Abstract

BackgroundThe detection of early warning signs is essential in the long-term treatment of bipolar disorders. However, in bipolar patients’ daily life and outpatient treatment the assessment of upcoming state changes faces several difficulties. In this trial, we examine the effectiveness of a smartphone based automated feedback about ambulatory assessed early warning signs in prolonging states of euthymia and therefore preventing hospitalization. This study aims to assess, whether patients experience longer episodes of euthymia, when their treating psychiatrists receive automated feedback about changes in communication and activity. With this additional information an intervention at an earlier stage in the development of mania or depression could be facilitated. We expect that the amount of time will be longer between affective episodes in the intervention group.Methods/designThe current study is designed as a randomized, multi-center, observer-blind, active-control, parallel group trial within a nationwide research project on the topic of innovative methods for diagnostics, prevention and interventions of bipolar disorders. One hundred and twenty patients with bipolar disorder will be randomly assigned to (1) the experimental group with included automated feedback or (2) the control group without feedback. During the intervention phase, the psychopathologic state of all participants is assessed every four weeks over 18 months. Kaplan-Meier estimators will be used for estimating the survival functions, a Log-Rank test will be used to formally compare time to a new episode across treatment groups. An intention-to-treat analysis will include data from all randomized patients.DiscussionThis article describes the design of a clinical trial investigating the effectiveness of a smartphone-based feedback loop. This feedback loop is meant to elicit early interventions at the detection of warning signs for the prevention of affective episodes in bipolar patients. This approach will hopefully improve the chances of a timely intervention helping patients to keep a balanced mood for longer periods of time. In detail, if our hypothesis can be confirmed, clinical practice treating psychiatrists will be enabled to react quickly when changes are automatically detected. Therefore, outpatients would receive an even more individually tailored treatment concerning time and frequency of doctor’s appointments.Trial registrationClinicalTrials.gov: NCT02782910: Title: “Smartphone-based Ambulatory Assessment of Early Warning Signs (BipoLife_A3)”. Registered May 25 2016.Protocol Amendment Number: 03. Issue Date: 26 March 2018. Author(s): ES.

Highlights

  • The detection of early warning signs is essential in the long-term treatment of bipolar disorders

  • This article describes the design of a clinical trial investigating the effectiveness of a smartphone-based feedback loop

  • Though not yet proven the detection of early warning signs (EWS) is considered to improve the course of bipolar illness [7] but it is mainly the patient’s own responsibility as he or she is usually seen by the treating psychiatrist once every few weeks or even months, especially when euthymic

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Summary

Introduction

The detection of early warning signs is essential in the long-term treatment of bipolar disorders. This study aims to assess, whether patients experience longer episodes of euthymia, when their treating psychiatrists receive automated feedback about changes in communication and activity With this additional information an intervention at an earlier stage in the development of mania or depression could be facilitated. Bipolar disorder as an affective illness with chronic features shows a very diverse and often unpredictable course of illness concerning the number, length and frequency of recurrent depressive and (hypo) manic states [1]. This condition causes high costs both from an individual as well as from a societal point of view [2]. As the course of bipolar illness remains highly unpredictable even after long periods of euthymia, the cessation of mood charting may turn out to be detrimental [11]

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