research-article

Huggable: The Impact of Embodiment on Promoting Socio-emotional Interactions for Young Pediatric Inpatients

Authors:

Cynthia Breazeal,

Peter WeinstockAuthors Info & Claims

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Paper No.: 495, Pages 1 - 13

https://doi.org/10.1145/3173574.3174069

Published: 21 April 2018 Publication History

Abstract

Most hospitals make efforts to provide socio-emotional support for patients and their families during care. In order to expand the service provided by certified child life specialists, we created a social robot and a virtual avatar that augment part of the care CCLS offers to patients by engaging pediatric patients in playful interactions and promoting their socio-emotional wellbeing. We ran a randomized controlled trial in a form of a Wizard-of-Oz study at a local pediatric hospital to study how three different interactive media (a plush teddy bear, a virtual agent on a screen, and a social robot) influence the pediatric patient's affect, joyful play, and social interactions with others. Behavioral analyses of verbal utterance transcriptions and children's physical behavior revealed that the social robot is most effective in producing socially energetic conversations as well as increasing positivity and promoting multi-party interactions. The virtual avatar was socially engaging but children tended to attend more exclusively to a virtual avatar and were less responsive to others. The plush toy was least engaging of the three interventions, but children touched it the most. Based on these findings, we recommend use cases for each agent appropriate for individual pediatric patients' health conditions and needs. These analyses of behavioral data suggest the benefit of deploying a physically embodied social robot in pediatric inpatient-care contexts on young patients'; social and emotional wellbeing.

References

[1]

Aoalgeirsson, S.O. 2008. MeBot: The design of a portable mobile robotic platform for robot-mediated interaction at a distance. Massachusetts Institute of Technology.

[2]

von Baeyer, C.L. 2009. Numerical rating scale for self-report of pain intensity in children and adolescents: recent progress and further questions. European journal of pain (London, England). 13, 10 (Nov. 2009), 1005--7.

[3]

Bakx, I. et al. 2003. Facial orientation during multi-party interaction with information kiosks. Proceedings of INTERACT (2003), 701--704.

[4]

Beran, T.N. et al. 2013. Reducing children's pain and distress towards flu vaccinations: A novel and effective application of humanoid robotics. Vaccine. 31, 25 (2013), 2772--2777.

[5]

Bers, M.U. et al. 1998. Interactive Storytelling Environments: Coping with Cardiac Illness at Boston's Children's Hospital. the SIGCHI conference on Human factors in computing systems (1998), 603--610.

Digital Library

[6]

Bickmore, T.W. et al. 2009. Taking the time to care: empowering low health literacy hospital patients with virtual nurse agents. Proceedings of the 27th international conference on Human factors in computing systems (2009), 1265--1274.

Digital Library

[7]

Braun, C. et al. 2009. Animal-assisted therapy as a pain relief intervention for children. Complementary therapies in clinical practice. 15, 2 (May 2009), 105--9. http://doi.acm.org/10.1145/503376.503378

[8]

Chambers, C.T. et al. 2002. The impact of maternal behavior on children's pain experiences: An experimental analysis. Journal of Pediatric Psychology. 27, 3 (2002), 293--301.

[9]

Cohen, S. and Wills, T.A. 1985. Stress, Social Support, and the Buffering Hypothesis. Psychological Bulletin. 98, 2 (1985), 310--357.

[10]

Davis, M.J. 2010. Contrast coding in multiple regression analysis: Strengths, weaknesses, and utility of popular coding structures. Journal of Data Science. 8, (2010), 61--73.

[11]

DiMatteo, M. 2004. Social support and patient adherence to medical treatment: a meta-analysis. Health psychology. 23, 2 (2004), 207--18.

[12]

van der Drift, E. et al. 2014. A remote social robot to motivate and support diabetic children in keeping a diary. Proceedings of Human-Robot Interaction 2014. (2014).

Digital Library

[13]

Fasola, J. and Mataric, M. 2011. Comparing physical and virtual embodiment in a socially assistive robot exercise coach for the elderly.

[14]

Feil-Seifer, D. and Mataric, M. 2005. Defining socially assistive robotics. Proceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics (2005), 465--468.

[15]

Greeff, J. De and Henkemans, O.B. 2014. Child-robot interaction in the wild: field testing activities of the ALIZ-E project. Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction (2014), 148--149.

Digital Library

[16]

Han, S. et al. 2005. Distinct neural substrates for the perception of real and virtual visual worlds. NeuroImage. 24, 3 (2005), 928--935.

[17]

Harlow, H.F. 1959. The Nature of Love. American psychologist. 13, 12 (1959), 673--685.

[18]

Hicks, C.L. et al. 2001. The Faces Pain Scale-Revised: toward a common metric in pediatric pain measurement. Pain. 93, 2 (2001), 173--183.

[19]

Jeong, S. et al. 2015. A Social Robot to Mitigate Stress, Anxiety, and Pain in Hospital Pediatric Care. Proceedings of the 2015 ACM/IEEE international conference on Human-Robot Interaction (2015), 103--104.

Digital Library

[20]

Jeong, S. et al. 2015. Designing a Socially Assistive Robot for Pediatric Care. Proceedings of the 14th international conference on Interaction Design and Children, 387--390.

Digital Library

[21]

Jeong, S. et al. 2017. Huggable: Impact of Embodiment on Promoting Verbal and Physical Engagement for Young Pediatric Inpatients. 26th iEEE Interantional Symposium on Robot and Human Interactive Communication (RO-MAN) (2017).

[22]

Shibata, T., et al. 2008. Robot therapy at elder care institutions: Effects of long-term interaction with seal robots. The engineering handbook of smart technology for aging, disability, and independence, 405--418.

[23]

Kaminski, M. et al. 2002. Play and Pets: The Physical and Emotional Impact of Child-Life and Pet Therapy on Hospitalized Children. Children's Health Care. 31, 4 (Dec. 2002), 321--335.

[24]

Li, J. 2015. 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. 77, (2015), 23--27.

Digital Library

[25]

Li, J. 2013. The Nature of the Bots: How People Respond to Robots, Virtual Agents and Humans as Multimodal Stimuli. Proceeding ICMI '13 Proceedings of the 15th ACM on International conference on multimodal interaction (2013), 337--340.

Digital Library

[26]

McCullagh, P. and Nelder, J.A. 1989. Generalized Linear Models, Second Edition.

[27]

Mostafa, M. et al. 2016. Incorporating Emotion and Personality-Based Analysis in User-Centered Modelling. Research and Development in Intelligent Systems XXXIII: Incorporating Applications and Innovations in Intelligent Systems XXIV (2016), 383--389.

[28]

Nilsson, S. et al. 2014. The Facial Affective Scale as a Predictor for Pain Unpleasantness When Children Undergo Immunizations. Nursing Research and Practice. 2014, (2014), 1--7.

[29]

Ringoot, A.P. et al. 2013. Young Children's Self-reported Emotional, Behavioral, and Peer Problems: The Berkeley Puppet Interview. Psychological Assessment. 25, 4 (2013), 1273--1285.

[30]

Sobo, E.J. et al. 2006. Canine visitation (pet) therapy: pilot data on decreases in child pain perception. Journal of holistic nursing: official journal of the American Holistic Nurses' Association. 24, 1 (2006), 51--7.

[31]

Spielberger, C. and Edwards, C. 1973. State-trait Anxiety Inventory for Children: STAIC: How I Feel Questionnaire: Professional Manual. Mind Garden. (1973), 2014.

[32]

Uchino, B.N. et al. 1996. The Relationship Between Social Support and Physiological Processes: A Review With Emphasis on Underlying Mechanisms and Implications for Health. Psychological Bulletin. 119, 3 (1996), 488--531.

[33]

Vandewater, E.A. 2006. Time Well Spent? Relating Television Use to Children's Free-Time Activities. Pediatrics. 117, 2 (2006), 181--191.

[34]

Wainer, J. et al. 2006. The role of physical embodiment in human-robot interaction. Proceedings - IEEE International Workshop on Robot and Human Interactive Communication. (2006), 117--122.

[35]

Watson, D. et al. 1988. Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales. Journal of Personality and Social Psychology. 54, 6 (1988), 1063--1070.

[36]

What is a Child Life Specialist? .

[37]

Wilson, J.M. 2006. Child life services. Pediatrics. 118, 4 (Oct. 2006), 1757--63.

[38]

Robins, B., et al. 2005. Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills?. Universal Access in the Information Society, 4(2), 105--120.

Digital Library

[39]

Mazzei, D., et al. 2011. Development and evaluation of a social robot platform for therapy in autism. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, 4515--4518.

[40]

Jeong, S., 2017. The Impact of Social Robots on Young Patients' Socio-emotional Well-being in a Pediatric Inpatient Care Context. MS Thesis. Media Arts and Sciences, MIT.

[41]

Peterson, A. M., et al. 2007. Parents' interpersonal distance and touch behavior and child pain and distress during painful pediatric oncology procedures. Journal of Nonverbal Behavior 31, 2 (2007), 79--97.

[42]

Wilson, J. M., Goldberger, J. 1996. Children in the process of becoming. Arch Pediatr Adolesc Med. 150 (1996), 1234--1235.

[43]

Thompson, R. H. 1995. Documenting the value of play for hospitalized children: the challenge of playing the game. ACCH Advocate. 2 (1995), 11--19.

[44]

Solnit, A. 1984. Preparing. Psychoanal Study Child. 7 (1984), 613--632

[45]

Southall, D. P., Burr, S., Smith, R. D., et al. 2000. The child-friendly healthcare initiative (CFHI): healthcare provision in accordance with the UN convention on the rights of the child. Pediatrics. 106 (2000), 1054--1064

[46]

Rollins, J. A., Bolig, R., Mahan, C. 2005. Meeting Children's Psychosocial Needs: Across the Health-Care Continuum. Austin, TX: Pro-Ed.

Cited By

McLaren DGao JYin XReis Guerra RVyas PMorton CCang XChen YSun YLi YMadden JMacLean K(2024)What is Affective Touch Made Of? A Soft Capacitive Sensor Array Reveals the Interplay between Shear, Normal Stress and IndividualityProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676346(1-31)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676346
MacDonald SFreeman EPollick FBrewster S(2024)Prototyping and Evaluation of Emotionally Resonant Vibrotactile Comfort Objects as a Calming Social Anxiety InterventionACM Transactions on Computer-Human Interaction10.1145/364861531:4(1-48)Online publication date: 19-Sep-2024
https://dl.acm.org/doi/10.1145/3648615
Macdonald SBretin RElSayed S(2024)Evaluating Transferable Emotion Expressions for Zoomorphic Social Robots using VR Prototyping2024 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR62088.2024.00125(1087-1096)Online publication date: 21-Oct-2024
https://doi.org/10.1109/ISMAR62088.2024.00125
Show More Cited By

Index Terms

Huggable: The Impact of Embodiment on Promoting Socio-emotional Interactions for Young Pediatric Inpatients
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Designing a socially assistive robot for pediatric care
IDC '15: Proceedings of the 14th International Conference on Interaction Design and Children

We present the design of the Huggable robot that can playfully interact with children and provide socio-emotional support for them in pediatric care context. Our design takes into consideration that many young patients are nervous, intimidated, and are ...
Measuring young children's long-term relationships with social robots
IDC '18: Proceedings of the 17th ACM Conference on Interaction Design and Children

Social robots are increasingly being developed for long-term interactions with children in domains such as healthcare, education, therapy, and entertainment. As such, we need to deeply understand how children's relationships with robots develop through ...
Assessing Children's Perceptions and Acceptance of a Social Robot
IDC '19: Proceedings of the 18th ACM International Conference on Interaction Design and Children

Children's interactions with social robots and other technologies are increasingly longitudinal, especially in areas such as healthcare, therapy, and education. As such, we need to understand how children perceive social robots over time and the kinds ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

April 2018

8489 pages

ISBN:9781450356206

DOI:10.1145/3173574

General Chairs:
Regan Mandryk
University of Saskatchewan, Canada
,
Mark Hancock
University of Waterloo, Canada
,
Program Chairs:
Mark Perry
Brunel University London, UK
,
Anna Cox
University College London, UK

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Boston Children's Hospital

Conference

CHI '18

Sponsor:

SIGCHI

CHI '18: CHI Conference on Human Factors in Computing Systems

April 21 - 26, 2018

Montreal QC, Canada

Acceptance Rates

CHI '18 Paper Acceptance Rate 666 of 2,590 submissions, 26%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

40
Total Citations
View Citations
1,166
Total Downloads

Downloads (Last 12 months)170
Downloads (Last 6 weeks)18

Reflects downloads up to 01 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

McLaren DGao JYin XReis Guerra RVyas PMorton CCang XChen YSun YLi YMadden JMacLean K(2024)What is Affective Touch Made Of? A Soft Capacitive Sensor Array Reveals the Interplay between Shear, Normal Stress and IndividualityProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676346(1-31)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676346
MacDonald SFreeman EPollick FBrewster S(2024)Prototyping and Evaluation of Emotionally Resonant Vibrotactile Comfort Objects as a Calming Social Anxiety InterventionACM Transactions on Computer-Human Interaction10.1145/364861531:4(1-48)Online publication date: 19-Sep-2024
https://dl.acm.org/doi/10.1145/3648615
Macdonald SBretin RElSayed S(2024)Evaluating Transferable Emotion Expressions for Zoomorphic Social Robots using VR Prototyping2024 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR62088.2024.00125(1087-1096)Online publication date: 21-Oct-2024
https://doi.org/10.1109/ISMAR62088.2024.00125
Yi EPark D(2024)Potential User Segmentation Based on Expectations of Social Robots Using Q-MethodologyIEEE Access10.1109/ACCESS.2024.343086412(100295-100315)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3430864
Solórzano Alcívar NPaillacho Chiluiza DArce Sierra MPincay Lino AEras Zamora E(2024)Facial expression analysis in children with autism spectrum disorder using a refined Human-Robot-Game platform for active learningBehaviour & Information Technology10.1080/0144929X.2024.2434896(1-13)Online publication date: 6-Dec-2024
https://doi.org/10.1080/0144929X.2024.2434896
Neerinex ABrito JCouto MCampos Jde Graaf MMasthoff JPaiva A(2024)Social Robotics in Psychological Interventions for ChildrenDigital Technologies for Learning and Psychological Interventions10.1007/978-3-031-76414-1_6(123-147)Online publication date: 20-Dec-2024
https://doi.org/10.1007/978-3-031-76414-1_6
Purps CHettmann WZylowski TSautchuk-Patrício NHepperle DWölfel M(2024)Exploring Perception and Preference in Public Human-Agent Interaction: Virtual Human Vs. Social RobotArtsIT, Interactivity and Game Creation10.1007/978-3-031-55312-7_25(342-358)Online publication date: 21-Mar-2024
https://doi.org/10.1007/978-3-031-55312-7_25
Alabduljabbar RAlsakran R(2023)Leveraging IoT to Address Separation Anxiety in Preschoolers: A Techno-Psychological ApproachElectronics10.3390/electronics1216347912:16(3479)Online publication date: 17-Aug-2023
https://doi.org/10.3390/electronics12163479
Monzen MMochizuki SOhshima T(2023)Augmentation of Medical Preparation for Children by Using Projective and Tangible InterfaceSIGGRAPH Asia 2023 Posters10.1145/3610542.3626128(1-2)Online publication date: 12-Dec-2023
https://dl.acm.org/doi/10.1145/3610542.3626128
Reynolds-Cuéllar PSalazar-Gómez ACastellano GRiek LCakmak MLeite I(2023)Nature-Robot InteractionCompanion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568294.3580034(30-39)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3568294.3580034
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten