Department of Health Sciences and Human Performance, College of Natural and Health Sciences, The University of Tampa, Tampa, FL, USA.
Helath and Management Policy Program, School of Social and Behavioral Health Science, College of Public Health and Human Science, Oregon State University, Corvallis, OR, USA.
Disabil Rehabil Assist Technol. 2024 Jan;19(1):131-138. doi: 10.1080/17483107.2022.2071485. Epub 2022 May 5.
The study aims to investigate the prevalence of individuals with disabilities who reported using wearable devices, to examine the association between wearable device usage and disability status, and to determine the characteristic of individuals with disabilities associated with wearable device usage using the 2017 Behavioural Risk Factor Surveillance System (BRFSS) through secondary data analysis.
Data from the 2017 BRFSS of eight states were used in the analysis. Descriptive analysis, chi-square analysis, and multivariable logistic regressions were performed. Subsample analyses were also conducted for individuals with disabilities and different types of disability, including visual impairments, hearing impairments, cognitive disability, independent living disability, self-care disability, and mobility disability on wearable device usage.
14.6% (95% CI [11.7, 17.5]) of participants with disabilities were wearable device users. Individuals with disabilities were .63 (95% CI [.48, .83], < 0.001) and .67 (95% CI [.50, .90], = 0.007) times the odds of individuals without disabilities in using wearable devices, respectively, according to unadjusted and adjusted logistic regression. Individuals with mobility disability were less likely to utilise wearable devices than their counterparts. Among individuals with disabilities, those who were age 65 years or older had a lower odds of using wearable devices (OR = .55, 95% CI [0.35, 0.85), = 0.007).
Individuals with disabilities are using wearable devices in collecting various health-related information. Further research is needed to determine reasons why individuals with disabilities are not using wearable devices and how individuals with disabilities are using wearable devices.IMPLICATIONS FOR REHABILITATIONWearable devices can track various health-related information such as physical activity levels, sleep patterns, calories intakes, and chronic health conditions.Using nationally represent data, individuals with disabilities have access and utilise wearable devices in free living setting.Compare to individuals without disabilities, individuals with disabilities are less likely to utilise wearable devices in free living setting.Further research is needed to determine the accessibility of wearable devices for individuals with disabilities and its usage in rehabilitation setting.
本研究旨在调查报告使用可穿戴设备的残疾个体的流行率，探讨可穿戴设备使用与残疾状况之间的关联，并使用二次数据分析 2017 年行为风险因素监测系统（BRFSS）确定与可穿戴设备使用相关的残疾个体特征。
本研究使用了来自八个州的 2017 年 BRFSS 数据。进行了描述性分析、卡方分析和多变量逻辑回归。还对残疾个体和不同类型残疾（包括视力障碍、听力障碍、认知障碍、独立生活障碍、自理障碍和行动障碍）的可穿戴设备使用情况进行了亚组分析。
14.6%（95%置信区间[11.7,17.5]）的残疾个体是可穿戴设备使用者。与无残疾个体相比，残疾个体使用可穿戴设备的几率分别为未调整（优势比[OR]，95%置信区间[0.48,0.83]， < 0.001）和调整后（OR，95%置信区间[0.50,0.90]， = 0.007）的 0.63 倍和 0.67 倍。有行动障碍的个体使用可穿戴设备的可能性较小。在残疾个体中，65 岁及以上的个体使用可穿戴设备的几率较低（OR=0.55，95%置信区间[0.35,0.85]， = 0.007）。
残疾个体正在使用可穿戴设备收集各种健康相关信息。需要进一步研究确定残疾个体不使用可穿戴设备的原因以及残疾个体如何使用可穿戴设备。
可穿戴设备可以跟踪各种健康相关信息，如身体活动水平、睡眠模式、卡路里摄入量和慢性健康状况。
使用全国代表性数据，残疾个体在自由生活环境中可以获得并使用可穿戴设备。
与无残疾个体相比，残疾个体在自由生活环境中使用可穿戴设备的可能性较小。
需要进一步研究确定可穿戴设备对残疾个体的可及性及其在康复环境中的使用情况。
