Comparison of outcomes in children with hearing aids and cochlear implants
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to document the performance of a group of children with moderately severe to severe hearing loss who use hearing aids on a range of speech recognition, speech-language, and literacy measures and to compare these results to children with severe to profound hearing loss, who have learned language through cochlear implants. METHODS: This study involved 41 children with bilateral sensorineural hearing impairment, aged 6-18 years. Twenty children had moderately severe/severe hearing loss and used hearing aids, and 21 had severe to profound hearing loss and used cochlear implants. Communication and academic skills were assessed using speech recognition tests and standardized measures of speech production, language, phonology, and literacy. RESULTS: The two groups did not differ in their open-set speech recognition abilities or speech production skills. However, children with hearing aids obtained higher scores than their peers with cochlear implants in the domains of receptive vocabulary, language, phonological memory, and reading comprehension. The findings also indicate that children with moderately severe or severe hearing loss can develop spoken language skills that are within the range expected for normal hearing children. CONCLUSIONS: School-aged children with moderately severe and severe hearing loss performed better in several domains than their peers with profound hearing loss who received cochlear implants between age 2 and 5 years. Further research is required to evaluate the benefits of hearing aids and cochlear implants in children with hearing loss who are diagnosed and receive intervention within the first year of life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".