When Language Breaks Down: Analysing Discourse in Clinical Contexts

leondumoulin.nl: When Language Breaks Down: Analysing Discourse in Clinical Contexts (): Elissa D. Asp, Jessica de de Villiers: Books.
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Home Academic Languages and linguistics Psycholinguistics and neurolinguistics. Add to cart Add to wishlist Other available formats: Hardback , eBook Looking for an inspection copy? This title is not currently available on inspection. Presents new models for describing and analysing language in disorders Examples are based on the author's own research on the language of people with Alzheimer's disease and autism spectrum disorders The descriptions of discourse patterns are presented in non-technical language.

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When Language Breaks Down: Analysing Discourse in Clinical Contexts

Pragmatic and Discourse Disorders A Workbook. Case Studies in Communication Disorders. Applied Psycholinguistics Applied Psycholinguistics publishes original research papers on the psychological processes involved in language. Language and Cognition Bilingualism: Journal of Child Language A key publication in the field, Journal of Child Language publishes articles on all aspects of the scientific study…. Acta Neuropsychiatrica Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. Browse by related subject. African and Caribbean language and linguistics Applied linguistics and second language acquisition Arabic and Middle Eastern language and linguistics Asian language and linguistics Cognitive linguistics Computational linguistics Discourse analysis English language and linguistics: European language and linguistics Evolution of language Grammar and syntax Historical linguistics History of the English language Latin American language and linguistics Morphology Other languages and linguistics.

Phonetics and phonology Psycholinguistics and neurolinguistics Research methods in linguistics Semantics and pragmatics Sign language Sociolinguistics Stylistics. Sign In Please sign in to access your account Email Address. Password Forgotten your password? Language deficits in MCI have been object of scrutiny in the literature, allowing well-known disturbances in tasks of fluency, naming, and semantic knowledge [13]. The HC and AD groups differed in all parameters, except for the time taken to execute the task and the number of words. Discourse is recognized as a fundamental component in language assessments and should be considered for the identification of language disorders in dementias, as well as in the follow-up for these individuals [16].

It is indispensable, therefore, to advance in the nature of such shortcomings and obtaining cognitive and discursive markers for the differential diagnosis of pathologies. The well-rooted theory of Kintsch and van Dijk [18] supports the analysis model of microstructure and macrostructure to study the discourse of individuals with Alzheimer's disease [17] , [19]. Cinderella's storytelling has been used in aphasia studies [20] and is included in the assessments of subjects because of their penetration in Western culture, including Brazil. Advances in new techniques of Natural Language Processing combined with Data Science techniques are expanding.

Computational methods are applied in texts, seeking to identify signs of neurological or psychiatric impairments and automatically extract linguistic characteristics for recognition, classification, and description of diseases [21] , [22]. Among the obstacles in studies about discourse, transcription and analysis are vital and reports concerning computational analysis are scarce. Because they are laborious and difficult, research on a large scale becomes challenging and reinforces the benefits from the speed and systematic nature of computerized analyzes.


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  4. Introduction.
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  6. The Evolution of Group Analysis (International Library of Group Analysis).

Hence, searching for markers and performance profiles using unbiased techniques becomes fundamental and may guide clinical practice with greater objectivity and accuracy [23]. The Coh-Metrix tool [24] was developed at Memphis University to capture cohesion and difficulty of a text.

This tool was adapted to Portuguese, so-called Coh-Metrix-Port [25]. The use of the tool for the dementia population motivated the creation of Coh-Metrix-Dementia [26] , used in the present study. New features include Latent Semantic Analysis, measures of lexical diversity, syntactic complexity, and semantic density. By means of this technology, we aimed to verify if Cinderella's storytelling, a prototypic narrative very well known in Western culture [20] , distinguished individuals with AD or MCI and HC; using both quantitative parameters, such as the occurrence frequency of distinguishing traits, and qualitative parameters, to verify the nature of macrostructural aspects.

The study was justified by the need to identify and characterize the differences between groups, different diagnoses, and the possibility of creating tools that facilitate the observation of results of clinical intervention in language in dementia. The authors hypothesized that certain metrics could differentiate the three groups with being the worst performance for mild Alzheimer's disease mAD , followed by amnestic mild cognitive impairment aMCI and HC, finding performance markers for each group. The sample size consisted of 60 individuals divided into 3 groups: All individuals had their diagnosis confirmed by a neurologist that was blind to the procedure, subsequently going through the proposed protocol.

The MCI group was constituted only by amnestic, single or multiple domain, individuals. HC group was comprised by age- and education-matched community-dwelling volunteers and nonconsanguineous caregivers who fulfilled criteria for inclusion and exclusion. For the evaluation of discourse, a book with 22 sequenced scenes, portraying the Cinderella story without subtitles, was used.

Evaluations were carried out individually by the same researcher C. Subjects were instructed to narrate the story in their own words as if telling to someone who did not know it. There was no time limit. All collected discourses were transcribed, and then Coh-Metrix-Dementia was used to extract the metrics for computerized analysis.

This program is able to display the value of 73 features in several linguistic aspects.

There was a need to edit the transcripts, segmenting them into sentences to ensure better system performance. In this study, experts participated in phases 1 and 2 were 4 professionals, and phase 3 was performed by 2 professionals. The professionals were divided into pairs for the annotation of a sample of each group. The Kappa index was calculated to verify the concordance between the judges, and the data were adjusted. Both texts with the manual segmentation performed by the evaluators were analyzed by Coh-Metrix-Dementia for the extraction of metrics.

The original story was taken into account, and the main ideas were then selected.

When Language Breaks Down: Analysing Discourse in Clinical Contexts

The 28 propositions were also grouped according to four major components of the narrative structure:. Using features provided by the tool and by manual marking, the macrostructural characteristics were extracted. The analyses of the macrostructural characteristics were carried out as follows: The groups were matched for age, education, and, although not controlled, gender was balanced among groups.

Lecture 13: Convolutional Neural Networks

Coh-Metrix-Dementia was used to capture discourse features. Statistical analyses were performed to verify the features and metrics capable of differentiating the groups. Regarding the number of propositions reported in the discourse, mAD individuals presented lower numbers in relation to aMCI and HC, indicating less informative discourses. The number of propositions in each item was superior to mAD. Demographical and global cognitive results and analysis of the amount of proposition and narrative structure.

In the average features between adjacent sentences and mean of similarity between all sentence pairs in the text, a difference was found only between aMCI and mAD. The aMCI presented the lowest values in these measurements. The mAD individuals presented the highest values in the metric standard deviation among sentences, among all sentence pairs. In the other features of the latent semantic analysis category, no differences were found between the groups.

The total idea density of the text showed that mAD individuals presented a lower total number of propositions. Empty emissions analysis, total idea density analysis, latent semantic analysis, and number of modalizations. The purpose of this study was to verify the differences between mAD, aMCI, and HC in the task of producing narratives, exploring an innovative method of computational discourse analysis that could identify performance markers in macrostructural aspects and help differentiate individuals in each stage.

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We did not differentiate multiple or single domain in our sample, as most language studies in the literature [39] , [40] , [41]. In relation to macrostructural aspects, informativity, global coherence, and modalization were analyzed. The informativity refers to the target propositions expected for the narrative. Twenty-eight propositions were defined in Cinderella's story. The results showed that the mAD individuals presented less propositions than the aMCI and HC individuals, indicating less informative discourses with less reference to what was expected for the narrative. These findings corroborate the literature that indicates alteration in the content of individuals with AD [14] , [19].

We minimize memory impact in discourse production since the Cinderella scenes were available for consultation during the task. Fleming and Harris [43] found differences between individuals with MCI and healthy subjects regarding discourse length and quality, impaired in the former by the absence of central elements. The performance compromised in semantic activities may occur due to shortcomings in executive skills related to semantic processing, which is responsible for retrieving, maintaining, monitoring, and manipulating semantic representations.

The study by Lira [19] reported that the AD group presented half of the propositions in comparison to the total of the control group in a narrative task and linked this difficulty to a loss in content processing. In the present study, the expected number of propositions was high, which may have contributed to the results found. The fact that no subject has produced a discourse with all the selected propositions should be emphasized.

This was also found in Toledo [44] with normal individuals and corroborates the results of Alves and Souza [45] , who evaluated the differences of priorities between examiner and subject in the construction of narratives. Individuals with AD presented discourses with lower relevant content than those of MCI and healthy subjects, who presented similar performance, as found in the present study. Another hypothesis that explains the amount of information produced by the individuals would be the context of the evaluation.

In this hypothesis, the individuals produced less information because they assumed that the evaluator already knew the figure. In the present study, the structure of the narrative by the division in orientation, problem, development, and outcome was analyzed. For the analysis of the global coherence, the empty emissions, the total idea density feature, and the latent semantic analysis feature were verified. Greater difficulty was found in the discourse of the mAD individuals. They also presented higher numbers of empty emissions without reference to the narrative, indicating greater difficulty to maintain the theme.

The mAD presented lower values in the total idea density feature when compared with the other groups. This feature takes into account the ideas transmitted by the subject and how each transmitted information cell is related to the target propositions. The features that analyze the similarity between sentences and their contribution to global coherence are highlighted. In the metric standard deviation between sentences, higher values in mAD among all pairs of sentences were found, indicating greater difficulty in keeping the theme throughout the discourse.

The average metric between adjacent sentences and average similarity between all sentence pairs differentiated the aMCI from the mAD, which presented the highest values and shows more repetitive discourse without introducing new information. It was not possible to discriminate each group based on these features. This study demonstrates an innovative method for the analysis of global coherence, using automatically extracted metrics and empty emission marking.

The authors state that these difficulties are associated with the semantic-pragmatic and lexical components of language. Of course, the degree of precision that analysts need to meet and the level of coding they choose depend on the object of their inquiry. For instance, if what one wishes to assess is the degree of morphosyntactic complexity, detailed coding of conversational structure such as topic continuation and shifts might be unnecessary.

This, however, presupposes that researchers already know what they are looking for; that is, that they have at their disposal diagnostic criteria that include precisely circumscribed linguistic problems. But, of course, many linguistic and communicative properties of neurodegenerative and neurodevelopmental deficiencies remain unknown, and more often than not nosological uncertainty looms large. The fourth section of Ch. No doubt it is important to explain where the analytical tools and concepts that are used come from, and to clarify their theoretical presuppositions.

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