Designing Emotions for Health Care Chatbots: Text-Based or Icon-Based Approach

Abstract

Health care chatbots, which are being widely adopted by providers, offer many benefits to users [1]. However, the limited communication capabilities of chatbots hinder their interactions with humans [2]. Therefore, text-based (ie, verbal emotional expression, eg, saying “I am so sorry to hear that”) and icon-based (ie, nonverbal emotional expression, eg, using emojis, emoticons, or stickers) approaches are adopted to communicate emotion in chatbot messages. Previous studies have suggested that both emotion design approaches are effective in improving the evaluation of health care chatbots [3,4]. However, the two approaches differ greatly from each other in their presentation, mechanism, and effectiveness. Understanding such differences could help system developers to optimize their health care chatbots. Nevertheless, research comparing these two approaches of emotion designs, to our knowledge, is nonexistent. This study aims to understand the mechanism and the interaction effect of these two approaches to see if the effect of one approach depends on the other one. In general, we proposed the following hypothesis: both text-based and icon-based emotional clues for health care chatbots can increase perceived emotional intensity (H1). To test the interaction effect of the two approaches, we hypothesized that the addition of an icon-based clue would not significantly affect emotional intensity when a text-based clue is already present (H2). Furthermore, emotional intensity will reduce psychological distance and increase behavioral intention (H3). Please refer to

Multimedia Appendix 1 for the theoretical framework and hypothesis development.