As conversational agents become increasingly common in behaviour change interventions, understanding optimal feedback delivery mechanisms becomes increasingly important. However, choosing a style that both lessens psychological reactance (perceived threats to freedom) while simultaneously eliciting feelings of surprise and engagement represents a complex design problem. We explored how three different feedback styles: 'Direct', 'Politeness', and 'Verbal Leakage' (slips or disfluencies to reveal a desired behaviour) affect user perceptions and behavioural intentions. Matching expectations from literature, the 'Direct' chatbot led to lower behavioural intentions and higher reactance, while the 'Politeness' chatbot evoked higher behavioural intentions and lower reactance. However, 'Politeness' was also seen as unsurprising and unengaging by participants. In contrast, 'Verbal Leakage' evoked reactance, yet also elicited higher feelings of surprise, engagement, and humour. These findings highlight that effective feedback requires navigating trade-offs between user reactance and engagement, with novel approaches such as 'Verbal Leakage' offering promising alternative design opportunities.

翻译：随着对话代理在行为改变干预中日益普及，理解最优反馈传递机制变得愈发重要。然而，选择一种既能减轻心理抗拒（对自由感的威胁感知），又能同时引发惊喜感与参与度的风格，构成了一个复杂的设计难题。本研究探讨了三种不同反馈风格——"直接型"、"礼貌型"与"言语泄露型"（通过口误或非流利表达揭示期望行为）——如何影响用户感知与行为意向。与文献预期相符，"直接型"聊天机器人导致较低的行为意向与较高的心理抗拒，而"礼貌型"则引发较高的行为意向与较低的心理抗拒。然而，参与者同时认为"礼貌型"缺乏惊喜感与吸引力。相比之下，"言语泄露型"虽会引发心理抗拒，却能带来更高的惊喜感、参与度与幽默感。这些发现表明，有效的反馈设计需要在用户抗拒与参与度之间进行权衡，而诸如"言语泄露型"等创新方法为设计提供了具有前景的替代路径。