基于关键图的文本挖掘叙事分析:日本在世人群与牙医口腔健康观和口腔风险认知的异同

Fukiko Kobayashi, Y. Nara
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引用次数: 2

摘要

口腔健康管理过程中的主要利益相关者是活人(seikatsu-sya)和牙医,他们之间的相互认识和理解应该是提高活人和牙医口腔健康治疗质量不可或缺的基础。本研究旨在透过访谈资料,检视各主要利益相关者对口腔健康及口腔风险认知的异同点,以期为其相互认知及了解提供线索。围绕叙事分析的方法,论述了研究的具体过程、结果和意义。对5位在世的人和5位牙医进行了访谈,并通过文本挖掘工具Key Graph分析了他们的叙述。然后我们用KJ方法安排关键概念,或者亲和图,这是一个头脑风暴的工具,它将大量的想法组织成它们的自然关系。通过这一分析,笔者将日本生活人群对口腔健康和口腔风险认知的异同与牙医的异同排列在一张表格中。从表中可以看出,日本生者与牙医对口腔风险的认知存在一定差异,而日本生者对口腔健康的超纵坐标观与牙医基本一致。本研究揭示了关键图和KJ方法的协同应用,如文本挖掘和头脑风暴的机械处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Narrative Analysis by Text Mining Technique Using Key Graph: Similarity and Difference of a View of Oral Health and Oral Risk Cognition between Japanese Living People and Dentists
The main stakeholders in oral health management process are living people (seikatsu-sya) and dentists, the mutual awareness and understanding of them are supposed to be the indispensable basements to improve the quality of oral health treatments for both of living people and dentists. This study aims to examine the similarity and difference of a view of oral health and oral risk cognition between the main stakeholders with interview data in order to obtain a clue for generating their mutual awareness and understanding. Focusing on the method of narrative analysis, the authors discuss on the specifically process, the result, and the significance in this study. It was conducted interviews with five living people and five dentists analyzed their narratives by Key Graph which is a text mining tool. And then we arranged key concepts by KJ method, or an Affinity Diagram, which is a brainstorming tool which organizes a large number of ideas into their natural relationships. Through this analysis, the authors arranged the similarity and difference between Japanese living people's view of oral health and oral risk cognition, and those of dentists in a table. It is observed from the table that oral risk cognitions between Japanese living people and dentists have some difference, on the other side Japanese living people's super ordinate view of oral health and that of dentists are almost the same. This study revealed that it is desirable to apply the collaboration of Key Graph and KJ Method, such as the mechanical processing by the text-mining and the brainstorming.
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