communication Augmented Mental Health Care

The Use of Electronic Communications-based Automated Technologies to Augment Traditional Mental Health Care

Mood and anxiety disorders are the most common mental health conditions in the United States, and are associated with significant morbidity, mortality and overall impairment in functioning. These conditions often have an onset in adolescence and can be especially problematic during this time-period because it can impede normal development and attainment of important milestones. While there are evidence-based treatments for these disorders, these disorders often go untreated or under-treated with negative outcomes, particularly suicide in the case of mood disorders. Electronic communication via text messages and social media are ubiquitous and are often the predominant form of communication in adolescents and young adults. A growing body of research suggests that - at the individual level - electronic communication, including social media, activity can reflect the underlying course of mood and anxiety disorders and reveal associated risks for worsening course and negative outcomes such as suicide. In this pilot study, the investigators propose to develop and evaluate a dashboard for mental health therapists to augment the care of patients with mood/anxiety disorders.

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.

Participants will receive augmented psychotherapy which includes use of an electronic media dashboard as part of treatment.

A participant-specific dashboard that highlights patterns of patient electronic communication usage relevant to understanding participants' mental health will be developed and used to augment treatment as usual.

Items are rated on a 4-point scale (0=not at all, 3=Nearly every day). A total score range of 0-27 is computed based on patient self-reports on the nine items. Depression severity is interpreted based on the total score (1-4= Minimal depression; 20-27= Severe depression).

Items are rated on a 4-point scale (0=not at all; 3=Nearly every day). A total score range (0-21) is computed based on patient self-reports on the seven items. Anxiety severity is interpreted based on the total score (1-5 = Minimal anxiety; 15-21= Severe anxiety).

Change in self-reported quality of life as assessed by Short Form 36 Mental Health Component (SF-36 MHC)

Items are dichotomous (yes or no), and rated on 5-point (1= Not at all; 5= Extremely) and 6-point (1=All of the time; 6= None of the time)scales

Change in therapist satisfaction with electronic communication data discussion as assessed by Electronic Data and Mental Health Satisfaction Questionnaire

Items are rated on a 7-point scale (1= Not at all; 7= A great deal) including additional items that inquire about effects of electronic communication data discussion

Inclusion Criteria: Patients ages 12-100 years With any diagnosis of a mood or anxiety disorder Already established and receiving care in community psychiatry at the Johns Hopkins Bayview Medical Center or at Johns Hopkins Hospital or Kennedy Krieger Institute. Exclusion Criteria: Non-English speaking

Avenevoli S, Swendsen J, He JP, Burstein M, Merikangas KR. Major depression in the national comorbidity survey-adolescent supplement: prevalence, correlates, and treatment. J Am Acad Child Adolesc Psychiatry. 2015 Jan;54(1):37-44.e2. doi: 10.1016/j.jaac.2014.10.010. Epub 2014 Oct 29.

Brent D, Emslie G, Clarke G, Wagner KD, Asarnow JR, Keller M, Vitiello B, Ritz L, Iyengar S, Abebe K, Birmaher B, Ryan N, Kennard B, Hughes C, DeBar L, McCracken J, Strober M, Suddath R, Spirito A, Leonard H, Melhem N, Porta G, Onorato M, Zelazny J. Switching to another SSRI or to venlafaxine with or without cognitive behavioral therapy for adolescents with SSRI-resistant depression: the TORDIA randomized controlled trial. JAMA. 2008 Feb 27;299(8):901-913. doi: 10.1001/jama.299.8.901. Erratum In: JAMA. 2019 Nov 5;322(17):1718.

Kim-Cohen J, Caspi A, Moffitt TE, Harrington H, Milne BJ, Poulton R. Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Arch Gen Psychiatry. 2003 Jul;60(7):709-17. doi: 10.1001/archpsyc.60.7.709.

McLaughlin KA. The public health impact of major depression: a call for interdisciplinary prevention efforts. Prev Sci. 2011 Dec;12(4):361-71. doi: 10.1007/s11121-011-0231-8.