Ditroilo Massimiliano, Mesquida Cristian, Abt Grant, Lakens Daniël
School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.
Human Technology Interaction, Eindhoven University of Technology, Eindhoven, The Netherlands.
J Sports Sci. 2025 Jun;43(12):1108-1120. doi: 10.1080/02640414.2025.2486871. Epub 2025 Apr 8.
Quantitative exploratory research implies a flexible examination of a dataset with the purpose of finding patterns, associations, and interactions between variables to help formulate a hypothesis, which should be severely tested in a future confirmatory study. In many fields, including sport and exercise science, exploratory research is not openly reported, a practice that leads to serious problems. At the same time, exploration is a crucial step in scientific knowledge generation, and a substantial proportion of studies will be exploratory in nature, or include both confirmatory and exploratory analyses. Using a flowchart, we review how data are typically collected and used, and we distinguish exploratory from confirmatory studies by arguing that data-driven analyses, where the Type I and Type II error cannot be controlled, is what characterises exploratory research. We ask which factors increase the quality and value of exploratory analyses, and highlight large sample sizes, uncommon sample compositions, rigorous data collection, widely used measures, observing a logical and coherent pattern across multiple variables, and the potential for generating new research questions as the main factors. Finally, we provide guidelines for carrying out and transparently writing up an exploratory study.
定量探索性研究意味着对数据集进行灵活的考察，目的是发现变量之间的模式、关联和相互作用，以帮助形成一个假设，该假设应在未来的验证性研究中进行严格检验。在包括体育和运动科学在内的许多领域，探索性研究并未公开报告，这种做法会导致严重问题。同时，探索是科学知识生成中的关键一步，相当一部分研究本质上是探索性的，或者包含验证性和探索性分析。我们使用流程图回顾了数据通常是如何收集和使用的，并通过论证数据驱动分析（其中I型和II型错误无法控制）是探索性研究的特征，从而区分探索性研究和验证性研究。我们探讨了哪些因素会提高探索性分析的质量和价值，并强调大样本量、不常见的样本构成、严格的数据收集、广泛使用的测量方法、观察多个变量之间逻辑连贯的模式以及产生新研究问题的潜力是主要因素。最后，我们提供了开展和透明撰写探索性研究的指导方针。
