User-centered, interaction design research approaches to inform the development of health risk behavior intervention...

Computers have tremendous potential for helping people change behaviors that put their health at risk. This potential has led to the development of a variety of health behavior intervention technologies (BITs) in recent years. While many of these BITs have been informed by scientific theories on behavior change, poor design can fail to engage intended users. User-centered, interaction design (IxD) research can help BIT developers create tools that are intuitive and enjoyable and that align with intended users' goals. In this manuscript, we describe an IxD research process we used to inform the development of a tablet-optimized web application designed to help heavy drinking gay and bisexual men reduce their risk for HIV when they seek HIV testing.

We conducted focus groups with subject matter experts (SMEs, N = 10) and intended users (N = 25). In the SME group, HIV test counselors were recruited to provide an understanding of the priorities and challenges of post-test counseling. In focus groups with intended users, participants created detailed, personalized models of two "typical" users of the proposed app ("personas") that could be used to guide design decisions.

SMEs emphasized the importance of putting patients at ease, and suggested that interventions should prioritize identifying personal risks and provide options for change. Personas created by intended users provided important details about users' attitudinal and emotional contexts, and their possible motivations and goals for using the app. These suggested that users might be most motivated to use the app in order to understand their personal risks, compare their behavior with others like them, help them decide whether they want to change to reduce their risk, and see all their options for doing so. Personas also provided insights about the aesthetic experience that might be most appealing to users.

Interaction design research can provide BIT development teams with personal models of likely users to help guide decisions about the allocation of design resources and the overall form and spirit of the software. These insights can help teams build BITs that are more engaging and interesting to intended users.