Agility as a predictor of physical literacy, activity levels and sport involvement
Objective: Given the increasing importance being placed on levels of youths’ physical literacy (PL), physical activity (PA) and sport involvement (SI), it would seem plausible to investigate a common physical activity outcome (PAO) that would go to predict success throughout these domains. The impac...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2019-01-01
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| Series: | Cogent Education |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/2331186X.2019.1661582 |
| _version_ | 1797715179589337088 |
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| author | Wayne Usher |
| author_facet | Wayne Usher |
| author_sort | Wayne Usher |
| collection | DOAJ |
| description | Objective: Given the increasing importance being placed on levels of youths’ physical literacy (PL), physical activity (PA) and sport involvement (SI), it would seem plausible to investigate a common physical activity outcome (PAO) that would go to predict success throughout these domains. The impact of various demographic variables, on physical performance, is of interest. This study hypothesised that levels of agility predict the success in a number of PAOs. Design: A variance (ANOVA), with repeated measures, was conducted to determine if the physical performance responses differed significantly from each other for selected PAO. Setting: Two hundred and thirty-four (234) school-aged students (11–17+ years) had data (quantitative) collected across six PAOs, which were selected based on their inherent connections to domains. Method: Correlation matrices and Structural Equation Modelling (SEM) were further used to examine and diagrammatically represent the significance (p < 0.05—p < 0.000) of associations and relationships (r) between levels of agility and each PAO. Results: Strength of the direct effect identifies that higher levels of agility, being male (r = .208**, p < 0.001) and a light—moderate BMI (r = .223**, p < 0.05), significantly moderates the pathways between all PAOs. The SEM indicated that the approach fits the data set very well (p < .05, Chi Square/DF<3, and other fit values in the .95–1.00 region). Conclusion: Findings suggest that more attention should be directed towards promoting the inherent benefits of improving school-aged students’ agility levels, with an aim to developing reciprocating positive impacts on domains. |
| first_indexed | 2024-03-12T08:03:04Z |
| format | Article |
| id | doaj.art-8176ccdb738b4fd9af8b407856844aa4 |
| institution | Directory Open Access Journal |
| issn | 2331-186X |
| language | English |
| last_indexed | 2024-03-12T08:03:04Z |
| publishDate | 2019-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Education |
| spelling | doaj.art-8176ccdb738b4fd9af8b407856844aa42023-09-02T19:44:07ZengTaylor & Francis GroupCogent Education2331-186X2019-01-016110.1080/2331186X.2019.16615821661582Agility as a predictor of physical literacy, activity levels and sport involvementWayne Usher0Gold Coast campus, Griffith UniversityObjective: Given the increasing importance being placed on levels of youths’ physical literacy (PL), physical activity (PA) and sport involvement (SI), it would seem plausible to investigate a common physical activity outcome (PAO) that would go to predict success throughout these domains. The impact of various demographic variables, on physical performance, is of interest. This study hypothesised that levels of agility predict the success in a number of PAOs. Design: A variance (ANOVA), with repeated measures, was conducted to determine if the physical performance responses differed significantly from each other for selected PAO. Setting: Two hundred and thirty-four (234) school-aged students (11–17+ years) had data (quantitative) collected across six PAOs, which were selected based on their inherent connections to domains. Method: Correlation matrices and Structural Equation Modelling (SEM) were further used to examine and diagrammatically represent the significance (p < 0.05—p < 0.000) of associations and relationships (r) between levels of agility and each PAO. Results: Strength of the direct effect identifies that higher levels of agility, being male (r = .208**, p < 0.001) and a light—moderate BMI (r = .223**, p < 0.05), significantly moderates the pathways between all PAOs. The SEM indicated that the approach fits the data set very well (p < .05, Chi Square/DF<3, and other fit values in the .95–1.00 region). Conclusion: Findings suggest that more attention should be directed towards promoting the inherent benefits of improving school-aged students’ agility levels, with an aim to developing reciprocating positive impacts on domains.http://dx.doi.org/10.1080/2331186X.2019.1661582agilityphysical literacyphysical activitysporting involvementrugby leaguejunior participation |
| spellingShingle | Wayne Usher Agility as a predictor of physical literacy, activity levels and sport involvement Cogent Education agility physical literacy physical activity sporting involvement rugby league junior participation |
| title | Agility as a predictor of physical literacy, activity levels and sport involvement |
| title_full | Agility as a predictor of physical literacy, activity levels and sport involvement |
| title_fullStr | Agility as a predictor of physical literacy, activity levels and sport involvement |
| title_full_unstemmed | Agility as a predictor of physical literacy, activity levels and sport involvement |
| title_short | Agility as a predictor of physical literacy, activity levels and sport involvement |
| title_sort | agility as a predictor of physical literacy activity levels and sport involvement |
| topic | agility physical literacy physical activity sporting involvement rugby league junior participation |
| url | http://dx.doi.org/10.1080/2331186X.2019.1661582 |
| work_keys_str_mv | AT wayneusher agilityasapredictorofphysicalliteracyactivitylevelsandsportinvolvement |