Kang Minsoo, Ragan Brian G, Park Jae-Hyeon
Middle Tennessee State University, Murfreesboro, TN, USA.
J Athl Train. 2008 Apr-Jun;43(2):215-21. doi: 10.4085/1062-6050-43.2.215.
To review and describe randomization techniques used in clinical trials, including simple, block, stratified, and covariate adaptive techniques.
Clinical trials are required to establish treatment efficacy of many athletic training procedures. In the past, we have relied on evidence of questionable scientific merit to aid the determination of treatment choices. Interest in evidence-based practice is growing rapidly within the athletic training profession, placing greater emphasis on the importance of well-conducted clinical trials. One critical component of clinical trials that strengthens results is random assignment of participants to control and treatment groups. Although randomization appears to be a simple concept, issues of balancing sample sizes and controlling the influence of covariates a priori are important. Various techniques have been developed to account for these issues, including block, stratified randomization, and covariate adaptive techniques.
Athletic training researchers and scholarly clinicians can use the information presented in this article to better conduct and interpret the results of clinical trials. Implementing these techniques will increase the power and validity of findings of athletic medicine clinical trials, which will ultimately improve the quality of care provided.
回顾并描述临床试验中使用的随机化技术，包括简单随机化、区组随机化、分层随机化和协变量适应性技术。
需要通过临床试验来确定许多运动训练方法的治疗效果。过去，我们依赖科学价值存疑的证据来辅助治疗选择的判定。在运动训练行业，基于证据的实践的关注度正在迅速增长，这更加凸显了开展良好的临床试验的重要性。临床试验中强化结果的一个关键要素是将参与者随机分配到对照组和治疗组。尽管随机化看似是个简单的概念，但事先平衡样本量和控制协变量的影响等问题很重要。为解决这些问题已开发出各种技术，包括区组随机化、分层随机化和协变量适应性技术。
运动训练研究人员和学术临床医生可以利用本文提供的信息更好地开展和解释临床试验结果。应用这些技术将提高运动医学临床试验结果的效力和有效性，最终改善所提供的护理质量。
