Severity of depression and anxiety symptoms is reflected in physiological and behavioral metrics collected from a consumer-grade wearable ring.

IF 8.7 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Saeid Azadifar, Alireza Sameh, Laura Nauha, Mikko Kärmeniemi, Maisa Niemelä, Vahid Farrahi
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引用次数: 0

Abstract

Background: Modern wearable devices generate a multitude of digital metrics, which can be used to measure human function in health and disease. This study investigated whether and how digital metrics generated from a consumer-grade smart ring were different in individuals with varying severity of depression and anxiety symptoms in a large population-based cohort.

Methods: Cross-sectional data were obtained from the Northern Finland Birth Cohort 1986 when participants were 33-35 years of age. Participants were asked to wear the Oura Ring for two weeks, which provided digital measures of sleep architecture, nocturnal heart rate (HR), nocturnal heart rate variability indexed by the root mean square of successive differences between normal heartbeats (RMSSD), and minute-by-minute movement intensity. Participants with at least one weekday and a weekend day with no less than 15 h of wear time were included. Two screening tools were used to assess depression and anxiety symptoms. Symptoms of anxiety were assessed using the Generalized Anxiety Disorder 7-item scale (GAD-7) and symptoms of depression and anxiety using Hopkins Symptom Checklist-25 (HSCL-25). Participants were grouped into no, mild, and moderate-to-severe anxiety symptom groups based on GAD-7, and with and without depression and anxiety symptoms based on HSCL-25. Time-series data were visualized, and statistical differences between groups were assessed using one-way ANCOVA followed by Tukey's post hoc test.

Results: A total of 1,290 participants provided enough valid data and were included. Participants with moderate-to-severe anxiety assessed by GAD-7 and with depression and anxiety symptoms assessed by HSCL-25 exhibited lower percentage of rapid eye movement (REM) and deep sleep, and increased light sleep compared with the group without depression and anxiety. These two groups also showed higher HR, lower RMSSD during sleep, and lower levels of physical activity during the day. The differences between mild anxiety group with no and moderate-to-severe anxiety groups were overall less apparent on average.

Conclusions: Findings suggest that severity of depression and anxiety can be reflected in behavioral and physiological metrics generated by a consumer-grade wearable ring. These findings suggest that they may be a promising tool for enhancing symptoms tracking and informing personalized care strategies.

抑郁和焦虑症状的严重程度反映在从消费级可穿戴戒指收集的生理和行为指标上。
背景:现代可穿戴设备产生大量数字指标,可用于测量健康和疾病中的人体功能。本研究调查了在一个以人口为基础的大型队列中,消费级智能戒指产生的数字指标在不同抑郁和焦虑症状严重程度的个体中是否以及如何不同。方法:从1986年芬兰北部出生队列中获得横断面数据,参与者年龄为33-35岁。参与者被要求佩戴Oura环两周,该环提供睡眠结构、夜间心率(HR)、夜间心率变异性(由正常心跳连续差异(RMSSD)的均方根索引)和每分钟运动强度的数字测量。包括至少一个工作日和一个周末穿戴时间不少于15小时的参与者。两种筛查工具用于评估抑郁和焦虑症状。使用广泛性焦虑障碍7项量表(GAD-7)评估焦虑症状,使用霍普金斯症状检查表-25 (HSCL-25)评估抑郁和焦虑症状。参与者根据GAD-7分为无、轻度和中度至重度焦虑症状组,根据HSCL-25分为有无抑郁和焦虑症状组。将时间序列数据可视化,并采用单向ANCOVA和Tukey事后检验评估组间的统计学差异。结果:共有1290名参与者提供了足够的有效数据并被纳入。与没有抑郁和焦虑的组相比,GAD-7评估的中度至重度焦虑和HSCL-25评估的抑郁和焦虑症状的参与者表现出较低的快速眼动(REM)和深度睡眠百分比,以及增加的浅睡眠。这两组人在睡眠期间的HR较高,RMSSD较低,白天的体力活动水平较低。总体而言,无焦虑的轻度焦虑组和中度至重度焦虑组之间的差异不太明显。结论:研究结果表明,抑郁和焦虑的严重程度可以反映在消费级可穿戴戒指产生的行为和生理指标上。这些发现表明,它们可能是一种有前途的工具,用于加强症状跟踪和告知个性化护理策略。
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
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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