Abstract：
BACKGROUND: The proper interpretation of a study\'s results requires both excellent understanding of good methodological practices and deep knowledge of prior results, aided by the availability of effect sizes.
METHODS: This review takes the form of an expository essay exploring the complex and nuanced relationships among statistical significance, clinical importance, and effect sizes.
RESULTS: Careful attention to study design and methodology will increase the likelihood of obtaining statistical significance and may enhance the ability of investigators/readers to accurately interpret results. Measures of effect size show how well the variables used in a study account for/explain the variability in the data. Studies reporting strong effects may have greater practical value/utility than studies reporting weak effects. Effect sizes need to be interpreted in context. Verbal summary characterizations of effect sizes (e.g., \"weak\", \"strong\") are fundamentally flawed and can lead to inappropriate characterization of results. Common language effect size (CLES) indicators are a relatively new approach to effect sizes that may offer a more accessible interpretation of results that can benefit providers, patients, and the public at large.
CONCLUSIONS: It is important to convey research findings in ways that are clear to both the research community and to the public. At a minimum, this requires inclusion of standard effect size data in research reports. Proper selection of measures and careful design of studies are foundational to the interpretation of a study\'s results. The ability to draw useful conclusions from a study is increased when investigators enhance the methodological quality of their work.
METHODS: This review takes the form of an expository essay exploring the complex and nuanced relationships among statistical significance, clinical importance, and effect sizes.
RESULTS: Careful attention to study design and methodology will increase the likelihood of obtaining statistical significance and may enhance the ability of investigators/readers to accurately interpret results. Measures of effect size show how well the variables used in a study account for/explain the variability in the data. Studies reporting strong effects may have greater practical value/utility than studies reporting weak effects. Effect sizes need to be interpreted in context. Verbal summary characterizations of effect sizes (e.g., \"weak\", \"strong\") are fundamentally flawed and can lead to inappropriate characterization of results. Common language effect size (CLES) indicators are a relatively new approach to effect sizes that may offer a more accessible interpretation of results that can benefit providers, patients, and the public at large.
CONCLUSIONS: It is important to convey research findings in ways that are clear to both the research community and to the public. At a minimum, this requires inclusion of standard effect size data in research reports. Proper selection of measures and careful design of studies are foundational to the interpretation of a study\'s results. The ability to draw useful conclusions from a study is increased when investigators enhance the methodological quality of their work.
摘要：
背景：对研究结果的正确解释既需要对良好的方法实践的深刻理解，又需要对先前结果的深入了解，由效果大小的可用性辅助。
方法：这篇综述采用了一篇说明性文章的形式，探讨了统计意义之间的复杂而细微的关系，临床重要性，和效果大小。
结果：仔细注意研究设计和方法将增加获得统计学意义的可能性，并可能增强研究人员/读者准确解释结果的能力。效应大小的度量表明研究中使用的变量如何很好地解释/解释数据中的变异性。报告强效应的研究可能比报告弱效应的研究具有更大的实用价值/效用。效应大小需要在上下文中解释。效果大小的口头摘要表征(例如，\"弱\",\“strong\”）从根本上是有缺陷的，可能导致对结果的不恰当表征。通用语言效果大小（CLES）指标是一种相对较新的效果大小方法，可以提供更易于理解的结果解释，可以使提供者受益。病人,和广大公众。
结论：以研究界和公众都清楚的方式传达研究结果非常重要。至少,这需要在研究报告中纳入标准效应大小数据。正确选择措施和仔细设计研究是解释研究结果的基础。当研究人员提高其工作的方法学质量时，从研究中得出有用结论的能力就会增强。
方法：这篇综述采用了一篇说明性文章的形式，探讨了统计意义之间的复杂而细微的关系，临床重要性，和效果大小。
结果：仔细注意研究设计和方法将增加获得统计学意义的可能性，并可能增强研究人员/读者准确解释结果的能力。效应大小的度量表明研究中使用的变量如何很好地解释/解释数据中的变异性。报告强效应的研究可能比报告弱效应的研究具有更大的实用价值/效用。效应大小需要在上下文中解释。效果大小的口头摘要表征(例如，\"弱\",\“strong\”）从根本上是有缺陷的，可能导致对结果的不恰当表征。通用语言效果大小（CLES）指标是一种相对较新的效果大小方法，可以提供更易于理解的结果解释，可以使提供者受益。病人,和广大公众。
结论：以研究界和公众都清楚的方式传达研究结果非常重要。至少,这需要在研究报告中纳入标准效应大小数据。正确选择措施和仔细设计研究是解释研究结果的基础。当研究人员提高其工作的方法学质量时，从研究中得出有用结论的能力就会增强。
