The Application of Implicit Measures Evaluating Implicit Attitudes to Assess User Experience in the Human-Technology Interaction Field: A Scoping Review

User experience (UX) research in the Human-Technology Interaction (HTI) field makes use mainly of explicit (self-reported) measures to evaluate the UX of a technical product. Unfortunately, explicit measures present some limitations. For this reason, UX research could benefit from the inclusion of implicit measures (IMs) in the UX evaluation. In the social-psychological literature, the application of IMs evaluating implicit attitudes is a topic of active research; however, less knowledge is present in HTI. To this aim, we present a scoping review of the application of IMs evaluating implicit attitudes in the UX field. We used the Joanna Briggs Institute framework for scoping reviews. A database search was undertaken using IEEE Xplore, Web of Science, ACM digital library, and Science Direct databases. Three research questions have been identified. Of the 8943 identified records, only 12 articles matched the inclusion/exclusion criteria. Results suggest that a combined use of implicit and explicit measures provide a more comprehensive understanding of users’ evaluation of UX yet revealing participant’s divergences in attitudes toward technology especially in studies with robots or chatbots. More research is needed to disentangle this discrepancy and single out the specific factors that could influence this relationship. Taken together, IMs evaluating implicit attitudes should be strongly considered within a more integrated approach to evaluating UX.