Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review
BackgroundCommunication is a crucial element of every health care profession, rendering communication skills training in all health care professions as being of great importance. Technological advances such as artificial intelligence (AI) and particularly machine learning (ML...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2023-06-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2023/1/e43311 |
| _version_ | 1797734029800243200 |
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| author | Tjorven Stamer Jost Steinhäuser Kristina Flägel |
| author_facet | Tjorven Stamer Jost Steinhäuser Kristina Flägel |
| author_sort | Tjorven Stamer |
| collection | DOAJ |
| description |
BackgroundCommunication is a crucial element of every health care profession, rendering communication skills training in all health care professions as being of great importance. Technological advances such as artificial intelligence (AI) and particularly machine learning (ML) may support this cause: it may provide students with an opportunity for easily accessible and readily available communication training.
ObjectiveThis scoping review aimed to summarize the status quo regarding the use of AI or ML in the acquisition of communication skills in academic health care professions.
MethodsWe conducted a comprehensive literature search across the PubMed, Scopus, Cochrane Library, Web of Science Core Collection, and CINAHL databases to identify articles that covered the use of AI or ML in communication skills training of undergraduate students pursuing health care profession education. Using an inductive approach, the included studies were organized into distinct categories. The specific characteristics of the studies, methods and techniques used by AI or ML applications, and main outcomes of the studies were evaluated. Furthermore, supporting and hindering factors in the use of AI and ML for communication skills training of health care professionals were outlined.
ResultsThe titles and abstracts of 385 studies were identified, of which 29 (7.5%) underwent full-text review. Of the 29 studies, based on the inclusion and exclusion criteria, 12 (3.1%) were included. The studies were organized into 3 distinct categories: studies using AI and ML for text analysis and information extraction, studies using AI and ML and virtual reality, and studies using AI and ML and the simulation of virtual patients, each within the academic training of the communication skills of health care professionals. Within these thematic domains, AI was also used for the provision of feedback. The motivation of the involved agents played a major role in the implementation process. Reported barriers to the use of AI and ML in communication skills training revolved around the lack of authenticity and limited natural flow of language exhibited by the AI- and ML-based virtual patient systems. Furthermore, the use of educational AI- and ML-based systems in communication skills training for health care professionals is currently limited to only a few cases, topics, and clinical domains.
ConclusionsThe use of AI and ML in communication skills training for health care professionals is clearly a growing and promising field with a potential to render training more cost-effective and less time-consuming. Furthermore, it may serve learners as an individualized and readily available exercise method. However, in most cases, the outlined applications and technical solutions are limited in terms of access, possible scenarios, the natural flow of a conversation, and authenticity. These issues still stand in the way of any widespread implementation ambitions. |
| first_indexed | 2024-03-12T12:37:17Z |
| format | Article |
| id | doaj.art-5cedb05e43a44ee8804a10b2e7f75ccc |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:37:17Z |
| publishDate | 2023-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-5cedb05e43a44ee8804a10b2e7f75ccc2023-08-29T00:04:35ZengJMIR PublicationsJournal of Medical Internet Research1438-88712023-06-0125e4331110.2196/43311Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping ReviewTjorven Stamerhttps://orcid.org/0000-0002-9011-3775Jost Steinhäuserhttps://orcid.org/0000-0002-9386-6078Kristina Flägelhttps://orcid.org/0000-0002-1416-6293 BackgroundCommunication is a crucial element of every health care profession, rendering communication skills training in all health care professions as being of great importance. Technological advances such as artificial intelligence (AI) and particularly machine learning (ML) may support this cause: it may provide students with an opportunity for easily accessible and readily available communication training. ObjectiveThis scoping review aimed to summarize the status quo regarding the use of AI or ML in the acquisition of communication skills in academic health care professions. MethodsWe conducted a comprehensive literature search across the PubMed, Scopus, Cochrane Library, Web of Science Core Collection, and CINAHL databases to identify articles that covered the use of AI or ML in communication skills training of undergraduate students pursuing health care profession education. Using an inductive approach, the included studies were organized into distinct categories. The specific characteristics of the studies, methods and techniques used by AI or ML applications, and main outcomes of the studies were evaluated. Furthermore, supporting and hindering factors in the use of AI and ML for communication skills training of health care professionals were outlined. ResultsThe titles and abstracts of 385 studies were identified, of which 29 (7.5%) underwent full-text review. Of the 29 studies, based on the inclusion and exclusion criteria, 12 (3.1%) were included. The studies were organized into 3 distinct categories: studies using AI and ML for text analysis and information extraction, studies using AI and ML and virtual reality, and studies using AI and ML and the simulation of virtual patients, each within the academic training of the communication skills of health care professionals. Within these thematic domains, AI was also used for the provision of feedback. The motivation of the involved agents played a major role in the implementation process. Reported barriers to the use of AI and ML in communication skills training revolved around the lack of authenticity and limited natural flow of language exhibited by the AI- and ML-based virtual patient systems. Furthermore, the use of educational AI- and ML-based systems in communication skills training for health care professionals is currently limited to only a few cases, topics, and clinical domains. ConclusionsThe use of AI and ML in communication skills training for health care professionals is clearly a growing and promising field with a potential to render training more cost-effective and less time-consuming. Furthermore, it may serve learners as an individualized and readily available exercise method. However, in most cases, the outlined applications and technical solutions are limited in terms of access, possible scenarios, the natural flow of a conversation, and authenticity. These issues still stand in the way of any widespread implementation ambitions.https://www.jmir.org/2023/1/e43311 |
| spellingShingle | Tjorven Stamer Jost Steinhäuser Kristina Flägel Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review Journal of Medical Internet Research |
| title | Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review |
| title_full | Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review |
| title_fullStr | Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review |
| title_full_unstemmed | Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review |
| title_short | Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review |
| title_sort | artificial intelligence supporting the training of communication skills in the education of health care professions scoping review |
| url | https://www.jmir.org/2023/1/e43311 |
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