The Relationship between Anthropometric, Biomotor, and Psychomotor Factors on the Performance of Paralympic 100 Meters Freestyle Swimming Athletes in National Paralympic Committee Indonesia

Authors

  • Alviyan Yoga Pratama Study Program of Sports Science, Faculty of Sports, Universitas Sebelas Maret https://orcid.org/0009-0009-5847-6726
  • Agus Kristiyanto Study Program of Sports Science, Faculty of Sports, Universitas Sebelas Maret
  • Rony Syaifullah Study Program of Sports Science, Faculty of Sports, Universitas Sebelas Maret
  • Slamet Riyadi Study Program of Sports Science, Faculty of Sports, Universitas Sebelas Maret https://orcid.org/0000-0002-6403-7051
  • Slamet Raharjo Department of Sport Science, Faculty of Sport Science, Universitas Negeri Malang https://orcid.org/0000-0002-0708-867X

DOI:

https://doi.org/10.47197/retos.v56.104869

Keywords:

Anthropometry, biomotor, psychomotor, disabled athletes, swimming speed, achievement

Abstract

This research aims to relationship the anthropometric, biomotor, and psychomotor factors with disabled athlete's swimming speed in the National Paralympic Committee (NPC) (Indonesian) 100-meter freestyle competition in 2022. This research was a cross-sectional study conducted by the National Paralympic Committee (NPC) (Indonesia). The sample used in this research was 15 disabled athletes from NPC Indonesia with the S7-S10 classification who got medals at the ASEAN Para Games event in 2022. The data collection includes seven independent variable tests there are anthropometric factors (height, weight, body mass index, arm length, and leg length); biomotor factors (abdominal muscle strength and arm muscle power); psychomotor factors by measuring balance using Balance Tests; and dependent variables by measuring swimming speed using the 100-meter freestyle swimming ability test. Statistical analysis used the Pearson correlation coefficient test with a significance level of 5%. The results of the Pearson correlation coefficient analysis show that swimming speed was negatively related to body height, body weight, arm length, abdominal muscle strength, and arm muscle power indicating a moderate correlation between variables (p ≤ 0.001). However, unfortunately, other anthropometric variables such as leg length and age showed a weak negative correlation with swimming speed (p ≤ 0.05). Meanwhile, body mass index and balance did not show a significant correlation with swimming speed (p ≥ 0.05). Based on the research results, it was concluded that anthropometric and biomotor factors showed a negative relationship with swimming speed, while psychomotor factors did not.

Keyword: Anthropometry, biomotor, psychomotor, disabled athletes, swimming speed, achievement.

References

Alkhawaldeh, I. M., & Alzughilat, M. O. (2023). Extent of Knowledge and Application the Basics of Biomechanics Among Paralympic Games Coaches. International Journal of Disabilities Sports and Health Sciences, 6(3), 482–495. https://doi.org/10.33438/IJDSHS.1328438.

Bi, Y., Zhao, X., Zhou, Y., Lao, L., & Jiang, S. (2020). Factors associated with the depression among people with disabilities: A cross-sectional study in Chinese communities of Shanghai. Medicine, 99(47), e23331. https://doi.org/10.1097/MD.0000000000023331.

Bond, D., Goodson, L., Oxford, S.W., Nevill, A.M., Duncan, M.J. (2015). The Association between Anthropometric Variables, Functional Movement Screen Scores and 100 m Freestyle Swimming Performance in Youth Swimmers. Sports, 3, 1-11. https://doi.org/10.3390/sports3010001.

Born, D. P., Stöggl, T., Petrov, A., Burkhardt, D., Lüthy, F., & Romann, M. (2020). Analysis of Freestyle Swimming Sprint Start Performance After Maximal Strength or Vertical Jump Training in Competitive Female and Male Junior Swimmers. Journal of Strength and Conditioning Research, 34(2), 323–331. https://doi.org/10.1519/JSC.0000000000003390.

Canpolat, B., & Akyol, B. (2023). Paralympic Awareness of Sports Science Students: Example of TRB1 Region. International Journal of Disabilities Sports and Health Sciences, 6(1), 227–239. https://doi.org/10.33438/ijdshs.1355219.

Cratty, B.J., & Noble, C.E. (2022). Psychomotor Learning. Encyclopedia Britannica. https://www.britannica.com/science/psychomotor-learning.

Delas, S., Babin, J., & Katić, R. (2007). Effects of biomotor structures on performance of competitive gymnastics elements in elementary school female sixth-graders. Collegium antropologicum, 31(4), 979–985.

Engdahl-Høgåsen, L., & Bentzen, M. (2023). How is the participation of individuals with disabilities studied and understood in current research within the sport context? A systematic literature review. International Review of Sport and Exercise Psychology, 1–33. https://doi.org/10.1080/1750984X.2023.2261115.

Ersöz, G., & Esen, S. (2023). An Overview of Paralympic Sport from a Historical and Psychosocial Perspective. International Journal of Disabilities Sports and Health Sciences, 6(1), 475–489. https://doi.org/10.33438/ijdshs.1357682.

Fernandes, A., Afonso, J., Noronha, F., Mezêncio, B., Vilas-Boas, J. P., & Fernandes, R. J. (2023). Intracycle Velocity Variation in Swimming: A Systematic Scoping Review. Bioengineering, 10(3), 1–24. https://doi.org/10.3390/bioengineering10030308.

Gonjo, T., Fernandes, R. J., Vilas-Boas, J. P., & Sanders, R. (2021). Body roll amplitude and timing in backstroke swimming and their differences from front crawl at the same swimming intensities. Scientific Reports, 11(1), 1–12. https://doi.org/10.1038/s41598-020-80711-5.

González Palacio, E. V., Ramírez González, A. F., & Hernández Villa, A. M. (2022). Design and validation of three tests of aerobic power and speed in swimming children. Retos, 44, 1001–1008. https://doi.org/10.47197/retos.v44i0.87910.

Jiménez-Alfageme, R., Jordán, B. R., Camacho, J. D. H., Sospedra, I., Ferriz-Valero, A., Soriano, J. M., & Martínez-Sanz, J. M. (2022). Anthropometric profile in young swimmers. Cultura, Ciencia y Deporte, 17(52), 69–88. https://doi.org/10.12800/ccd.v17i52.1845.

Kauki, M. K., Prasetyo, Y., Rismayanthi, C., Asmuddin, A., Saman, A., Razali, M. N., Mustapha, A., Ali, S. K. S., Hutkemri, H., Sutapa, P., Hardianto, D., Auliana, R., Utami, D., Utami, D. Y., Riyana, A., Amran, A., Pratama, K. W., Trisnadi, R. A., & Astuti, A.T. (2024). Effect of Basic Water Confidence, Flexibility, and Technique on Freestyle Swimming Skill among Elementary School Pupils. Retos, 51, 1415–1423. https://doi.org/10.47197/retos.v51.101599.

Lee, D.-H., Kim, S. Y., Park, J. E., Jeon, H. J., Park, J.-H., & Kawachi, I. (2021). Nationwide trends in prevalence of underweight, overweight, and obesity among people with disabilities in South Korea from 2008 to 2017. International Journal of Obesity, 46(3), 613–622. https://doi.org/10.1038/s41366-021-01030-x.

Lui, C. W., & Lui, H. K. (2023). Who wins the paralympic medals? An analysis of the socio-economic determinants. Journal of Asian Business and Economic Studies, 30(4), 242–256. https://doi.org/10.1108/JABES-01-2022-0020.

Montejano Lozoya, R., Martínez-Alzamora, N., Clemente Marín, G., Guirao-Goris, S. J. A., & Ferrer-Diego, R. M. (2017). Predictive ability of the Mini Nutritional Assessment Short Form (MNA-SF) in a free-living elderly population: a cross-sectional study. PeerJ, 5, e3345. https://doi.org/10.7717/peerj.3345.

Morais, J. E., Barbosa, T. M., Forte, P., Silva, A. J., & Marinho, D. A. (2021). Young Swimmers’ Anthropometrics, Biomechanics, Energetics, and Efficiency as Underlying Performance Factors: A Systematic Narrative Review. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.691919.

Morais, J. E., Barbosa, T. M., Nevill, A. M., Cobley, S., & Marinho, D. A. (2022). Understanding the Role of Propulsion in the Prediction of Front-Crawl Swimming Velocity and in the Relationship Between Stroke Frequency and Stroke Length. Frontiers in physiology, 13, 876838. https://doi.org/10.3389/fphys.2022.876838.

Post, A. K., Koning, R. H., Visscher, C., & Elferink-Gemser, M. T. (2023). Tracking performance and its underlying characteristics in talented swimmers: a longitudinal study during the junior-to-senior transition. Frontiers in Physiology, 14(August). https://doi.org/10.3389/fphys.2023.1221567.

Powell, L., Polsley, S., Casey, D., & Hammond, T. (2023). The Real-Time Classification of Competency Swimming Activity Through Machine Learning. International Journal of Aquatic Research and Education, 14(1). https://doi.org/10.25035/ijare.14.01.06.

Pranoto, A., Cahyono, M. B. A., Yakobus, R., Izzatunnisa, N., Ramadhan, R. N., Rejeki, P. S., Miftahussurur, M., Effendi, W. I., Wungu, C. D. K., & Yamaoka, Y. (2023). Long-Term Resistance-Endurance Combined Training Reduces Pro-Inflammatory Cytokines in Young Adult Females with Obesity. Sports (Basel, Switzerland), 11(3), 54. https://doi.org/10.3390/sports11030054.

Price, T., Cimadoro, G., & Legg, H. S. (2024). Physical performance determinants in competitive youth swimmers: a systematic review. BMC Sports Science, Medicine and Rehabilitation, 16(1). https://doi.org/10.1186/s13102-023-00767-4.

Puce, L., Marinelli, L., Pierantozzi, E., Mori, L., Pallecchi, I., Bonifazi, M., Bove, M., Franchini, E., & Trompetto, C. (2018). Training methods and analysis of races of a top level Paralympic swimming athlete. Journal of Exercise Rehabilitation, 14(4), 612–620. https://doi.org/10.12965/jer.1836254.127.

Raharjo, S., Pranoto, A., Rejeki, P. S., Harisman, A. S. M., Pamungkas, Y. P., & Andiana, O. (2021). Negative Correlation between Serum Brain-derived Neurotrophic Factor Levels and Obesity Predictor Markers and Inflammation Levels in Females with Obesity. Open Access Macedonian Journal of Medical Sciences, 9(B), 1021-1026. https://doi.org/10.3889/oamjms.2021.6840.

Sellés-Pérez, S., Arévalo, H., Altavilla, C., Guerrero, D. J., & Cejuela, R. (2023). Effect of training with fins on swimming performance in kids and young recreational swimmers. Journal of Physical Education and Sport, 23(2), 532–537. https://doi.org/10.7752/jpes.2023.02066.

Verrelli, C. M., Romagnoli, C., Colistra, N., Ferretti, I., Annino, G., Bonaiuto, V., & Manzi, V. (2023). Golden ratio and self-similarity in swimming: breast-stroke and the back-stroke. Frontiers in Human Neuroscience, 17. https://doi.org/10.3389/fnhum.2023.1176866.

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Published

2024-07-01

How to Cite

Pratama, A. Y., Kristiyanto, A., Syaifullah, R., Riyadi, S., & Raharjo, S. (2024). The Relationship between Anthropometric, Biomotor, and Psychomotor Factors on the Performance of Paralympic 100 Meters Freestyle Swimming Athletes in National Paralympic Committee Indonesia. Retos, 56, 648–653. https://doi.org/10.47197/retos.v56.104869

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