StopAdvisor is a new web-based smoking cessation program, which takes smokers from preparation for the target quit date to the quit date itself. It achieves this by offering expert advice through a combination of interactive menus and personalised sessions. Post quit date, it encourages users to report important information that the program will use to help them overcome the difficulties they encounter along the way. In their study¹ Robert West and Susan Michie from University College London and collaborators describe the development process of the StopAdvisor intervention. Their work appears online in Translational Behavioral Medicine: Practice, Policy, Research², published by Springer.

Since smoking remains the largest single preventable cause of premature death and illness worldwide, there is a pressing need to find better ways to help smokers to quit. The internet has huge potential and is extremely cost-effective, i.e. low cost per user.

StopAdvisor is the result of the analysis and synthesis of 19 theoretical principles, 33 evidence- or theory-based behavior change techniques, 26 web-design principles and 9 principles from user-testing. It is designed to be attractive and effective across social groups. In order to make StopAdvisor relevant to all social groups, user-testing was conducted among less educated smokers in lower paid jobs, a group notoriously difficult to reach and engage.

What is unique about the research team's approach is the use of an open-source web-development platform (LifeGuide), which allowed the researchers to test individual elements of their intervention and adjust them as they went along, based on user and researcher feedback throughout the development phase.

The authors comment: "To our knowledge, this is the first attempt to be fully transparent about the content and development of a population-reach behavior change intervention."

The paper describes the development process of the StopAdvisor intervention and provides a full description of how the intervention works. Its effectiveness is currently being evaluated in a randomised controlled trial (the highest level of evidence for a scientific study). The authors have made a commitment to continue incrementally developing and building the technology as a community of researchers.