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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Bibliographic Details
Published in:Children (Basel) 2022-11, Vol.9 (11), p.1-9
Main Authors: Rodrigues, Luis Paulo, Luz, Carlos J., Cordovil, Rita, Pombo, André, Lopes, Vitor
Format: Article
Language:English
Subjects:
Age groups
Data collection
Human development
Lifespan
Motor ability
Motor development
Motor performance
Motor test
Pediatrics
Standard scores
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Summary: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 This work was supported by the Portuguese Science Foundation (FCT) under Grant number UIDB/00447/2020 (unit 447); the European Regional Development Fund (ERDF) through the Regional Operational Program North 2020 under Project TECH—Technology, Environment, Creativity and Health, Grant number Norte-01-0145-FEDER-00004; and the Portuguese Science Foundation (FCT) under Grant number UID04045/2020
ISSN:2227-9067
2227-9067
DOI:10.3390/children9111769