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- MakaleAçık Erişim2025Investigation of mental endurance levels of canoe athletes in sport: a cross-sectional study
Tanyeri, Levent; Kirkbir, Hakan; Çinan, Ismet; Yilmaz, Busra; Hacicaferoglu, Serkan
Background and Study Aim Material and Methods Mental endurance is considered akeypsychological component that influences athletic performance, particularly in sports that demand high levels of focus and persistence. The aim of the study was to investigate the level of mental endurance in athletes engaged in canoeing. The sample of the study consisted of 163 voluntary canoe athlete students who were studying in the faculties of sport sciences and doing canoeing as licensed students, selected by simple random sampling method. In order to collect the necessary data in the study, the 'Mental Endurance Scale in Sport' was used. The scale consists of the sub-dimensions 'Trust', 'Continuity', and 'Control'. In the analyses of the data, t-test and ANOVA test were used. Statistically, the level of error p<.05 was accepted as Alpha (alpha). Results As a result of the study, it was determined that there was a significant difference in the control sub-dimension according to the gender variable of the students in the sample. It was found that there was a significant difference in terms of age variable. The students aged between 18-20 years were more self-confident, while the students aged between 21-23 years showed more control and continuity. In the sport branch variable, it was found that there was a significant difference in the 'Trust' and 'Control' sub-dimensions, and the effect value was at a moderate level. It was determined that there was a significant difference in the sub-dimension of confidence in the variable of years of doing sports, and the effect value was at a moderate level. The self-confidence of the students who had been doing sports between 1 and 3 years was higher. Conclusions In addition to the physical training and technical skills-enhancing practices of student athletes in sports schools, it will give positive results to carry out actions to increase mental endurance in order to be ready for sportive activities (competitions, recreative activities, etc.). Especially female students or younger students can be less affected by the negativities that may develop instantly within the framework of the difficulties of the sports branch.
AtıfWoS1
İncele - MakaleAçık Erişim2024Investigation of the nutritional habits of students receiving coaching education: a cross-sectional study
Kirkbir, Hakan; Tanyeri, Ozge Sezik; Hacicaferoglu, Serkan
Background and Study Aim Material and Methods The aim of this study is to examine the nutritional knowledge levels and habits of the students who will work in the field of sport sciences in Turkey and who are studying in the Faculties of Sport Sciences. The sample of the study consisted of 186 volunteer university students studying in the coaching departments of the Faculties of Sport Sciences, selected by simple random sampling method. General scanning model was used in the research. The data in the study were collected using the 32-item Nutrition Knowledge Scale for Adults. Results Within the scope of the scores in both sub-dimensions of the scale, it was determined that the perception scores of the participants in terms of independent variables were statistically close to each other and they had knowledge about nutrition in general. It was determined that there was a statistically significant difference between the nutritional knowledge levels according to the age variable, and the effect level was close to the middle. It was determined that there was no significant difference between other variables and nutrition. Conclusions In addition to a healthy life, healthy nutrition is important for coaches in the continuity of their professional life. It would be beneficial to have more information about nutrition in school curriculum. This will contribute to the fight against obesity, which is today's disease.
AtıfWoS1OpenAlex1İncele - MakaleAçık Erişim2023The success of critical velocity protocol on predicting 10000 meters running performance
Çabuk, Baris; Demirarar, Onur; Cin, Merve; Çabuk, Refik; Özçaldiran, Bahtiyar
Background and Study Aim The study aims to evaluate which of the critical velocity (CV) estimates of the three widely used models and the best-fit model successfully predict the running performance of 10000 meters. Material and Methods The group of participants in this study consisted of 11 British endurance athletes. The CV estimations were obtained from the models with the athletes' running velocity and exhaustion times of 1500, 3000, and 5000 meters (m). The information was taken from a website where the results of the British athletes are recorded. In terms of selecting endurance athletes, the data of the athletes who ran 1500 m, 3000 m, 5000 m, and 10000 m in the same two years were included in this study. By fitting the data into mathematical models, the CV estimates of the three mathematical models and the individual best-fit model were compared with the 10000 m running velocity. The CV estimates were obtained by fitting the relevant data on the running velocity, exhaustion time, and running distance of the three running distances of athletes to each of the three mathematical models. Results 10000 m running velocity and times of the athletes corresponded to 19.65 +/- 1.26 km/h and 30.4 +/- 1.94 minutes, respectively. The CV values obtained from the three mathematical models and 10000 m running velocity were similar (p > 0.05). Although the lowest total standard error levels were obtained with the best individual fit method, the 10000 m running velocity was overestimated (p < 0.05). Conclusions Three mathematical models predicted 10000 meters of race velocity when an exhaustion interval between 2-15 minutes was used. Even though the mathematically most valid CV value was obtained with the best individual fit method, it overestimated the 10000 m running velocity. When comparing the values of CV and the velocity of running 10,000 meters, our study suggests using the model. This is because the model has the smallest effect size, and there is no statistically significant difference in the total standard error level between the model and the best-fit model.
AtıfWoS1İncele - DergiPHYSICAL EDUCATION OF STUDENTS