Understanding Barriers to the Collection of Mobile and Wearable Device Data to Monitor Health and Cognition in Older Adults: A Scoping Review.

Ibukun E Fowe, Edie C Sanders, Walter R Boot
{"title":"Understanding Barriers to the Collection of Mobile and Wearable Device Data to Monitor Health and Cognition in Older Adults: A Scoping Review.","authors":"Ibukun E Fowe, Edie C Sanders, Walter R Boot","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Advances in technology have made continuous/remote monitoring of digital health data possible, which can enable the early detection and treatment of age-related cognitive and health declines. Using Arksey and O'Malley's methodology, this scoping review evaluated potential barriers to the collection of mobile and wearable device data to monitor health and cognitive status in older adults with and without mild cognitive impairment (MCI). Selected articles were US based and focused on experienced or perceived barriers to the collection of mobile and wearable device data by adults 55 years of age or older. Fourteen articles met the study's inclusion criteria. Identified themes included barriers related to usability, users' prior experiences with health technologies, first and second level digital divide, aesthetics, comfort, adherence, and attitudinal barriers. Addressing these barriers will be crucial for effective digital data-collection among older adults to achieve goals of improving quality of life and reducing care costs.</p>","PeriodicalId":72181,"journal":{"name":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283138/pdf/2117.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Advances in technology have made continuous/remote monitoring of digital health data possible, which can enable the early detection and treatment of age-related cognitive and health declines. Using Arksey and O'Malley's methodology, this scoping review evaluated potential barriers to the collection of mobile and wearable device data to monitor health and cognitive status in older adults with and without mild cognitive impairment (MCI). Selected articles were US based and focused on experienced or perceived barriers to the collection of mobile and wearable device data by adults 55 years of age or older. Fourteen articles met the study's inclusion criteria. Identified themes included barriers related to usability, users' prior experiences with health technologies, first and second level digital divide, aesthetics, comfort, adherence, and attitudinal barriers. Addressing these barriers will be crucial for effective digital data-collection among older adults to achieve goals of improving quality of life and reducing care costs.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
了解收集移动和可穿戴设备数据以监测老年人健康和认知情况的障碍:范围审查》。
技术的进步使持续/远程监测数字健康数据成为可能,从而能够及早发现和治疗与年龄相关的认知和健康衰退。本范围界定综述采用 Arksey 和 O'Malley 的方法,评估了收集移动和可穿戴设备数据以监测患有或未患有轻度认知障碍(MCI)的老年人的健康和认知状况的潜在障碍。所选文章均来自美国,重点关注 55 岁或以上成年人在收集移动和可穿戴设备数据时遇到的或感知到的障碍。有 14 篇文章符合研究的纳入标准。确定的主题包括与可用性相关的障碍、用户以前使用健康技术的经验、第一级和第二级数字鸿沟、美学、舒适度、依从性和态度障碍。解决这些障碍对于在老年人中有效收集数字数据以实现提高生活质量和降低护理成本的目标至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Implementation of a Machine Learning Risk Prediction Model for Postpartum Depression in the Electronic Health Records. Clarifying Chronic Obstructive Pulmonary Disease Genetic Associations Observed in Biobanks via Mediation Analysis of Smoking. CLASSify: A Web-Based Tool for Machine Learning. Clinical Note Structural Knowledge Improves Word Sense Disambiguation. Cluster Analysis of Cortical Amyloid Burden for Identifying Imaging-driven Subtypes in Mild Cognitive Impairment.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1