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Santana CCDA, Barros MVGD, Medeiros FRCD, Rangel Júnior JFLB, Cantieri FP, Alarcon D, Prado WLD. Does Physical Fitness Relate to Academic Achievement in High School Students? J Phys Act Health 2023; 20:1018-1026. [PMID: 37536682 DOI: 10.1123/jpah.2022-0534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 06/07/2023] [Accepted: 06/12/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND Academic achievement (AA) is an important issue not only during the school period since it is a strong predictor of long-term professional and social success. Physical fitness (PF) components are associated with AA, and previous studies were conducted with relatively small samples, lack of statistical power, and the conclusions are based on simple correlational analyses. The objective of this study was to analyze the association between PF (single and clustered) with AA in a large and representative sample of high school students. METHODS Cross-sectional design study conducted with 911 students, aged 13-15 years (38.52% boys) enrolled in the first year of high school. Cardiorespiratory fitness (20-m shuttle run test), muscular strength (dynamometer), and body composition (skinfolds) were measured. PF components were clustered (Z-cardiorespiratory fitness + Z-muscular strength - Z-body fatness). AA was analyzed through standard math tests. Hierarchical linear regression analysis was applied to verify the independent contribution of each single component and PF's cluster on AA. Age, screen time, maternal education, race, and type of residence were used as covariates. RESULTS Among boys, cardiorespiratory fitness was negatively associated with AA (β = -0.137; P = .041), while strength was positively associated with AA (β = 0.188; P = .004). There was no association between clustered PF indicators and AA (β = 0.064; P = .297). There was a negative association between age and AA in girls (β = -0.151; P = .003) and in boys (β = -0.128; P = .045). CONCLUSIONS These results support current literature, indicating an association between PF's component, namely muscular strength and AA (mathematics) in adolescents, even when controlled for several covariates.
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Affiliation(s)
| | | | | | | | | | - Daniela Alarcon
- California State University San Bernardino, San Bernardino, CA,USA
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Robinson K, Riley N, Owen K, Drew R, Mavilidi MF, Hillman CH, Faigenbaum AD, Garcia-Hermoso A, Lubans DR. Effects of Resistance Training on Academic Outcomes in School-Aged Youth: A Systematic Review and Meta-Analysis. Sports Med 2023; 53:2095-2109. [PMID: 37466900 PMCID: PMC10587249 DOI: 10.1007/s40279-023-01881-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/19/2023] [Indexed: 07/20/2023]
Abstract
BACKGROUND The primary aim of our systematic review and meta-analysis was to investigate the effect of resistance training on academic outcomes in school-aged youth. METHODS We conducted a systematic search of six electronic databases (CINAHL Complete, PsycINFO, SCOPUS, Ovid MEDLINE, SPORTDiscus and EMBASE) with no date restrictions. Studies were eligible if they: (a) included school-aged youth (5-18 years), and (b) examined the effect of resistance training on academic outcomes (i.e., cognitive function, academic achievement, and/or on-task behaviour in the classroom). Risk of bias was assessed using the appropriate Cochrane Risk of Bias Tools, funnel plots and Egger's regression asymmetry tests. A structural equation modelling approach was used to conduct the meta-analysis. RESULTS Fifty-three studies were included in our systematic review. Participation in resistance training (ten studies with 53 effect sizes) had a small positive effect on the overall cognitive, academic and on-task behaviours in school-aged youth (standardized mean difference (SMD) 0.19, 95% confidence interval (CI) 0.05-0.32). Resistance training was more effective (SMD 0.26, 95% CI 0.10-0.42) than concurrent training, i.e., the combination of resistance training and aerobic training (SMD 0.11, 95% CI - 0.05-0.28). An additional 43 studies (including 211 effect sizes) examined the association between muscular fitness and cognition or academic achievement, also yielding a positive relationship (SMD 0.13, 95% CI 0.10-0.16). CONCLUSION This review provides preliminary evidence that resistance training may improve cognitive function, academic performance, and on-task behaviours in school-aged youth. PROSPERO REGISTRATION CRD42020175695.
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Affiliation(s)
- Katie Robinson
- Centre for Active Living and Learning, College of Human and Social Futures, University of Newcastle, Callaghan Campus, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute (HMRI), New Lambton, NSW, Australia
| | - Nicholas Riley
- Centre for Active Living and Learning, College of Human and Social Futures, University of Newcastle, Callaghan Campus, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute (HMRI), New Lambton, NSW, Australia
| | - Katherine Owen
- Prevention Research Collaboration, Sydney School of Public Health, The University of Sydney, Sydney, NSW, Australia
| | - Ryan Drew
- Centre for Active Living and Learning, College of Human and Social Futures, University of Newcastle, Callaghan Campus, Callaghan, NSW, 2308, Australia
- School of Environmental and Life Sciences, College of Engineering, Science and Environment, Newcastle, NSW, Australia
| | - Myrto F Mavilidi
- School of Education/Early Start, University of Wollongong, Wollongong, NSW, Australia
- Illawarra Health and Medical Research Institute (IHMRI), Keiraville, Australia
| | - Charles H Hillman
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University, Boston, MA, USA
| | - Avery D Faigenbaum
- Department of Kinesiology and Health Sciences, The College of New Jersey, Ewing, NJ, 08628, USA
| | - Antonio Garcia-Hermoso
- Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain
| | - David Revalds Lubans
- Centre for Active Living and Learning, College of Human and Social Futures, University of Newcastle, Callaghan Campus, Callaghan, NSW, 2308, Australia.
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
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The Relationship between Physical Activity and Academic Achievement in Multimodal Environment Using Computational Analysis. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:9418004. [PMID: 36082350 PMCID: PMC9448553 DOI: 10.1155/2022/9418004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/04/2022] [Accepted: 07/13/2022] [Indexed: 11/30/2022]
Abstract
Health has always been recognized as the imperative parameter to excel in any field whether professional or personal. People with sound health having regular habit of physical activities show more potential in their professional and personal lives than the people who do not participate in the physical activities. Many state-of-the-art studies exist in the literature where researchers have proved the significance of physical activities as supportive treatment for the existing ailments and in improving the overall health of human beings. Our research aims at accessing the correlation between physical activities carried out by the students and its impact on the success rate of academic achievements. The study is using computational techniques to investigate the relevance of physical activities on the academic achievements of middle school children. The study employs data mining techniques for processing the data. The computational methods are used in a multimodal environment where the surrounding parameters of the environment are considered before performing computational techniques on the subjects (participants in terms of sample for the study). In this cross-sectional study, we have considered the data on various physical activities such as aerobic fitness, running, playing, and participation in extracurricular activities. After collection of data in a real multimodal environment from middle school students, the data preprocessing is performed to handle the missing values. Then, the computational techniques are applied in a step-by-step approach using regression and the bootstrap methods to examine the data and predict the outcome. The correlation is assessed between academic achievements and physical activities. The outcome predicts that physical activities promote the success rate of academic achievements including extra-curricular activities.
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