Identifying Data Quality Dimensions for Person-Generated Wearable Device Data: Multi-Method Study.

ABSTRACT:

Background

There is a growing interest in using person-generated wearable device data for biomedical research, but there are also concerns regarding the quality of data such as missing or incorrect data. This emphasizes the importance of assessing data quality before conducting research. In order to perform data quality assessments, it is essential to define what data quality means for person-generated wearable device data by identifying the data quality dimensions.

Objective

This study aims to identify data quality dimensions for person-generated wearable device data for research purposes.

Methods

This study was conducted in 3 phases: literature review, survey, and focus group discussion. The literature review was conducted following the PRISMA (Preferred Reporting I

SUBMITTER: Cho S 

PROVIDER: S-EPMC8738984 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature