数字表型-认知功能和痴呆的一个案例?

C. Montag, J. Elhai
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引用次数: 3

摘要

背景:目前的意见工作为读者提供了心理信息学领域最新进展的简短背景。心理信息学代表了计算机科学和心理学学科之间的融合,除其他外,它使研究人员能够在利用与物联网(IoT)交互产生的无处不在的数字痕迹的同时进行数字表型。物联网描述了一个完全互联的世界,从家用电器到智能手机的所有东西都通过互联网相互连接。目标:近年来,在社会人口统计学和个性领域,哪些心理变量可以从社交媒体平台数据和/或智能手机中预测出来,这一问题已经得到了很多研究。这些变量值得研究,因为它们与许多重要的生活变量有关,如寿命、健康行为和工作表现。方法:由于心理信息学对认知的研究相对较少,因此本综述工作的重点将更多地放在认知功能和阿尔茨海默病(AD)等痴呆症如何与物联网数据协同变化的想法上。结果:通过数字足迹可以不同程度地预测包括认知变量在内的社会人口学和心理变量。结论:除了应用心理信息学方法改善AD诊断和监测的大量机会之外,这些方法的局限性也得到了解决,并提出了相关的伦理考虑。
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Digital Phenotyping - A Case for Cognitive Functions and Dementia?
Background:  The present opinion work provides the reader with a short background on recent advances in the field of Psychoinformatics. Psychoinformatics represents a merger between the disciplines of computer science and psychology, among others to enable researchers to conduct digital phenotyping while exploiting the ubiquitously available digital traces resulting from interaction with the Internet of Things (IoT). IoT describes a totally interconnected world, where everything from the household appliance to the smartphone is linked to each other via the Internet. Objectives: In recent years, much work has been dedicated to the question of which psychological variables, in the realm of socio-demographics and personality, can be predicted from social media platform data and/or smartphones in general. These variables are of interest to be studied, because they have been associated with many important life variables such as longevity, health behavior and job performance. Methods: As research concerning cognition has been comparably less studied in Psychoinformatics, the focus of the present review-work will lie more on ideas regarding how cognitive functions and precisely dementia such as Alzheimer’s Disease (AD) might covary with data from the IoT. Results: It is demonstrated that different sociodemographic and psychological variables including cognitive variables currently can be predicted to different extent via digital footprints. Conclusions: Beyond abundant chances due to applying methods from Psychoinformatics to improve diagnostics and monitoring of AD, limitations of such approaches are also addressed together with relevant thoughts on ethical considerations.
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