A practitioner’s guide to developing critical appraisal skills What is the difference between clinical and statistical significance?
Brignardello Petersen, Romina
Carrasco Labra, Raúl
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Artículo de publicación ISI
Background. It is common to find published studies in
which the authors claim to have found significant results.
However, many times these results are only statistically
significant with no meaningful impact in clinical settings.
Methods. The authors aim to clarify and differentiate
the concepts of statistical and clinical significance, as well as
to provide guidance on how to interpret research results to determine
whether an observed difference is meaningful.
Results. Study results are considered to be statistically significant if
statistical tests that examine the null hypothesis of no difference yield
P values that are smaller than the significance level prespecified by the
authors. In this way, researchers can use hypothesis testing to assess the
possibility that observed results could have arisen by chance. However,
hypothesis testing cannot establish the clinical implications of these results.
Rather, clinical significance can be established once the magnitude
of results is larger than the minimal clinically important difference. Clinical
significance then would encompass not only statistical significance,
but also the importance of the outcomes to patients, clinicians and
Conclusion. The values for statistical significance alone cannot convey
the complete picture of the effectiveness of an intervention or of a difference
between two groups. Both clinical and statistical significance are
important measures for interpretation of clinical research results and
should complement each other.
Practical Implications. Any benefit in terms of improved health outcomes
must be both clinically and statistically significant. If there is no
benefit at the threshold of both clinical and statistical improvement, then
the intervention should not be used for that purpose.