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Record W4385270983 · doi:10.1002/pits.23041

Challenges of inclusive schooling for children and adolescents with congenital heart disease: A phenomenological study

2023· article· en· W4385270983 on OpenAlexaff
Verónica Violant, Sarah Muñoz‐Violant, Olga Rodrigo Pedrosa

Bibliographic record

VenuePsychology in the Schools · 2023
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocializationPsychologyDevelopmental psychologyInterpretative phenomenological analysisEducational attainmentQualitative researchPedagogyMedical educationMedicineSociology

Abstract

fetched live from OpenAlex

Abstract Educational attainment is closely associated with health. The objective is to explore the extent to which children and adolescents with congenital heart disease (CHD) are afforded the same educational and socialization opportunities as their healthy peers. We used a qualitative phenomenological design with convenience sampling. Data gathered 27 semistructured interviews: children with CHD ( n = 9), parents ( n = 10), and professionals ( n = 8) in Catalonia, Spain. Interview transcripts were coded using the constant comparative method and analyzed using ATLAS.ti software. The analysis revealed three themes describing the experience of schooling for children with CHD: (1) Empowering and enabling a child with CHD to achieve academically and engage socially is a challenge for parents; (2) Teachers lack the resources and specific skills necessary to meet the diversity needs of children with CHD; (3) Parents and teachers have low expectations regarding the academic achievement of a child with CHD. Further application of the constant comparison method yielded a core theme: (4) Children with CHD experience exclusion from peer group social learning activities. Further efforts are needed for more effective collaboration and coordination between educational and health professionals to provide support for teachers and families and enable children to be better integrated within schools.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.365
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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