Avatar Appearance Beyond Pixels -- User Ratings and Avatar Preferences within Health Applications

TL;DR

The study investigates how avatar appearance influences user ratings and willingness to disclose health data in a PROMIS-based healthcare application. Using a within-subject design, six avatars with varied genders, attire, and roles were shown to 47 participants who rated warmth, competence, attractiveness, human-likeness, and data-sharing willingness, and selected a favorite avatar. Results identify competence as the primary determinant of avatar preference, with clothing significantly affecting competence and notable gender-by-clothing interactions; warmth and attractiveness play lesser roles and human-likeness is only weakly related to data sharing. The findings underscore the need for careful avatar design in healthcare apps to optimize user experience while mitigating gender-stereotype biases that can skew perceptions and engagement.

Abstract

The appearance of a virtual avatar significantly influences its perceived appropriateness and the user's experience, particularly in healthcare applications. This study analyzed interactions with six avatars of varying characteristics in a patient-reported outcome measures (PROMs) application to investigate correlations between avatar ratings and user preferences. Forty-seven participants completed a healthcare survey involving 30 PROMIS items (Global Health and Physical Function) and then rated the avatars on warmth, competence, attractiveness, and human-likeness, as well as their willingness to share personal data. The results showed that competence was the most critical factor in avatar selection, while human-likeness had minimal impact on health data disclosure. Gender did not significantly affect the ratings, but clothing style played a key role, with male avatars in professional attire rated higher in competence due to gender-stereotypical expectations. In contrast, professional female avatars were rated lower in warmth and attractiveness. These findings underline the importance of thoughtful avatar design in healthcare applications to enhance user experience and engagement.

Figures (4)

• Figure 1: Virtual agents used for the experiment with different gender and social roles. Top left: Avatar A [F,P], top middle: Avatar B [M,P], top right: Avatar C [M,C], buttom left: Avatar D [F,C], buttom middle: Avatar E [F,O], and buttom right Avatar F [O] (M: Male, F: Female, C: Casual, P: Professional, O: Others)
• Figure 2: Experiment setup including two adjacent monitors for displaying the scene with the avatars (on the left desktop) and the questionnaires (on the right desktop).
• Figure 3: Mean values over all recorded user inputs for each avatar rating plus mean values for the final avatar choices. The ratings belong to all six avatars with a specification of social role and gender.
• Figure 4: Mean comparisons of avatars' competence ratings based on clothing style (professional vs. casual) and gender (male vs. female). The bars represent estimated marginal means with error bars indicating standard errors. Pairwise comparisons between conditions are marked with significance levels: (*** p< 0.001 ** p< 0.01 * p< 0.05 n.s. not significant). The results indicate a significant difference in competence ratings between professional and casual clothing, as well as between certain gender and clothing combinations.