Sharp Gemma, Dwyer Bronwyn, Xie Jue, McNaney Roisin, Shrestha Pranita, Prawira Christopher, Fernando Anne Nileshni, de Boer Kathleen, Hu Hao
Department of Neuroscience, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia.
Department of Human Centred Computing, Monash University, Melbourne, Australia.
J Eat Disord. 2025 Mar 11;13(1):46. doi: 10.1186/s40337-025-01225-x.
Early treatment is critical to improve eating disorder prognosis. Single session interventions have been proposed as a strategy to provide short term support to people on waitlists for eating disorder treatment, however, it is not always possible to access this early intervention. Conversational artificial intelligence agents or "chatbots" reflect a unique opportunity to attempt to fill this gap in service provision. The aim of this research was to co-design a novel chatbot capable of delivering a single session intervention for adults on the waitlist for eating disorder treatment across the diagnostic spectrum and ascertain its preliminary acceptability and feasibility.
A Double Diamond co-design approach was employed which included four phases: discover, define, develop, and deliver. There were 17 participants in total in Australia; ten adults with a lived experience of an eating disorder and seven registered psychologists working in the field of eating disorders, who participated in online interviews and workshops. Thematic and content analyses were undertaken with interview/workshop transcriptions with findings from the previous phase informing the ideas and development of the next phase. A final prototype of a single session intervention chatbot was presented to the participants in the deliver phase.
Thematic and content analyses identified four main themes that were present across the four phases of interviews/workshops: conversational tone, safety and risk management, user journey and session structure, and content.
Overall, the feedback on the single session intervention chatbot was positive throughout the Double Diamond process from both people with a lived experience of an eating disorder and psychologists. Incorporating the feedback across the four themes and four co-design phases allowed for refinement of the chatbot. Further research is required to evaluate the chatbot's efficacy in early treatment settings.
早期治疗对于改善饮食失调的预后至关重要。单次会话干预已被提议作为一种策略，为等待饮食失调治疗的人群提供短期支持，然而，并非总能获得这种早期干预。对话式人工智能代理或“聊天机器人”为填补这一服务提供缺口提供了独特的机会。本研究的目的是共同设计一种新型聊天机器人，能够为处于饮食失调治疗等待名单上的成年人提供单次会话干预，涵盖整个诊断范围，并确定其初步的可接受性和可行性。
采用双钻石共同设计方法，包括四个阶段：发现、定义、开发和交付。澳大利亚共有17名参与者；10名有饮食失调生活经历的成年人和7名在饮食失调领域工作的注册心理学家，他们参与了在线访谈和研讨会。对访谈/研讨会记录进行了主题和内容分析，前一阶段的结果为下一阶段的想法和开发提供了参考。在交付阶段向参与者展示了单次会话干预聊天机器人的最终原型。
主题和内容分析确定了在访谈/研讨会的四个阶段中都存在的四个主要主题：对话语气、安全与风险管理、用户旅程和会话结构以及内容。
总体而言，在双钻石过程中，饮食失调生活经历者和心理学家对单次会话干预聊天机器人的反馈都是积极的。纳入四个主题和四个共同设计阶段的反馈，使聊天机器人得以优化。需要进一步研究来评估该聊天机器人在早期治疗环境中的疗效。
