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The purpose of this study was to develop a scale to measure extreme sports participants’ levels of compulsive exercising. There are a number of compulsive exercising scales; however, none of them is targeted for extreme sports participants, whose emotional responses differ from those of non-extreme sports participants. Five hundred extreme sports participants were involved in this study, which included literature analysis, expert review, and exploratory and confirmatory factor analysis. Firstly, 95 items were selected from previous studies related to extreme sports and compulsive exercising. Secondly, nine experts scrutinized the content validity of the 95 items, and 82 items were found to be valid. Thirdly, the 82-item survey was initially administered to 253 participants for the purposes of exploratory factor analysis. Lastly, the 20-item survey that came out as a result of the 82 items being put through the exploratory factor analysis was distributed to the other 247 participants in the confirmatory factor analysis. In the final results, 16 items regarding the four factors of the “withdrawal symptom”, “attachment”, “struggle”, and “obsession” were confirmed. The factors used to measure extreme sports participants’ compulsiveness in this study reflect somewhat different dimensions from those developed in previous studies for non-extreme sports participants or exercisers. Only factors in the affective and behavioral dimensions are included in the present study’s scale, while factors in the cognitive or the combined cognitive, affective, and behavioral dimensions were investigated in previous studies. This explains the need for the present study.

This study aims to identify the most accurate prediction model for the possibility of victory from the annual average data of 25 seasons (1993–2017) of the Ladies Professional Golf Association (LPGA), and to determine the importance of the predicting factors. The four prediction models considered in this study were a decision tree, discriminant analysis, logistic regression, and artificial neural network analysis. The mean difference in the classification accuracy of these models was analyzed using SPSS 22.0 software (IBM Corp., Armonk, NY, USA) and the one-way analysis of variance (ANOVA). When the prediction was based on technical variables, the most important predicting variables for determining victory were greens in regulation (GIR) and putting average (PA) in all four prediction models. When the prediction was based on the output of the technical variables, the most important predicting variable for determining victory was birdies in all four prediction models. When the prediction was based on the season outcome, the most important predicting variables for determining victory were the top 10 finish% (T10) and official money. A significant mean difference in classification accuracy was observed while performing the one-way ANOVA, and the least significant difference post-hoc test showed that artificial neural network analysis exhibited higher accuracy than the other models, especially, for larger data sizes. From the results of this study, it can be inferred that the player who wants to win the LPGA should aim to increase GIR, reduce PA, and improve driving distance and accuracy through training to increase the birdies chance at each hole, which can lead to lower average strokes and increased possibility of being within T10.

We investigated the effects of fluid ingestion during exercise in different environments on the serum brain-derived neurotrophic factor and cognition among athletes. Ten collegiate male athletes (soccer, n = 5; rugby, n = 5) were enrolled, and they completed running tests in the following four conditions (60 min each): 1) thermoneutral temperature at 18°C (group 18); 2) high ambient temperature at 32°C without fluid ingestion (group 32); 3) high ambient temperature at 32°C with water ingestion (group 32+W); and 4) high ambient temperature at 32°C with sports drink ingestion (group 32+S). Serum brain-derived neurotrophic factor levels significantly increased in group 18 immediately after exercise when compared with those at rest and were significantly higher than those in group 32 immediately and 60 min after exercise (p < 0.05). In the Stroop Color and Word Test, significantly increased Word, Color, and Color-Word scores were observed in group 18 immediately after exercise compared to those at rest (p < 0.05). However, the Color-Word score appeared to be significantly lower in group 32 immediately after exercise compared to the other groups (p < 0.05) and at 60 min post-exercise compared to group 18 (p < 0.05). We found that the exercise performed in a thermoneutral environment improved cognitive function, but the exercise performed in a hot environment did not. The differences according to the exercise environment would be largely affected by brain-derived neurotrophic factor, and fluid ingestion regardless of the type of drink (water or sports beverage) was assumed to have contributed to the improvement in cognitive function caused by exercising in a hot environment.

The purpose of this study was to examine the relationship between the perceived physical health status of Korean adolescents, adults, and elderly adults and their frequency, intensity, time, and duration of exercise. In 2012, 1,144 adolescents (under 18 years old), 6,474 adults (19-64 years old), and 1,382 elderly adults (over 65 years old) participated in the Korean Survey on Citizens’ Sports Participation Project (N = 9,000). The association between selfreported health status and exercise was assessed using multivariate logistic regression analyses, controlling for sex and age. The study found that the health status of adolescents showed little or no association with the frequency, intensity, time, or duration of exercise. However, the health status of adults and elderly Koreans was associated with the frequency, intensity, time, and duration of exercise. The physical condition and health status of adolescents was better than that of adults and the elderly, many of whom had declining health. Our findings show the need for exercisepromotion programs customized for particular age groups. The limitations and strengths of the study are discussed, as well as the implications for future research and managerial applications for promoting exercise in each age group.