Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice
Abstract To explore the attitudes of healthcare professionals and the public on applying ChatGPT in clinical practice. The successful application of ChatGPT in clinical practice depends on technical performance and critically on the attitudes and perceptions of non-healthcare and healthcare. This st...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-84512-y |
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| author | Lizhen Lu Yueli Zhu Jiekai Yang Yuting Yang Junwei Ye Shanshan Ai Qi Zhou |
| author_facet | Lizhen Lu Yueli Zhu Jiekai Yang Yuting Yang Junwei Ye Shanshan Ai Qi Zhou |
| author_sort | Lizhen Lu |
| collection | DOAJ |
| description | Abstract To explore the attitudes of healthcare professionals and the public on applying ChatGPT in clinical practice. The successful application of ChatGPT in clinical practice depends on technical performance and critically on the attitudes and perceptions of non-healthcare and healthcare. This study has a qualitative design based on artificial intelligence. This study was divided into five steps: data collection, data cleaning, validation of relevance, sentiment analysis, and content analysis using the K-means algorithm. This study comprised 3130 comments amounting to 1,593,650 words. The dictionary method showed positive and negative emotions such as anger, disgust, fear, sadness, surprise, good, and happy emotions. Healthcare professionals prioritized ChatGPT’s efficiency but raised ethical and accountability concerns, while the public valued its accessibility and emotional support but expressed worries about privacy and misinformation. Bridging these perspectives by improving reliability, safeguarding privacy, and clearly defining ChatGPT’s role is essential for its practical and ethical integration into clinical practice. |
| format | Article |
| id | doaj-art-e88c5d60044f47c9b2720aed923a0066 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e88c5d60044f47c9b2720aed923a00662025-01-12T12:16:22ZengNature PortfolioScientific Reports2045-23222025-01-0115111110.1038/s41598-024-84512-yHealthcare professionals and the public sentiment analysis of ChatGPT in clinical practiceLizhen Lu0Yueli Zhu1Jiekai Yang2Yuting Yang3Junwei Ye4Shanshan Ai5Qi Zhou6 Integrated Traditional and Western Medicine Hospital of Linping District Integrated Traditional and Western Medicine Hospital of Linping DistrictDepartment of Nursing, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang UniversityDepartment of Nursing, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University Integrated Traditional and Western Medicine Hospital of Linping District Integrated Traditional and Western Medicine Hospital of Linping District Integrated Traditional and Western Medicine Hospital of Linping DistrictAbstract To explore the attitudes of healthcare professionals and the public on applying ChatGPT in clinical practice. The successful application of ChatGPT in clinical practice depends on technical performance and critically on the attitudes and perceptions of non-healthcare and healthcare. This study has a qualitative design based on artificial intelligence. This study was divided into five steps: data collection, data cleaning, validation of relevance, sentiment analysis, and content analysis using the K-means algorithm. This study comprised 3130 comments amounting to 1,593,650 words. The dictionary method showed positive and negative emotions such as anger, disgust, fear, sadness, surprise, good, and happy emotions. Healthcare professionals prioritized ChatGPT’s efficiency but raised ethical and accountability concerns, while the public valued its accessibility and emotional support but expressed worries about privacy and misinformation. Bridging these perspectives by improving reliability, safeguarding privacy, and clearly defining ChatGPT’s role is essential for its practical and ethical integration into clinical practice.https://doi.org/10.1038/s41598-024-84512-yArtificial intelligenceMedicineClinical competenceAttitudeChatGPT |
| spellingShingle | Lizhen Lu Yueli Zhu Jiekai Yang Yuting Yang Junwei Ye Shanshan Ai Qi Zhou Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice Scientific Reports Artificial intelligence Medicine Clinical competence Attitude ChatGPT |
| title | Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice |
| title_full | Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice |
| title_fullStr | Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice |
| title_full_unstemmed | Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice |
| title_short | Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice |
| title_sort | healthcare professionals and the public sentiment analysis of chatgpt in clinical practice |
| topic | Artificial intelligence Medicine Clinical competence Attitude ChatGPT |
| url | https://doi.org/10.1038/s41598-024-84512-y |
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