Annisa Ristya Rahmanti, Hsuan-Chia Yang, Chih-Wei Huang, Ching-Tzu Huang, Lutfan Lazuardi, Che-Wei Lin, Yu-Chuan Jack Li
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Consensus was determined based on median responses and expert scoring percentages, with statistical agreement and stability assessed using Kendall's coefficient of concordance (Kendall's W) and Wilcoxon signed-rank test. Analyses were conducted using SPSS, version 23.0 with significance set at <i>p</i> < 0.05. Of the 72 experts invited, 37 (51%) agreed to participate, with 35 completing the first round (95% completion rate). Eight significant nonverbal cues were identified in the first round, though one did not reach consensus. The second round obtained an 89% response rate (31/35), with three new cues introduced; one did not reach consensus. Round 3 achieved a 94% response rate (29/31), finalizing nine key cues: facial expression, eye contact, tone of voice, smiling, head nodding, body posture, hand gesture, distance, and environmental cues. Among these, facial expression, eye contact, and tone of voice were identified as the most crucial. 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引用次数: 0
摘要
非语言交流在医患互动中是必不可少的,特别是在远程医疗中,语言提示可能有限。本研究旨在通过德尔菲法识别和验证远程医疗会诊中评估医生移情的关键非语言线索。2022年6月至11月进行了三轮德尔菲研究,涉及学者、医疗保健专业人员、人工智能/远程医疗研究人员、行业专业人员和患者等各种专家。专家们评估了潜在的非语言线索的重要性、有效性和可靠性。共识是根据中位反应和专家评分百分比确定的,统计一致性和稳定性评估使用肯德尔的一致性系数(肯德尔的W)和Wilcoxon符号秩检验。采用SPSS 23.0进行分析,显著性设置为p p p p
Validating nonverbal cues for assessing physician empathy in telemedicine: a Delphi study.
Nonverbal communication is essential in physician-patient interaction, especially in telemedicine where verbal cues may be limited. This study aimed to identify and validate key nonverbal cues for assessing physician empathy in telemedicine consultations through a Delphi method. A three-round Delphi study was conducted from June to November 2022, involving various experts, including academics, healthcare professionals, AI/telemedicine researchers, industry professionals, and patients. Experts evaluated the importance, validity, and reliability of potential nonverbal cues. Consensus was determined based on median responses and expert scoring percentages, with statistical agreement and stability assessed using Kendall's coefficient of concordance (Kendall's W) and Wilcoxon signed-rank test. Analyses were conducted using SPSS, version 23.0 with significance set at p < 0.05. Of the 72 experts invited, 37 (51%) agreed to participate, with 35 completing the first round (95% completion rate). Eight significant nonverbal cues were identified in the first round, though one did not reach consensus. The second round obtained an 89% response rate (31/35), with three new cues introduced; one did not reach consensus. Round 3 achieved a 94% response rate (29/31), finalizing nine key cues: facial expression, eye contact, tone of voice, smiling, head nodding, body posture, hand gesture, distance, and environmental cues. Among these, facial expression, eye contact, and tone of voice were identified as the most crucial. Inter-expert agreement was statistically significant across all items with strong agreement on the importance (W = 0.739, p < 0.001), good agreement on their validity (W = 0.689, p < 0.001), and moderate agreement on their reliability (W = 0.452, p < 0.001). This study highlights the importance of specific nonverbal cues in telemedicine, particularly facial expression, eye contact, and tone of voice. It provides a validated foundation for developing tools to enhance physician-patient interactions and potentially improve health outcomes in telemedicine.
期刊介绍:
Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends.
Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to:
-Basic science education
-Clinical science education
-Residency education
-Learning theory
-Problem-based learning (PBL)
-Curriculum development
-Research design and statistics
-Measurement and evaluation
-Faculty development
-Informatics/web