Context: Clinicians who use the medical literature to guide their practice need to make judgments about the clinical significance of medical interventions.
General question: How likely is an intervention to be clinically worthwhile?
Specific research challenge: Given the results of a study, determining the probability that the true effect of an intervention is at least as great as some minimum worthwhile effect.
Current approach: P values are widely used to convey the probability of observed effects arising by chance if there truly is no effect. By convention, P values less than 0.05 are interpreted as being "statistically significant."
Potential difficulties: Statistical significance is often confused with clinical significance.
Alternate approach: A different probability could be reported, a probability I call a Q value. A Q value is the probability that the true effect of an intervention is at least as great as some minimum worthwhile effect. Q values are calculated in a manner analogous to that used for P values, except that the null hypothesis becomes a minimum worthwhile effect instead of no effect. Q values encourage researchers and clinicians to be explicit about what they think a worthwhile effect is and could help shift the focus of study interpretation away from arbitrary statistical conventions.