Motor Competence Assessment (MCA) Scoring Method

The Motor Competence Assessment (MCA) is a quantitative test battery that assesses motor competence across the whole lifespan. It is composed of three sub-scales: locomotor, stability, and manipulative, each of them assessed by two different objectively measured tests. The MCA construct validity for...

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Main Authors: Luis Paulo Rodrigues, Carlos Luz, Rita Cordovil, André Pombo, Vitor P. Lopes
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Children
Subjects:
Online Access:https://www.mdpi.com/2227-9067/9/11/1769
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author Luis Paulo Rodrigues
Carlos Luz
Rita Cordovil
André Pombo
Vitor P. Lopes
author_facet Luis Paulo Rodrigues
Carlos Luz
Rita Cordovil
André Pombo
Vitor P. Lopes
author_sort Luis Paulo Rodrigues
collection DOAJ
description The Motor Competence Assessment (MCA) is a quantitative test battery that assesses motor competence across the whole lifespan. It is composed of three sub-scales: locomotor, stability, and manipulative, each of them assessed by two different objectively measured tests. The MCA construct validity for children and adolescents, having normative values from 3 to 23 years of age, and the configural invariance between age groups, were recently established. The aim of this study is to expand the MCA’s development and validation by defining the best and leanest method to score and classify MCA sub-scales and total score. One thousand participants from 3 to 22 years of age, randomly selected from the Portuguese database on MC, participated in the study. Three different procedures to calculate the sub-scales and total MCA values were tested according to alternative models. Results were compared to the reference method, and Intraclass Correlation Coefficient, Cronbach’s Alpha, and Bland–Altman statistics were used to describe agreement between the three methods. The analysis showed no substantial differences between the three methods. Reliability values were perfect (0.999 to 1.000) for all models, implying that all the methods were able to classify everyone in the same way. We recommend implementing the most economic and efficient algorithm, i.e., the configural model algorithm, averaging the percentile scores of the two tests to assess each MCA sub-scale and total scores.
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spelling doaj.art-766f983587d7460f9004c8db5c131e322023-11-24T08:00:43ZengMDPI AGChildren2227-90672022-11-01911176910.3390/children9111769Motor Competence Assessment (MCA) Scoring MethodLuis Paulo Rodrigues0Carlos Luz1Rita Cordovil2André Pombo3Vitor P. Lopes4Instituto Politécnico de Viana do Castelo, Escola Superior Desporto e Lazer de Melgaço, 4900-347 Viana do Castelo, PortugalResearch Center in Sports Performance, Recreation, Innovation and Technology (SPRINT), 4960-320 Melgaço, PortugalFaculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, PortugalResearch Center in Sports Performance, Recreation, Innovation and Technology (SPRINT), 4960-320 Melgaço, PortugalResearch Center in Sports Sciences, Health and Human Development (CIDESD), 5000-801 Vila Real, PortugalThe Motor Competence Assessment (MCA) is a quantitative test battery that assesses motor competence across the whole lifespan. It is composed of three sub-scales: locomotor, stability, and manipulative, each of them assessed by two different objectively measured tests. The MCA construct validity for children and adolescents, having normative values from 3 to 23 years of age, and the configural invariance between age groups, were recently established. The aim of this study is to expand the MCA’s development and validation by defining the best and leanest method to score and classify MCA sub-scales and total score. One thousand participants from 3 to 22 years of age, randomly selected from the Portuguese database on MC, participated in the study. Three different procedures to calculate the sub-scales and total MCA values were tested according to alternative models. Results were compared to the reference method, and Intraclass Correlation Coefficient, Cronbach’s Alpha, and Bland–Altman statistics were used to describe agreement between the three methods. The analysis showed no substantial differences between the three methods. Reliability values were perfect (0.999 to 1.000) for all models, implying that all the methods were able to classify everyone in the same way. We recommend implementing the most economic and efficient algorithm, i.e., the configural model algorithm, averaging the percentile scores of the two tests to assess each MCA sub-scale and total scores.https://www.mdpi.com/2227-9067/9/11/1769human developmentmotor developmentmotor testmotor performancelifespan
spellingShingle Luis Paulo Rodrigues
Carlos Luz
Rita Cordovil
André Pombo
Vitor P. Lopes
Motor Competence Assessment (MCA) Scoring Method
Children
human development
motor development
motor test
motor performance
lifespan
title Motor Competence Assessment (MCA) Scoring Method
title_full Motor Competence Assessment (MCA) Scoring Method
title_fullStr Motor Competence Assessment (MCA) Scoring Method
title_full_unstemmed Motor Competence Assessment (MCA) Scoring Method
title_short Motor Competence Assessment (MCA) Scoring Method
title_sort motor competence assessment mca scoring method
topic human development
motor development
motor test
motor performance
lifespan
url https://www.mdpi.com/2227-9067/9/11/1769
work_keys_str_mv AT luispaulorodrigues motorcompetenceassessmentmcascoringmethod
AT carlosluz motorcompetenceassessmentmcascoringmethod
AT ritacordovil motorcompetenceassessmentmcascoringmethod
AT andrepombo motorcompetenceassessmentmcascoringmethod
AT vitorplopes motorcompetenceassessmentmcascoringmethod