基于症状群落理论对阳明病辨证诊断思维的研究
[Abstract]:Objective: to explore the effect of different syndromes representation methods on the correct rate of syndrome differentiation and diagnosis of TCM students and the cognition of TCM students to the symptom community of Yangming disease by means of self-made questionnaire. Thus, the characteristics of symptom community thinking and its influence on TCM students' thinking of syndrome differentiation and diagnosis were studied. Methods: 1, literature research: combing and summarizing the basic concepts of TCM, such as "disease", "syndrome", "pathogenesis" and so on; To explore the current situation and development of TCM dialectical thinking. 2. Empirical study: 2013 grade Chinese medicine seven-year undergraduate and 2014 grade Chinese medicine graduate students were selected by random cluster sampling method as the objects of investigation. The effect of different syndromes on the correct rate of diagnosis of Yangming disease was investigated. The data were collected and analyzed. Results: 1. On the whole, the correct rate of symptom community representation pattern was the highest, and that of random free representation model was the lowest. 2. In symptom community representation model, the correct rate of graduate student syndrome diagnosis was significantly higher than that of undergraduate students. The correct rate of syndrome diagnosis of female students was significantly higher than that of boys. 3. The overall mastery of Yangming disease in TCM students was obviously better than that of changing syndrome, among which, the internal syndrome of Yang Ming dryness and heat evil was the best. Conclusion: 1. The degree of knowledge mastery and their own clinical experience in TCM students have an important influence on the correct rate of diagnosis of syndrome differentiation. 2. The symptom community representation model focuses on the classification and characterization of the basic pathogenesis of the disorder symptoms. It is beneficial for the students of TCM to improve the correct rate of syndrome differentiation and diagnosis on the basis of comprehensive analysis of the pathogenesis.
【学位授予单位】:山东中医药大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:B844.2
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