Purpose <p>This study aims to explain the role of the minimal clinically important difference (MCID) in sport science. When an intervention leads to improvement, is that improvement only statistically significant, or is it also large enough to be meaningful in practice?</p> Methods <p>This study introduces the definition of MCID, describes two common approaches used to determine it, namely anchor-based and distribution-based methods, and compares MCID with traditional statistical indicators. It also discusses how MCID can be applied in three common sport science contexts: competitive performance, injury prevention, and rehabilitation management.</p> Results <p>MCID addresses a different question from p-values and effect sizes. While <i>p</i>-values and effect sizes indicate whether a change exists and how large it is statistically, MCID helps judge whether the change is meaningful enough to support real decisions. MCID can improve study design, result reporting, and interpretation, especially when used together with statistical significance and effect size.</p> Conclusion <p>MCID helps shift sport science research from focusing only onstatistical significance to considering practical meaning. Its use can make research findings easier to interpret and more useful for real-world decision-making.</p>

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From statistical significance to meaningful change: the role of the minimal clinically important difference in sports science

  • Lidian Meng,
  • He Zheng

摘要

Purpose

This study aims to explain the role of the minimal clinically important difference (MCID) in sport science. When an intervention leads to improvement, is that improvement only statistically significant, or is it also large enough to be meaningful in practice?

Methods

This study introduces the definition of MCID, describes two common approaches used to determine it, namely anchor-based and distribution-based methods, and compares MCID with traditional statistical indicators. It also discusses how MCID can be applied in three common sport science contexts: competitive performance, injury prevention, and rehabilitation management.

Results

MCID addresses a different question from p-values and effect sizes. While p-values and effect sizes indicate whether a change exists and how large it is statistically, MCID helps judge whether the change is meaningful enough to support real decisions. MCID can improve study design, result reporting, and interpretation, especially when used together with statistical significance and effect size.

Conclusion

MCID helps shift sport science research from focusing only onstatistical significance to considering practical meaning. Its use can make research findings easier to interpret and more useful for real-world decision-making.