Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-23T04:20:09.223Z Has data issue: false hasContentIssue false

Impact of Cognitive Impairment and Dysarthria on Spoken Language in Multiple Sclerosis

Published online by Cambridge University Press:  16 November 2020

Lynda Feenaughty*
Affiliation:
Department of Communicative Disorders and Sciences, University at Buffalo, Buffalo, NY 14214, USA
Ling-Yu Guo
Affiliation:
Department of Communicative Disorders and Sciences, University at Buffalo, Buffalo, NY 14214, USA
Bianca Weinstock-Guttman
Affiliation:
Department of Neurology, University at Buffalo, Buffalo, NY 14214, USA
Meredith Ray
Affiliation:
Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN 38152, USA
Ralph H.B. Benedict
Affiliation:
Department of Neurology, University at Buffalo, Buffalo, NY 14214, USA
Kris Tjaden
Affiliation:
Department of Communicative Disorders and Sciences, University at Buffalo, Buffalo, NY 14214, USA
*
*Correspondence and reprint requests to: Lynda Feenaughty, Ph.D., CCC-SLP, School of Communication Sciences and Disorders, University of Memphis, 4055 N. Park Loop, Memphis, TN38152, USA. Tel.: (901) 678-3555. Email: [email protected]

Abstract

Objective:

To investigate the impact of cognitive impairment on spoken language produced by speakers with multiple sclerosis (MS) with and without dysarthria.

Method:

Sixty speakers comprised operationally defined groups. Speakers produced a spontaneous speech sample to obtain speech timing measures of speech rate, articulation rate, and silent pause frequency and duration. Twenty listeners judged the overall perceptual severity of the samples using a visual analog scale that ranged from no impairment to severe impairment (speech severity). A 2 × 2 factorial design examined main and interaction effects of dysarthria and cognitive impairment on speech timing measures and speech severity in individuals with MS. Each speaker group with MS was further compared to a healthy control group. Exploratory regression analyses examined relationships between cognitive and biopsychosocial variables and speech timing measures and perceptual judgments of speech severity, for speakers with MS.

Results:

Speech timing was significantly slower for speakers with dysarthria compared to speakers with MS without dysarthria. Silent pause durations also significantly differed for speakers with both dysarthria and cognitive impairment compared to MS speakers without either impairment. Significant interactions between dysarthria and cognitive factors revealed comorbid dysarthria and cognitive impairment contributed to slowed speech rates in MS, whereas dysarthria alone impacted perceptual judgments of speech severity. Speech severity was strongly related to pause duration.

Conclusions:

The findings suggest the nature in which dysarthria and cognitive symptoms manifest in objective, acoustic measures of speech timing and perceptual judgments of severity is complex.

Type
Regular Research
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

a

Now at the University of Memphis.

References

REFERENCES

Amato, M.P., Langdon, D., Montalban, X., Benedict, R.H.B., DeLuca, J., Krupp, L.B., … Comi, G. (2013). Treatment of cognitive impairment in multiple sclerosis: Position paper. Journal of Neurology, 260(6), 14521468. https://doi.org/10.1007/s00415–012–6678–0 CrossRefGoogle ScholarPubMed
Amato, M.P., Ponziani, G., Siracusa, G., & Sorbi, S. (2001). Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Archives of Neurology, 58(10), 16021606.CrossRefGoogle ScholarPubMed
Anand, S. & Stepp, C.E. (2015). Listener perception of monopitch, naturalness, and intelligibility for speakers with Parkinson’s disease. Journal of Speech, Language, and Hearing Research, 58(4), 11341144.CrossRefGoogle ScholarPubMed
Asgari, M., Kaye, J., & Dodge, H. (2017). Predicting mild cognitive impairment from spontaneous spoken utterances. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 3(2), 219228.Google ScholarPubMed
Baddeley, A.D. & Hitch, G.J. (1974). Working memory. The Psychology of Learning and Motivation, 8, 4789.CrossRefGoogle Scholar
Bayles, K.A. & Tomoeda, C.K. (1993). Arizona Battery for Communication Disorders of Dementia. Tucson, AZ: Canyonlands.Google Scholar
Benedict, R.H. & Zivadinov, R. (2011). Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nature Reviews Neurology, 7(6), 332.CrossRefGoogle ScholarPubMed
Boersma, P. & Weenink, D. (2012) Pratt: A system for doing phonetics by computer [computer program] (version 5.4.04) Retrieved from http://www.pratt.org/ Google Scholar
Ceyhan, E. & Goad, C.L. (2009). A comparison of analysis of covariate-adjusted residuals and analysis of covariance. Communications in Statistics-Simulation and Computation, 38(10), 20192038.CrossRefGoogle Scholar
Cohen, J. (1988). Statistical Power Analysis for Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
Dagenais, P.A., Watts, C.R., Turnage, L.M., & Kennedy, S. (1999). Intelligibility and acceptability of moderately dysarthric speech by three types of listeners. Journal of Medical Speech Language Pathology, 7, 9196.Google Scholar
De Looze, C., Moreau, N., Renié, L., Kelly, F., Ghio, A., Rico, A., … & Petrone, C. (2017). Effects of cognitive impairment on prosodic parameters of speech production planning in multiple sclerosis. Journal of Neuropsychology, 13(1), 2245.CrossRefGoogle ScholarPubMed
Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Function System. San Antonio, Texas: Psychological Corporation.Google Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (2000). California Verbal Learning Test Manual, Adult Version (2nd ed.). San Antonio, Texas: Psychological Corporation.Google Scholar
DeLuca, G.C., Yates, R.L., Beale, H., & Morrow, S.A. (2015). Cognitive impairment in multiple sclerosis: clinical, radiologic and pathologic insights. Brain pathology (Zurich, Switzerland), 25(1), 7998. https://doi.org/10.1111/bpa.12220 CrossRefGoogle ScholarPubMed
Dromey, C., Boyce, K., & Channell, R. (2014). Effects of age and syntactic complexity on speech motor performance. Journal of Speech, Language, and Hearing Research, 57(6), 21422151.CrossRefGoogle ScholarPubMed
Duffy, J.R. (2013). Motor Speech Disorders: Substrates, Differential Diagnosis, and Management. (3rd ed.) Mosby Incorporated.Google Scholar
Feenaughty, L., Tjaden, K., Benedict, R.H., & Weinstock-Guttman, B. (2013). Speech and pause characteristics in multiple sclerosis: A preliminary study of speakers with high and low neuropsychological test performance. Clinical Linguistics & Phonetics, 27(2), 134151.CrossRefGoogle ScholarPubMed
Feenaughty, L., Tjaden, K., Weinstock-Guttman, B., & Benedict, R.H. (2018). Separate and combined influence of cognitive impairment and dysarthria on functional communication in multiple sclerosis. American Journal of Speech-Language Pathology, 27(3), 10511065.CrossRefGoogle ScholarPubMed
Friedova, L., Rusz, J., Motyl, J., Srpova, B., Vodehnalova, K., Andelova, M., … & Havrdova, E.K. (2019). Slowed articulation rate is associated with information processing speed decline in multiple sclerosis: A pilot study. Journal of Clinical Neuroscience, 65, 2833.CrossRefGoogle ScholarPubMed
Gronwall, D.M.A. (1977). Paced auditory serial addition task: A measure of recovery from concussion. Perceptual and Motor Skills, 44(2), 367373.CrossRefGoogle ScholarPubMed
Hartelius, L., Nord, L., & Buder, E.H. (1995). Acoustic analysis of dysarthria associated with multiple sclerosis. Clinical Linguistics & Phonetics, 9(2), 95120.CrossRefGoogle Scholar
Hartelius, L., Runmarker, B., Andersen, O., & Nord, L. (2000). Temporal speech characteristics of individuals with multiple sclerosis and ataxic dysarthria:‘Scanning speech’revisited. Folia phoniatrica et logopaedica, 52(5), 228238.CrossRefGoogle Scholar
Hickok, G. & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8(5), 393402.CrossRefGoogle ScholarPubMed
Kail, R. & Salthouse, T.A. (1994). Processing speed as a mental capacity. Acta Psychologica, 86(2), 199225.CrossRefGoogle ScholarPubMed
Keintz, C.K., Bunton, K., & Hoit, J.D. (2007). Influence of visual information on the intelligibility of dysarthric speech. American Journal of Speech-Language Pathology, 16, 222234.CrossRefGoogle ScholarPubMed
Levelt, W.J.M., Roelofs, A., & Meyer, A.S. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22(01), 138.CrossRefGoogle ScholarPubMed
Lowit, A., Brendel, B., Dobinson, C., & Howell, P. (2006). An Investigation into the influences of age, pathology and cognition on speech production. Journal of Medical Speech-Language Pathology, 12, 253262.Google Scholar
MacGregor, L.J., Corley, M., & Donaldson, D.I. (2010). Listening to the sound of silence: Disfluent silent pauses in speech have consequences for listeners. Neuropsychologia, 48(14), 39823992.CrossRefGoogle ScholarPubMed
Mackenzie, C. & Green, J. (2009). Cognitive-linguistic deficit and speech intelligibility in chronic progressive multiple sclerosis. International Journal of Language & Communication Disorders, 44, 401420.CrossRefGoogle ScholarPubMed
Milenkovic, P. (2011). TF32. [Computer program]. University of Wisconsin-Madison.Google Scholar
Murray, L.L. (2000). Spoken language production in Huntington’s and Parkinson’s diseases. Journal of Speech, Language, and Hearing Research, 43(6), 13501366.CrossRefGoogle ScholarPubMed
Neel, A.T. (2009). Effects of loud and amplified speech on sentence and word intelligibility in Parkinson disease. Journal of Speech, Language, and Hearing Research, 52(4), 10211033.CrossRefGoogle ScholarPubMed
Noffs, G., Perera, T., Kolbe, S.C., Shanahan, C.J., Boonstra, F., Evans, A., Butzkueven, H., … Vogel, A.P. (2018). What speech can tell us: A systematic review of dysarthria characteristics in Multiple Sclerosis. Autoimmunity reviews, 17(12), 12021209. doi: 10.1016/j.autrev.2018.06.010 CrossRefGoogle ScholarPubMed
Parmenter, B.A., Testa, S.M., Schretlen, D.J., Weinstock-Guttman, B., & Benedict, R.H. (2010). The utility of regression-based norms in interpreting the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS). Journal of the International Neuropsychological Society, 16(1), 616.CrossRefGoogle Scholar
Polman, C.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.P., Kappos, L., … & Sandberg-Wollheim, M. (2005). Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Annals of Neurology: Official Journal of the American Neurological Association and the Child Neurology Society, 58(6), 840846.CrossRefGoogle ScholarPubMed
Priva, U.C. (2017). Not so fast: Fast speech correlates with lower lexical and structural information. Cognition, 160, 2734.CrossRefGoogle Scholar
Rodgers, J.D., Tjaden, K., Feenaughty, L., Weinstock-Guttman, B., & Benedict, R.H. (2013). Influence of cognitive function on speech and articulation rate in multiple sclerosis. Journal of the International Neuropsychological Society, 19(02), 173180.CrossRefGoogle ScholarPubMed
Rosen, K.M., Goozée, J.V., & Murdoch, B.E. (2008). Examining the effects of multiple sclerosis on speech production: Does phonetic structure matter? Journal of Communication Disorders, 41(1), 4969.CrossRefGoogle ScholarPubMed
Sidtis, D. & Sidtis, J.J. (2017). Subcortical effects on voice and fluency in dysarthria: Observations from subthalamic nucleus stimulation. Journal of Alzheimer’s disease & Parkinsonism, 7(6).CrossRefGoogle ScholarPubMed
Simonyan, K., Ackermann, H., Chang, E.F., & Greenlee, J.D. (2016). New developments in understanding the complexity of human speech production. Journal of Neuroscience, 36(45), 1144011448.CrossRefGoogle ScholarPubMed
Smiljanić, R. & Bradlow, A.R. (2009). Speaking and hearing clearly: Talker and listener factors in speaking style changes. Language and linguistics compass, 3(1), 236264.CrossRefGoogle ScholarPubMed
Smith, A. (1982). Symbol Digit Modalities Test (SDMT) manual (revised). Los Angeles: Western Psychological Services.Google Scholar
Smith, M.M. & Arnett, P.A. (2005). Factors related to employment status changes in individuals with multiple sclerosis. Multiple Sclerosis Journal, 11(5), 602609.CrossRefGoogle ScholarPubMed
Smith, M. & Arnett, P.A. (2007). Dysarthria predicts poorer performance on cognitive tasks requiring a speeded oral response in an MS population. Journal of Clinical and Experimental Neuropsychology, 29(8), 804812.CrossRefGoogle Scholar
Smith, K.M. & Caplan, D.N. (2018). Communication impairment in Parkinson’s disease: Impact of motor and cognitive symptoms on speech and language. Brain and Language, 185, 3846.CrossRefGoogle ScholarPubMed
Sussman, J.E. & Tjaden, K. (2012). Perceptual measures of speech from individuals with Parkinson’s disease and multiple sclerosis: Intelligibility and beyond. Journal of Speech, Language, and Hearing Research, 55(4), 12081219.CrossRefGoogle ScholarPubMed
Svindt, V., Bóna, J., & Hoffmann, I. (2020). Changes in temporal features of speech in secondary progressive multiple sclerosis (SPMS)–case studies. Clinical Linguistics & Phonetics, 34(4), 339356.CrossRefGoogle ScholarPubMed
Tjaden, K., Sussman, J.E., & Wilding, G.E. (2014). Impact of clear, loud, and slow speech on scaled intelligibility and speech severity in Parkinson’s disease and multiple sclerosis. Journal of Speech, Language, and Hearing Research, 57(3), 779792.CrossRefGoogle ScholarPubMed
Tjaden, K. & Wilding, G.E. (2004). Rate and loudness manipulations in dysarthria: Acoustic and perceptual findings. Journal of Speech, Language and Hearing Research, 47(4), 766.CrossRefGoogle ScholarPubMed
Tjaden, K. & Wilding, G. (2011). Speech and pause characteristics associated with voluntary rate reduction in Parkinson’s disease and multiple sclerosis. Journal of Communication Disorders, 44(6), 655665.CrossRefGoogle ScholarPubMed
Tomczak, M. & Tomczak, E. (2014). The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends in sport sciences, 1(21), 1925.Google Scholar
Turner, G.S. & Weismer, G. (1993). Characteristics of speaking rate in the dysarthria associated with amyotrophic lateral sclerosis. Journal of Speech and Hearing Research, 36(6), 11341144.CrossRefGoogle ScholarPubMed
Yorkston, K.M., Klasner, E.R., Bowen, J., Ehde, D.M., Gibbons, L.E., Johnson, K., & Kraft, G. (2003). Characteristics of multiple sclerosis as a function of the severity of speech disorders. Journal of Medical Speech-Language Pathology, 11(2), 7384.Google Scholar
Yorkston, K.M., Beukelman, D.R., Strand, E.A., & Hakel, M. (2010). Management of Motor Speech Disorders in Children and Adults (3rd ed.). Austin, TX: PRO-ED.Google Scholar
Yunusova, Y., Graham, N.L., Shellikeri, S., Phuong, K., Kulkarni, M., Rochon, E., … & Green, J.R. (2016). Profiling speech and pausing in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). PloS One, 11(1).CrossRefGoogle Scholar