1887
Volume 23, Issue 2
  • ISSN 1572-0373
  • E-ISSN: 1572-0381
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Abstract

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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/content/journals/10.1075/is.21027.abb
2023-03-24
2024-04-23
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References

  1. Abbasi, N. I., Spitale, M., Anderson, J., Ford, T., Jones, P. B. & Gunes, H.
    (2022) Can robots help in the evaluation of mental wellbeing in children? an empirical study. In2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 1459–1466. IEEE. 10.1109/RO‑MAN53752.2022.9900843
    https://doi.org/10.1109/RO-MAN53752.2022.9900843 [Google Scholar]
  2. Abe, K., Iwasaki, A., Nakamura, T., Nagai, T., Yokoyama, A., Shimotomai, T., Okada, H. & Omori, T.
    (2012) Playmate robots that can act according to a child’s mental state. In2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 4660–4667. IEEE. 10.1109/IROS.2012.6386037
    https://doi.org/10.1109/IROS.2012.6386037 [Google Scholar]
  3. Abe, K., Hamada, Y., Nagai, T., Shiomi, M. & Omori, T.
    (2017) Estimation of child personality for child-robot interaction. In2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 910–915. IEEE. 10.1109/ROMAN.2017.8172411
    https://doi.org/10.1109/ROMAN.2017.8172411 [Google Scholar]
  4. Adi, Y., Killoran, A., Schrader McMillan, A. & Stewart-Brown, S.
    (2007) Systematic review of interventions to promote mental wellbeing in primary schools. Natl. Inst. Heal. Clin. Excell. (NICE).
    [Google Scholar]
  5. Alimardani, M., Kemmeren, L., Okumura, K. & Hiraki, K.
    (2020) Robot-assisted mindfulness practice: Analysis of neurophysiological responses and affective state change. In2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 683–689. IEEE. 10.1109/RO‑MAN47096.2020.9223428
    https://doi.org/10.1109/RO-MAN47096.2020.9223428 [Google Scholar]
  6. Ardito, G., Mosley, P. & Scollins, L.
    (2014) We, robot: Using robotics to promote collaborative and mathematics learning in a middle school classroom. Middle Grades Res. J. 91.
    [Google Scholar]
  7. Arseneault, L., Kim-Cohen, J., Taylor, A., Caspi, A. & Moffitt, T. E.
    (2005) Psychometric evaluation of 5-and 7-year-old children’s self-reports of conduct problems. J. abnormal child psychology331, 537–550. 10.1007/s10802‑005‑6736‑5
    https://doi.org/10.1007/s10802-005-6736-5 [Google Scholar]
  8. Baxter, P. E., Wood, R., Morse, A. & Belpaeme, T.
    (2011) Memory-centred architectures: Perspectives on human-level cognitive competencies. In2011 AAAI Fall Symposium Series.
    [Google Scholar]
  9. Baxter, P. & Belpaeme, T.
    (2014) Pervasive memory: The future of long-term social hri lies in the past. InThird international symposium on new frontiers in human-robot interaction at AISB.
    [Google Scholar]
  10. Baxter, P., Ashurst, E., Kennedy, J., Senft, E., Lemaignan, S. & Belpaeme, T.
    (2015) The wider supportive role of social robots in the classroom for teachers. In1st Int. Workshop on Educational Robotics at the Int. Conf. Social Robotics. Paris, France, vol.61. Citeseer.
    [Google Scholar]
  11. Baxter, P., Ashurst, E., Read, R., Kennedy, J. & Belpaeme, T.
    (2017) Robot education peers in a situated primary school study: Personalisation promotes child learning. PloS one121, e0178126. 10.1371/journal.pone.0178126
    https://doi.org/10.1371/journal.pone.0178126 [Google Scholar]
  12. Beaudoin, C. & Beauchamp, M. H.
    (2020) Social cognition. InHandbook of Clinical Neurology, vol.1731, 255–264. Elsevier.
    [Google Scholar]
  13. Belpaeme, T., Baxter, P., Read, R., Wood, R., Cuayáhuitl, H., Kiefer, B., Racioppa, S., Kruijff-Korbayová, I., Athanasopoulos, G. & Enescu, V.
    (2012) Multimodal child-robot interaction: Building social bonds. J. Human-Robot Interact. 11.
    [Google Scholar]
  14. Bennion, M., Hardy, G., Moore, R. & Millings, A.
    (2017) E-therapies in england for stress, anxiety or depression: what is being used in the nhs? a survey of mental health services. BMJ open71, e014844. 10.1136/bmjopen‑2016‑014844
    https://doi.org/10.1136/bmjopen-2016-014844 [Google Scholar]
  15. Berger, T., Krieger, T., Sude, K., Meyer, B. & Maercker, A.
    (2018) Evaluating an e-mental health program (,Äúdeprexis, Äù) as adjunctive treatment tool in psychotherapy for depression: Results of a pragmatic randomized controlled trial. J. affective disorders2271, 455–462. 10.1016/j.jad.2017.11.021
    https://doi.org/10.1016/j.jad.2017.11.021 [Google Scholar]
  16. Berking, M. & Wupperman, P.
    (2012) Emotion regulation and mental health: recent findings, current challenges, and future directions. Curr. opinion psychiatry251, 128–134. 10.1097/YCO.0b013e3283503669
    https://doi.org/10.1097/YCO.0b013e3283503669 [Google Scholar]
  17. Bethel, C. L., Stevenson, M. R. & Scassellati, B.
    (2011) Secret-sharing: Interactions between a child, robot, and adult. In2011 IEEE International Conference on systems, man, and cybernetics, 2489–2494. IEEE. 10.1109/ICSMC.2011.6084051
    https://doi.org/10.1109/ICSMC.2011.6084051 [Google Scholar]
  18. Bethel, C. L., Henkel, Z., Stives, K., May, D. C., Eakin, D. K., Pilkinton, M., Jones, A. & Stubbs-Richardson, M.
    (2016) Using robots to interview children about bullying: Lessons learned from an exploratory study. In2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 712–717. IEEE. 10.1109/ROMAN.2016.7745197
    https://doi.org/10.1109/ROMAN.2016.7745197 [Google Scholar]
  19. Bharadwaj, P., Pai, M. M. & Suziedelyte, A.
    (2017) Mental health stigma. Econ. Lett. 1591, 57–60. 10.1016/j.econlet.2017.06.028
    https://doi.org/10.1016/j.econlet.2017.06.028 [Google Scholar]
  20. Bóo, S. J., Childs-Fegredo, J., Cooney, S., Datta, B., Dufour, G., Jones, P. B. & Galante, J.
    (2020) A follow-up study to a randomised control trial to investigate the perceived impact of mindfulness on academic performance in university students. Couns. Psychother. Res. 201, 286–301. 10.1002/capr.12282
    https://doi.org/10.1002/capr.12282 [Google Scholar]
  21. Braun, V. & Clarke, V.
    (2012) Thematic analysis. 10.1037/13620‑004
    https://doi.org/10.1037/13620-004 [Google Scholar]
  22. Bremner, P., Celiktutan, O. & Gunes, H.
    (2016) Personality perception of robot avatar tele-operators. In2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 141–148. IEEE. 10.1109/HRI.2016.7451745
    https://doi.org/10.1109/HRI.2016.7451745 [Google Scholar]
  23. Broekens, J., Heerink, M., Rosendal, H.
    (2009) Assistive social robots in elderly care: a review. Gerontechnology81, 94–103. 10.4017/gt.2009.08.02.002.00
    https://doi.org/10.4017/gt.2009.08.02.002.00 [Google Scholar]
  24. Cabibihan, J.-J., Javed, H., Ang, M. & Aljunied, S. M.
    (2013) Why robots? a survey on the roles and benefits of social robots in the therapy of children with autism. Int. journal social robotics51, 593–618. 10.1007/s12369‑013‑0202‑2
    https://doi.org/10.1007/s12369-013-0202-2 [Google Scholar]
  25. Carey, S. & Markman, E. M.
    (1999) Cognitive development. InCognitive science, 201–254. Elsevier. 10.1016/B978‑012601730‑4/50007‑X
    https://doi.org/10.1016/B978-012601730-4/50007-X [Google Scholar]
  26. Carter, R. B. & Mason, P. S.
    (1998) The selection and use of puppets in counseling. Prof. Sch. Couns. 11, 50–53.
    [Google Scholar]
  27. Catania, F., Spitale, M. & Garzotto, F.
    (2021) Conversational agents in therapeutic interventions for neurodevelopmental disorders: A survey. ACM Comput. Surv. (CSUR).
    [Google Scholar]
  28. Causo, A., Vo, G. T., Chen, I.-M. & Yeo, S. H.
    (2016) Design of robots used as education companion and tutor. InRobotics and mechatronics, 75–84. Springer. 10.1007/978‑3‑319‑22368‑1_8
    https://doi.org/10.1007/978-3-319-22368-1_8 [Google Scholar]
  29. Chen, H., Park, H. W. & Breazeal, C.
    (2020) Teaching and learning with children: Impact of reciprocal peer learning with a social robot on children, Äôs learning and emotive engagement. Comput. & Educ. 1501, 103836. 10.1016/j.compedu.2020.103836
    https://doi.org/10.1016/j.compedu.2020.103836 [Google Scholar]
  30. Coeckelbergh, M., Pop, C., Simut, R., Peca, A., Pintea, S., David, D. & Vanderborght, B.
    (2016) A survey of expectations about the role of robots in robot-assisted therapy for children with asd: ethical acceptability, trust, sociability, appearance, and attachment. Sci. engineering ethics221, 47–65. 10.1007/s11948‑015‑9649‑x
    https://doi.org/10.1007/s11948-015-9649-x [Google Scholar]
  31. Coninx, A., Baxter, P., Oleari, E., Bellini, S., Bierman, B., Henkemans, O., Cañamero, L., Cosi, P., Enescu, V. & Espinoza, R.
    (2016) Towards long-term social child-robot interaction: using multi-activity switching to engage young users. J. Human-Robot Interact.
    [Google Scholar]
  32. Cook, A., Encarnação, P. & Adams, K.
    (2010) Robots: Assistive technologies for play, learning and cognitive development. Technol. Disabil. 221, 127–145. 10.3233/TAD‑2010‑0297
    https://doi.org/10.3233/TAD-2010-0297 [Google Scholar]
  33. Cooke, A., Smith, D. & Booth, A.
    (2012) Beyond pico: the spider tool for qualitative evidence synthesis. Qual. health research221, 1435–1443. 10.1177/1049732312452938
    https://doi.org/10.1177/1049732312452938 [Google Scholar]
  34. Corrigan, P.
    (2004) How stigma interferes with mental health care. Am. psychologist591, 614. 10.1037/0003‑066X.59.7.614
    https://doi.org/10.1037/0003-066X.59.7.614 [Google Scholar]
  35. Cronch, L. E., Viljoen, J. L. & Hansen, D. J.
    (2006) Forensic interviewing in child sexual abuse cases: Current techniques and future directions. Aggress. violent behavior111, 195–207. 10.1016/j.avb.2005.07.009
    https://doi.org/10.1016/j.avb.2005.07.009 [Google Scholar]
  36. Cross, E. S., Riddoch, K. A., Pratts, J., Titone, S., Chaudhury, B. & Hortensius, R.
    (2019) A neurocognitive investigation of the impact of socializing with a robot on empathy for pain. Philos. Transactions Royal Soc. B3741, 20180034. 10.1098/rstb.2018.0034
    https://doi.org/10.1098/rstb.2018.0034 [Google Scholar]
  37. De Greeff, J., Janssen, J. B., Looije, R., Mioch, T., Alpay, L., Neerincx, M. A., Baxter, P. & Belpaeme, T.
    (2013) Activity switching in child-robot interaction: a hospital case study. In5th International Conference on Social Robotics (ICSR), vol.82391, 585–586. SPRINGER-VERLAG BERLIN.
    [Google Scholar]
  38. de Greeff, J., Henkemans, O. B., Fraaije, A., Solms, L., Wigdor, N. & Bierman, B.
    (2014) Child-robot interaction in the wild: field testing activities of the aliz-e project. In2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 148–149. IEEE. 10.1145/2559636.2559804
    https://doi.org/10.1145/2559636.2559804 [Google Scholar]
  39. Deighton, J., Croudace, T., Fonagy, P., Brown, J., Patalay, P. & Wolpert, M.
    (2014) Measuring mental health and wellbeing outcomes for children and adolescents to inform practice and policy: a review of child self-report measures. Child adolescent psychiatry mental health81, 1–14. 10.1186/1753‑2000‑8‑14
    https://doi.org/10.1186/1753-2000-8-14 [Google Scholar]
  40. Di Nuovo, A., Varrasi, S., Lucas, A., Conti, D., McNamara, J. & Soranzo, A.
    (2019) Assessment of cognitive skills via human-robot interaction and cloud computing. J. bionic engineering161, 526–539. 10.1007/s42235‑019‑0043‑2
    https://doi.org/10.1007/s42235-019-0043-2 [Google Scholar]
  41. Diener, E. & Suh, E.
    (1997) Measuring quality of life: Economic, social, and subjective indicators. Soc. indicators research401, 189–216. 10.1023/A:1006859511756
    https://doi.org/10.1023/A:1006859511756 [Google Scholar]
  42. Diener, E., Suh, E. M., Lucas, R. E. & Smith, H. L.
    (1999) Subjective well-being: Three decades of progress. Psychol. bulletin1251, 276. 10.1037/0033‑2909.125.2.276
    https://doi.org/10.1037/0033-2909.125.2.276 [Google Scholar]
  43. Dodge, R., Daly, A. P., Huyton, J. & Sanders, L. D.
    (2012) The challenge of defining wellbeing. Int. journal wellbeing21. 10.5502/ijw.v2i3.4
    https://doi.org/10.5502/ijw.v2i3.4 [Google Scholar]
  44. Druga, S., Williams, R., Breazeal, C. & Resnick, M.
    (2017) “hey google is it ok if i eat you?” initial explorations in child-agent interaction. InProceedings of the 2017 conference on interaction design and children, 595–600. 10.1145/3078072.3084330
    https://doi.org/10.1145/3078072.3084330 [Google Scholar]
  45. Esteban, P. G., Cao, H.-L., De Beir, A., Van de Perre, G., Lefeber, D. & Vanderborght, B.
    (2016) A multilayer reactive system for robots interacting with children with autism. arXiv preprint arXiv:1606.03875.
    [Google Scholar]
  46. Esteban, P. G., Baxter, P., Belpaeme, T., Billing, E., Cai, H., Cao, H.-L., Coeckelbergh, M., Costescu, C., David, D. & De Beir, A.
    (2017) How to build a supervised autonomous system for robot-enhanced therapy for children with autism spectrum disorder. Paladyn, J. Behav. Robotics81, 18–38. 10.1515/pjbr‑2017‑0002
    https://doi.org/10.1515/pjbr-2017-0002 [Google Scholar]
  47. Feil-Seifer, D. & Mataric, M. J.
    (2005) Defining socially assistive robotics. In9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005, 465–468. IEEE. 10.1109/ICORR.2005.1501143
    https://doi.org/10.1109/ICORR.2005.1501143 [Google Scholar]
  48. Feil-Seifer, D. & Matarić, M. J.
    (2009) Toward socially assistive robotics for augmenting interventions for children with autism spectrum disorders. InExperimental robotics, 201–210. Springer. 10.1007/978‑3‑642‑00196‑3_24
    https://doi.org/10.1007/978-3-642-00196-3_24 [Google Scholar]
  49. Fischer, K. W. & Bullock, D.
    (1984) Cognitive development in school-age children: Conclusions and new directions. Dev. during middle childhood: The years from six to twelve70–146.
    [Google Scholar]
  50. Ford, T., Vizard, T., Sadler, K., McManus, S., Goodman, A., Merad, S., Tejerina-Arreal, M., Collinson, D. & MHCYP Collaboration
    (2020) Data resource profile: Mental health of children and young people (mhcyp) surveys. Int. journal epidemiology491, 363–364g. 10.1093/ije/dyz259
    https://doi.org/10.1093/ije/dyz259 [Google Scholar]
  51. Ford, T., John, A. & Gunnell, D.
    (2021) Mental health of children and young people during pandemic. 10.1136/bmj.n614
    https://doi.org/10.1136/bmj.n614 [Google Scholar]
  52. Gamborino, E., Yueh, H.-P., Lin, W., Yeh, S.-L. & Fu, L.-C.
    (2019) Mood estimation as a social profile predictor in an autonomous, multi-session, emotional support robot for children. In2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 1–6. IEEE. 10.1109/RO‑MAN46459.2019.8956460
    https://doi.org/10.1109/RO-MAN46459.2019.8956460 [Google Scholar]
  53. Godoi, D., Romero, R. A. F., Azevedo, H., Ramos, J., Beraldo Filho, G. & Garcia, Márcia Ap Thome
    (2020) Proteger: A social robotics system to support child psychological evaluation. In2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE), 1–6. IEEE. 10.1109/LARS/SBR/WRE51543.2020.9306975
    https://doi.org/10.1109/LARS/SBR/WRE51543.2020.9306975 [Google Scholar]
  54. Goldschmidt, K.
    (2020) The covid-19 pandemic: Technology use to support the wellbeing of children. J. pediatric nursing531, 88. 10.1016/j.pedn.2020.04.013
    https://doi.org/10.1016/j.pedn.2020.04.013 [Google Scholar]
  55. Goris, K., Saldien, J., Vanderniepen, I. & Lefeber, D.
    (2008) The huggable robot probo, a multi-disciplinary research platform. InInternational Conference on Research and Education in Robotics, 29–41. Springer.
    [Google Scholar]
  56. Gustafson, D. H.
    (2011) An e-health solution for people with alcohol problems. Alcohol Res. & Heal. 331, 327.
    [Google Scholar]
  57. Haleemunnissa, S., Didel, S., Swami, M. K., Singh, K. & Vyas, V.
    (2021) Children and covid19: Understanding impact on the growth trajectory of an evolving generation. Child. youth services review1201, 105754. 10.1016/j.childyouth.2020.105754
    https://doi.org/10.1016/j.childyouth.2020.105754 [Google Scholar]
  58. Hartwig, J. & Wilson, J. C.
    (2002) Factors affecting children’s disclosure of secrets in an investigatory interview. Child Abus. Rev. J. Br. Assoc. for Study Prev. Child Abus. Negl. 111, 77–93. 10.1002/car.725
    https://doi.org/10.1002/car.725 [Google Scholar]
  59. Hood, D., Lemaignan, S. & Dillenbourg, P.
    (2015) When children teach a robot to write: An autonomous teachable humanoid which uses simulated handwriting. InProceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, 83–90. 10.1145/2696454.2696479
    https://doi.org/10.1145/2696454.2696479 [Google Scholar]
  60. Ismail, L. I., Shamsudin, S., Yussof, H., Hanapiah, F. A. & Zahari, N. I.
    (2012) Estimation of concentration by eye contact measurement in robot-based intervention program with autistic children. Procedia Eng. 411, 1548–1552. 10.1016/j.proeng.2012.07.348
    https://doi.org/10.1016/j.proeng.2012.07.348 [Google Scholar]
  61. Jayawardena, C., Kuo, I.-H., Broadbent, E. & MacDonald, B. A.
    (2014) Socially assistive robot healthbot: Design, implementation, and field trials. IEEE Syst. J. 101, 1056–1067. 10.1109/JSYST.2014.2337882
    https://doi.org/10.1109/JSYST.2014.2337882 [Google Scholar]
  62. Kabacińska, K., Prescott, T. J. & Robillard, J. M.
    (2021) Socially assistive robots as mental health interventions for children: a scoping review. Int. J. Soc. Robotics131, 919–935. 10.1007/s12369‑020‑00679‑0
    https://doi.org/10.1007/s12369-020-00679-0 [Google Scholar]
  63. Kanda, T. & Ishiguro, H.
    (2006) An approach for a social robot to understand human relationships: Friendship estimation through interaction with robots. Interact. Stud. 71, 369–403. 10.1075/is.7.3.12kan
    https://doi.org/10.1075/is.7.3.12kan [Google Scholar]
  64. Kawaguchi, Y., Wada, K., Okamoto, M., Tsujii, T., Shibata, T. & Sakatani, K.
    (2012) Investigation of brain activity after interaction with seal robot measured by fnirs. In2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, 571–576. IEEE. 10.1109/ROMAN.2012.6343812
    https://doi.org/10.1109/ROMAN.2012.6343812 [Google Scholar]
  65. Kennedy, J., Baxter, P. & Belpaeme, T.
    (2013) Constraining content in mediated unstructured social interactions: Studies in the wild. In2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, 728–733. IEEE. 10.1109/ACII.2013.135
    https://doi.org/10.1109/ACII.2013.135 [Google Scholar]
  66. Kim, J. C., Azzi, P., Jeon, M., Howard, A. M. & Park, C. H.
    (2017) Audio-based emotion estimation for interactive robotic therapy for children with autism spectrum disorder. In2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 39–44. IEEE. 10.1109/URAI.2017.7992881
    https://doi.org/10.1109/URAI.2017.7992881 [Google Scholar]
  67. Komatsubara, T., Shiomi, M., Kaczmarek, T., Kanda, T. & Ishiguro, H.
    (2019) Estimating children’s social status through their interaction activities in classrooms with a social robot. Int. J. Soc. Robotics111, 35–48. 10.1007/s12369‑018‑0474‑7
    https://doi.org/10.1007/s12369-018-0474-7 [Google Scholar]
  68. Kozlova, E. A., Slobodskaya, H. R. & Gartstein, M. A.
    (2020) Early temperament as a predictor of child mental health. Int. J. Mental Heal. Addict. 181, 1493–1506. 10.1007/s11469‑019‑00181‑3
    https://doi.org/10.1007/s11469-019-00181-3 [Google Scholar]
  69. Kretzschmar, K., Tyroll, H., Pavarini, G., Manzini, A., Singh, I. & NeurOx Young People’s Advisory Group
    (2019) Can your phone be your therapist? young people, Äôs ethical perspectives on the use of fully automated conversational agents (chatbots) in mental health support. Biomed. informatics insights111, 1178222619829083. 10.1177/1178222619829083
    https://doi.org/10.1177/1178222619829083 [Google Scholar]
  70. Kruijff-Korbayová, I., Kiefer, B., Baroni, I. & Zelati, M. C.
    (2013) Making human-robot quiz dialogue more conversational by adding non-quiz talk. InThe 17th Workshop on the Semantics and Pragmatics of Dialogue (DialDam)(p. Poster). Amsterdam, The Netherlands.
    [Google Scholar]
  71. Kumar Singh, D., Sharma, S., Shukla, J. & Eden, G.
    (2020) Toy, tutor, peer, or pet? preliminary findings from child-robot interactions in a community school. InCompanion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 325–327.
    [Google Scholar]
  72. Landry, S. H., Zucker, T. A., Taylor, H. B., Swank, P. R., Williams, J. M., Assel, M., Crawford, A., Huang, W., Clancy-Menchetti, J. & Lonigan, C. J.
    (2014) Enhancing early child care quality and learning for toddlers at risk: the responsive early childhood program. Dev. psychology501, 526. 10.1037/a0033494
    https://doi.org/10.1037/a0033494 [Google Scholar]
  73. Leigh, E., Chiu, K. & Clark, D. M.
    (2021) Is concentration an indirect link between social anxiety and educational achievement in adolescents?PloS one161, e0249952. 10.1371/journal.pone.0249952
    https://doi.org/10.1371/journal.pone.0249952 [Google Scholar]
  74. Leite, I., Martinho, C., Pereira, A. & Paiva, A.
    (2009) As time goes by: Long-term evaluation of social presence in robotic companions. InRO-MAN 2009-the 18th IEEE international symposium on robot and human interactive communication, 669–674. IEEE. 10.1109/ROMAN.2009.5326256
    https://doi.org/10.1109/ROMAN.2009.5326256 [Google Scholar]
  75. Li, J.
    (2015) The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresent robots and virtual agents. Int. J. Human-Computer Stud. 771, 23–37. 10.1016/j.ijhcs.2015.01.001
    https://doi.org/10.1016/j.ijhcs.2015.01.001 [Google Scholar]
  76. Lim, V., Rooksby, M. & Cross, E. S.
    (2021) Social robots on a global stage: establishing a role for culture during human-robot interaction. Int. J. Soc. Robotics131, 1307–1333. 10.1007/s12369‑020‑00710‑4
    https://doi.org/10.1007/s12369-020-00710-4 [Google Scholar]
  77. Lyakso, E., Frolova, O. & Grigorev, A.
    (2017) Perception and acoustic features of speech of children with autism spectrum disorders. InInternational Conference on Speech and Computer, 602–612. Springer. 10.1007/978‑3‑319‑66429‑3_60
    https://doi.org/10.1007/978-3-319-66429-3_60 [Google Scholar]
  78. Mak, W. W., Poon, C. Y., Pun, L. Y. & Cheung, S. F.
    (2007) Meta-analysis of stigma and mental health. Soc. science & medicine651, 245–261. 10.1016/j.socscimed.2007.03.015
    https://doi.org/10.1016/j.socscimed.2007.03.015 [Google Scholar]
  79. Moyle, W., Cooke, M., Beattie, E., Jones, C., Klein, B., Cook, G. & Gray, C.
    (2013) Exploring the effect of companion robots on emotional expression in older adults with dementia: a pilot randomized controlled trial. J. gerontological nursing391, 46–53. 10.3928/00989134‑20130313‑03
    https://doi.org/10.3928/00989134-20130313-03 [Google Scholar]
  80. Neerincx, A., Sacchitelli, F., Kaptein, R., Van Der Pal, S., Oleari, E. & Neerincx, M. A.
    (2016) Child’s culture-related experiences with a social robot at diabetes camps. In2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 485–86. IEEE. 10.1109/HRI.2016.7451818
    https://doi.org/10.1109/HRI.2016.7451818 [Google Scholar]
  81. Nock, M. K. & Kazdin, A. E.
    (2001) Parent expectancies for child therapy: Assessment and relation to participation in treatment. J. Child Fam. Stud. 101, 155–180. 10.1023/A:1016699424731
    https://doi.org/10.1023/A:1016699424731 [Google Scholar]
  82. World Health Organization
    (2004) Promoting mental health: Concepts, emerging evidence, practice: Summary report. World Health Organization.
    [Google Scholar]
  83. Pachidis, T., Vrochidou, E., Kaburlasos, V. G., Kostova, S., Bonković, M. & Papić, V.
    (2018) Social robotics in education: State-of-the-art and directions. InInternational Conference on Robotics in Alpe-Adria Danube Region, 689–700. Springer.
    [Google Scholar]
  84. Parrish, E., Giaschi, D., Boden, C. & Dougherty, R.
    (2005) The maturation of form and motion perception in school age children. Vis. Res. 451, 827–837. 10.1016/j.visres.2004.10.005
    https://doi.org/10.1016/j.visres.2004.10.005 [Google Scholar]
  85. Pescosolido, B. A., Jensen, P. S., Martin, J. K., Perry, B. L., Olafsdottir, S. & Fettes, D.
    (2008) Public knowledge and assessment of child mental health problems: Findings from the national stigma study-children. J. Am. Acad. Child & Adolesc. Psychiatry471, 339–349. 10.1097/CHI.0b013e318160e3a0
    https://doi.org/10.1097/CHI.0b013e318160e3a0 [Google Scholar]
  86. Rauchbauer, B., Nazarian, B., Bourhis, M., Ochs, M., Prévot, L. & Chaminade, T.
    (2019) Brain activity during reciprocal social interaction investigated using conversational robots as control condition. Philos. Transactions Royal Soc. B3741, 20180033. 10.1098/rstb.2018.0033
    https://doi.org/10.1098/rstb.2018.0033 [Google Scholar]
  87. Rauchbauer, B., Hmamouche, Y., Bigi, B., Prevot, L., Ochs, M. & Thierry, C.
    (2020) Multimodal corpus of bidirectional conversation of human-human and human-robot interaction during fmri scanning. InProceedings of The 12th Language Resources and Evaluation Conference, 661–668. European Language Resources Association.
    [Google Scholar]
  88. Riek, L. D.
    (2012) Wizard of oz studies in hri: a systematic review and new reporting guidelines. J. Human-Robot Interact. 11, 119–136. 10.5898/JHRI.1.1.Riek
    https://doi.org/10.5898/JHRI.1.1.Riek [Google Scholar]
  89. Rivenbark, J. G., Copeland, W. E., Davisson, E. K., Gassman-Pines, A., Hoyle, R. H., Piontak, J. R., Russell, M. A., Skinner, A. T. & Odgers, C. L.
    (2019) Perceived social status and mental health among young adolescents: Evidence from census data to cellphones. Dev. psychology551, 574. 10.1037/dev0000551
    https://doi.org/10.1037/dev0000551 [Google Scholar]
  90. Robinette, P., Wagner, A. R. & Howard, A. M.
    (2016) Assessment of robot to human instruction conveyance modalities across virtual, remote and physical robot presence. In2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 1044–1050. IEEE. 10.1109/ROMAN.2016.7745237
    https://doi.org/10.1109/ROMAN.2016.7745237 [Google Scholar]
  91. Rockhill, C. M., Fan, M.-Y., Katon, W. J., McCauley, E., Crick, N. R., Pleck, J. H.
    (2007) Friendship interactions in children with and without depressive symptoms: Observation of emotion during game-playing interactions and post-game evaluations. J. abnormal child psychology351, 429–441. 10.1007/s10802‑007‑9101‑z
    https://doi.org/10.1007/s10802-007-9101-z [Google Scholar]
  92. Rolls, E. T.
    (2019) The cingulate cortex and limbic systems for emotion, action, and memory. Brain Struct. Funct. 2241, 3001–3018. 10.1007/s00429‑019‑01945‑2
    https://doi.org/10.1007/s00429-019-01945-2 [Google Scholar]
  93. Ros, R., Nalin, M., Wood, R., Baxter, P., Looije, R., Demiris, Y., Belpaeme, T., Giusti, A. & Pozzi, C.
    (2011) Child-robot interaction in the wild: advice to the aspiring experimenter. InProceedings of the 13th international conference on multimodal interfaces, 335–342. 10.1145/2070481.2070545
    https://doi.org/10.1145/2070481.2070545 [Google Scholar]
  94. Ros, R. & Demiris, Y.
    (2013) Creative dance: An approach for social interaction between robots and children. InInternational Workshop on Human Behavior Understanding, 40–51. Springer. 10.1007/978‑3‑319‑02714‑2_4
    https://doi.org/10.1007/978-3-319-02714-2_4 [Google Scholar]
  95. Rudovic, O., Lee, J., Mascarell-Maricic, L., Schuller, B. W. & Picard, R. W.
    (2017) Measuring engagement in robot-assisted autism therapy: a cross-cultural study. Front. Robotics AI41, 36. 10.3389/frobt.2017.00036
    https://doi.org/10.3389/frobt.2017.00036 [Google Scholar]
  96. Sabanovic, S., Michalowski, M. P. & Simmons, R.
    (2006) Robots in the wild: Observing human-robot social interaction outside the lab. In9th IEEE International Workshop on Advanced Motion Control, 20061., 596–601. IEEE. 10.1109/AMC.2006.1631758
    https://doi.org/10.1109/AMC.2006.1631758 [Google Scholar]
  97. Salter, T., Werry, I. & Michaud, F.
    (2008) Going into the wild in child-robot interaction studies: issues in social robotic development. Intell. Serv. Robotics11, 93–108. 10.1007/s11370‑007‑0009‑9
    https://doi.org/10.1007/s11370-007-0009-9 [Google Scholar]
  98. Sandygulova, A. & O’Hare, G. M.
    (2018) Age-and gender-based differences in children’s interactions with a gender-matching robot. Int. J. Soc. Robotics101, 687–700. 10.1007/s12369‑018‑0472‑9
    https://doi.org/10.1007/s12369-018-0472-9 [Google Scholar]
  99. Sano, T., Horii, T., Abe, K. & Nagai, T.
    (2020) Explainable temperament estimation of toddlers by a childcare robot. In2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 159–164. IEEE. 10.1109/RO‑MAN47096.2020.9223574
    https://doi.org/10.1109/RO-MAN47096.2020.9223574 [Google Scholar]
  100. Scassellati, B., Admoni, H. & Matarić, M.
    (2012) Robots for use in autism research. Annu. review biomedical engineering141, 275–294. 10.1146/annurev‑bioeng‑071811‑150036
    https://doi.org/10.1146/annurev-bioeng-071811-150036 [Google Scholar]
  101. Shahid, S., Krahmer, E. & Swerts, M.
    (2014) Child-robot interaction across cultures: How does playing a game with a social robot compare to playing a game alone or with a friend?Comput. Hum. Behav. 401, 86–100. 10.1016/j.chb.2014.07.043
    https://doi.org/10.1016/j.chb.2014.07.043 [Google Scholar]
  102. Shi, Z., Groechel, T. R., Jain, S., Chima, K., Rudovic, O. & Matarić, M. J.
    (2021) Toward personalized affect-aware socially assistive robot tutors in long-term interventions for children with autism. arXiv preprint arXiv:2101.10580.
    [Google Scholar]
  103. Siegler, R. S.
    (1994) Cognitive variability: A key to understanding cognitive development. Curr. directions psychological science31, 1–5. 10.1111/1467‑8721.ep10769817
    https://doi.org/10.1111/1467-8721.ep10769817 [Google Scholar]
  104. Spitale, M., Silleresi, S., Cosentino, G., Panzeri, F. & Garzotto, F.
    (2020) “whom would you like to talk with?” exploring conversational agents for children’s linguistic assessment. InProceedings of the Interaction Design and Children Conference, 262–272. 10.1145/3392063.3394421
    https://doi.org/10.1145/3392063.3394421 [Google Scholar]
  105. Taumoepeau, M. & Ruffman, T.
    (2008) Stepping stones to others’ minds: Maternal talk relates to child mental state language and emotion understanding at 15, 24, and 33 months. Child development791, 284–302. 10.1111/j.1467‑8624.2007.01126.x
    https://doi.org/10.1111/j.1467-8624.2007.01126.x [Google Scholar]
  106. Thieme, A., Wallace, J., Meyer, T. D. & Olivier, P.
    (2015) Designing for mental wellbeing: towards a more holistic approach in the treatment and prevention of mental illness. InProceedings of the 2015 British HCI Conference, 1–10. 10.1145/2783446.2783586
    https://doi.org/10.1145/2783446.2783586 [Google Scholar]
  107. Ting, K. L. H., Voilmy, D., Iglesias, A., Pulido, J. C., García, J., Romero-Garcés, A., Bandera, J. P., Marfil, R. & Dueñas, Á.
    (2017) Integrating the users in the design of a robot for making comprehensive geriatric assessments (cga) to elderly people in care centers. In2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 483–488. IEEE. 10.1109/ROMAN.2017.8172346
    https://doi.org/10.1109/ROMAN.2017.8172346 [Google Scholar]
  108. Tozadore, D., Pinto, A., Romero, R. & Trovato, G.
    (2017) Wizard of oz vs autonomous: Children’s perception changes according to robot’s operation condition. In2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 664–669. IEEE. 10.1109/ROMAN.2017.8172374
    https://doi.org/10.1109/ROMAN.2017.8172374 [Google Scholar]
  109. Tsoi, N., Connolly, J., Adéníran, E., Hansen, A., Pineda, K. T., Adamson, T., Thompson, S., Ramnauth, R., Vázquez, M. & Scassellati, B.
    (2021) Challenges deploying robots during a pandemic: An effort to fight social isolation among children. InProceedings of the 2021 ACM/IEEE International Conference on Human-Robot Interaction, 234–242. 10.1145/3434073.3444665
    https://doi.org/10.1145/3434073.3444665 [Google Scholar]
  110. Uchida, T., Takahashi, H., Ban, M., Shimaya, J., Yoshikawa, Y. & Ishiguro, H.
    (2017) A robot counseling system, Äîwhat kinds of topics do we prefer to disclose to robots?In2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 207–212. IEEE. 10.1109/ROMAN.2017.8172303
    https://doi.org/10.1109/ROMAN.2017.8172303 [Google Scholar]
  111. van Agteren, J., Iasiello, M., Lo, L., Bartholomaeus, J., Kopsaftis, Z., Carey, M. & Kyrios, M.
    (2021) A systematic review and meta-analysis of psychological interventions to improve mental wellbeing. Nat. Hum. Behav. 51, 631–652. 10.1038/s41562‑021‑01093‑w
    https://doi.org/10.1038/s41562-021-01093-w [Google Scholar]
  112. Van Der Drift, E. J., Beun, R.-J., Looije, R., Henkemans, O. A. B. & Neerincx, M. A.
    (2014) A remote social robot to motivate and support diabetic children in keeping a diary. In2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 463–70. IEEE. 10.1145/2559636.2559664
    https://doi.org/10.1145/2559636.2559664 [Google Scholar]
  113. Vanderborght, R. S., Vanderfaeillie, J., Cao, H.-L., Lefeber, D. & Vanderborght, B.
    (2016) Are social robots social enough for preschoolers with autism spectrum disorder?InXI Autism Europe International Conference.
    [Google Scholar]
  114. Venture, G., Indurkhya, B. & Izui, T.
    (2017) Dance with me! child-robot interaction in the wild. InInternational Conference on Social Robotics, 375–382. Springer. 10.1007/978‑3‑319‑70022‑9_37
    https://doi.org/10.1007/978-3-319-70022-9_37 [Google Scholar]
  115. Villani, V., Righi, M., Sabattini, L. & Secchi, C.
    (2020) Wearable devices for the assessment of cognitive effort for human-robot interaction. IEEE Sensors J. 201, 13047–13056. 10.1109/JSEN.2020.3001635
    https://doi.org/10.1109/JSEN.2020.3001635 [Google Scholar]
  116. Wassell, E. & Dodge, R.
    (2015) A multidisciplinary framework for measuring and improving wellbeing. Int. J. Sci. Basic Appl. Res211, 97–107.
    [Google Scholar]
  117. Wellman, H. M., Song, J.-H. & Peskin-Shepherd, H.
    (2019) Children’s early awareness of comprehension as evident in their spontaneous corrections of speech errors. Child Dev. 901, 196–209. 10.1111/cdev.12862
    https://doi.org/10.1111/cdev.12862 [Google Scholar]
  118. Williams, R., Machado, C. V., Druga, S., Breazeal, C. & Maes, P.
    (2018) “my doll says it’s ok” a study of children’s conformity to a talking doll. InProceedings of the 17th ACM Conference on Interaction Design and Children, 625–631. 10.1145/3202185.3210788
    https://doi.org/10.1145/3202185.3210788 [Google Scholar]
  119. Woodward, K., Kanjo, E., Brown, D. J. & Inkster, B.
    (2020) Tangtoys: smart toys to communicate and improve children’s wellbeing. InAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, 497–449. 10.1145/3410530.3414375
    https://doi.org/10.1145/3410530.3414375 [Google Scholar]
  120. Woolf, C., Caute, A., Haigh, Z., Galliers, J., Wilson, S., Kessie, A., Hirani, S., Hegarty, B. & Marshall, J.
    (2016) A comparison of remote therapy, face to face therapy and an attention control intervention for people with aphasia: a quasi-randomised controlled feasibility study. Clin. rehabilitation301, 359–373. 10.1177/0269215515582074
    https://doi.org/10.1177/0269215515582074 [Google Scholar]
  121. Xiuqin, H., Huimin, Z., Mengchen, L., Jinan, W., Ying, Z. & Ran, T.
    (2010) Mental health, personality, and parental rearing styles of adolescents with internet addiction disorder. Cyberpsychology, Behav. Soc. Netw. 131, 401–06. 10.1089/cyber.2009.0222
    https://doi.org/10.1089/cyber.2009.0222 [Google Scholar]
  122. Yousif, J.
    (2021) Social and telepresence robots a future of teaching. 10.36227/techrxiv.15152073.v1
    https://doi.org/10.36227/techrxiv.15152073.v1 [Google Scholar]
  123. Ziemer, C. J., Wyss, S. & Rhinehart, K.
    (2021) The origins of touchscreen competence: Examining infants’ exploration of touchscreens. Infant Behav. Dev. 641, 101609. 10.1016/j.infbeh.2021.101609
    https://doi.org/10.1016/j.infbeh.2021.101609 [Google Scholar]
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  • Article Type: Research Article
Keyword(s): children; mental wellbeing assessment; robots
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