Using XML and XSLT for flexible elicitation of mental-health risk knowledge.

C D Buckingham, A Ahmed, A E Adams
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引用次数: 21

Abstract

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge.

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使用XML和XSLT灵活地获取心理健康风险知识。
目前评估与心理健康问题相关的风险的工具要求评估人员根据临床经验做出高水平的判断。本文描述了新技术如何增强定性研究方法,以识别这些判断背后的低级线索,这些线索可以由没有专业心理健康背景的人收集。对46位多学科心理健康专家的访谈内容分析揭示了这些线索和它们之间的相互关系,这些线索通过使用将地图存储为XML的软件的思维导图来表示。所有46个思维导图都集成到一个XML知识结构中,并由一个Lisp程序进行分析,以生成与每个部分相关的专家数量的定量信息。专家们使用Flash开发的软件将他们的集体观点记录在XML本身中,对这些知识进行了提炼。这些视图指定了应该如何通过XSLT(一种呈现XML的技术)转换XML,从而产生将患者线索与风险关联起来的经过验证的分层知识结构。使用XSLT对XML数据进行灵活转换,以适应不断变化的知识获取需求,这也有助于生成适合不同评估环境和心理健康知识水平的多种数据收集工具。
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