Predicting the psychological productivity of karatekas based on demographic variables

Document Type : Original research

Authors

1 PhD Student in Sports Management. Department of physical education, Borujerd Branch, Islamic Azad University, Borujerd, Iran

2 Department of physical education, Borujerd Branch, Islamic Azad University, Borujerd, Iran

3 Department of physical education, Malayer Branch, Islamic Azad University, Malayer, Iran

4 Associate Professor of Sport Management Department, Kharazmi University

Abstract

The present study was designed and conducted to investigate the prediction of psychological productivity of karatekas with emphasis on the demographic variable. The statistical population of the study included karate athletes in Isfahan who were selected as a sample according to the available selection of 365 people. Finally, after distributing and collecting research questionnaires, 341 questionnaires were analyzed. Data collection tools included a standard questionnaire. The results showed that in the first step, age alone predicted 29% of the variances of karatekas psychological productivity. Also, in the second step, the role of age and marriage predicted 36% of the variances of psychological productivity of karatekas. In the third step, the role of age, marriage, and income was predicted by 40% of the variances of karate psychological productivity. In the fourth step, age, marriage, income, and education accounted for 44% of the variations in karatekas' psychological productivity. In other words, among demographic variables, age, marriage, income and education, respectively, had a strong predictive role in the psychological productivity of karatekas. The results of the present study can provide a basis for identifying talented karatekas in psychological fields.

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References

  1. Boccia, G., Brustio, P. R., Moisè, P., Franceschi, A., La Torre, A., Schena, F., ..., & Cardinale, M. (2019). Elite national athletes reach their peak performance later than non-elite in sprints and throwing events. Journal of Science and Medicine in Sport, 22(3), 342-347.
  2. Bonk, D., & Tamminen, K. A. (2022). Athletes’ perspectives of preparation strategies in open-skill sports. Journal of Applied Sport Psychology, 34(4), 825-845.
  3. Daniels, K., & Harris, C. (2000). Work, psychological well-being and performance. Occupational Medicine, 50(5), 304-309.
  4. Gulbin, J., Weissensteiner, J., Oldenziel, K., & Gagné, F. (2013). Patterns of performance development in elite athletes. European Journal of Sport Science, 13(6), 605-614.
  5. Henriksen, K., Schinke, R., Moesch, K., McCann, S., Parham, W. D., Larsen, C. H., & Terry, P. (2020). Consensus statement on improving the mental health of high performance athletes. International Journal of Sport and Exercise Psychology, 18(5), 553-560.
  6. Iranzadeh, Suleiman, Pakdel-Banab. (2014) Investigating the role of implementing knowledge management on increasing the productivity of human resources in the Islamic Azad University of Tabriz branch. Productivity management.; 28(7):51-74
  7. Krylovas, A., Kosareva, N., Dadelienė, R., & Dadelo, S. (2020).

 

Evaluation of elite athletes training management efficiency based on multiple criteria measure of conditioning using fewer data. Mathematics, 8(1), 66- 83.

  1. Maszczyk, A., Dobrakowski, P., Nitychoruk, M., Żak, M., Kowalczyk, M., & Toborek, M. (2020). The effect of neurofeedback training on the visual processing efficiency in judo athletes. Journal of Human Kinetics, 71, 219- 227.
  2. Mujika, I. (2017). Quantification of training and competition loads in endurance sports: Methods and applications. International Journal of Sports Physiology and Performance, 12(s2), S2-9-S2-17.
  3. Ohtani, M., Sugita, M., & Maruyama, K. (2006). Amino acid mixture improves training efficiency in athletes. The Journal of Nutrition, 136(2), 538S-543S.
  4. Pavlidis, G., & Gargalianos, D. (2014). High performance athletes' education: Value, challenges and opportunities. Journal of Physical Education and Sport, 14(2), 293- 300.
  5. Reynolds, L., Fisher, D., & Cavil, J. K. (2012). Impact of demographic variables on african-american student athletes' academic performance. Educational Foundations, 26, 93-111.
  6. Singh, A., & Parmar, D. S. (2016). A comparative study of psychological factor among female athletes. International Research Journal of Engineering, IT & Scientific Research, 2(1), 8-21.

 

  1. Vaez Mosavi, S., & Mosavi, S. (2015). Factors influencing sports success based on related theories and models. Sports Psychology Studies, 10, 25-50. (In Persian).
  2. Vassos, M. V., & Nankervis, K. L. (2012). Investigating the importance of various individual, interpersonal, organisational and demographic variables when predicting job burnout in disability support workers. Research in Developmental Disabilities, 33(6), 1780-1791.
  3. Vargas, P. C., & Jiménez, J. M. (2020). The association between sleep efficiency and physical performance in taekwondo athletes. Retos: nuevas tendencias

 

en educación física, deporte y recreación, (37), 227-232.

  1. Wright, T. A., & Cropanzano, R. (2000). Psychological well-being and job satisfaction as predictors of job performance. Journal of Occupational Health Psychology, 5(1), 84- 94.
  2. Yazici, M., & Duzenci, S. (2020). Investigation of burnout level of active athletes according to some sportive and demographic variables.International Journal of Applied Exercise Physiology, 9(9), 114-126.

 

Sport Psychology Studies
Volume 12, Issue 43
April 2023
Pages 175-188

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History

  • Receive Date: 06 June 2021
  • Revise Date: 04 October 2021
  • Accept Date: 11 October 2021

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