Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study.

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES JMIR mHealth and uHealth Pub Date : 2025-02-05 DOI:10.2196/56185
Zixu Yang, Creighton Heaukulani, Amelia Sim, Thisum Buddhika, Nur Amirah Abdul Rashid, Xuancong Wang, Shushan Zheng, Yue Feng Quek, Sutapa Basu, Kok Wei Lee, Charmaine Tang, Swapna Verma, Robert J T Morris, Jimmy Lee
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Abstract

Background: Digital phenotyping provides insights into an individual's digital behaviors and has potential clinical utility.

Objective: In this observational study, we explored digital biomarkers collected from wrist-wearable devices and smartphones and their associations with clinical symptoms and functioning in patients with schizophrenia.

Methods: We recruited 100 outpatients with schizophrenia spectrum disorder, and we collected various digital data from commercially available wrist wearables and smartphones over a 6-month period. In this report, we analyzed the first week of digital data on heart rate, sleep, and physical activity from the wrist wearables and travel distance, sociability, touchscreen tapping speed, and screen time from the smartphones. We analyzed the relationships between these digital measures and patient baseline measurements of clinical symptoms assessed with the Positive and Negative Syndrome Scale, Brief Negative Symptoms Scale, and Calgary Depression Scale for Schizophrenia, as well as functioning as assessed with the Social and Occupational Functioning Assessment Scale. Linear regression was performed for each digital and clinical measure independently, with the digital measures being treated as predictors.

Results: Digital data were successfully collected from both the wearables and smartphones throughout the study, with 91% of the total possible data successfully collected from the wearables and 82% from the smartphones during the first week of the trial-the period under analysis in this report. Among the clinical outcomes, negative symptoms were associated with the greatest number of digital measures (10 of the 12 studied here), followed by overall measures of psychopathology symptoms, functioning, and positive symptoms, which were each associated with at least 3 digital measures. Cognition and cognitive/disorganization symptoms were each associated with 1 or 2 digital measures.

Conclusions: We found significant associations between nearly all digital measures and a wide range of symptoms and functioning in a community sample of individuals with schizophrenia. These findings provide insights into the digital behaviors of individuals with schizophrenia and highlight the potential of using commercially available wrist wearables and smartphones for passive monitoring in schizophrenia.

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基于手腕可穿戴设备和智能手机的数字表型在精神病中的应用:观察性研究。
背景:数字表型提供了对个人数字行为的见解,并具有潜在的临床用途。目的:在这项观察性研究中,我们探讨了从手腕可穿戴设备和智能手机收集的数字生物标志物及其与精神分裂症患者临床症状和功能的关系。方法:我们招募了100名精神分裂症谱系障碍门诊患者,在6个月的时间里,我们从市售的手腕可穿戴设备和智能手机上收集了各种数字数据。在这份报告中,我们分析了第一周的数字数据,包括心率、睡眠、手腕可穿戴设备的身体活动,以及智能手机的旅行距离、社交能力、触屏速度和屏幕时间。我们分析了这些数字测量与患者临床症状基线测量(用阳性和阴性综合征量表、短暂阴性症状量表和卡尔加里精神分裂症抑郁量表评估)以及社会和职业功能评估量表评估的功能之间的关系。对每个数字和临床测量独立进行线性回归,数字测量被视为预测因子。结果:在整个研究过程中,可穿戴设备和智能手机都成功收集了数字数据,在试验的第一周(本报告分析的时期),可穿戴设备和智能手机成功收集了91%和82%的可能数据。在临床结果中,阴性症状与数字测量的数量最多(这里研究的12个中有10个),其次是精神病理症状、功能和阳性症状的总体测量,每一个都与至少3个数字测量相关。认知和认知/紊乱症状分别与1或2个数字测量相关。结论:我们发现在精神分裂症患者的社区样本中,几乎所有的数字测量与广泛的症状和功能之间存在显著的关联。这些发现为精神分裂症患者的数字行为提供了见解,并强调了使用市售的手腕可穿戴设备和智能手机进行精神分裂症被动监测的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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