An Evaluation of Linguistic Variables for Identifying Agrammatic Production in People with Aphasia
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1
University of Pittsburgh, Department Communication Science and Disorders, United States
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2
Universidade Federal São Paulo, Department of Speech, Language and Hearing Sciences, Brazil
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3
Mt. Oliver Intermediate Unit, United States
While there is no agreed upon definition or criteria for diagnosing agrammatic production, it has been identified by limited use or errors in grammatical morphemes (e.g., Lonzi & Luzzatti, 1993), structural syntactic errors (Zingeser & Berndt, 1990), low proportion of grammatical sentences (Kim & Thompson, 2004), high open-to-closed class words (Kim & Thompson, 2004) increased noun-to-verb ratios (Kim & Thompson, 2004), and reduced use of light verbs (Gordon, 2008). However, a few studies reported different results regarding light verbs and noun-to-verb ratio (Breedin, Saffran, & Schwartz, 1998; Kim & Thompson, 2004). These inconsistencies support the need for unified and experimentally derived criteria including replicable speech elicitation procedures and scoring methods.
Connected language samples from 32 people with aphasia (PWA) (Mean age 63.7, Female 16, Male 16, average education of 14.47 years) were elicited using the Story Retell Procedure (SRP) (McNeil et al., 2007). They were screened for memory impairments using the immediate/delayed story retell task from the Arizona Battery for Communication Disorders of Dementia (Bayles & Tomoeda, 1993). Participants met the diagnosis of aphasia based on their performance on the Porch Index of Communicative Abilities (PICA)(Porch, 1981) and produced an average score of 13.03 (SD=.98).
A two-step cluster analysis was performed using ten variables derived from their story retells: 1) the ratio of embedded clause to total number of utterances (TNU), 2) ratio of non-grammatical to grammatical clauses, 3) ratio of auxiliary score (counting inflections in the auxiliary and main verbs) to total number of verbs (TNV), 4) percent information unit per minute, 5) ratio of number of propositions to TNU, 6) ratio of number of words in verb phrase to TNU, 7) ratio of number of words in subject phrase to TNU, 8) ratio of number of open-to-closed class words, 9) total number of utterance per minute, and 10) ratio of non-canonical clause to TNU. Based on results of the cluster analysis, the groups were divided into a “more grammatical” and a “less grammatical” group. After assigning participants to groups and after controlling for the aphasic severity using an analysis of covariance (ANCOVA), the ratio of light verbs to TNV and noun-to-verb ratio were compared between the two groups.
The first cluster was composed of 10 PWA, defined as the “less grammatical” group. The second “more grammatical” cluster was composed of 22 PWA. Unlike previous reports, the average ratio of light verbs to TNV was .33 (SD=.10) for group 1 and .33 (SD=.13) for group 2. The ratio of light verbs to TNV was not significantly different between two groups after adjusting for the PICA score (F(1,29)=.045, p=.834). Additionally, group 1 had a lower average noun-to-verb ratio (mean=.86, SD=.48) than group 2 (mean .92, SD=.24). This noun-to-verb ratio was significantly different between two groups after adjusting for the PICA score (F(1,29)=7.556, p=.010).
Based on the previous literature, it was expected that there would be fewer light verbs to TNV in the less grammatical group. As there was no significant difference in production of light verbs relative to TNV, this variable failed to differentiate the groups. Additionally, it was anticipated that the less grammatical group would produce more nouns than verbs, however, the results revealed the opposite pattern. The use of these two variables in the selection of agrammatic PWA requires re-examination for the reliable identification of agrammatic speech in PWA.
Acknowledgements
This work was supported by the following grants from VA RR&D awarded to Dr. McNeil and colleagues:
Quantifying and Predicting Quality of Life Outcomes in Stroke Survivors. 2001-2004.
Quantifying Spoken Language Handicap in Aphasia II. 2000-2003.
Assessing Visual and Auditory Language Processing Modalities in Aphasia. 2007-2009.
The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
References
Bayles, K. A., & Tomoeda, M. S. (1993). Arizona Battery for Communication Disorders of Dementia. Tucson, AZ: Canyonlands Publishing.
Breedin, S. D., Saffran, E. M., & Schwartz, M. F. (1998). Semantic factors in verb retrieval: An effect of complexity. Brain and Language, 63(1-31).
Gordon, J. K. (2008). Measuring the lexical semantics of picture description in aphasia. Aphasiology, 22(7-8), 839-852.
Kim, M., & Thompson, C. K. (2004). Verb deficits in Alzheimer's disease and agrammatism: Implications for lexical organization. Brain and Language, 88(1), 1-20.
Lonzi, L., & Luzzatti, C. (1993). Relevance of adverb distribution for the analysis of sentence representation in agrammatic patients. Brain and Language, 45, 306-317.
McNeil, M. R., Sung, J. E., Yang, D., Pratt, S. R., Fossett, T. R. D., Doyle, P., J., & Pavelko, S. (2007). Comparing connected language elicitation procedures in persons with aphasia: Concurrent valiation of the story retell procedure. Aphasiology, 21(6), 775-790.
Porch, B. E. (1981). Porch Index of Communicative Ability. Palo Alto, CA: Consulting Psychologists Press.
Zingeser, L. B., & Berndt, R. S. (1990). Retrieval of nouns and verbs in agrammatism and anomia. Brain and Language, 39, 14-32.
Keywords:
Agrammatic speech production,
Noun to verb ratio,
light verb to total number of verbs,
story retell procedure,
Cluster analysis
Conference:
Academy of Aphasia 55th Annual Meeting , Baltimore, United States, 5 Nov - 7 Nov, 2017.
Presentation Type:
poster presentation
Topic:
Consider for student award
Citation:
Kim
H,
McNeil
MR,
Ortiz
K and
Bowers
K
(2019). An Evaluation of Linguistic Variables for Identifying Agrammatic Production in People with Aphasia.
Conference Abstract:
Academy of Aphasia 55th Annual Meeting .
doi: 10.3389/conf.fnhum.2017.223.00008
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Received:
03 May 2017;
Published Online:
25 Jan 2019.
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Correspondence:
Ms. Hyun Seung Kim, University of Pittsburgh, Department Communication Science and Disorders, Pittsburgh, 15260, United States, nlpurumi@gmail.com