Educational experience of children living with congenital heart disease: a systematic scoping review
Bibliographic record
Abstract
BACKGROUND: Educational experience of children with CHD is often adversely impacted by factors such as medical burden, social and school functioning challenges. It is, therefore, vitally important that adequate support is provided at an early stage in order to facilitate better educational outcomes for this cohort. The role of the teacher is pivotal in supporting the overall healthy development of a child with CHD. Thus, it is important to understand how we can also support teachers to provide optimal support to this cohort. This systematic scoping review aimed to offer a comprehensive understanding of existing research in this area and identify any knowledge gaps. METHODS: The methodological framework for scoping reviews developed by Arksey and O'Malley (2005) was employed. FINDINGS: Children with CHD face educational challenges in cognitive, psychomotor, behavioural, and affective domains and also with school attendance. The main challenges for teachers include a lack of information around CHD and how it affects the individual child. Building a strong relationship and having frequent communication between the teacher/ parent/ child were considered key in alleviating anxiety and promoting a supportive environment. CONCLUSIONS: Children with CHD often require additional support from educational professionals in the classroom. Teachers of children with CHD would benefit from condition-specific training, updated on a regular basis.
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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 | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".