Long seconds: how AI text-loading design affects the subjective feeling of waiting for users

An AI doctor agent is an intelligent medical tool that interacts with users through text-based dialogues to provide convenient health consultations and preliminary diagnostic services. However, during the interaction process, users inevitably encounter loading delays, making the design of appropriate text-based loading indicators particularly crucial. These loading indicators not only provide visual feedback but also help alleviate user anxiety, enhance trust in the system, and improve the overall user experience (UX). This study primarily explores the impact of different loading indicator designs—specifically, animation, gradient, and loop—on users' perceived waiting times and preferences. We conducted an experimental analysis with 30 participants recruited through convenience sampling. The results indicate that (1) loading indicators with gradient effects can effectively reduce users' subjective perception of loading duration, making the wait seem shorter; (2) animated and gradient loading methods can effectively reduce user boredom during waiting periods, helping to maintain a positive experiential state; (3) in practical use, users generally prefer animated loading presentations, finding them more engaging and visually appealing; and (4) compared to loop and gradient methods, the animated loading method received higher scores on the System Usability Scale (SUS), further validating its design advantages. The findings of this study provide important references for the practice and design of medical conversational agents and offer valuable insights for application development in other fields, enriching the theoretical foundation of generative AI within the domain of Human-Computer Interaction (HCI).