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Related Experiment Videos

A model for presenting accelerometer paradata in large studies: ISCOLE.

Catrine Tudor-Locke1, Emily F Mire2, Kara N Dentro3

  • 1Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA, 70808, USA. tudor-locke@pbrc.edu.

The International Journal of Behavioral Nutrition and Physical Activity
|May 1, 2015
PubMed

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Summary
This summary is machine-generated.

This study introduces a model for reporting accelerometer paradata in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE). Detailed paradata improves survey management, representativeness, and cost control for multi-national research.

Area of Science:

  • Epidemiology
  • Public Health
  • Biostatistics

Background:

  • Presents a model for reporting accelerometer paradata from the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE).
  • ISCOLE is a multi-national investigation involving over 7000 children across 12 countries.
  • Focuses on process-related data generated during survey administration.

Purpose of the Study:

  • To establish a standardized model for collecting and reporting accelerometer paradata.
  • To enhance the management and quality of data in large-scale, multi-national health studies.
  • To improve the representativeness and comparability of survey findings.

Main Methods:

  • Utilized a 24-hour, waist-worn, 7-day accelerometer protocol (ActiGraph GT3X+).

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  • Documented paradata using checklists, flow charts, and data queries from enrollment to data treatment.
  • Collected data on participant consent, eligibility, device distribution, data adequacy, wear time, and activity intensity.
  • Main Results:

    • 7372 out of 7806 consented participants were eligible.
    • 90.0% of participants (6553) provided valid data meeting study criteria.
    • Average waking wear time was 14.8 hours/day, with 9.4% of participants showing implausibly high activity counts.

    Conclusions:

    • Detailed accelerometer paradata is crucial for standardizing communication and facilitating study management.
    • Paradata aids in improving survey representativeness and tracking study endpoint attainment.
    • Utilizing paradata helps in anticipating and controlling research costs in multi-national studies.