Unit of Clinical Psychiatry, Department of Neurosciences/DIMSC, School of Medicine, Polytechnic University of Marche, 60126 Ancona, Italy.
Int J Mol Sci. 2020 Oct 16;21(20):7684. doi: 10.3390/ijms21207684.
Bipolar disorder (BD) is a complex neurobiological disorder characterized by a pathologic mood swing. Digital phenotyping, defined as the 'moment-by-moment quantification of the individual-level human phenotype in its own environment', represents a new approach aimed at measuring the human behavior and may theoretically enhance clinicians' capability in early identification, diagnosis, and management of any mental health conditions, including BD. Moreover, a digital phenotyping approach may easily introduce and allow clinicians to perform a more personalized and patient-tailored diagnostic and therapeutic approach, in line with the framework of precision psychiatry. The aim of the present paper is to investigate the role of digital phenotyping in BD. Despite scarce literature published so far, extremely heterogeneous methodological strategies, and limitations, digital phenotyping may represent a grounding research and clinical field in BD, by owning the potentialities to quickly identify, diagnose, longitudinally monitor, and evaluating clinical response and remission to psychotropic drugs. Finally, digital phenotyping might potentially constitute a possible predictive marker for mood disorders.
双相情感障碍(BD)是一种复杂的神经生物学障碍,其特征是病理性的情绪波动。数字表型,定义为“在其自身环境中对个体水平人类表型的实时定量”,代表了一种新的方法,旨在测量人类行为,并可能从理论上增强临床医生对任何心理健康状况(包括 BD)的早期识别、诊断和管理能力。此外,数字表型方法可以很容易地引入并允许临床医生执行更个性化和针对患者的诊断和治疗方法,符合精准精神病学的框架。本文旨在探讨数字表型在 BD 中的作用。尽管到目前为止发表的文献很少,方法策略极其多样化,存在局限性,但数字表型可能代表了 BD 中的一个基础研究和临床领域,具有快速识别、诊断、纵向监测和评估抗精神病药物的临床反应和缓解的潜力。最后,数字表型可能是情绪障碍的一个潜在预测标志物。