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Factors Associated with Development of Speech Perception Skills in Children Implanted by Age Five

2003· article· en· W1971788022 on OpenAlexaboutno aff
Ann E. Geers, Christine Brenner, Lisa S. Davidson

Bibliographic record

VenueEar and Hearing · 2003
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsCochlear implantSpeech perceptionAudiologyActive listeningPsychologyPerceptionLoudnessHearing aidMedicineCommunication

Abstract

fetched live from OpenAlex

In Brief Objective This study investigated factors contributing to speech perception outcomes in children with prelingual deafness after 4 to 7 yr of multichannel cochlear implant use. The analysis controlled for the effects of child, family and implant characteristics so that educational factors most conducive to maximum implant benefit could be identified. Design One hundred eighty-one 8- and 9-yr-old children from across the US and Canada who received a cochlear implant by age 5 were administered a battery of speech perception tests. Type and amount of educational intervention since implantation constituted the independent variables. Characteristics of the child, the family, and the implant itself constituted intervening variables. A series of multiple regression analyses determined the amount of variance in speech perception ability accounted for by the intervening variables and the amount of additional variance attributable to independent variables. Results The children achieved an average level of about 50% open-set speech perception through listening alone and almost 80% through lipreading and listening together, but with scores for individual children ranging from 0 to 100% correct. Over half of the variance in speech perception scores was predicted by characteristics of the child, family, implant and educational program. Significant predictors of good speech perception included greater nonverbal intelligence, smaller family size, longer use of the updated SPEAK/CIS processing strategy, a fully active electrode array, greater electrical dynamic range between threshold and maximum comfort level, and greater growth of loudness with increasing stimulus intensity. After the variance due to these variables was controlled, the primary rehabilitative factor associated with good speech perception skill development was educational emphasis on oral-aural communication. Conclusions Children with profound hearing loss achieved unprecedented levels of speech perception skill 4 to 7 yr after cochlear implantation. Use of an updated speech processor, such as SPEAK, contributed significantly to improved speech perception skills, even in children who were initially fitted with an earlier strategy, such as M-PEAK. In addition, the audiologist who programs the cochlear implant makes an important contribution to the child’s successful outcome with the device. A well-fitted map, as evidenced by a wide dynamic range and optimal growth of loudness characteristics, contributed substantially to the child’s ability to hear speech. Finally, the classroom communication mode used in the child’s school affects speech perception outcome. Children whose educational program emphasized dependence on speech and audition for communication were better able to use the information provided by the implant to understand speech. A variety of speech perception skills were assessed in this study of prelingually deaf 8 to 9 year olds after 4 to 7 years of using a cochlear implant: perception of specific features of vowels, consonants and suprasegmentals, perception of words in a closed set of choices, perception of words and sentences in an open set format, and the amount of enhancement provided to lipreading when audition is added. A wide range of speech perception ability was observed, with better skills seen in children with a wellprogrammed, up-to-date speech processor. Children who had used the SPEAK (as opposed to the MSP) processor the longest and had a greater number of active electrodes in their map with a wide dynamic range and those who could reliably order increases in loudness with increased stimulus intensity achieved the highest speech perception scores. After controlling for these implant characteristics, as well as other contributing factors, most of the remaining variance in speech perception outcome was due to oral classroom communication mode, with the best perceivers having received more auditory and speech emphasis in their educational program since receiving a cochlear implant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.264
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations538
Published2003
Admission routes1
Has abstractyes

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