This paper reports the design and qualitative evaluation of a social robot programmed to deliver a talk-based treatment program to improve health behaviour change for food intake and weight loss. A qualitative study was conducted to investigate factors that influenced human-robot interaction and its relationship to health treatment outcomes. Semi-structured interviews were undertaken on completion of a randomised controlled trial that used an autonomous robot to deliver a 4-week behavioral intervention to help coach people to decrease the consumption of high calorie foods. Questions focused on individuals’ preferences, learnings and outcomes from their participation in the trial. Twenty participants completed the treatment, and 18 conducted an interview. Content analysis found that a social robot to deliver a psychotherapeutic treatment was effective and feasible. Participants did make changes to their health behaviour change with a >50% reduction in high calorie intake and average reduction of 4.4 kilograms in weight loss. The robot received positive evaluations on its interactive nature and sociable persona. Most participants made improvements that were aligned with their chosen health goal after completing the robot-delivered sessions, and reported that the robot sessions helped them to achieve their behaviour change goals, such as consuming fewer high calorie foods. Detailed recommendations are provided for the future design of healthcare interventions by robots, including key considerations for robot behaviour, treatment content, and presentation of the program. Future recommendations are presented for the development of robot personalization to more closely resemble techniques and skills from client-centred counselling.

本文报告了一个社交机器人的设计和定性评估，该机器人被编程为提供基于谈话的治疗计划，以改善食物摄入和减肥的健康行为改变。进行了一项定性研究，以调查影响人机交互的因素及其与健康治疗结果的关系。在完成一项随机对照试验后进行了半结构化访谈，该试验使用自主机器人进行为期 4 周的行为干预，以帮助指导人们减少高热量食物的摄入。问题集中在个人参与试验的偏好、学习和结果上。20 名参与者完成了治疗，18 名参与者进行了采访。内容分析发现，提供心理治疗的社交机器人是有效且可行的。参与者确实改变了他们的健康行为，高热量摄入减少了 50% 以上，体重平均减少了 4.4 公斤。该机器人因其互动性和社交性而获得了积极的评价。大多数参与者在完成机器人提供的课程后做出了与他们选择的健康目标一致的改进，并报告说机器人课程帮助他们实现了他们的行为改变目标，例如少吃高热量食物。为未来机器人医疗干预的设计提供了详细的建议，包括机器人行为、治疗内容和程序呈现的关键考虑因素。