Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
125 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A Longitudinal Study of Child Wellbeing Assessment via Online Interactions with a Social Robots (2404.10593v2)

Published 16 Apr 2024 in cs.HC and cs.RO

Abstract: Socially Assistive Robots are studied in different Child-Robot Interaction settings. However, logistical constraints limit accessibility, particularly affecting timely support for mental wellbeing. In this work, we have investigated whether online interactions with a robot can be used for the assessment of mental wellbeing in children. The children (N=40, 20 girls and 20 boys; 8-13 years) interacted with the Nao robot (30-45 mins) over three sessions, at least a week apart. Audio-visual recordings were collected throughout the sessions that concluded with the children answering user perception questionnaires pertaining to their anxiety towards the robot, and the robot's abilities. We divided the participants into three wellbeing clusters (low, med and high tertiles) using their responses to the Short Moods and Feelings Questionnaire (SMFQ) and further analysed how their wellbeing and their perceptions of the robot changed over the wellbeing tertiles, across sessions and across participants' gender. Our primary findings suggest that (I) online mediated-interactions with robots can be effective in assessing children's mental wellbeing over time, and (II) children's overall perception of the robot either improved or remained consistent across time. Supplementary exploratory analyses have also revealed that gender affected the children's wellbeing assessments as well as their perceptions of the robot.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (99)
  1. F. Tanaka, K. Isshiki, F. Takahashi, M. Uekusa, R. Sei, and K. Hayashi, “Pepper learns together with children: Development of an educational application,” in 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), pp. 270–275, IEEE, 2015.
  2. A. Henschel, G. Laban, and E. S. Cross, “What makes a robot social? a review of social robots from science fiction to a home or hospital near you,” Current Robotics Reports, pp. 9–19, 2021.
  3. B. Scassellati, L. Boccanfuso, C.-M. Huang, M. Mademtzi, M. Qin, N. Salomons, P. Ventola, and F. Shic, “Improving social skills in children with asd using a long-term, in-home social robot,” Science Robotics, vol. 3, no. 21, p. eaat7544, 2018.
  4. N. I. Abbasi, M. Spitale, J. Anderson, T. Ford, P. B. Jones, and H. Gunes, “Can robots help in the evaluation of mental wellbeing in children? an empirical study,” in 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1459–1466, IEEE, 2022.
  5. G. Laban, V. Morrison, and E. Cross, “Social robots for health psychology: A new frontier for improving human health and well-being,” European Health Psychologist, vol. 23, pp. 1095–1102, 2 2024.
  6. J. M. Kory-Westlund and C. Breazeal, “A long-term study of young children’s rapport, social emulation, and language learning with a peer-like robot playmate in preschool,” Frontiers in Robotics and AI, vol. 6, p. 81, 2019.
  7. M. De Haas, P. Vogt, and E. Krahmer, “The effects of feedback on children’s engagement and learning outcomes in robot-assisted second language learning,” Frontiers in Robotics and AI, vol. 7, p. 101, 2020.
  8. B.-o. Thepthien, P. Busprachong, and N. Hongkeilert, “Self-disclosure among youth with problematic methamphetamine use who received treatment in public health centers of the bangkok metropolitan administration: A qualitative analysis,” Journal of Child & Adolescent Substance Abuse, vol. 28, no. 5, pp. 363–375, 2019.
  9. D. Yang, Z. Yao, J. Seering, and R. Kraut, “The channel matters: Self-disclosure, reciprocity and social support in online cancer support groups,” in Proceedings of the 2019 chi conference on human factors in computing systems, pp. 1–15, 2019.
  10. M. Punukollu and M. Marques, “Use of mobile apps and technologies in child and adolescent mental health: a systematic review,” BMJ Ment Health, vol. 22, no. 4, pp. 161–166, 2019.
  11. The Guilford Press, 2000.
  12. P. W. Corrigan, B. G. Druss, and D. A. Perlick, “The impact of mental illness stigma on seeking and participating in mental health care,” Psychological Science in the Public Interest, vol. 15, pp. 37–70, 9 2014.
  13. A. Chandra and C. S. Minkovitz, “Stigma starts early: Gender differences in teen willingness to use mental health services,” Journal of adolescent health, vol. 38, no. 6, pp. 754–e1, 2006.
  14. E. Gamborino, H.-P. Yueh, W. Lin, S.-L. Yeh, and L.-C. Fu, “Mood estimation as a social profile predictor in an autonomous, multi-session, emotional support robot for children,” in 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1–6, IEEE, 2019.
  15. G. Laban, A. Kappas, V. Morrison, and E. S. Cross, “Building long-term human–robot relationships: Examining disclosure, perception and well-being across time,” International Journal of Social Robotics 2023, pp. 1–27, 11 2023.
  16. S. Rossi, S. J. Santini, D. Di Genova, G. Maggi, A. Verrotti, G. Farello, R. Romualdi, A. Alisi, A. E. Tozzi, and C. Balsano, “Using the social robot nao for emotional support to children at a pediatric emergency department: Randomized clinical trial,” Journal of Medical Internet Research, vol. 24, no. 1, p. e29656, 2022.
  17. C. L. Bethel, Z. Henkel, K. Stives, D. C. May, D. K. Eakin, M. Pilkinton, A. Jones, and M. Stubbs-Richardson, “Using robots to interview children about bullying: Lessons learned from an exploratory study,” in 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 712–717, IEEE, 2016.
  18. R. Yamazaki, S. Nishio, Y. Nagata, Y. Satake, M. Suzuki, H. Kanemoto, M. Yamakawa, D. Figueroa, H. Ishiguro, and M. Ikeda, “Long-term effect of the absence of a companion robot on older adults: A preliminary pilot study,” Frontiers in Computer Science, vol. 5, p. 1129506, 2023.
  19. M. Sorter, L. J. Stark, T. Glauser, J. McClure, J. Pestian, K. Junger, and T. L. Cheng, “Addressing the pediatric mental health crisis: Moving from a reactive to a proactive system of care,” The Journal of Pediatrics, vol. 265, 2024.
  20. T. C. Campbell, A. Reupert, K. Sutton, S. Basu, G. Davidson, C. M. Middeldorp, M. Naughton, and D. Maybery, “Prevalence of mental illness among parents of children receiving treatment within child and adolescent mental health services (camhs): a scoping review,” European Child & Adolescent Psychiatry, vol. 30, pp. 997–1012, 2021.
  21. T. Ford, T. Vizard, K. Sadler, S. McManus, A. Goodman, S. Merad, M. Tejerina-Arreal, D. Collinson, and M. Collaboration, “Data resource profile: Mental health of children and young people (mhcyp) surveys,” International journal of epidemiology, vol. 49, no. 2, pp. 363–364g, 2020.
  22. K. Mansfield, C. Jindra, and M. Fazel, “The oxwell school survey 2020,” Report of Preliminary Findings, 2020.
  23. A.-M. Burn, T. J. Ford, J. Stochl, P. B. Jones, J. Perez, and J. K. Anderson, “Developing a web-based app to assess mental health difficulties in secondary school pupils: qualitative user-centered design study,” JMIR Formative Research, vol. 6, no. 1, p. e30565, 2022.
  24. R. Tourangeau, L. J. Rips, and K. Rasinski, “The psychology of survey response,” 2000.
  25. M. K. Nock and A. E. Kazdin, “Parent expectancies for child therapy: Assessment and relation to participation in treatment,” Journal of Child and Family Studies, vol. 10, pp. 155–180, 2001.
  26. D. Godoi, R. A. Romero, H. Azevedo, J. Ramos, G. Beraldo Filho, and M. A. T. Garcia, “Proteger: A social robotics system to support child psychological evaluation,” in 2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE), pp. 1–6, IEEE, 2020.
  27. G. Laban, A. Kappas, V. Morrison, and E. S. Cross, “Opening up to social robots: How emotions drive self-disclosure behavior,” pp. 1697–1704, IEEE, 8 2023.
  28. C. Di Dio, F. Manzi, G. Peretti, A. Cangelosi, P. L. Harris, D. Massaro, and A. Marchetti, “Shall i trust you? from child–robot interaction to trusting relationships,” Frontiers in psychology, vol. 11, p. 469, 2020.
  29. M. Fior, S. Nugent, T. N. Beran, A. Ramirez-Serrano, and R. Kuzyk, “Children’s relationships with robots: robot is child’s new friend,” 2010.
  30. T. Kanda, T. Hirano, D. Eaton, and H. Ishiguro, “Interactive robots as social partners and peer tutors for children: A field trial,” Human–Computer Interaction, vol. 19, no. 1-2, pp. 61–84, 2004.
  31. G. Laban, Z. Ben-Zion, and E. S. Cross, “Social robots for supporting post-traumatic stress disorder diagnosis and treatment,” Frontiers in Psychiatry, vol. 12, p. 2610, 2022.
  32. O. A. B. Henkemans, B. P. Bierman, J. Janssen, R. Looije, M. A. Neerincx, M. M. van Dooren, J. L. de Vries, G. J. van der Burg, and S. D. Huisman, “Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1,” International Journal of Human-Computer Studies, vol. 106, pp. 63–76, 2017.
  33. A. Meghdari, A. Shariati, M. Alemi, G. R. Vossoughi, A. Eydi, E. Ahmadi, B. Mozafari, A. Amoozandeh Nobaveh, and R. Tahami, “Arash: A social robot buddy to support children with cancer in a hospital environment,” Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, vol. 232, no. 6, pp. 605–618, 2018.
  34. C. V. Smedegaard, “Reframing the role of novelty within social hri: from noise to information,” in 2019 14th acm/ieee international conference on human-robot interaction (hri), pp. 411–420, IEEE, 2019.
  35. H. Kozima and C. Nakagawa, “Longitudinal child-robot interaction at preschool.,” in AAAI Spring Symposium: Multidisciplinary Collaboration for Socially Assistive Robotics, pp. 27–32, 2007.
  36. M. Abdelmohsen and Y. Arafa, “Virtual social robot enhances the social skills of children with hfa,” in Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings 13, pp. 497–508, Springer, 2021.
  37. J. K. Russell, E. Strodl, and D. Kavanagh, “Use of a social robot in the implementation of a narrative intervention for young people with cystic fibrosis: a feasibility study,” International Journal of Social Robotics, pp. 1–15, 2021.
  38. S. Serholt and W. Barendregt, “Robots tutoring children: Longitudinal evaluation of social engagement in child-robot interaction,” in Proceedings of the 9th nordic conference on human-computer interaction, pp. 1–10, 2016.
  39. T. Salter, K. Dautenhahn, and R. Bockhorst, “Robots moving out of the laboratory-detecting interaction levels and human contact in noisy school environments,” in RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication (IEEE Catalog No. 04TH8759), pp. 563–568, IEEE, 2004.
  40. E. J. Van Der Drift, R.-J. Beun, R. Looije, O. A. Blanson Henkemans, and M. A. Neerincx, “A remote social robot to motivate and support diabetic children in keeping a diary,” in Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, pp. 463–470, 2014.
  41. C. Lytridis, C. Bazinas, G. Sidiropoulos, G. A. Papakostas, V. G. Kaburlasos, V.-A. Nikopoulou, V. Holeva, and A. Evangeliou, “Distance special education delivery by social robots,” Electronics, vol. 9, no. 6, p. 1034, 2020.
  42. D. Pasupuleti, S. Sasidharan, R. Sharma, and G. Manikutty, “Exploring collaborative game play with robots to encourage good hand hygiene practises among children,” in 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 308–315, IEEE, 2022.
  43. N. Calvo-Barajas and G. Castellano, “Understanding children’s trust development through repeated interactions with a virtual social robot,” in 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1451–1458, IEEE, 2022.
  44. C. L. Gittens and D. Garnes, “Zenbo on zoom: Evaluating the human-robot interaction user experience in a video conferencing session,” in 2022 IEEE International Conference on Consumer Electronics (ICCE), pp. 1–6, IEEE, 2022.
  45. J. Kennedy, P. Baxter, and T. Belpaeme, “Comparing robot embodiments in a guided discovery learning interaction with children,” International Journal of Social Robotics, vol. 7, pp. 293–308, 2015.
  46. R. Pearson, “Masculinity and emotionality in education: critical reflections on discourses of boys’ behaviour and mental health,” Educational Review, vol. 75, no. 6, pp. 1101–1130, 2023.
  47. M. A. Lindsey, S. Joe, and V. Nebbitt, “Family matters: The role of mental health stigma and social support on depressive symptoms and subsequent help seeking among african american boys,” Journal of Black Psychology, vol. 36, no. 4, pp. 458–482, 2010.
  48. B. Mutlu, S. Osman, J. Forlizzi, J. Hodgins, and S. Kiesler, “Task structure and user attributes as elements of human-robot interaction design,” in ROMAN 2006-The 15th IEEE International Symposium on Robot and Human Interactive Communication, pp. 74–79, IEEE, 2006.
  49. M. Strait, P. Briggs, and M. Scheutz, “Gender, more so than age, modulates positive perceptions of language-based human-robot interactions,” in 4th international symposium on new frontiers in human robot interaction, pp. 21–22, 2015.
  50. M. Choi and H. Choung, “Mediated communication matters during the covid-19 pandemic: The use of interpersonal and masspersonal media and psychological well-being:,” Journal of Social and Personal Relationships, vol. 38, pp. 2397–2418, 7 2021.
  51. D. Feil-Seifer, K. S. Haring, S. Rossi, A. R. Wagner, and T. Williams, “Where to next? the impact of covid-19 on human-robot interaction research,” ACM Transactions on Human-Robot Interaction (THRI), vol. 10, 6 2020.
  52. G. Laban, V. Morrison, A. Kappas, and E. S. Cross, “Coping with emotional distress via self-disclosure to robots: Intervention with caregivers,” PsyArxiv, 2023.
  53. Palgrave Macmillan UK, 2016.
  54. G. Laban, J.-N. George, V. Morrison, and E. S. Cross, “Tell me more! assessing interactions with social robots from speech,” Paladyn, Journal of Behavioral Robotics, vol. 12, pp. 136–159, 2021.
  55. S. Honig and T. Oron-Gilad, “Comparing laboratory user studies and video-enhanced web surveys for eliciting user gestures in human-robot interactions,” pp. 248–250, Association for Computing Machinery, 3 2020.
  56. C. L. Gittens, “Remote hri: a methodology for maintaining covid-19 physical distancing and human interaction requirements in hri studies,” Information Systems Frontiers, vol. 26, pp. 91–106, 2 2021.
  57. C. L. Gittens and D. Garnes, “Zenbo on zoom: Evaluating the human-robot interaction user experience in a video conferencing session,” Digest of Technical Papers - IEEE International Conference on Consumer Electronics, vol. 2022-January, 2022.
  58. J. Huberty, J. Green, M. Puzia, and C. Stecher, “Evaluation of mood check-in feature for participation in meditation mobile app users: retrospective longitudinal analysis,” JMIR mHealth and uHealth, vol. 9, no. 4, p. e27106, 2021.
  59. J. Li, “The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresent robots and virtual agents,” International Journal of Human-Computer Studies, vol. 77, pp. 23–37, 2015.
  60. G. Laban, V. Morrison, A. Kappas, and E. S. Cross, “Informal caregivers disclose increasingly more to a social robot over time,” pp. 1–7, Association for Computing Machinery, 2022.
  61. N. Abbasi, M. Spitale, J. Anderson, T. Ford, P. Jones, and H. Gunes, “Humanoid robots for wellbeing assessment in children: How does anxiety towards the robot affect perceptions of robot role, behaviour and capabilities?,” 2023.
  62. M. Spitale, M. Axelsson, and H. Gunes, “Robotic mental well-being coaches for the workplace: An in-the-wild study on form,” in Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, pp. 301–310, 2023.
  63. L. A. Jackson, Y. Zhao, W. Qiu, A. Kolenic III, H. E. Fitzgerald, R. Harold, and A. von Eye, “Culture, gender and information technology use: A comparison of chinese and us children,” Computers in human behavior, vol. 24, no. 6, pp. 2817–2829, 2008.
  64. United Nations Children’s Fund, 2020.
  65. A. Angold, E. J. Costello, S. C. Messer, and A. Pickles, “Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents.,” International journal of methods in psychiatric research, 1995.
  66. L. Bellak and S. S. Bellak, “Children’s apperception test.,” 1949.
  67. B. F. Chorpita, C. Ebesutani, and S. Spence, “Revised children’s anxiety and depression scale,” Hämtad från, 2015.
  68. F. Faul, E. Erdfelder, A. Buchner, and A.-G. Lang, “Statistical power analyses using g*power 3.1: Tests for correlation and regression analyses,” Behavior Research Methods, vol. 41, pp. 1149–1160, 2009. ID: Faul2009.
  69. J. P. Simmons, L. D. Nelson, and U. Simonsohn, “False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant,” Psychological Science, vol. 22, pp. 1359–1366, 10 2011.
  70. M. I. Ahmad, O. Mubin, and J. Orlando, “Adaptive social robot for sustaining social engagement during long-term children–robot interaction,” International Journal of Human–Computer Interaction, vol. 33, pp. 943–962, 12 2017.
  71. J. de Greeff, O. Blanson Henkemans, A. Fraaije, L. Solms, N. Wigdor, B. Bierman, J. B. Janssen, R. Looije, P. Baxter, M. A. Neerincx, et al., “Child-robot interaction in the wild: Field testing activities of the aliz-e project,” in Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, pp. 148–149, 2014.
  72. B. Arsić, A. Gajić, S. Vidojković, D. Maćešić-Petrović, A. Bašić, and R. Z. Parezanović, “The use of nao robots in teaching children with autism,” European Journal of Alternative Education Studies, vol. 7, no. 1, 2022.
  73. M. Cervin, A. Veas, J. A. Piqueras, and A. E. Martínez-González, “A multi-group confirmatory factor analysis of the revised children’s anxiety and depression scale (rcads) in spain, chile and sweden,” Journal of Affective Disorders, vol. 310, pp. 228–234, 2022.
  74. P. Bremner, O. Celiktutan, and H. Gunes, “Personality perception of robot avatar tele-operators,” in 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 141–148, IEEE, 2016.
  75. A. Di Nuovo, S. Varrasi, A. Lucas, D. Conti, J. McNamara, and A. Soranzo, “Assessment of cognitive skills via human-robot interaction and cloud computing,” Journal of bionic engineering, vol. 16, pp. 526–539, 2019.
  76. C. Sharp, I. M. Goodyer, and T. J. Croudace, “The short mood and feelings questionnaire (smfq): a unidimensional item response theory and categorical data factor analysis of self-report ratings from a community sample of 7-through 11-year-old children,” Journal of abnormal child psychology, vol. 34, pp. 365–377, 2006.
  77. M. Murray, N. Walker, A. Nanavati, P. Alves-Oliveira, N. Filippov, A. Sauppe, B. Mutlu, and M. Cakmak, “Learning backchanneling behaviors for a social robot via data augmentation from human-human conversations,” in Conference on robot learning, pp. 513–525, PMLR, 2022.
  78. T. Nomura, T. Suzuki, T. Kanda, and K. Kato, “Measurement of anxiety toward robots,” in ROMAN 2006-The 15th IEEE International Symposium on Robot and Human Interactive Communication, pp. 372–377, IEEE, 2006.
  79. C. Bartneck, D. Kulić, E. Croft, and S. Zoghbi, “Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots,” International journal of social robotics, vol. 1, pp. 71–81, 2009.
  80. N. I. Abbasi, G. Laban, T. Ford, P. B. Jones, and H. Gunes, “Robotising psychometrics: Validating wellbeing assessment tools in child-robot interactions,” 2 2024.
  81. L. Jachens and J. Houdmont, “Effort-reward imbalance and job strain: a composite indicator approach,” International journal of environmental research and public health, vol. 16, no. 21, p. 4169, 2019.
  82. F. Munir, J. Houdmont, S. Clemes, K. Wilson, R. Kerr, and K. Addley, “Occupational sitting time and its association with work engagement and job demand-control,” in European Academy of Occupational Health Psychology Conference, European Academy of Occupational Health Psychology, 2014.
  83. A. P. Villatoro, M. J. DuPont-Reyes, J. C. Phelan, K. Painter, and B. G. Link, “Parental recognition of preadolescent mental health problems: Does stigma matter?,” Social Science & Medicine, vol. 216, pp. 88–96, 11 2018.
  84. H. W. Marsh and K.-T. Hau, “Multilevel modeling of longitudinal growth and change: Substantive effects or regression toward the mean artifacts?,” Multivariate Behavioral Research, vol. 37, no. 2, pp. 245–282, 2002.
  85. A. G. Barnett, J. C. Van Der Pols, and A. J. Dobson, “Regression to the mean: what it is and how to deal with it,” International journal of epidemiology, vol. 34, no. 1, pp. 215–220, 2005.
  86. M. K. Crossman, A. E. Kazdin, and E. R. Kitt, “The influence of a socially assistive robot on mood, anxiety, and arousal in children.,” Professional Psychology: Research and Practice, vol. 49, no. 1, p. 48, 2018.
  87. D. Kumar Singh, S. Sharma, J. Shukla, and G. Eden, “Toy, tutor, peer, or pet? preliminary findings from child-robot interactions in a community school,” in Companion of the 2020 ACM/IEEE international conference on human-robot interaction, pp. 325–327, 2020.
  88. M. Nalin, I. Baroni, A. Sanna, and C. Pozzi, “Robotic companion for diabetic children: emotional and educational support to diabetic children, through an interactive robot,” in Proceedings of the 11th international conference on interaction design and children, pp. 260–263, 2012.
  89. P. Robinette, A. R. Wagner, and A. M. Howard, “Assessment of robot to human instruction conveyance modalities across virtual, remote and physical robot presence,” in 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 1044–1050, IEEE, 2016.
  90. D. Conti, S. Di Nuovo, and A. Di Nuovo, “Kindergarten children attitude towards humanoid robots: What is the effect of the first experience?,” in 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 630–631, IEEE, 2019.
  91. E. B. Sandoval, O. Mubin, and M. Obaid, “Human robot interaction and fiction: A contradiction,” in Social Robotics: 6th International Conference, ICSR 2014, Sydney, NSW, Australia, October 27-29, 2014. Proceedings 6, pp. 54–63, Springer, 2014.
  92. A. C. Horstmann and N. C. Krämer, “Great expectations? relation of previous experiences with social robots in real life or in the media and expectancies based on qualitative and quantitative assessment,” Frontiers in psychology, vol. 10, p. 939, 2019.
  93. W. Rikkers, D. Lawrence, J. Hafekost, and S. R. Zubrick, “Internet use and electronic gaming by children and adolescents with emotional and behavioural problems in australia–results from the second child and adolescent survey of mental health and wellbeing,” BMC public health, vol. 16, pp. 1–16, 2016.
  94. K. K. Rapinda, T. Kempe, R. S. Kruk, J. D. Edgerton, H. R. Wallbridge, and M. T. Keough, “Examining the temporal associations between depression and pathological gaming.,” Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, vol. 53, no. 3, p. 274, 2021.
  95. F. Stenseng, B. W. Hygen, and L. Wichstrøm, “Time spent gaming and psychiatric symptoms in childhood: cross-sectional associations and longitudinal effects,” European child & adolescent psychiatry, vol. 29, no. 6, pp. 839–847, 2020.
  96. I. Leite, G. Castellano, A. Pereira, C. Martinho, and A. Paiva, “Long-term interactions with empathic robots: Evaluating perceived support in children,” in Social Robotics: 4th International Conference, ICSR 2012, Chengdu, China, October 29-31, 2012. Proceedings 4, pp. 298–307, Springer, 2012.
  97. I. P. Bodala, N. Churamani, and H. Gunes, “Teleoperated robot coaching for mindfulness training: A longitudinal study,” in 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), pp. 939–944, IEEE, 2021.
  98. I. Leite, C. Martinho, and A. Paiva, “Social robots for long-term interaction: a survey,” International Journal of Social Robotics, vol. 5, pp. 291–308, 2013.
  99. A. Coninx, P. Baxter, E. Oleari, S. Bellini, B. Bierman, O. Henkemans, L. Cañamero, P. Cosi, V. Enescu, R. Espinoza, et al., “Towards long-term social child-robot interaction: using multi-activity switching to engage young users,” Journal of Human-Robot Interaction, 2016.
Citations (1)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets