Abbasi Nida Itrat, Spitale Micol, Jones Peter B, Gunes Hatice
Department of Computer Science and Technology, University of Cambridge (15 JJ Thomson Ave, Cambridge CB3 0FD).
Dept. of Psychiatry, University of Cambridge (Young Peoples Centre Douglas House, 18b Trumpington Rd, Cambridge CB2 8AH).
Interact Stud. 2022 Dec 31;23(2):157-203. doi: 10.1075/is.21027.abb. Epub 2023 Mar 24.
During the last decade, children have shown an increasing need for mental wellbeing interventions due to their anxiety and depression issues, which the COVID-19 pandemic has exacerbated. Socially Assistive Robotics have been shown to have a great potential to support children with mental wellbeing-related issues. However, understanding how robots can be used to aid the measurement of these issues is still an open challenge. This paper presents a narrative review of child-robot interaction (cHRI) papers (IEEE ROMAN proceedings from 2016-2021 and keyword-based article search using Google Scholar) to investigate the open challenges and potential knowledge gaps in the evaluation of mental wellbeing or the assessment of factors affecting mental wellbeing in children. We exploited the SPIDER framework to search for the key elements for the inclusion of relevant studies. Findings from this work (10 screened papers in total) investigate the challenges in cHRI studies about mental wellbeing by categorising the current research in terms of robot-related factors (robot autonomy and type of robot), protocol-related factors (experiment purpose, tasks, participants and user sensing) and data related factors (analysis and findings). The main contribution of this work is to highlight the potential opportunities for cHRI researchers to carry out measurements concerning children's mental wellbeing.
在过去十年中，由于焦虑和抑郁问题，儿童对心理健康干预的需求日益增加，而新冠疫情使这些问题进一步恶化。社交辅助机器人已被证明在支持有心理健康相关问题的儿童方面具有巨大潜力。然而，了解如何利用机器人辅助测量这些问题仍是一个悬而未决的挑战。本文对儿童与机器人交互（cHRI）相关论文进行了叙述性综述（2016年至2021年的IEEE ROMAN会议论文集以及使用谷歌学术进行的基于关键词的文章搜索），以调查在评估儿童心理健康或影响儿童心理健康的因素方面存在的开放性挑战和潜在知识空白。我们利用SPIDER框架搜索纳入相关研究的关键要素。这项工作的结果（总共筛选了10篇论文）通过根据与机器人相关的因素（机器人自主性和机器人类型）、与协议相关的因素（实验目的、任务、参与者和用户感知）以及与数据相关的因素（分析和结果）对当前研究进行分类，来研究cHRI研究中有关心理健康的挑战。这项工作的主要贡献在于突出了cHRI研究人员在进行有关儿童心理健康测量方面的潜在机会。
