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Record W2118135421 · doi:10.1177/1049732310384119

The Perceptions of Caregivers Toward Physical Activity and Health in Youth with Congenital Heart Disease

2010· article· en· W2118135421 on OpenAlexaffabout
Fiona J. Moola, Caroline Fusco, Joel A. Kirsh

Bibliographic record

VenueQualitative Health Research · 2010
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsConstruct (python library)Physical activityPerspective (graphical)PerceptionPsychologyDiseaseGerontologyHeart diseaseDevelopmental psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Medical advances have reduced mortality in youth with congenital heart disease (CHD). Although physical activity is associated with enhanced quality of life, most patients are inactive. By addressing medical and psychological barriers, previous literature has reproduced discourses of individualism which position cardiac youth as personally responsible for physical inactivity. Few sociological investigations have sought to address the influence of social barriers to physical activity, and the insights of caregivers are absent from the literature. In this study, caregiver perceptions toward physical activity for youth with CHD were investigated at a Canadian hospital. Media representations, school liability, and parental overprotection construct cardiac youth as "at risk" during physical activity, and position their health precariously. Indeed, from the perspective of hospital staff, the findings indicate the centrality of sociological factors to the physical activity experiences of youth with CHD, and the importance of attending to the contextual barriers that constrain their health and physical activity.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.257
GPT teacher head0.546
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations61
Published2010
Admission routes2
Has abstractyes

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