EVIDENCE Publication Checklist for Studies Evaluating Connected Sensor Technologies: Explanation and Elaboration.

Q1 Computer Science Digital Biomarkers Pub Date : 2021-05-18 eCollection Date: 2021-05-01 DOI:10.1159/000515835
Christine Manta, Nikhil Mahadevan, Jessie Bakker, Simal Ozen Irmak, Elena Izmailova, Siyeon Park, Jiat-Ling Poon, Santosh Shevade, Sarah Valentine, Benjamin Vandendriessche, Courtney Webster, Jennifer C Goldsack
{"title":"EVIDENCE Publication Checklist for Studies Evaluating Connected Sensor Technologies: Explanation and Elaboration.","authors":"Christine Manta,&nbsp;Nikhil Mahadevan,&nbsp;Jessie Bakker,&nbsp;Simal Ozen Irmak,&nbsp;Elena Izmailova,&nbsp;Siyeon Park,&nbsp;Jiat-Ling Poon,&nbsp;Santosh Shevade,&nbsp;Sarah Valentine,&nbsp;Benjamin Vandendriessche,&nbsp;Courtney Webster,&nbsp;Jennifer C Goldsack","doi":"10.1159/000515835","DOIUrl":null,"url":null,"abstract":"<p><p>The EVIDENCE (EValuatIng connecteD sENsor teChnologiEs) checklist was developed by a multidisciplinary group of content experts convened by the Digital Medicine Society, representing the clinical sciences, data management, technology development, and biostatistics. The aim of EVIDENCE is to promote high quality reporting in studies where the primary objective is an evaluation of a digital measurement product or its constituent parts. Here we use the terms digital measurement product and connected sensor technology interchangeably to refer to tools that process data captured by mobile sensors using algorithms to generate measures of behavioral and/or physiological function. EVIDENCE is applicable to 5 types of evaluations: (1) proof of concept; (2) verification, (3) analytical validation, and (4) clinical validation as defined by the V3 framework; and (5) utility and usability assessments. Using EVIDENCE, those preparing, reading, or reviewing studies evaluating digital measurement products will be better equipped to distinguish necessary reporting requirements to drive high-quality research. With broad adoption, the EVIDENCE checklist will serve as a much-needed guide to raise the bar for quality reporting in published literature evaluating digital measurements products.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 2","pages":"127-147"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515835","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000515835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/5/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 15

Abstract

The EVIDENCE (EValuatIng connecteD sENsor teChnologiEs) checklist was developed by a multidisciplinary group of content experts convened by the Digital Medicine Society, representing the clinical sciences, data management, technology development, and biostatistics. The aim of EVIDENCE is to promote high quality reporting in studies where the primary objective is an evaluation of a digital measurement product or its constituent parts. Here we use the terms digital measurement product and connected sensor technology interchangeably to refer to tools that process data captured by mobile sensors using algorithms to generate measures of behavioral and/or physiological function. EVIDENCE is applicable to 5 types of evaluations: (1) proof of concept; (2) verification, (3) analytical validation, and (4) clinical validation as defined by the V3 framework; and (5) utility and usability assessments. Using EVIDENCE, those preparing, reading, or reviewing studies evaluating digital measurement products will be better equipped to distinguish necessary reporting requirements to drive high-quality research. With broad adoption, the EVIDENCE checklist will serve as a much-needed guide to raise the bar for quality reporting in published literature evaluating digital measurements products.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
评估连接传感器技术研究的证据出版清单:解释和阐述。
EVIDENCE(评估连接传感器技术)清单是由数字医学协会召集的多学科内容专家小组制定的,代表临床科学、数据管理、技术开发和生物统计学。EVIDENCE的目的是促进以评估数字测量产品或其组成部分为主要目标的研究的高质量报告。在这里,我们交替使用数字测量产品和连接传感器技术这两个术语,指的是使用算法处理移动传感器捕获的数据以生成行为和/或生理功能测量的工具。EVIDENCE适用于5种评价类型:(1)概念证明;(2)验证,(3)分析验证,(4)V3框架定义的临床验证;(5)效用和可用性评估。使用EVIDENCE,那些准备、阅读或审查评估数字测量产品的研究的人将更好地区分必要的报告要求,以推动高质量的研究。随着广泛采用,EVIDENCE清单将作为急需的指南,提高已发表文献评估数字测量产品的质量报告标准。
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
Digital Biomarkers
Digital Biomarkers Medicine-Medicine (miscellaneous)
CiteScore
10.60
自引率
0.00%
发文量
12
审稿时长
23 weeks
期刊最新文献
The Imperative of Voice Data Collection in Clinical Trials. eHealth and mHealth in Antimicrobial Stewardship Programs. Detecting Longitudinal Trends between Passively Collected Phone Use and Anxiety among College Students. Video Assessment to Detect Amyotrophic Lateral Sclerosis. Digital Vocal Biomarker of Smoking Status Using Ecological Audio Recordings: Results from the Colive Voice Study.
×
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