Evaluation of Within- and Between-Site Agreement for Direct Observation of Physical Behavior Across Four Research Groups

Author:

Keadle Sarah Kozey1ORCID,Martinez Julian2ORCID,Strath Scott J.2,Sirard John3,John Dinesh4ORCID,Intille Stephen45ORCID,Arguello Diego4ORCID,Amalbert-Birriel Marcos3,Barnett Rachel1,Thapa-Chhetry Binod45ORCID,Cox Melanna3ORCID,Chase John3,Dooley Erin6ORCID,Marcotte Rob3,Tolas Alexander1ORCID,Staudemayer John W.7

Affiliation:

1. Department of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA, USA

2. Department of Kinesiology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA

3. Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA

4. Department of Health Sciences, Northeastern University, Boston, MA, USA

5. Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA

6. Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA

7. Department of Math and Statistics, University of Massachusetts Amherst, Amherst, MA, USA

Abstract

Direct observation (DO) is a widely accepted ground-truth measure, but the field lacks standard operational definitions. Research groups develop project-specific annotation platforms, limiting the utility of DO if labels are not consistent. Purpose: The purpose was to evaluate within- and between-site agreement for DO taxonomies (e.g., activity intensity category) across four independent research groups who have used video-recorded DO. Methods: Each site contributed video files (508 min) and had two trained research assistants annotate the shared video files according to their existing annotation protocols. The authors calculated (a) within-site agreement for the two coders at the same site expressed as intraclass correlation and (b) between-site agreement, the proportion of seconds that agree between any two coders regardless of site. Results: Within-site agreement at all sites was good–excellent for both activity intensity categories (intraclass correlation range: .82–.9) and posture/whole-body movement (intraclass correlation range: .77–.98). Between-site agreement for intensity categories was 94.6% for sedentary, 80.9% for light, and 82.8% for moderate–vigorous. Three of the four sites had common labels for eight posture/whole-body movements and had within-site agreements of 94.5% and between-site agreements of 86.1%. Conclusions: Distinct research groups can annotate key features of physical behavior with good-to-excellent interrater reliability. Operational definitions are provided for core metrics for researchers to consider in future studies to facilitate between-study comparisons and data pooling, enabling the deployment of deep learning approaches to wearable device algorithm calibration.

Publisher

Human Kinetics

Subject

Public Health, Environmental and Occupational Health,Statistics, Probability and Uncertainty,General Psychology,General Engineering,General Computer Science

Reference37 articles.

1. 2011 compendium of physical activities: A second update of codes and MET values;Ainsworth, B.E.,2011

2. American time use survey,2020

3. A novel video-based direct observation system for assessing physical activity and sedentary behavior in children and young adults;Cox, M.F.,2020

4. Validity of ActiGraph 2-regression model, Matthews cut-points, and NHANES cut-points for assessing free-living physical activity;Crouter, S.E.,2013

5. Datavyu: Video coding tool,2014

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