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Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time

BACKGROUND: When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of ge...

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Autores principales: Rich, Carly, Geraci, Marco, Griffiths, Lucy, Sera, Francesco, Dezateux, Carol, Cortina-Borja, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691227/
https://www.ncbi.nlm.nih.gov/pubmed/23826236
http://dx.doi.org/10.1371/journal.pone.0067206
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author Rich, Carly
Geraci, Marco
Griffiths, Lucy
Sera, Francesco
Dezateux, Carol
Cortina-Borja, Mario
author_facet Rich, Carly
Geraci, Marco
Griffiths, Lucy
Sera, Francesco
Dezateux, Carol
Cortina-Borja, Mario
author_sort Rich, Carly
collection PubMed
description BACKGROUND: When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability. METHODS: Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r) of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours) and wear days (one to seven days). Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data. RESULTS: At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86) and sample size (n = 6,528) was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear. CONCLUSION: Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It’s unnecessary to include only children with accelerometer data collected during weekends in analyses.
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spelling pubmed-36912272013-07-03 Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time Rich, Carly Geraci, Marco Griffiths, Lucy Sera, Francesco Dezateux, Carol Cortina-Borja, Mario PLoS One Research Article BACKGROUND: When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability. METHODS: Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r) of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours) and wear days (one to seven days). Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data. RESULTS: At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86) and sample size (n = 6,528) was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear. CONCLUSION: Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It’s unnecessary to include only children with accelerometer data collected during weekends in analyses. Public Library of Science 2013-06-24 /pmc/articles/PMC3691227/ /pubmed/23826236 http://dx.doi.org/10.1371/journal.pone.0067206 Text en © 2013 Rich et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Rich, Carly
Geraci, Marco
Griffiths, Lucy
Sera, Francesco
Dezateux, Carol
Cortina-Borja, Mario
Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title_full Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title_fullStr Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title_full_unstemmed Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title_short Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
title_sort quality control methods in accelerometer data processing: defining minimum wear time
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691227/
https://www.ncbi.nlm.nih.gov/pubmed/23826236
http://dx.doi.org/10.1371/journal.pone.0067206
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