By Zoe Fisher, Mark G. A. Opler, Ph.D., MPH, and Gianna Capodilupo
Modern clinical trials increasingly rely on technologies to help accelerate startup, capture endpoints, and facilitate recruitment. In the midst of this technological revolution, it becomes increasingly important to understand patient perspectives and to anticipate how subjects in research studies may be impacted by the presence of digital tools, devices, and mobile health applications in clinical research.
One area that deserves further exploration is how technologies impact participant beliefs in clinical trials and whether this may alter responses to treatment by modulating suggestibility.
This paper describes how suggestions are classified, the three primary areas of suggestibility, and how researchers can manage the variable that is suggestion. This information can then be used to solve the issue of suggestibility in clinical trials by researchers identifying participants’ overall level of suggestibility and then focus on the minimization of this characteristic.