Development and Validation of The Questionnaire for Assessing Qi-blood-fluid Patterns for Pre-graduate Kampo Medicine Education

Ryutaro ARITA; Tetsuharu KAMIYA; Soichiro KANEKO; Akiko KIKUCHI; Minoru OHSAWA; Natsumi SAITO; Yoshiyasu MURAKAMI; Satoko SUZUKI; Rie ONO; Shinichi NAGATA; Shin TAKAYAMA; Tadashi ISHII

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Development and Validation of The Questionnaire for Assessing Qi-blood-fluid Patterns for Pre-graduate Kampo Medicine Education

VernacularTitle:漢方医学の卒前教育に活用できる気血津液体質チェックアンケートの開発と妥当性の検討
Author: Ryutaro ARITA ¹ ; Tetsuharu KAMIYA ² ; Soichiro KANEKO ¹ ; Akiko KIKUCHI ² ; Minoru OHSAWA ¹ ; Natsumi SAITO ¹ ; Yoshiyasu MURAKAMI ² ; Satoko SUZUKI ¹ ; Rie ONO ² ; Shinichi NAGATA ¹ ; Shin TAKAYAMA ¹ ; Tadashi ISHII ¹
Author Information

1. Department of Education and Support for Regional Medicine, Department of Kampo Medicine, Tohoku University Hospital
2. Department of Kampo and Integrative Medicine, Tohoku University Graduate School of Medicine
Keywords: Kampo medicine; traditional Chinese medicine; pre-graduate education; simulation-based education; qi-blood-fluid
From:Kampo Medicine 2024;75(2):152-167
CountryJapan
Language:Japanese
Abstract: Some simulation-based education tools have been introduced in Kampo medicine. However, there are only a few brief simulation tools to learn qi-blood-fluid (QBF) patterns of traditional Chinese medicine (TCM). In this study, we developed a self-diagnostic questionnaire that allows students learn TCM interviews and QBF patterns by answering the questionnaire and evaluated its reliability and validity. We extracted questionnaire items to classify six QBF patterns (qi deficiency, blood deficiency, yin deficiency, qi stagnation, blood stasis, and phlegm-fluid retention) based on some textbooks of TCM and Kampo medicine. Then we developed an initial questionnaire comprising 35 items. Fifth year medical students at Tohoku University School of Medicine answered the questionnaire of small group teaching during 2017-2020. We evaluated the accuracy of the questionnaire if compared with the diagnosis of academic supervisors. To improve the accuracy, we adjusted the questionnaire’s thresholds and created a predictive model of the patterns using logistic regression analysis. The questionnaire’s sensitivity improved by adjusting the thresholds. Logistic regression analysis resulted in a predictive model that could determine QBF patterns with the same level of accuracy as the original for 20 items overall. The results suggest that the use of a simple questionnaire with ensured accuracy may contribute to better pre-graduate education by making it easier for students to understand their own Kampo medicine patterns.