Yu Chien-Lin, Cheng Ming-Yang, An Xin, Chueh Ting-Yu, Wu Jia-Hao, Wang Kuo-Pin, Hung Tsung-Min
Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan.
Department of Sport Science Research, Taiwan Institute of Sports Science, Kaohsiung, Taiwan.
Scand J Med Sci Sports. 2025 May;35(5):e70055. doi: 10.1111/sms.70055.
Neurofeedback training (NFT) has emerged as a promising technique for enhancing sports performance by enabling individuals to self-regulate their neural activity. However, only 53% of the 13 included studies, all of which published before 2021, in the latest meta-analyses of NFT and motor performance focused on motor performance outcomes. Due to the rapid development of neurofeedback, 8 high-quality articles were published in 2023-2024 alone. Therefore, there is a need for a new meta-analysis to update the impact of NFT on sports performance. In this systematic review and meta-analysis, we have not only reassessed the knowledge of the effect of EEG neurofeedback in motor performance but have also incorporated a standardized methodology, known as the CRED-nf checklist (Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies), for methodological evaluation of previous EEG neurofeedback studies. The study protocol was pre-registered, and a systematic search was conducted across major databases to identify relevant randomized controlled trials. A total of 25 studies were included in the qualitative synthesis, with 21 studies eligible for the meta-analysis. The meta-analysis revealed a moderate positive effect of NFT on sport motor tasks, with a Hedges's g of 0.78 with a 95% confidence interval (CI) of 0.49-1.07. Importantly, subgroup analyses showed that studies with higher methodological quality scores, as assessed by the CRED-nf checklist, had significantly larger effect sizes (Hedges's g = 1.07) compared to lower than median studies (Hedges's g = 0.49). This finding highlights the importance of addressing key methodological gaps, such as reporting on participant strategies, data processing methods, and the relationship between regulation success and behavioral outcomes. In conclusion, NFT showcases a moderate positive impact on sport motor task, particularly when high-quality methodologies are employed, as assessed by the CRED-nf checklist, underscoring the importance of rigorous study designs in future research.
神经反馈训练(NFT)已成为一种有前景的技术,通过使个体能够自我调节神经活动来提高运动表现。然而,在最新的关于NFT与运动表现的荟萃分析中,纳入的13项研究(均在2021年之前发表)中只有53%聚焦于运动表现结果。由于神经反馈的快速发展,仅在2023 - 2024年就发表了8篇高质量文章。因此,需要进行新的荟萃分析来更新NFT对运动表现的影响。在这项系统评价和荟萃分析中,我们不仅重新评估了脑电图神经反馈对运动表现影响的知识,还纳入了一种标准化方法,即CRED - nf清单(临床和认知行为神经反馈研究报告与实验设计共识),用于对先前脑电图神经反馈研究进行方法学评估。该研究方案已预先注册,并在主要数据库中进行了系统检索,以识别相关的随机对照试验。定性综合分析共纳入25项研究,其中21项研究符合荟萃分析的条件。荟萃分析显示,NFT对运动任务有中等程度的积极影响,Hedges's g为0.78,95%置信区间(CI)为0.49 - 1.07。重要的是,亚组分析表明,根据CRED - nf清单评估,方法学质量得分较高的研究与得分低于中位数的研究相比,效应量显著更大(Hedges's g = 1.07对比Hedges's g = 0.49)。这一发现凸显了解决关键方法学差距的重要性,如报告参与者策略、数据处理方法以及调节成功与行为结果之间的关系。总之,NFT对运动任务显示出中等程度的积极影响,特别是在采用高质量方法时,如通过CRED - nf清单评估,这突出了未来研究中严谨研究设计的重要性。