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Measuring Mental Wellbeing of Children via Human-Robot Interaction: Challenges and Opportunities
Nida Itrat Abbasi1, Micol Spitale1, Peter B Jones2
1Department of Computer Science and Technology, University of Cambridge (15 JJ Thomson Ave, Cambridge CB3 0FD).
Insights
Socially Assistive Robots show promise for children's mental wellbeing, but measuring these effects is challenging. This review identifies knowledge gaps in child-robot interaction (cHRI) for assessing child mental health.
Area of Science:
- Robotics
- Human-Computer Interaction
- Child Psychology
Background:
- Children's mental wellbeing interventions are increasingly needed, exacerbated by the COVID-19 pandemic.
- Socially Assistive Robotics (SAR) offer potential for supporting children with mental health issues.
- Measuring the impact of robots on child mental wellbeing remains an open challenge.
Purpose of the Study:
- To review child-robot interaction (cHRI) literature concerning children's mental wellbeing.
- To identify challenges and knowledge gaps in evaluating mental wellbeing or related factors in children using robots.
- To explore opportunities for cHRI researchers in measuring children's mental wellbeing.
Main Methods:
- Narrative review of cHRI papers from IEEE ROMAN (2016-2021) and Google Scholar searches.
- Utilized the SPIDER framework for study inclusion criteria.
- Analyzed 10 screened papers.
Main Results:
- Current research categorizes challenges in cHRI for mental wellbeing into robot-related factors (autonomy, type), protocol-related factors (purpose, tasks, participants, sensing), and data-related factors (analysis, findings).
- Identified specific challenges in robot design, experimental protocols, and data analysis for assessing child mental wellbeing.
- Highlighted a need for standardized methodologies in cHRI research for mental health.
Conclusions:
- Significant challenges exist in evaluating children's mental wellbeing through cHRI.
- Opportunities lie in developing more robust methodologies for robot-assisted mental health assessment in children.
- Further research is needed to bridge knowledge gaps in utilizing robots for measuring child mental wellbeing.
Abstract:
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.
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