Speech and language skills and cognitive functioning in children with Apert syndrome: A pilot study
Bibliographic record
Abstract
There are few studies that report findings on the speech and language characteristics of Apert syndrome and little is known about the cognitive profile of the syndrome. The current study addresses this gap and explores speech, language, resonance/voice, attention oro-motor and cognitive skills in a group of 10 children (4;1-5;11) with Apert syndrome. The speech and language battery included: the CELF-Pre-school, the PLS-3, the Vocal Profile Analysis, GOS.SP.ASS, PACS; and the Brodsky Drooling Scale. Subscales of the BAS II-Early Years Version were used to assess cognition. Data were also collected on other factors that could influence developmental outcome such as audiological history and management; occlusion/dentition; respiratory problems and management; neuroanatomical abnormalities; the number and nature of cranial surgeries; and the occurrence of raised intracranial pressure. All children for whom a Performance IQ was obtained (n = 8) had abilities within the average range and IQ scores were considerably higher than those reported in previous studies. Eight children had moderate or severe language difficulties and expressive language difficulties were the most frequent. These language difficulties were not associated with a general cognitive deficit. All the children had problems with attention, speech and oro-motor skills. Nine had abnormal voice. In addition, a range of other associated factors that could affect functioning were identified. The discrepancies between the current study and previous investigations are outlined. Parameters for assessment are considered. The implications of these findings for valid assessments of children with Apert syndrome are discussed. Multidisciplinary assessment of children with Apert syndrome across a broad range of dimensions is recommended to obtain a profile of each child's strengths and weaknesses to ensure that appropriate educational placements and early interventions are implemented. Considering patterns of development over time at key ages is also argued to be of central importance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".