Planning and implementing an n of 1 behaviour change service: innovative health services research

Abstract

Background: In a clinical encounter, both clinician and patient want the patient to achieve health behavior change, so the clinician reviews the evidence from between-subject randomized controlled trials and recommends the best intervention to the patient. However, due to the heterogeneity of response in the RCT, we know it is unlikely that the intervention will be successful for the individual patient. Methods: The most scientifically rigorous-- and potentially efficient-- method for determining optimal behavioral intervention for a specific patient is a single patient (n-of-1) RCT, in which data are collected objectively, continuously, and in the real-world, for a sufficient time period to determine whether the intervention, compared to a placebo, another intervention, or a different type of delivery or schedule, is optimal for that particular patient (e.g. worsening sleep with increased exercise, etc). Systematic data collection can also obtain off-target behavioral changes, for particular patients, so that a more complex picture can emerge about the overall therapeutic benefits and harms that can be attributed to the behavioral intervention. Findings: An overview of our vision of an n-of-1 trial service will be presented, as well as the findings and lessons learned from our first patients desiring changes to their exercise, stress, or sitting behavior. Discussion: With sufficient data from several n-of-1 trials, we will be able to engage in inductive theory-building, and examine emerging behavioral phenotypes. Hence, another aspiration of our service is to establish an automated, effective platform that behavioral scientists can use to engage in n-of-1 discovery-based, inductive science.