Designing Social Robots for Inclusive Child Wellbeing Assessment: Insights from Communities Supporting Developmental Language Disorder and Forced Migration

2026-08-04

AI Summary

Traditional child mental health assessments rely heavily on verbal expression, posing significant challenges for children with developmental language disorders or those from forcibly displaced backgrounds. This study addresses this gap by designing child–robot interaction probes and employing focus group interviews coupled with thematic analysis to explore how social robots can support more inclusive, contextually appropriate, and ethically acceptable well-being assessments. The work presents the first systematic framework of ethical and inclusive design guidelines for robot-mediated assessment tailored to children with diverse communication needs. It identifies critical factors—including robot role, interaction dynamics, individual differences, and child agency—and distills actionable interaction design recommendations. These contributions provide both theoretical grounding and practical guidance for advancing inclusive approaches to child mental health evaluation.

Abstract

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.

Problem

• social robots
• child wellbeing assessment
• Developmental Language Disorder
• forced migration
• inclusive design

Innovation

• social robots
• inclusive design
• child wellbeing assessment
• developmental language disorder
• forced migration