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Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses

BACKGROUND: The Canadian Assessment of Physical Literacy (CAPL) is a 25-indicator assessment tool comprising four domains of physical literacy: (1) Physical Competence, (2) Daily Behaviour, (3) Motivation and Confidence, and (4) Knowledge and Understanding. The purpose of this study was to re-examin...

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Autores principales: Gunnell, Katie E., Longmuir, Patricia E., Barnes, Joel D., Belanger, Kevin, Tremblay, Mark S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167769/
https://www.ncbi.nlm.nih.gov/pubmed/30285682
http://dx.doi.org/10.1186/s12889-018-5899-2
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author Gunnell, Katie E.
Longmuir, Patricia E.
Barnes, Joel D.
Belanger, Kevin
Tremblay, Mark S.
author_facet Gunnell, Katie E.
Longmuir, Patricia E.
Barnes, Joel D.
Belanger, Kevin
Tremblay, Mark S.
author_sort Gunnell, Katie E.
collection PubMed
description BACKGROUND: The Canadian Assessment of Physical Literacy (CAPL) is a 25-indicator assessment tool comprising four domains of physical literacy: (1) Physical Competence, (2) Daily Behaviour, (3) Motivation and Confidence, and (4) Knowledge and Understanding. The purpose of this study was to re-examine the factor structure of CAPL scores and the relative weight of each domain for an overall physical literacy factor. Our goal was to maximize content representation, and reduce construct irrelevant variance and participant burden, to inform the development of CAPL-2 (a revised, shorter, and theoretically stronger version of CAPL). METHODS: Canadian children (n = 10,034; M(age) = 10.6, SD = 1.2; 50.1% girls) completed CAPL testing at one time point. Confirmatory factor analysis was used. RESULTS: Based on weak factor loadings (λs < 0.32) and conceptual alignment, we removed body mass index, waist circumference, sit-and-reach flexibility, and grip strength as indicators of Physical Competence. Based on the factor loading (λ < 0.35) and conceptual alignment, we removed screen time as an indicator of Daily Behaviour. To reduce redundancy, we removed children’s activity compared to other children as an indicator of Motivation and Confidence. Based on low factor loadings (λs < 0.35) and conceptual alignment, we removed knowledge of screen time guidelines, what it means to be healthy, how to improve fitness, activity preferences, and physical activity safety gear indicators from the Knowledge and Understanding domain. The final refined CAPL model was comprised of 14 indicators, and the four-factor correlated model fit the data well (r ranged from 0.08 to 0.76), albeit with an unexpected cross-loading from Daily Behaviour to knowledge of physical activity guidelines (mean- and variance-adjusted weighted least square [WLSMV] χ(2)((70)) = 1221.29, p < 0.001, Comparative Fit Index [CFI] = 0.947, root mean square error of approximation [RMSEA] = 0.041[0.039, 0.043]). Finally, our higher-order model with Physical Literacy as a factor with indicators of Physical Competence (λ = 0.68), Daily Behaviour (λ = 0.91), Motivation and Confidence (λ = 0.80), and Knowledge and Understanding (λ = 0.21) fit the data well. CONCLUSIONS: The scores from the revised and much shorter 14-indicator model of CAPL can be used to assess the four correlated domains of physical literacy and/or a higher-order aggregate physical literacy factor. The results of this investigation will inform the development of CAPL-2.
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spelling pubmed-61677692018-10-09 Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses Gunnell, Katie E. Longmuir, Patricia E. Barnes, Joel D. Belanger, Kevin Tremblay, Mark S. BMC Public Health Research BACKGROUND: The Canadian Assessment of Physical Literacy (CAPL) is a 25-indicator assessment tool comprising four domains of physical literacy: (1) Physical Competence, (2) Daily Behaviour, (3) Motivation and Confidence, and (4) Knowledge and Understanding. The purpose of this study was to re-examine the factor structure of CAPL scores and the relative weight of each domain for an overall physical literacy factor. Our goal was to maximize content representation, and reduce construct irrelevant variance and participant burden, to inform the development of CAPL-2 (a revised, shorter, and theoretically stronger version of CAPL). METHODS: Canadian children (n = 10,034; M(age) = 10.6, SD = 1.2; 50.1% girls) completed CAPL testing at one time point. Confirmatory factor analysis was used. RESULTS: Based on weak factor loadings (λs < 0.32) and conceptual alignment, we removed body mass index, waist circumference, sit-and-reach flexibility, and grip strength as indicators of Physical Competence. Based on the factor loading (λ < 0.35) and conceptual alignment, we removed screen time as an indicator of Daily Behaviour. To reduce redundancy, we removed children’s activity compared to other children as an indicator of Motivation and Confidence. Based on low factor loadings (λs < 0.35) and conceptual alignment, we removed knowledge of screen time guidelines, what it means to be healthy, how to improve fitness, activity preferences, and physical activity safety gear indicators from the Knowledge and Understanding domain. The final refined CAPL model was comprised of 14 indicators, and the four-factor correlated model fit the data well (r ranged from 0.08 to 0.76), albeit with an unexpected cross-loading from Daily Behaviour to knowledge of physical activity guidelines (mean- and variance-adjusted weighted least square [WLSMV] χ(2)((70)) = 1221.29, p < 0.001, Comparative Fit Index [CFI] = 0.947, root mean square error of approximation [RMSEA] = 0.041[0.039, 0.043]). Finally, our higher-order model with Physical Literacy as a factor with indicators of Physical Competence (λ = 0.68), Daily Behaviour (λ = 0.91), Motivation and Confidence (λ = 0.80), and Knowledge and Understanding (λ = 0.21) fit the data well. CONCLUSIONS: The scores from the revised and much shorter 14-indicator model of CAPL can be used to assess the four correlated domains of physical literacy and/or a higher-order aggregate physical literacy factor. The results of this investigation will inform the development of CAPL-2. BioMed Central 2018-10-02 /pmc/articles/PMC6167769/ /pubmed/30285682 http://dx.doi.org/10.1186/s12889-018-5899-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Gunnell, Katie E.
Longmuir, Patricia E.
Barnes, Joel D.
Belanger, Kevin
Tremblay, Mark S.
Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title_full Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title_fullStr Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title_full_unstemmed Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title_short Refining the Canadian Assessment of Physical Literacy based on theory and factor analyses
title_sort refining the canadian assessment of physical literacy based on theory and factor analyses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167769/
https://www.ncbi.nlm.nih.gov/pubmed/30285682
http://dx.doi.org/10.1186/s12889-018-5899-2
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