The effects of sign language on spoken language acquisition in children with hearing loss: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Permanent childhood hearing loss affects 1 to 3 per 1000 children and frequently disrupts typical spoken language acquisition. Early identification of hearing loss through universal newborn hearing screening and the use of new hearing technologies including cochlear implants make spoken language an option for most children. However, there is no consensus on what constitutes optimal interventions for children when spoken language is the desired outcome. Intervention and educational approaches ranging from oral language only to oral language combined with various forms of sign language have evolved. Parents are therefore faced with important decisions in the first months of their child's life. METHODS/DESIGN: This article presents the protocol for a systematic review of the effects of using sign language in combination with oral language intervention on spoken language acquisition. Studies addressing early intervention will be selected in which therapy involving oral language intervention and any form of sign language or sign support is used. Comparison groups will include children in early oral language intervention programs without sign support. The primary outcomes of interest to be examined include all measures of auditory, vocabulary, language, speech production, and speech intelligibility skills. We will include randomized controlled trials, controlled clinical trials, and other quasi-experimental designs that include comparator groups as well as prospective and retrospective cohort studies. Case-control, cross-sectional, case series, and case studies will be excluded. Several electronic databases will be searched (for example, MEDLINE, EMBASE, CINAHL, PsycINFO) as well as grey literature and key websites. We anticipate that a narrative synthesis of the evidence will be required. We will carry out meta-analysis for outcomes if clinical similarity, quantity and quality permit quantitative pooling of data. We will conduct subgroup analyses if possible according to severity/type of hearing disorder, age of identification, and type of hearing technology. DISCUSSION: This review will provide evidence on the effectiveness of using sign language in combination with oral language therapies for developing spoken language in children with hearing loss who are identified at a young age. The information from this review can provide guidance to parents and intervention specialists, inform policy decisions and provide directions for future research. PROSPERO REGISTRATION NUMBER: CRD42013005426.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".