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Comprehending Adverbs of Doubt and Certainty in Health Communication: A Multidimensional Scaling Approach

机译:理解健康交流中的疑问和确定性副词:多维尺度法

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This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as “doctors' opinions.” Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.
机译:这项研究探索了使用多维标度(MDS)分析与其他技术进行新颖组合以研究表达疑问和确定性的认知副词(例如,显然,显然,可能)的可行性,因为它们与临床环境中的健康交流有关。在研究1中,讲英语的澳大利亚人执行了包含单词目标刺激的句子对的异同评分任务,并以“医生的意见”表示。使用文化共识分析(参与者之间的因素分析),加权数据经典MDS和聚类分析的组合来分析评分。分析表明,考虑到个体差异的3维语义空间解决方案具有很强的社区内部一致性,MDS结果在压力和解释方差方面具有很强的统计可接受性,并且语义结构可以从语言的语言分析方面进行解释。目标副词。结果证实了在这种情况下使用MDS的可行性。研究2与讲加拿大英语的人在同一任务上重复了结果。在澳大利亚和加拿大的数据集上进行了语义分析和压力分解分析,揭示了两组之间的异同。总体而言,结果支持使用MDS研究对健康交流至关重要的单词的理解,包括在未来的研究中,例如说第二语言的患者和/或从业人员。从更广泛的角度来看,结果表明,所描述的技术在临床和其他领域的许多交流领域中的理解研究中应该是很有前途的,包括针对语言其他方面的研究,并着重于不同语音社区之间的比较。

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