Reducing the rate and duration of Re-ADMISsions among patients with unipolar disorder and bipolar disorder using smartphone-based monitoring and treatment – the RADMIS trials: study protocol for two randomized controlled trials

Unipolar disorder and bipolar disorder are common mental diseases with a lifetime prevalence of 15–20% and 1–2%, respectively [1, 2]. Unipolar disorder and bipolar disorder combined account for nearly half of all morbidity and mortality due to mental and substance use disorders [3] and burden society with the highest health care costs of all psychiatric and neurological disorders [4].

Although psychiatric treatment internationally, and in Denmark, has shifted more from inpatient treatment to outpatient treatment during recent decades, costs due to psychiatric hospitalization are still a major burden comprising two thirds of all direct costs in the five Regions of Denmark [5]. Patients with affective disorders are more frequently hospitalized than any other patient group, counting more than 10,800 patients in 2013 among the entire Danish population of 5.4 million people, and 20% of all psychiatric hospitalizations in Denmark [6]. The cost of these hospitalizations alone is estimated to be DKK648 million (approximately €8.7 million) per year in Denmark (10,800 hospitalizations with a mean of 20 days’ stay for a cost of 3000 DKK/day (€400)). The discharge period after hospitalization is a high-risk period with a more than 300 times increased risk of suicide during the first week [7] and a high risk of re-admission [8, 9]. Patients are often afraid of leaving the hospital, feeling alone with the prospect of an appointment with a physician 1 or more months ahead. A pilot study from our group in which 45 patients discharged from psychiatric hospital self-monitored symptoms using a daily computer-based self-monitoring system emphasized the pivotal importance of continued contact with a clinician such as a nurse [10]. Smartphones comprise a unique platform for the monitoring and treatment of depression and mania. Depression and mania are associated with changes in several behavioral components (e.g., reduction in activity level, change in speech) and motivational states (e.g., anhedonia), some of which may be detectable using readily available smartphone sensors [11‐13]. Prior work done by our group has developed and tested a unique smartphone-based system for the treatment of bipolar disorder (the MONARCA system) [14, 15]. The MONARCA system is capable of collecting subjective self-assessment data and automatically generated objective smartphone data from patients on a daily basis while allowing simple bidirectional communication between clinicians and the patients [15]. We find it likely that daily contact with a psychiatric hospital nurse using a bidirectional feedback system combined with objective smartphone-based early warning signs, assessed using a smartphone app, will reduce the risk of re-admission and the risk of relapse of depressive and (hypo)manic symptoms.

Treatment of unipolar disorder and bipolar disorder applies a variety of methods, including antidepressants, mood stabilizers, psychoeducation, and cognitive behavioral psychotherapy (CBT).

CBT has proven efficacious in the treatment and prevention of depressive episodes in unipolar disorder [16], but the effect in relation to bipolar disorder is controversial [17]. Depressive symptoms dominate bipolar disorder as 80% of episodes are depressive [18], but bipolar depression is difficult to treat as only a few drugs have proven effects [19] and psychological interventions have proven ambient effects on depressive symptoms revealing positive effects in some studies [20‐22], but not in others [23‐25]. Specifically targeting depressive rumination, rumination-focused cognitive therapy and concreteness training (a facilitated self-help intervention intended to increase specificity of processing in patients with depression) have shown encouraging results in the treatment of residual depression [26]. However, the number of CBT therapists is very low compared with the huge demand for CBT. Internet- and computer-based CBT systems exist and have been proved effective in relation to depression [27]. Recently, CBT has been suggested for smartphones [28] but the effect has never been tested in a randomized controlled trial (RCT).

In the RADMIS trial we will develop a smartphone-based CBT program that includes methods to relieve depressive ruminations [23, 29]. The smartphone-based system used in the RADMIS trials is inspired by the MONARCA system (see below), and is called the Monsenso system. By using the sensing, computational and communication capabilities of smartphones, it is possible to continuously monitor an individual’s context including physical activity, location, and environment. Thus, smartphones hold significant promise as a platform to monitor behavioral and environmental indicators of depression and mania and for treatment, facilitating early intervention and smartphone-based CBT.

Prior research on using smartphones in the detection of unipolar disorder and bipolar disorder has shown promising but preliminary results. A small study on eight patients with depression (not including a control group) found that sensor data from smartphones could detect social patterns [30]. Another study found that sensors from smartphones were effective at detecting social and sleep behaviors among patients with depression [31].

The MONARCA system, developed and tested by our group [14, 15], has been proved highly usable and useful by patients with bipolar disorder with a high self-assessment adherence (87–95%), and was considered to help patients to better manage their disease [32]. A study investigating the effect of the MONARCA system (daily self-monitoring including a two-level feedback loop to clinicians) in a RCT found no overall effect in primary analyses but secondary analyses suggested that the system was able to reduce manic symptoms, but may sustain depressive symptoms in patients with bipolar disorder [33]. These results are in accordance with the findings that psychological interventions for bipolar disorder in general have more effect on manic than depressive symptoms and more effect on preventing that treating acute depression [23‐25]. Consequently, emphasis on depressive symptoms should be a high priority including considerations on mechanisms to reduce the negative processing bias and depressive ruminations in patients with unipolar disorder and bipolar disorder [23, 33].

Finally, research by our group found that automatically generated objective smartphone data reflect illness activity in patients with bipolar disorder. Data on physical activity (the number of changes in cell tower ID/day), social activity (the number and duration of phone calls/day and the number of text messages/day) [11‐13] and voice features collected during phone calls [34] correlated significantly with the severity of clinically rated depressive and manic symptoms. Although these findings are encouraging and innovative, there is a need to integrate self-monitored smartphone data with automatically generated objective smartphone data on physical and social activity, as well as speech and sleep, into a composite smartphone-generated electronic measure. This composite measure should be modeled to have a high correlation with depressive and manic symptoms, and a high predictive ability to identify upcoming affective episodes for the individual patient in order to facilitate early intervention.