Oh Kyungjin, Lee Jea Woog, Kang Kyung Doo, Han Doug Hyun
Department of Psychiatry, Chung Ang University Hospital, Seoul, Republic of Korea.
College of Sports Science, Chung-Ang University, Anseong, Republic of Korea.
Psychiatry Investig. 2025 Jan;22(1):66-74. doi: 10.30773/pi.2024.0298. Epub 2025 Jan 15.
This study hypothesized that physical status, temperament and characteristics, and neurocognitive functions of basketball players could predict the result of Korean Basketball League (KBL) draft selection.
We recruited the number of 89 college elite basketball players (KBL selection, n=44; non-KBL selection, n=45), and the number of 82 age-matched healthy comparison subjects who major in sports education in college. All participants were assessed with the Temperament and Character Inventory, Sports Anxiety Scales, Beck Depression Inventory, Perceived Stress Scale-10, Trail Making Test, and Computerized Neuro-cognitive Test for Emotional Perception and Mental Rotation.
Current results showed that physical status, temperament and characteristics, and neurocognitive functions of college basketball players could predict the KBL draft selection. Among temperament and characteristics, novelty seeking and reward dependence were associated with KBL draft selection. The basketball performances including average scores and average rebound were associated with Emotional Perception and Mental Rotation.
In order to be a good basketball player for a long time, it was confirmed that temperamental factors and neurocognitive factors were very closely related. Furthermore, it is also judged that these results can be used as basic data to predict potential professional basketball players.
本研究假设篮球运动员的身体状况、气质性格及神经认知功能能够预测韩国篮球联赛(KBL)选秀结果。
我们招募了89名大学精英篮球运动员(入选KBL,n = 44;未入选KBL,n = 45),以及82名年龄匹配的、大学体育教育专业的健康对照受试者。所有参与者均接受了气质性格量表、运动焦虑量表、贝克抑郁量表、感知压力量表-10、连线测验以及情绪感知和心理旋转计算机化神经认知测试。
当前结果表明,大学篮球运动员的身体状况、气质性格及神经认知功能能够预测KBL选秀结果。在气质性格方面,寻求新奇和奖赏依赖与KBL选秀相关。包括平均得分和平均篮板在内的篮球表现与情绪感知和心理旋转相关。
为了长期成为优秀篮球运动员,已证实气质因素和神经认知因素密切相关。此外,还判断这些结果可作为预测潜在职业篮球运动员的基础数据。