Pedro F Saint-Maurice1, Youngwon Kim2, Paul Hibbing3, April Y Oh4, Frank M Perna5, Gregory J Welk3. 1. Department of Kinesiology, Iowa State University, Ames, Iowa; School of Psychology, University of Minho, Braga, Portugal. Electronic address: pedro.saintmaurice@nih.gov. 2. Department of Kinesiology, Iowa State University, Ames, Iowa; MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom. 3. Department of Kinesiology, Iowa State University, Ames, Iowa. 4. Health Communication and Informatics Research Branch, Behavioral Research Program, National Cancer Institute, Bethesda, Maryland. 5. Health Behaviors Research Branch, Behavioral Research Program, National Cancer Institute, Bethesda, Maryland.
Abstract
INTRODUCTION: This study describes the calibration and validity of the Youth Activity Profile (YAP) for use in the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating (FLASHE) study. The calibrated YAP was designed to estimate minutes of moderate to vigorous physical activity (MVPA) and sedentary behavior (SB). METHODS: The YAP was calibrated/validated in adolescents (aged 12-17 years) using cross-sectional data from the FLASHE study. Participants wore a GT3X+ ActiGraph on the dominant wrist for 7 days and then completed the YAP. Calibration was conducted for school (n=118); out of school (n=119); weekend (n=61); and SB (n=116) subsections of the YAP and by regressing percentage time in MVPA/SB (%MVPA/%SB) on each respective YAP subsection score, age, and the interaction between these two. The final algorithms were applied to independent samples (n=39-51) to examine validity (median absolute percentage error, equivalence testing). RESULTS: The final algorithms explained 15% (school); 16% (out of school); and 12% (weekend) of the variability in GT3X+ %MVPA and 7% of the variability in GT3X+ %SB. The calibrated algorithms were applied to independent samples and predicted GT3X+ minutes of MVPA/SB, with median absolute percentage error values ranging from 12.5% (SB section) to 32.5% (weekend section). Predicted values obtained from the YAP were within 10%-20% of those produced by the GT3X+. CONCLUSIONS: The YAP-predicted minutes of MVPA/SB resulted in similar group estimates obtained from an objective measure. The YAP offers good utility for large-scale research projects to characterize PA/SB levels among groups of youth.
INTRODUCTION: This study describes the calibration and validity of the Youth Activity Profile (YAP) for use in the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating (FLASHE) study. The calibrated YAP was designed to estimate minutes of moderate to vigorous physical activity (MVPA) and sedentary behavior (SB). METHODS: The YAP was calibrated/validated in adolescents (aged 12-17 years) using cross-sectional data from the FLASHE study. Participants wore a GT3X+ ActiGraph on the dominant wrist for 7 days and then completed the YAP. Calibration was conducted for school (n=118); out of school (n=119); weekend (n=61); and SB (n=116) subsections of the YAP and by regressing percentage time in MVPA/SB (%MVPA/%SB) on each respective YAP subsection score, age, and the interaction between these two. The final algorithms were applied to independent samples (n=39-51) to examine validity (median absolute percentage error, equivalence testing). RESULTS: The final algorithms explained 15% (school); 16% (out of school); and 12% (weekend) of the variability in GT3X+ %MVPA and 7% of the variability in GT3X+ %SB. The calibrated algorithms were applied to independent samples and predicted GT3X+ minutes of MVPA/SB, with median absolute percentage error values ranging from 12.5% (SB section) to 32.5% (weekend section). Predicted values obtained from the YAP were within 10%-20% of those produced by the GT3X+. CONCLUSIONS: The YAP-predicted minutes of MVPA/SB resulted in similar group estimates obtained from an objective measure. The YAP offers good utility for large-scale research projects to characterize PA/SB levels among groups of youth.
Authors: M Hagströmer; P Bergman; I De Bourdeaudhuij; F B Ortega; J R Ruiz; Y Manios; J P Rey-López; K Phillipp; J von Berlepsch; M Sjöström Journal: Int J Obes (Lond) Date: 2008-11 Impact factor: 5.095
Authors: C E Matthews; P S Freedson; J R Hebert; E J Stanek; P A Merriam; M C Rosal; C B Ebbeling; I S Ockene Journal: Am J Epidemiol Date: 2001-01-15 Impact factor: 4.897
Authors: Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell Journal: Med Sci Sports Exerc Date: 2008-01 Impact factor: 5.411
Authors: April Y Oh; Terisa Davis; Laura A Dwyer; Erin Hennessy; Tiandong Li; Amy L Yaroch; Linda C Nebeling Journal: Am J Prev Med Date: 2017-06 Impact factor: 5.043
Authors: Philip M Dixon; Pedro F Saint-Maurice; Youngwon Kim; Paul Hibbing; Yang Bai; Gregory J Welk Journal: Med Sci Sports Exerc Date: 2018-04 Impact factor: 5.411
Authors: Gregory J Welk; Pedro F Saint-Maurice; Youngwon Kim; Laura D Ellingson; Paul Hibbing; Dana L Wolff-Hughes; Frank M Perna Journal: Am J Prev Med Date: 2017-06 Impact factor: 5.043
Authors: Linda C Nebeling; Erin Hennessy; April Y Oh; Laura A Dwyer; Heather Patrick; Heidi M Blanck; Frank M Perna; Rebecca A Ferrer; Amy L Yaroch Journal: Am J Prev Med Date: 2017-06 Impact factor: 5.043