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Clinical Data Mining With the Listening Guide: An Approach to Narrative Big Qual
International Journal of Qualitative Methods ( IF 4.828 ) Pub Date : 2020-12-29 , DOI: 10.1177/1609406920951746
Claire M. Fontaine 1 , Amy Castro Baker 1 , Tooma H. Zaghloul 1 , Mae Carlson 1
Affiliation  

We developed a novel approach to narrative Big Qual research that combines Carol Gilligan and Lyn Mikel Brown’s Listening Guide with Irwin Epstein’s clinical data mining. We adapted the voice-based research methodology of the Listening Guide for use with a corpus of clinical case notes drawn from an integrated data system (IDS) of a social service intervention serving families in an immigrant enclave. This methodological innovation was inspired by the insight that the Listening Guide can be used to trace and name the layering of meaning within any narrative, whether that narrative reflects the experience of an individual person or, as in this case, the community and everyday life of a social service intervention. Critically, this approach pivots on theorizing the subject as the collective of the intervention itself, as narrated by case managers, who can be understood as narrating subjects within the cultural, figured world of the intervention. In the context of a larger process and outcome evaluation, marrying these two approaches provided context, texture, and depth to supplement existing data sources like self-report survey data and participant observation, and offered a glimpse inside the “black box” of the intervention. We adapted the Guide through three readings of the clinical case notes: once for stanza structure, once inspired by the I-Poem technique but modified for these third-person narratives, and once with an eye to the contrapuntal voices of the inner and outer worlds of the intervention. As a methodological innovation this approach represents an advance in Big Qual and a promising approach to conducting narrative research on large qualitative data sets within mixed methods studies.



中文翻译:

使用听力指南进行临床数据挖掘:叙事大质量的一种方法

我们开发了新颖的Big Qual叙事研究方法,将Carol Gilligan和Lyn Mikel Brown的听力指南与Irwin Epstein的临床数据挖掘相结合。我们对《听力指南》中基于语音的研究方法进行了调整,以配合临床案例注释的使用,这些案例注释是从为移民飞地中的家庭提供服务的社会服务干预措施的综合数据系统(IDS)中提取的。这种方法的创新源于以下洞察力,即《听力指南》可用于追踪和命名任何叙事中的意义层次,而不论该叙事反映的是个人的经历,还是在这种情况下反映的是社区的经历和日常生活,社会服务干预。至关重要的是,这种方法的重点是将案例理论作为干预本身的集合,如案例经理所言,可以理解为在干预的文化化,虚拟世界中叙述主题。在更大的过程和结果评估的背景下,将这两种方法结合起来可以提供背景,纹理和深度,以补充现有数据源(例如自我报告调查数据和参与者观察),并提供干预措施“黑匣子”的一瞥。 。我们通过对临床病例注释的三篇阅读材料对指南进行了修改:一次用于节结构,一次受到I-Poem技术的启发,但针对这些第三人称叙述进行了修改,一次着眼于内在和外部世界的矛盾声音的干预。

更新日期:2021-01-14
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