面向包容型儿童福祉评估的社交机器人设计：来自支持发育性语言障碍（DLD）和被迫移民儿童群体的见解
Designing Social Robots for Inclusive Child Wellbeing Assessment: Insights from Communities Supporting Developmental Language Disorder and Forced Migration
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中文总结 AI 辅助
针对沟通障碍儿童福祉评估的挑战，该研究通过焦点小组分析得出考量因素，提出机器人介导福祉评估的伦理与包容性设计建议，为相关设计提供指导。
中文摘要 AI 辅助
对于存在沟通障碍的儿童，如患有发育性语言障碍（Developmental Language Disorder，DLD）的儿童以及具有被迫移民背景的儿童，评估其福祉与心理健康会格外具有挑战性。在评估过程中，传统的自我报告问卷对语言理解和言语表达提出了极高要求。在此背景下，社交机器人已成为支持福祉评估的有潜力工具，无需完全依赖自我报告问卷，但现有研究中，针对如何设计此类交互以满足具有多样化沟通需求的儿童的包容性、适配性及伦理可接受性的探讨较为有限。为填补这一空白，本研究构建了候选的儿童-机器人交互活动作为设计探针，并与支持DLD儿童和被迫移民儿童的家长及专业人员开展焦点小组讨论。通过主题分析，本研究确定了与机器人角色及能力、交互动态、个体差异、儿童能动性相关的考量因素，以及由儿童沟通需求和生活经历所形成的特定群体考量因素。基于这些发现，本研究推导得出了一套用于机器人介导福祉评估的伦理与包容性设计建议。通过突出这些考量因素和建议，本研究为具有多样化沟通需求的儿童提供了包容型机器人介导福祉评估的设计指导。
英文摘要
Assessing children's wellbeing and mental health can be particularly challenging for children experiencing communication barriers, such as children with Developmental Language Disorder (DLD) and children with forced migration backgrounds. During the assessment process, traditional self-report questionnaires place substantial demands on language comprehension and verbal expression. In this context, social robots have emerged as a promising tool for supporting wellbeing assessment without solely relying on self-report questionnaires, yet limited research has examined how such interactions can be designed to be inclusive, appropriate, and ethically acceptable for children with diverse communication needs. To address this gap, we created candidate child--robot interaction activities as design probes and conducted focus groups with parents and professionals supporting children with DLD and children with forced migration backgrounds. Through thematic analysis, we identified considerations relating to robot role and capabilities, interactional dynamics, individual differences, and child agency, alongside population-specific considerations shaped by children's communication needs and lived experiences. Based on these findings, we derive a set of ethical and inclusive design recommendations for robot-mediated wellbeing assessment. By foregrounding these considerations and recommendations, this work contributes design guidance for inclusive robot-mediated wellbeing assessments for children with diverse communication needs.
