"Oh, Sorry, I Think I Interrupted You'': Designing Repair Strategies for Robotic Longitudinal Well-being Coaching

TL;DR

The study tackles how robotic longitudinal well-being coaches should repair mistakes to sustain effective coaching. It introduces a four-phase design process involving a professional mental well-being coach and real-world users to create, test, and refine repair strategies, comparing empathic versus non-empathic approaches. Findings reveal that user expectations diverge from human coaching norms, with repair preferences evolving over time and highly context-dependent; empathic repairs may help early on but can feel inauthentic if overused, while other repair forms (brief apologies, instructions) can be preferable in many scenarios. The work provides actionable, user-centered guidelines for deploying repair strategies in real-world robotic coaching and highlights the need for adaptable, stakeholder-informed designs as robot capabilities evolve.

Abstract

Robotic well-being coaches have been shown to successfully promote people's mental well-being. To provide successful coaching, a robotic coach should have the capability to repair the mistakes it makes. Past investigations of robot mistakes are limited to game or task-based, one-off and in-lab studies. This paper presents a 4-phase design process to design repair strategies for robotic longitudinal well-being coaching with the involvement of real-world stakeholders: 1) designing repair strategies with a professional well-being coach; 2) a longitudinal study with the involvement of experienced users (i.e., who had already interacted with a robotic coach) to investigate the repair strategies defined in (1); 3) a design workshop with users from the study in (2) to gather their perspectives on the robotic coach's repair strategies; 4) discussing the results obtained in (2) and (3) with the mental well-being professional to reflect on how to design repair strategies for robotic coaching. Our results show that users have different expectations for a robotic coach than a human coach, which influences how repair strategies should be designed. We show that different repair strategies (e.g., apologizing, explaining, or repairing empathically) are appropriate in different scenarios, and that preferences for repair strategies change during longitudinal interactions with the robotic coach.

Figures (2)

• Figure 1: A timeline of the four study phases with their goals, methodologies, and outcomes that steered the next phase.
• Figure 2: Longitudinal trends of quantitative measures in users' experiences of empathic and non-empathic repairs.