The Importance of Individual Beliefs in Assessing Treatment Efficacy: Insights from Neurostimulation Studies

In recent years, there has been debate about the effectiveness of treatments from different fields, such as neurostimulation, neurofeedback, brain training, and pharmacotherapy. This debate has been fuelled by contradictory and nuanced experimental findings. Notably, the effectiveness of a given treatment is commonly evaluated by comparing the effect of the active treatment versus the placebo on human health and/or behaviour. However, this approach neglects the individual’s subjective experience of the type of treatment s/he received in establishing treatment efficacy. Here, we show that individual differences in subjective treatment—the thought of receiving the active or placebo condition during an experiment—can explain variability in outcomes better than the actual treatment. We analysed four independent datasets (N=387 participants), including clinical patients and healthy adults from different age groups who were exposed to different neurostimulation treatments (transcranial magnetic stimulation: Study 1 & 2; transcranial direct current stimulation: Study 3 & 4). Our findings consistently show that the inclusion of subjective treatment provides a better model fit than objective treatment alone—the condition to which participants are assigned in the experiment. These results demonstrate the significant contribution of subjective experience in explaining the variability of clinical, cognitive and behavioural outcomes. Based on these findings, we advocate for existing and future studies in clinical and non-clinical research to start accounting for participants’ subjective beliefs when assessing the efficacy of treatments. This approach will be crucial in providing a more accurate estimation of the treatment effect and its source, allowing the development of effective and reproducible interventions. We demonstrate that individual differences in subjective treatment—the belief of receiving the active or placebo condition during an experiment—can explain variability in research outcomes better than objective treatment, the actual treatment to which participants are assigned. Even though it is a standard practice for intervention studies to collect data on subjective treatment, its contribution to research outcomes has been overlooked. By demonstrating the explanatory power of subjective treatment beyond objective treatment in four independent datasets, we show its potential to provide further insights into the effectiveness of different interventions. We, therefore, encourage researchers to adopt our approach in existing and new studies, to improve experimental design and ultimately increase the rigour and robustness of clinical and non-clinical interventions.