An interactive fitness-for-use data completeness tool to assess activity tracker data

Author:

Cho Sylvia1ORCID,Ensari Ipek23ORCID,Elhadad Noémie14,Weng Chunhua14,Radin Jennifer M5,Bent Brinnae6,Desai Pooja1,Natarajan Karthik14ORCID

Affiliation:

1. Department of Biomedical Informatics, Columbia University , New York, New York, USA

2. Department of Artificial Intelligence and Human Health, Icahn School of Medicine , New York, New York, USA

3. Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai , New York, New York, USA

4. Data Science Institute, Columbia University , New York, New York, USA

5. Scripps Research Translational Institute , La Jolla, California, USA

6. Department of Biomedical Engineering, Duke University , Durham, North Carolina, USA

Abstract

Abstract Objective To design and evaluate an interactive data quality (DQ) characterization tool focused on fitness-for-use completeness measures to support researchers’ assessment of a dataset. Materials and Methods Design requirements were identified through a conceptual framework on DQ, literature review, and interviews. The prototype of the tool was developed based on the requirements gathered and was further refined by domain experts. The Fitness-for-Use Tool was evaluated through a within-subjects controlled experiment comparing it with a baseline tool that provides information on missing data based on intrinsic DQ measures. The tools were evaluated on task performance and perceived usability. Results The Fitness-for-Use Tool allows users to define data completeness by customizing the measures and its thresholds to fit their research task and provides a data summary based on the customized definition. Using the Fitness-for-Use Tool, study participants were able to accurately complete fitness-for-use assessment in less time than when using the Intrinsic DQ Tool. The study participants perceived that the Fitness-for-Use Tool was more useful in determining the fitness-for-use of a dataset than the Intrinsic DQ Tool. Discussion Incorporating fitness-for-use measures in a DQ characterization tool could provide data summary that meets researchers needs. The design features identified in this study has potential to be applied to other biomedical data types. Conclusion A tool that summarizes a dataset in terms of fitness-for-use dimensions and measures specific to a research question supports dataset assessment better than a tool that only presents information on intrinsic DQ measures.

Funder

National Center for Advancing Translational Sciences

National Institute of Health’s All of Us Research Program

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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