Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms
Emergency medicine virtual simulation platforms have transformed student training, allowing students to engage with a variety of realistic and replicable emergency scenarios. However, the completion and pass rates are low. The aim of this study is to explore the factors influencing medical students&...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10845754/ |
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| author | Lingjiao Tang Yu Ning Hui Lv Xuebin Li Aihe Tang |
| author_facet | Lingjiao Tang Yu Ning Hui Lv Xuebin Li Aihe Tang |
| author_sort | Lingjiao Tang |
| collection | DOAJ |
| description | Emergency medicine virtual simulation platforms have transformed student training, allowing students to engage with a variety of realistic and replicable emergency scenarios. However, the completion and pass rates are low. The aim of this study is to explore the factors influencing medical students’ adoption of intelligent virtual simulation platforms in China via Technology Acceptance Model 3. A total of 819 medical students from southern Chinese universities participated in the study. Structural equation modeling is used to examine data from cross-sectional quantitative surveys. The results revealed that image, relevance, and result demonstrability significantly affected perceived usefulness, whereas computer self-efficacy, perceptions of external control, anxiety, perceived enjoyment, and playfulness shaped perceived ease of use. Subjective norms emerged as the strongest predictor of behavioral intention, despite not significantly influencing perceived usefulness. The combined influence of subjective norms, perceived usefulness, and perceived ease of use positively affected students’ behavioral intentions. These findings highlight the importance of establishing supportive environments and designing user-friendly virtual simulation tools to promote technology adoption in medical education. These insights can help educational institutions and policymakers integrate virtual simulations effectively into medical curricula, thereby providing better flexible and personalized training experiences, which enhance the quality of skills acquisition and accessibility of emergency medical training. |
| format | Article |
| id | doaj-art-df99303d4b904a8f805d6af13b4e30af |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-df99303d4b904a8f805d6af13b4e30af2025-01-31T23:05:15ZengIEEEIEEE Access2169-35362025-01-0113192371924710.1109/ACCESS.2025.353150710845754Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation PlatformsLingjiao Tang0Yu Ning1Hui Lv2https://orcid.org/0000-0001-5428-5783Xuebin Li3Aihe Tang4Modern Industrial College of Biomedicine and Great Health, Youjiang Medical University for Nationalities, Baise, ChinaYulin First People’s Hospital, Yulin, ChinaModern Industrial College of Biomedicine and Great Health, Youjiang Medical University for Nationalities, Baise, ChinaAffiliated Hospital of Youjiang Medical University for Nationalities, Baise, ChinaAffiliated Hospital of Youjiang Medical University for Nationalities, Baise, ChinaEmergency medicine virtual simulation platforms have transformed student training, allowing students to engage with a variety of realistic and replicable emergency scenarios. However, the completion and pass rates are low. The aim of this study is to explore the factors influencing medical students’ adoption of intelligent virtual simulation platforms in China via Technology Acceptance Model 3. A total of 819 medical students from southern Chinese universities participated in the study. Structural equation modeling is used to examine data from cross-sectional quantitative surveys. The results revealed that image, relevance, and result demonstrability significantly affected perceived usefulness, whereas computer self-efficacy, perceptions of external control, anxiety, perceived enjoyment, and playfulness shaped perceived ease of use. Subjective norms emerged as the strongest predictor of behavioral intention, despite not significantly influencing perceived usefulness. The combined influence of subjective norms, perceived usefulness, and perceived ease of use positively affected students’ behavioral intentions. These findings highlight the importance of establishing supportive environments and designing user-friendly virtual simulation tools to promote technology adoption in medical education. These insights can help educational institutions and policymakers integrate virtual simulations effectively into medical curricula, thereby providing better flexible and personalized training experiences, which enhance the quality of skills acquisition and accessibility of emergency medical training.https://ieeexplore.ieee.org/document/10845754/Behavioral intentionmedical educationtechnology acceptance model 3virtual simulation experiment |
| spellingShingle | Lingjiao Tang Yu Ning Hui Lv Xuebin Li Aihe Tang Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms IEEE Access Behavioral intention medical education technology acceptance model 3 virtual simulation experiment |
| title | Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms |
| title_full | Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms |
| title_fullStr | Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms |
| title_full_unstemmed | Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms |
| title_short | Predictors of Medical Students’ Adoption of Emergency Medicine Virtual Simulation Platforms |
| title_sort | predictors of medical students x2019 adoption of emergency medicine virtual simulation platforms |
| topic | Behavioral intention medical education technology acceptance model 3 virtual simulation experiment |
| url | https://ieeexplore.ieee.org/document/10845754/ |
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