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On the challenges of personalizing brain stimulation
Non-pharmacological interventions such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have shown some promise in the treatment of positive symptoms in schizophrenia. Yet, an urgent challenge remains: predicting whether the treatment is likely to work in a particular patient. Current treatment algorithms do not address this issue, often neglecting individual differences and relying on trial-and-error. It is, however, widely believed that there is considerable individual variability in treatment response, although this assumption is rarely tested explicitly. Here, we analyzed all original studies in positive symptoms from the last decades that used a randomized controlled design and compared sham with active stimulation. We assumed that the overall personal variation due to individual treatment response (present in the active group) can be separated from random variation (present in the active and sham group) by comparing the variances between groups. Thus, a personal element of response should be reflected by a clinically relevant increase in overall variance in the active compared to the sham group. To our surprise, however, we did not find evidence for a clinically relevant increase in variance in the active group. Thus, although it is often assumed that patients differ in their response to brain stimulation, we found strikingly little empirical support for this belief. We conclude that personalizing treatment may thus mean to put a strong focus on average treatment effects rather than arbitrary labels such as responders versus nonresponders.