How should a statistically significant muscle study result be interpreted?

Understanding the question

Statistical significance does not tell you whether an observed effect is large, useful or likely to apply to an individual. Start with the between group effect estimate in understandable units, then examine its confidence interval and the quality of the design. A small p value can accompany a modest difference in a large study, while a potentially important difference in a small study may remain imprecise. Confidence intervals describe uncertainty under the analysis assumptions, not a guarantee that the result is unbiased. Interpretation also requires a meaningful benchmark, suitable measurement methods and attention to the number of outcomes or comparisons tested.

What a useful investigation needs to consider

Prefer an absolute difference in force, walking time or another defined endpoint before relying on percentages or standardized effects. Relative changes depend on the starting value and can look dramatic when the baseline is small. Check whether the headline reports the treatment versus control difference or only change within the treated group.

Compare the entire uncertainty interval with thresholds for a worthwhile benefit and possible harm. A nonsignificant result can still be compatible with important effects, and a significant result can be too small to matter. Precision is one part of evidence quality, not a substitute for valid methods.

Read the detailed explanation

The companion article explores effect sizes and uncertainty in muscle research in more depth, with topic-specific explanations and source material.