Davidson Brittany I
Information, Decisions, and Operations Division, School of Management, University of Bath, United Kingdom; Department of Computer Science, University of Bristol, United Kingdom.
Gen Hosp Psychiatry. 2022 Jan-Feb;74:126-132. doi: 10.1016/j.genhosppsych.2020.11.009. Epub 2020 Nov 23.
The term 'Digital Phenotyping' has started to appear with increasing regularity in medical research, especially within psychiatry. This aims to bring together digital traces (e.g., from smartphones), medical data (e.g., electronic health records), and lived experiences (e.g., daily activity, location, social contact), to better monitor, intervene, and diagnose various psychiatric conditions. However, is this notion any different from digital traces or the quantified self? While digital phenotyping has the potential to transform and revolutionize medicine as we know it; there are a number of challenges that must be addressed if research is to blossom. At present, these issues include; (1) methodological issues, for example, the lack of clear theoretical links between digital markers (e.g., battery life, interactions with smartphones) and condition relapses, (2) the current tools being employed, where they typically have a number of security or privacy issues, and are invasive by nature, (3) analytical methods and approaches, where I question whether research should start in larger-scale epidemiological scale or in smaller (and potentially highly vulnerable) patient populations as is the current norm, (4) the current lack of security and privacy regulation adherence of apps used, and finally, (5) how do such technologies become integrated into various healthcare systems? This aims to provide deep insight into how the Digital Phenotyping could provide huge promise if we critically reflect now and gather clinical insights with a number of other disciplines such as epidemiology, computer- and the social sciences to move forward.
“数字表型分析”一词在医学研究中出现的频率越来越高,尤其是在精神病学领域。其目的是整合数字痕迹(如来自智能手机的痕迹)、医学数据(如电子健康记录)和生活经历(如日常活动、位置、社交接触),以更好地监测、干预和诊断各种精神疾病。然而,这个概念与数字痕迹或量化自我有何不同?虽然数字表型分析有可能改变和彻底变革我们所熟知的医学;但如果研究要蓬勃发展,就必须解决一些挑战。目前,这些问题包括:(1)方法学问题,例如数字标记(如电池寿命、与智能手机的交互)与病情复发之间缺乏明确的理论联系;(2)目前所使用的工具,这些工具通常存在一些安全或隐私问题,而且本质上具有侵入性;(3)分析方法和途径,我质疑研究是否应该像当前的常态那样从大规模流行病学规模开始,还是从较小(且可能高度脆弱)的患者群体开始;(4)目前使用的应用程序缺乏对安全和隐私规定的遵守,最后,(5)这些技术如何融入各种医疗保健系统?这旨在深入洞察,如果我们现在进行批判性反思,并与流行病学、计算机科学和社会科学等其他一些学科收集临床见解以推动前进,数字表型分析如何能够带来巨大的希望。