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[动态监测与数字表型分析在双相情感障碍诊断与治疗中的应用]

[Ambulatory monitoring and digital phenotyping in the diagnostics and treatment of bipolar disorders].

作者信息

Severus E, Ebner-Priemer U, Beier F, Mühlbauer E, Ritter P, Hill H, Bauer M

机构信息

Klinik und Poliklinik für Psychiatrie und Psychotherapie, Universitätsklinikum Dresden, Fetscherstraße 74, 01307, Dresden, Deutschland.

Institut für Sportwissenschaft, Karlsruher Institut für Technologie, Karlsruhe, Deutschland.

出版信息

Nervenarzt. 2019 Dec;90(12):1215-1220. doi: 10.1007/s00115-019-00816-9.

DOI:10.1007/s00115-019-00816-9
PMID:31748866
Abstract

BACKGROUND

Reliable and valid diagnostics and treatment of bipolar disorders and affective episodes are subject to extensive, especially methodological limitations in the clinical practice.

OBJECTIVE

The use of smartphones and mobile sensor technology for improvement in diagnostics and treatment of bipolar disorders.

METHODS

Critical discussion of current research on the use of ambulatory monitoring and digital phenotyping with bipolar disorders.

RESULTS

In many studies the observation periods were too short and the sensors applied were too inaccurate to enable reliable and valid detection of behavioral changes in the context of affective episodes.

CONCLUSION

The clarification and operationalization of psychopathological constructs to allow for the measurement of objectively observable and ascertainable behavioral changes during depressive and (hypo)manic states are essential for the successful application of modern mobile technologies in the diagnostics and treatment of bipolar disorders.

摘要

背景

双相情感障碍及情感发作的可靠且有效的诊断与治疗在临床实践中受到广泛限制,尤其是方法学上的限制。

目的

利用智能手机和移动传感器技术改善双相情感障碍的诊断与治疗。

方法

对当前关于双相情感障碍动态监测和数字表型应用的研究进行批判性讨论。

结果

在许多研究中,观察期过短且所应用的传感器不够精确,无法在情感发作背景下可靠且有效地检测行为变化。

结论

明确和细化精神病理学结构,以便能够测量抑郁和(轻)躁狂状态下客观可观察和可确定的行为变化,对于现代移动技术成功应用于双相情感障碍的诊断和治疗至关重要。

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本文引用的文献

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Reporting guidelines on remotely collected electronic mood data in mood disorder (eMOOD)-recommendations.报告心境障碍(eMOOD)中远程采集电子心境数据的指南——建议。
Transl Psychiatry. 2019 Jun 7;9(1):162. doi: 10.1038/s41398-019-0484-8.
2
The effect of smartphone-based monitoring on illness activity in bipolar disorder: the MONARCA II randomized controlled single-blinded trial.基于智能手机的监测对双相情感障碍疾病活动的影响:MONARCA II 随机对照单盲试验。
Psychol Med. 2020 Apr;50(5):838-848. doi: 10.1017/S0033291719000710. Epub 2019 Apr 4.
3
Emotional expression in psychiatric conditions: New technology for clinicians.
精神疾病中的情绪表达:临床医生的新技术。
Psychiatry Clin Neurosci. 2019 Feb;73(2):50-62. doi: 10.1111/pcn.12799. Epub 2018 Dec 25.
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Commentary on: Objective smartphone data as a potential diagnostic marker of bipolar disorder.
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Real-time Mobile Monitoring of the Dynamic Associations Among Motor Activity, Energy, Mood, and Sleep in Adults With Bipolar Disorder.实时移动监测双相情感障碍成人的运动活动、能量、情绪和睡眠之间的动态关联。
JAMA Psychiatry. 2019 Feb 1;76(2):190-198. doi: 10.1001/jamapsychiatry.2018.3546.
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Objective smartphone data as a potential diagnostic marker of bipolar disorder.目的:智能手机数据作为双相情感障碍潜在诊断标志物的研究。
Aust N Z J Psychiatry. 2019 Feb;53(2):119-128. doi: 10.1177/0004867418808900. Epub 2018 Nov 2.
7
Effectiveness of smartphone-based ambulatory assessment (SBAA-BD) including a predicting system for upcoming episodes in the long-term treatment of patients with bipolar disorders: study protocol for a randomized controlled single-blind trial.基于智能手机的动态评估(SBAA-BD)在双相情感障碍患者长期治疗中包括一个预测系统,用于预测即将到来的发作:一项随机对照单盲试验的研究方案。
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Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning.语音分析在健康领域的应用:当前的最新技术和深度学习的影响日益增大。
Methods. 2018 Dec 1;151:41-54. doi: 10.1016/j.ymeth.2018.07.007. Epub 2018 Aug 10.
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