Understanding the Effect Size of ADHD Medications: Implications for Clinical Care

Stephen V. Faraone, PhD


September 18, 2003

In This Article

Effect Size and ADHD Pharmacology

The intent of presenting these effect sizes is not to imply that all must be used by physicians who practice evidence-based medicine. Instead, by understanding the different measures and how they are computed, clinicians can sensibly read the literature using these terms and, perhaps more importantly, compute some they find particularly useful. Thinking in terms of effect size becomes particularly useful when you have learned about the effect sizes for other treatments. As an example, Table 2 gives the effect sizes for classes of ADHD medications and also for other medicines used for other psychiatric disorders. For physicians treating ADHD patients, it is reassuring that the effect sizes for ADHD medicine are greater than some other medicines routinely used in psychiatry and primary care.

The use of effect sizes for comparing the efficacy of different treatments is clearly an advance beyond qualitative comparisons of different studies. But it would be a mistake to compare effect sizes between studies without acknowledging the main limitation of this method. Put simply, the computation of effect sizes only makes sense if we are certain that the studies being compared are reasonably similar on any study design features that might increase or decrease the effect size. Comparing effect sizes between studies is questionable if the studies differ substantially on design features that might plausibly influence drug-placebo differences. For example, if a study of drug A used double-blind methodology and found a smaller effect size than a study of a drug B that was not blinded, we could not be sure if the difference in effect size was due to differences in drug efficacy or differences in methodology. As a report about ADHD medications noted, these differences can be considerable.[5]

This discussion of effect size focused on medication efficacy, but effect sizes could also be computed for adverse events. These are somewhat less useful because it is not straightforward to compare different adverse events. For example, many studies will only report the prevalence of adverse events for those that occurred with a certain frequency, say 10%. Thus, one study might present data on headaches and insomnia. Another might present data on anorexia and stomach aches. Using effect size measures to compare adverse events is obviously nonsensical when comparing serious events (eg, cardiac side effects) with minor ones (eg, stomach aches).


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