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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorZanten, G.A. van
dc.contributor.advisorQuene, H.
dc.contributor.authorSmilde, J.J.M.
dc.date.accessioned2011-08-18T17:01:37Z
dc.date.available2011-08-18
dc.date.available2011-08-18T17:01:37Z
dc.date.issued2011
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/8230
dc.description.abstractObjective: To evaluate the long-term development of patients with a cochlear implant of the University Medical Centre in Utrecht; with regard to three potential predictive factors: severity of preoperative hearing loss, duration of preoperative deafness and cause of deafness (the ‘bony disorders’ meningitis and otosclerosis vs. all other causes of deafness). Study design: Retrospective longitudinal clinical study. Predictors of speech perception, after cochlear implantation surgery, included preoperative hearing loss, duration of deafness and effect of a bony disorder as cause of deafness (meningitis or otosclerosis); with use of Multi-Level Modeling analysis. Patients: 247 adult patients with a cochlear implant. Interventions: Unilateral multichannel cochlear implantation. Main outcome measures: Postoperative speech perception (CVC) scores. Results and conclusion: Perception of CVC words after cochlear implantation is significantly predicted by duration of deafness, preoperative hearing loss and presence or absence of a bony disorder as cause of deafness. There is no effect of interaction of these prediction variables, nor among themselves nor with the time predictors (=duration of implant use). The development of speech perception over time is best described by a linear and a negative quadratic growth model. As Multi-Level Modeling has been demonstrated in previous studies to be more powerful in hypothesis testing than other analysis tools, our unexpected result of cause of deafness being a significant predictor of speech perception might be due to the sensitivity of the Multi-Level Modeling method.
dc.description.sponsorshipUtrecht University
dc.format.extent529465 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleA Multi-Level Modeling Approach of Speech Perception after Cochlear Implantation
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordscochlear implantation
dc.subject.keywordsspeech perception, multi-level modeling
dc.subject.courseuuLogopediewetenschap


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