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评估联网传感器技术的研究的证据发表清单:解释与阐述

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

作者信息

Manta Christine, Mahadevan Nikhil, Bakker Jessie, Ozen Irmak Simal, Izmailova Elena, Park Siyeon, Poon Jiat-Ling, Shevade Santosh, Valentine Sarah, Vandendriessche Benjamin, Webster Courtney, Goldsack Jennifer C

机构信息

Digital Medicine Society, Boston, Massachusetts, USA.

Elektra Labs, Boston, Massachusetts, USA.

出版信息

Digit Biomark. 2021 May 18;5(2):127-147. doi: 10.1159/000515835. eCollection 2021 May-Aug.

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.

摘要

“证据”(评估互联传感器技术)清单由数字医学协会召集的多学科内容专家小组制定,这些专家代表临床科学、数据管理、技术开发和生物统计学领域。“证据”的目的是在主要目标是评估数字测量产品或其组成部分的研究中促进高质量报告。在这里,我们互换使用数字测量产品和互联传感器技术这两个术语,来指代使用算法处理移动传感器捕获的数据以生成行为和/或生理功能测量值的工具。“证据”适用于5种类型的评估:(1)概念验证;(2)验证;(3)分析验证;(4)V3框架定义的临床验证;以及(5)效用和可用性评估。使用“证据”,那些准备、阅读或审查评估数字测量产品的研究的人员将更有能力区分必要的报告要求,以推动高质量研究。随着广泛采用,“证据”清单将成为提高已发表文献中评估数字测量产品的质量报告标准的急需指南。

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