BACKGROUND: Half-marathon races have become increasingly more popular with many recreational athletes all around the world. New and recreational runners are likely to have the greatest need for training advice to set running paces during long-distance races. PURPOSE: To develop a simple equation to estimate half-marathon time from the Cooper test and verify its validity. METHODS: One hundred ninety-eight recreational runners (177 men and 21 women, 40 [6.8] years and 33.7 [8] years, respectively) participated in this study. All runners completed the Cooper test 7 to 10 days prior to races. A stepwise multiple regression analysis was performed to select the main predictors of half-marathon time. RESULTS: Simple correlation analysis showed that Cooper test performance (distance) was a good construct to estimate half-marathon time (r = -.906; 95% confidence interval, -0.927 to -0.877; P < .0001). The authors also derived an equation with a high predictive validity (R2 = .82; standard error of estimation = 5.19 min) and low systematic bias (mean differences between the predicted value and the criterion of 0.48 [5.2] min). Finally, the concordance coefficient of correlation (.9038) and proportional bias analysis (Kendall τ = -.0799; 95% confidence interval, -0.184 to 0.00453; P = .09) confirmed a good concurrent validity. CONCLUSION: In this study, the authors derived an equation from the Cooper test data with a high predictive and concurrent validity and low bias.
BACKGROUND: Half-marathon races have become increasingly more popular with many recreational athletes all around the world. New and recreational runners are likely to have the greatest need for training advice to set running paces during long-distance races. PURPOSE: To develop a simple equation to estimate half-marathon time from the Cooper test and verify its validity. METHODS: One hundred ninety-eight recreational runners (177 men and 21 women, 40 [6.8] years and 33.7 [8] years, respectively) participated in this study. All runners completed the Cooper test 7 to 10 days prior to races. A stepwise multiple regression analysis was performed to select the main predictors of half-marathon time. RESULTS: Simple correlation analysis showed that Cooper test performance (distance) was a good construct to estimate half-marathon time (r = -.906; 95% confidence interval, -0.927 to -0.877; P < .0001). The authors also derived an equation with a high predictive validity (R2 = .82; standard error of estimation = 5.19 min) and low systematic bias (mean differences between the predicted value and the criterion of 0.48 [5.2] min). Finally, the concordance coefficient of correlation (.9038) and proportional bias analysis (Kendall τ = -.0799; 95% confidence interval, -0.184 to 0.00453; P = .09) confirmed a good concurrent validity. CONCLUSION: In this study, the authors derived an equation from the Cooper test data with a high predictive and concurrent validity and low bias.
Entities:
Keywords:
PRESS validation; concordance correlation coefficient; pace prediction; running performance
Authors: José Ramón Alvero-Cruz; Elvis A Carnero; Manuel Avelino Giráldez García; Fernando Alacid; Lorena Correas-Gómez; Thomas Rosemann; Pantelis T Nikolaidis; Beat Knechtle Journal: Int J Environ Res Public Health Date: 2020-11-09 Impact factor: 3.390