Current methods for evaluating speech sound disorders in multilingual preschoolers: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The objective of this review is to examine the current available evidence regarding the assessment of speech sound disorders (SSD) in multilingual preschoolers. This review will be conducted through the lens of the International Classification of Functioning and Disability-Child and Youth (ICF) framework, WHO. The ICF has been adopted by speech-language associations globally, offering an appropriate structure to inform this review. Most children across the world speak more than one language daily. However, measures designed to assess SSDs primarily focus on monolingual populations, placing multilingual children at risk for the misdiagnosis of SSD. A deeper understanding of available assessment measures, as well as what aspects of the ICF they address, will support clinicians in assessing SSD in multilingual children and aid researchers in identifying areas for future research. This review will explore studies that involve multilingual preschoolers (up to age 5 years 11 months) with SSD. It will examine measures used to evaluate the current status and/or progress over time in multilingual children with and without SSDs. METHODS AND ANALYSIS: This scoping review protocol implements the updated Joanna Briggs Institute (JBI) Scoping Review Methodology. The search will be conducted using Ovid MEDLINE, CINAHL Plus, EMBASE and Web of Science. Grey literature will also be searched using Google Scholar and ProQuest Dissertations and Theses Global. Search, screening, data extraction and data analysis will be conducted by a team of three reviewers. Data will be analysed and mapped through the ICF framework. ETHICS AND DISSEMINATION: Ethical approval is not required for this scoping review. Available evidence will be mapped according to the language pairings and the ICF. This review aims to support clinical and research speech-language pathologists in identifying current evidence and gaps in the knowledge base. Planned dissemination activities include a peer-reviewed publication and conference presentations.
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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 | 0.150 | 0.140 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.027 | 0.020 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.055 | 0.014 |
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".