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http://hdl.handle.net/20.500.12207/4981
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Title: Modeling fitness variable responses to training In prepubescent children
Authors: Alves, Ana R
Marta, Carlos
Neiva, Henrique P
Nunes, Célia
Izquierdo, Mikel
Marques, Mário C
Keywords: Concurrent training
Explosive
linear regression
Youth
Issue Date: 16-Nov-2017
Abstract: The aim of this study was to determine strength and oxygen uptake (VO2max) performances according to different training program intervention design with 8-weeks duration in prepubescent children through a multiple linear regression models. Two hundred and forty-five healthy prepubescent children (aged 10.9 ± 0.5 years) were randomly assigned to a specific training program (strength training only - S; aerobic training only - A; intra-session aerobic and strength training - AS; intra-session strength and aerobic training - SA; or concurrent training performed in different sessions - CT) or a control group (no training regimen - C). It was possible to develop indirect predictive models for each training method, by including each variable pre-training, body fat percentage and body mass index. The models provided explained 82% of variance in the VO2max, 98% in the 1kg ball-throw, 96% in the 3kg ball-throw, 92% in the counter-movement jump, 93% in the standing long jump and 98% in the 20m sprint performances. This novel approach to training evaluation and control aims to provide a tool to allow professionals to calculate changes with a high confidence level (CI 95%), to control gains and to choose the best training methodology to apply according to the defined purposes. The results of this study could be a great support to teachers, coaches and professionals providing important tools to improve the efficacy and individualization of training.
Peer reviewed: yes
URI: http://hdl.handle.net/20.500.12207/4981
metadata.dc.identifier.doi: 10.1519/JSC.0000000000002201
ISSN: 1064-8011
Publisher version: https://dx.doi.org/10.1519/JSC.0000000000002201
Appears in Collections:D-ECSC - Artigos em revistas com peer review

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