liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Perceptual Detection of Subtle Dysphonic Traits in Individuals with Cervical Spinal Cord Injury Using an Audience Response Systems Approach
Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Karolinska Institute, Sweden; Karolinska University Hospital, Sweden.
Karolinska Institute, Sweden.
Karolinska Institute, Sweden; Aix Marseille University, France.
Karolinska Institute, Sweden; Karolinska University Hospital, Sweden.
2017 (English)In: Journal of Voice, ISSN 0892-1997, E-ISSN 1873-4588, Vol. 31, no 1, UNSP 126.e7Article in journal (Refereed) Published
Abstract [en]

Objectives. Reduced respiratory function following lower cervical spinal cord injuries (CSCIs) may indirectly result in vocal dysfunction. Although self-reports indicate voice change and limitations following CSCI, earlier efforts using global perceptual ratings to distinguish speakers with CSCI from noninjured speakers have not been very successful. We investigate the use of an audience response system-based approach to distinguish speakers with CSCI from noninjured speakers, and explore whether specific vocal traits can be identified as characteristic for speakers with CSCI. Methods. Fourteen speech-language pathologists participated in a web-based perceptual task, where their overt reactions to vocal dysfunction were registered during the continuous playback of recordings of 36 speakers (18 with CSCI, and 18 matched controls). Dysphonic events were identified through manual perceptual analysis, to allow the exploration of connections between dysphonic events and listener reactions. Results. More dysphonic events, and more listener reactions, were registered for speakers with CSCI than for noninjured speakers. Strain (particularly in phrase-final position) and creak (particularly in nonphrase-final position) distinguish speakers with CSCI from noninjured speakers. Conclusions. For the identification of intermittent and subtle signs of vocal dysfunction, an approach where the temporal distribution of symptoms is registered offers a viable means to distinguish speakers affected by voice dysfunction from non-affected speakers. In speakers with CSCI, clinicians should listen for presence of final strain and nonfinal creak, and pay attention to self-reported voice function and voice problems, to identify individuals in need for clinical assessment and intervention.

Place, publisher, year, edition, pages
MOSBY-ELSEVIER , 2017. Vol. 31, no 1, UNSP 126.e7
Keyword [en]
cervical spinal cord injury; dysphonia; perceptual assessment; respiration; Voice Handicap Index (VHI)
National Category
Other Medical Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:liu:diva-134776DOI: 10.1016/j.jvoice.2015.12.015ISI: 000392619900064PubMedID: 26850470OAI: oai:DiVA.org:liu-134776DiVA: diva2:1077017
Available from: 2017-02-24 Created: 2017-02-24 Last updated: 2017-02-24

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Johansson, Kerstin
By organisation
Division of Neuro and Inflammation ScienceFaculty of Medicine and Health Sciences
In the same journal
Journal of Voice
Other Medical Sciences not elsewhere specified

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 7 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf