Department of Psychiatry and Psychotherapy, University Medical Center Dresden, Dresden, Germany.
Department of Sport and Sport Science and House of Competence, Karlsruhe Institute of Technology, Karlsruhe, Germany.
BMC Psychiatry. 2018 Oct 26;18(1):349. doi: 10.1186/s12888-018-1929-y.
The 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/DESIGN: The 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.
This 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.
ClinicalTrials.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.
在双相情感障碍的长期治疗中，早期预警信号的检测至关重要。然而，在双相患者的日常生活和门诊治疗中，评估即将发生的状态变化面临着一些困难。在这项试验中，我们研究了基于智能手机的自动反馈对日常生活中评估到的早期预警信号的有效性，以延长缓解期并预防住院。本研究旨在评估当治疗精神病医生收到关于沟通和活动变化的自动反馈时，患者是否会经历更长时间的缓解期。通过这些额外的信息，可以更早地干预躁狂或抑郁的发展阶段。我们预计干预组的情感发作之间的时间会更长。
方法/设计：本研究是一个在全国性的双相情感障碍创新诊断、预防和干预方法研究项目内进行的随机、多中心、观察者盲法、活性对照、平行组试验。120 名双相情感障碍患者将被随机分配到（1）实验组，包括自动反馈，或（2）对照组，无反馈。在干预阶段，所有参与者的精神病理学状态将在 18 个月内每四周评估一次。Kaplan-Meier 估计器将用于估计生存函数，对数秩检验将用于正式比较治疗组之间新发发作的时间。意向治疗分析将包括所有随机患者的数据。
本文描述了一项临床试验的设计，该试验旨在研究基于智能手机的反馈回路的有效性。该反馈回路旨在在发现双相患者的预警信号时引发早期干预，以预防情感发作。这种方法有望提高及时干预的机会，帮助患者保持更长时间的平衡情绪。具体来说，如果我们的假设能够得到证实，治疗精神病医生的临床实践将能够在自动检测到变化时迅速做出反应。因此，门诊患者将获得更个性化的治疗，包括就诊时间和频率。
ClinicalTrials.gov：NCT02782910：标题：“基于智能手机的日常生活评估早期预警信号（BipoLife_A3）”。注册于 2016 年 5 月 25 日。方案修正案编号：03。发布日期：2018 年 3 月 26 日。作者：ES。
