What is a best practice when publishing negative results in sport science?

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Multiple Choice

What is a best practice when publishing negative results in sport science?

Explanation:
Publishing negative results with transparency and accuracy is best practice in sport science. Even findings that show no effect or unexpected null results are valuable when they are reported with clear context. Providing context means detailing the study design, participant characteristics, interventions, measurement methods, duration, and any limitations. Including full statistical results—such as effect sizes, confidence intervals, and p-values when appropriate—helps others interpret the finding, assess its relevance, and combine it with other data in reviews or meta-analyses. This approach prevents misinterpretation and reduces publication bias, which occurs when only positive results see the light of day. It also clarifies why a result might be null—whether the effect truly isn’t there, the study was underpowered, adherence was low, or measurements were imprecise—so researchers can build on or refine the work rather than pursuing false leads. Why the other options don’t fit: Excluding context hides important details needed to understand and apply the result. Requiring funding before publication introduces bias and gatekeeping, potentially suppressing valuable information. Hiding negative results perpetuates publication bias and wastes resources by leaving the evidence base incomplete.

Publishing negative results with transparency and accuracy is best practice in sport science. Even findings that show no effect or unexpected null results are valuable when they are reported with clear context. Providing context means detailing the study design, participant characteristics, interventions, measurement methods, duration, and any limitations. Including full statistical results—such as effect sizes, confidence intervals, and p-values when appropriate—helps others interpret the finding, assess its relevance, and combine it with other data in reviews or meta-analyses.

This approach prevents misinterpretation and reduces publication bias, which occurs when only positive results see the light of day. It also clarifies why a result might be null—whether the effect truly isn’t there, the study was underpowered, adherence was low, or measurements were imprecise—so researchers can build on or refine the work rather than pursuing false leads.

Why the other options don’t fit: Excluding context hides important details needed to understand and apply the result. Requiring funding before publication introduces bias and gatekeeping, potentially suppressing valuable information. Hiding negative results perpetuates publication bias and wastes resources by leaving the evidence base incomplete.

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