Communication training for pharmacy students with standard patients using artificial intelligence
INTRODUCTIONThe objective structured clinical examination (OSCE) is among validated approaches used to assess clinical competence through structured and practical evaluation. Most studies of OSCE have used standardized patients (SPs). However, to our knowledge, there is limited information regarding...
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Published in | Currents in pharmacy teaching and learning Vol. 14; no. 7; pp. 854 - 862 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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01.07.2022
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Abstract | INTRODUCTIONThe objective structured clinical examination (OSCE) is among validated approaches used to assess clinical competence through structured and practical evaluation. Most studies of OSCE have used standardized patients (SPs). However, to our knowledge, there is limited information regarding the specific communication skills enhanced by providing communication training (CT) with SPs. Recently, an artificial intelligence (AI) technology was developed. The aim of this study was to evaluate the experience and outcomes of CT with SPs and impact of using AI for this training. METHODSThis study targeted fourth-year students participating in a pre-learning course for pharmacy practice experience offered at a Japanese university in 2020. The ENcode, Decode, Control, and REgulate model, which evaluates 24 communication skills, was utilized as a questionnaire-based survey. The survey was conducted prior to CT, following CT, and after a second CT session six weeks later with AI. RESULTSSeven skills, namely "desire suppression," "expectation acceptance," "facial expression," "emotional communication," "dominance," "maintaining relationships," and "dealing with disagreements," were enhanced by the CT with SPs. These skills were included in the broad categories of "management" and "expression" skills. They were not significantly enhanced by following AI training. However, differences observed between the students who underwent AI training and those who did not demonstrated a positive effect in almost all skills, suggesting that AI training can enhance certain skills. CONCLUSIONSCT with SPs enhances students' "management" and "expression" skills. Additionally, AI shows potential for improving the effect of CT. |
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AbstractList | INTRODUCTIONThe objective structured clinical examination (OSCE) is among validated approaches used to assess clinical competence through structured and practical evaluation. Most studies of OSCE have used standardized patients (SPs). However, to our knowledge, there is limited information regarding the specific communication skills enhanced by providing communication training (CT) with SPs. Recently, an artificial intelligence (AI) technology was developed. The aim of this study was to evaluate the experience and outcomes of CT with SPs and impact of using AI for this training. METHODSThis study targeted fourth-year students participating in a pre-learning course for pharmacy practice experience offered at a Japanese university in 2020. The ENcode, Decode, Control, and REgulate model, which evaluates 24 communication skills, was utilized as a questionnaire-based survey. The survey was conducted prior to CT, following CT, and after a second CT session six weeks later with AI. RESULTSSeven skills, namely "desire suppression," "expectation acceptance," "facial expression," "emotional communication," "dominance," "maintaining relationships," and "dealing with disagreements," were enhanced by the CT with SPs. These skills were included in the broad categories of "management" and "expression" skills. They were not significantly enhanced by following AI training. However, differences observed between the students who underwent AI training and those who did not demonstrated a positive effect in almost all skills, suggesting that AI training can enhance certain skills. CONCLUSIONSCT with SPs enhances students' "management" and "expression" skills. Additionally, AI shows potential for improving the effect of CT. |
Author | Nakagawa, Naoto Odanaka, Keita Ohara, Hiroshi Kisara, Shigeki |
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