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Article

An Overview of the Use of Chatbots in Medical and Healthcare Education

Authors:

Fotos Frangoudes,

Marios Hadjiaros,

Eirini C. Schiza,

Maria Matsangidou,

Olia Tsivitanidou,

Kleanthis NeokleousAuthors Info & Claims

Learning and Collaboration Technologies: Games and Virtual Environments for Learning: 8th International Conference, LCT 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part II

Pages 170 - 184

https://doi.org/10.1007/978-3-030-77943-6_11

Published: 24 July 2021 Publication History

Abstract

Chatbots are becoming a trend in many fields such as medical, service industry and more recently in education. Especially in healthcare education, there is a growing interest in integrating chatbots in the learning and teaching processes mostly because of their portability and affordance. In this paper, we seek to explore the primary uses of chatbots in medical education, as well as how they are developed. We elaborate on current chatbot applications and research enacted in the domains of medical and healthcare education, We focus in the areas of virtual patients in medical education, patients’ education related to healthcare matters but also chatbots as course assistance in for enhancing healthcare professionals’ curricula. Additionally, we examine the metrics that have been used to evaluate these chatbots, which include subjective ones like the usability and acceptability by the users, and objectives ones, like their accuracy and users’ skills evaluation. Overall, even though chatbots offer a flexible solution and a vast possibility to improve healthcare education, our literature review suggests that their efficacy has not been thoroughly tested. Also, limited examples of chatbots in European Healthcare curricula have been found. These call of the need for further research towards this direction.

References

[1]

Serban, I.V., et al.: A deep reinforcement learning chatbot. arXiv:1709.02349 [cs, stat] (2017)

[2]

Smutny P and Schreiberova P Chatbots for learning: a review of educational chatbots for the Facebook Messenger Comput. Educ. 2020 151 103862

[3]

Fryer L and Carpenter R Bots as language learning tools Lang. Learn. Technol. 2006 10 8-14

[4]

Rosruen, N., Samanchuen, T.: Chatbot utilization for medical consultant system. In: 2018 3rd Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), pp. 1–5 (2018)

[5]

European Commission: Communication from the commission to the European parliament, the 13 council, the European economic and social committee and the committee of the regions eHealth Action Plan 2012-2020: Innovative healthcare for the 21st century (2012). https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX%3A52012DC0736

[6]

Winkler, R., Söllner, M.: Unleashing the potential of chatbots in education: a state-of-the-art analysis. Presented at the Academy of Management Annual Meeting (AOM), Chicago, USA (2018)

[7]

Moher D, Liberati A, Tetzlaff J, Altman D.G, and PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement PLoS Med. 2009 6 e1000097

[8]

Amith M et al. Early usability assessment of a conversational agent for HPV vaccination Stud. Health Technol. Inform. 2019 257 17-23

[9]

Beaudry J, Consigli A, Clark C, and Robinson KJ Getting ready for adult healthcare: designing a chatbot to coach adolescents with special health needs through the transitions of care J. Pediatric Nurs. Nurs. Care Children Families 2019 49 85-91

[10]

Campillos-Llanos L, Thomas C, Bilinski É, Zweigenbaum P, and Rosset S Designing a virtual patient dialogue system based on terminology-rich resources: challenges and evaluation Nat. Lang. Eng. 2020 26 183-220

[11]

Carnell S, Halan S, Crary M, Madhavan A, and Lok B Brinkman W-P, Broekens J, and Heylen D Adapting virtual patient interviews for interviewing skills training of novice healthcare students Intelligent Virtual Agents 2015 Cham Springer 50-59

[12]

Chetlen A, Artrip R, Drury B, Arbaiza A, and Moore M Novel use of chatbot technology to educate patients before breast biopsy J. Am. Coll. Radiol. 2019 16 1305-1308

[13]

Datta D, Brashers V, Owen J, White C, and Barnes LE Traum D, Swartout W, Khooshabeh P, Kopp S, Scherer S, and Leuski A A deep learning methodology for semantic utterance classification in virtual human dialogue systems Intelligent Virtual Agents 2016 Cham Springer 451-455

[14]

El Zini, J., Rizk, Y., Awad, M., Antoun, J.: Towards a deep learning question-answering specialized chatbot for objective structured clinical examinations. In: 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, pp. 1–9. IEEE (2019)

[15]

Foster A et al. Using virtual patients to teach empathy: a randomized controlled study to enhance medical students’ empathic communication Simul. Healthc. 2016 11 181-189

[16]

Isaza-Restrepo A, Gómez MT, Cifuentes G, and Argüello A The virtual patient as a learning tool: a mixed quantitative qualitative study BMC Med. Educ. 2018 18 297

[17]

Jin, L., White, M., Jaffe, E., Zimmerman, L., Danforth, D.: Combining CNNs and pattern matching for question interpretation in a virtual patient dialogue system. In: Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, Copenhagen, Denmark, pp. 11–21. Association for Computational Linguistics (2017)

[18]

Laleye, F.A.A., Blanié, A., Brouquet, A., Behnamou, D., de Chalendar, G.: Semantic similarity to improve question understanding in a virtual patient. In: Proceedings of the 35th Annual ACM Symposium on Applied Computing, pp. 859–866. Association for Computing Machinery, New York (2020)

[19]

May R and Denecke K Alario-Hoyos C, Rodríguez-Triana MJ, Scheffel M, Arnedillo-Sánchez I, and Dennerlein SM Extending patient education with CLAIRE: an interactive virtual reality and voice user interface application Addressing Global Challenges and Quality Education 2020 Cham Springer 482-486

[20]

Pereira, J.: Leveraging chatbots to improve self-guided learning through conversational quizzes. In: Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality, pp. 911–918. Association for Computing Machinery, New York (2016)

[21]

Rose-Davis B, Van Woensel W, Stringer E, Abidi S, and Abidi SSR Using an artificial intelligence-based argument theory to generate automated patient education dialogues for families of children with juvenile idiopathic arthritis Stud. Health Technol. Inform. 2019 264 1337-1341

[22]

Tanana MJ, Soma CS, Srikumar V, Atkins DC, and Imel ZE Development and evaluation of ClientBot: patient-like conversational agent to train basic counseling skills J. Med. Internet Res. 2019 21 e12529

[23]

Wang C et al. Acceptability and feasibility of a virtual counselor (VICKY) to collect family health histories Genet. Med. 2015 17 822-830

[24]

Yadav, D., Malik, P., Dabas, K., Singh, P.: Feedpal: understanding opportunities for chatbots in breastfeeding education of women in India. Proc. ACM Hum.-Comput. Interact. 3, 170:1–170:30 (2019).

[25]

Yang W, Hebert D, Kim S, and Kang B MCRDR knowledge-based 3D dialogue simulation in clinical training and assessment J. Med. Syst. 2019 43 7 1-21

[26]

Cleland JA, Abe K, and Rethans J-J The use of simulated patients in medical education: AMEE guide no 42 Med. Teach. 2009 31 477-486

[27]

Bosse HM, Nickel M, Huwendiek S, Schultz JH, and Nikendei C Cost-effectiveness of peer role play and standardized patients in undergraduate communication training BMC Med. Educ. 2015 15 183

[28]

Kononowicz AA, Zary N, Edelbring S, Corral J, and Hege I Virtual patients - what are we talking about? A framework to classify the meanings of the term in healthcare education BMC Med. Educ. 2015 15 11

[29]

Agarwal R and Wadhwa M Review of state-of-the-art design techniques for chatbots SN Comput. Sci. 2020 1 5 1-12

[30]

Mehta N, Geissel K, Rhodes E, and Salinas G Comparative effectiveness in CME: evaluation of personalized and self-directed learning models J. Continuing Educ. Health Prof. 2015 35 S24

[31]

Haiech J and Kilhoffer M-C Personalized medicine and education: the challenge Croat. Med. J. 2012 53 298-300

[32]

Reiswich A and Haag M Evaluation of chatbot prototypes for taking the virtual patient’s history Stud. Health Technol. Inform. 2019 260 73-80

[33]

Stathakarou N et al. Students’ perceptions on chatbots’ potential and design characteristics in healthcare education Stud. Health Technol. Inform. 2020 272 209-212

[34]

Cunningham-Nelson, S., Boles, W., Trouton, L., Margerison, E.: A review of chatbots in education: practical steps forward. In: Proceedings of the AAEE2019 Conference, Brisbane, Australia, p. 9 (2019)

[35]

Zumstein D and Hundertmark S Chatbots - an interactive technology for personalized communication and transaction IADIS Int. J. WWW/Internet 2018 15 96-109

[36]

Bernardini, A.A., Sônego, A.A., Pozzebon, E.: Chatbots: an analysis of the state of art of literature. In: Workshop on Advanced Virtual Environments and Education, vol. 1, pp. 1–6 (2018).

[37]

Hobert, S., von Wolff, R.M.: Say hello to your new automated tutor – a structured literature review on pedagogical conversational agents. In: Wirtschaftsinformatik 2019 Proceedings (2019)

Cited By

Barbara Onyekwelu IShrestha REika Sandnes F(2024)“Not quite there yet”: On Users Perception of Popular Healthcare Chatbot Apps for Personal Health ManagementProceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/3652037.3652042(191-197)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1145/3652037.3652042
He LBraggaar ABasar EKrahmer EAntheunis MWiers R(2024)Exploring User Engagement Through an Interaction Lens: What Textual Cues Can Tell Us about Human-Chatbot InteractionsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665536(1-14)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3640794.3665536

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An Overview of the Use of Chatbots in Medical and Healthcare Education

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Information & Contributors

Information

Published In

cover image Guide Proceedings

Learning and Collaboration Technologies: Games and Virtual Environments for Learning: 8th International Conference, LCT 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part II

Jul 2021

359 pages

ISBN:978-3-030-77942-9

DOI:10.1007/978-3-030-77943-6

Editors:
Panayiotis Zaphiris
Department of Multimedia and Graphic Arts, Cyprus University of Technology, Lemesos, Cyprus
,
Andri Ioannou
Research Center on Interactive Media, Smart Systems and Emerging Technologies (CYENS), Cyprus University of Technology, Limassol, Cyprus

© Springer Nature Switzerland AG 2021.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 24 July 2021

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Cited By

Barbara Onyekwelu IShrestha REika Sandnes F(2024)“Not quite there yet”: On Users Perception of Popular Healthcare Chatbot Apps for Personal Health ManagementProceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/3652037.3652042(191-197)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1145/3652037.3652042
He LBraggaar ABasar EKrahmer EAntheunis MWiers R(2024)Exploring User Engagement Through an Interaction Lens: What Textual Cues Can Tell Us about Human-Chatbot InteractionsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665536(1-14)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3640794.3665536

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