Key changes to improve social presence of a virtual health assistant promoting colorectal cancer screening informed by a technology acceptance model.

Background: Understanding how older, minoritized patients attend to cues when interacting with web-based health messages may provide opportunities to improve engagement with novel health technologies. We assess acceptance-promoting and acceptance-inhibiting cues of a web-based, intervention promoting colorectal cancer (CRC) screening with a home stool test among Black women.

Materials And Methods: Focus group and individual interview data informed iterative changes to a race- and gender-concordant virtual health assistant (VHA). A user-centered design approach was used across 3 iterations to identify changes needed to activate cues described as important; such as portraying authority and expertise. Questionnaire data were analyzed using non-parametric tests for perceptions of cues. Analysis was guided by the Technology Acceptance Model.

Results: Perceptions of interactivity, social presence, expertise, and trust were important cues in a VHA-delivered intervention promoting CRC screening. Features of the web-based platform related to ease of navigation and use were also discussed. Participant comments varied across the 3 iterations and indicated acceptance of or a desire to improve source cues for subsequent iterations. We highlight the specific key changes made at each of three iterative versions of the interactive intervention in conjunction with user perception of changes.

Discussion: Virtual agents can be adapted to better meet patient expectations such as being a trustworthy and expert source. Across three evolving versions of a Black, VHA, cues for social presence were particularly important. Social presence cues helped patients engage with CRC screening messages delivered in this novel digital context.

Conclusions: When using a VHA to disseminate health information, cues associated with acceptability can be leveraged and adapted as needed for diverse audiences. Patient characteristics (age, identity, health status) are important to note as they may affect perceptions of a novel health technologies ease of use and relevancy according to the leading models.