Executive functioning in preschoolers with 22q11.2 deletion syndrome and the impact of congenital heart defects
Bibliographic record
Abstract
BACKGROUND: Executive functioning (EF) is an umbrella term for various cognitive functions that play a role in monitoring and planning to effectuate goal-directed behavior. The 22q11.2 deletion syndrome (22q11DS), the most common microdeletion syndrome, is associated with a multitude of both somatic and cognitive symptoms, including EF impairments in school-age and adolescence. However, results vary across different EF domains and studies with preschool children are scarce. As EF is critically associated with later psychopathology and adaptive functioning, our first aim was to study EF in preschool children with 22q11DS. Our second aim was to explore the effect of a congenital heart defects (CHD) on EF abilities, as CHD are common in 22q11DS and have been implicated in EF impairment in individuals with CHD without a syndromic origin. METHODS: All children with 22q11DS (n = 44) and typically developing (TD) children (n = 81) were 3.0 to 6.5 years old and participated in a larger prospective study. We administered tasks measuring visual selective attention, visual working memory, and a task gauging broad EF abilities. The presence of CHD was determined by a pediatric cardiologist based on medical records. RESULTS: Analyses showed that children with 22q11DS were outperformed by TD peers on the selective attention task and the working memory task. As many children were unable to complete the broad EF task, we did not run statistical analyses, but provide a qualitative description of the results. There were no differences in EF abilities between children with 22q11DS with and without CHDs. CONCLUSION: To our knowledge, this is the first study measuring EF in a relatively large sample of young children with 22q11DS. Our results show that EF impairments are already present in early childhood in children with 22q11DS. In line with previous studies with older children with 22q11DS, CHDs do not appear to have an effect on EF performance. These findings might have important implications for early intervention and support the improvement of prognostic accuracy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".