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Where outcomes are unequivocal (life or death; being able to walk v being paralysed) clinicians, researchers, and patients find it easy to speak the same language in evaluating results. However, in much of mental health work initial states and outcomes of treatments are measured on continuous scales and the distribution of the “normal” often overlaps with the range of the “abnormal.” In this situation, clinicians and researchers often talk different languages about change data, and both are probably poor at conveying their thoughts to patients.

Researchers traditionally compare means between groups. Their statistical methods, using distributions of the scores before and after treatment to suggest whether change is a sampling artefact or a chance finding, have been known for many years. 1 By contrast, clinicians are more often concerned with changes in particular individuals they are treating and often dichotomise …