The impact of patient narratives on medical students’ perceptions of shared decision making: A randomized controlled trial

Abstract

Successful shared decision making (SDM) in clinical practice requires that future clinicians learn to appreciate the value of patient participation as early as they can in their medical training. Narratives, such as patient testimonials, have been successfully used to support patients’ decision-making process. Previous research suggests that narratives may also be used for increasing clinicians’ empathy and responsiveness in medical consultations. However, so far, no studies have investigated the benefits of narratives for conveying the relevance of SDM to medical students. In this randomized controlled experiment, N = 167 medical students were put into a scenario where they prepared for medical consultation with a patient having Parkinson disease. After receiving general information, participants read either a narrative testimonial of a Parkinson patient or a fact-based information text. We measured their perceptions of SDM, their control preferences (i.e., their priorities as to who should make the decision), and the time they intended to spend for the consultation. Participants in the narrative patient testimonial condition referred more strongly to the patient as the one who should make decisions than participants who read the information text. Participants who read the patient narrative also considered SDM in situations with several equivalent treatment options to be more important than participants in the information text condition. There were no group differences regarding their control preferences. Participants who read the patient testimonial indicated that they would schedule more time for the consultation. These findings show that narratives can potentially be useful for imparting the relevance of SDM and patient-centered values to medical students. We discuss possible causes of this effect and implications for training and future research. Trial registration: The study was pre-registered on the pre-registration platform AsPredicted (aspredicted.org) before data collection began (registration number: #29,342). Date of registration: 17 October 2019.