Protocol for a Systematic Review and Meta-Analysis: The Magnitude of Cognitive, Linguistic, and Academic Impairments in Autistic Adolescents
Bibliographic record
Abstract
Adolescence is a critical developmental period for individuals with Autism Spectrum Disorder (ASD), marked by increasing social and academic demands. While numerous studies have examined specific skills, the literature remains fragmented, and no comprehensive quantitative synthesis has established the precise magnitude of the cognitive, linguistic, and academic challenges faced by this population. A systematic review and meta-analysis is necessary to synthesize the existing evidence, resolve inconsistencies, and provide a robust, statistically-powered estimate of these deficits to inform evidence-based practice. Objectives: The primary objectives of this review are: To quantitatively determine the magnitude of deficits in cognitive, linguistic, and academic domains in adolescents with ASD compared to their typically developing peers. To investigate the statistical interrelationships between core cognitive skills (executive functions, working memory), pragmatic language, and academic achievement. To conduct subgroup analyses to examine how the profile of academic deficits differs for adolescents with ASD with and without comorbid intellectual disability. Methods: This review will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. A comprehensive search will be performed across six electronic databases (MEDLINE/PubMed, Embase, Cochrane, Scopus, Web of Science, LILACS). Two independent reviewers will conduct study selection and data extraction. The risk of bias in included studies will be assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis will be performed to calculate pooled Standardized Mean Differences (SMD) and assess heterogeneity using the I² statistic.
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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 | 0.115 | 0.181 |
| Meta-epidemiology (narrow) | 0.011 | 0.009 |
| Meta-epidemiology (broad) | 0.036 | 0.037 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.102 | 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".