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Record W4412452984 · doi:10.1080/19325037.2025.2529786

Balancing Identity, Inclusion and Engagement: Lessons from the Fearless Physical Activity Program for Adults with Congenital Heart Disease

2025· article· en· W4412452984 on OpenAlexaff
Bradley MacCosham, François Gravelle

Bibliographic record

VenueAmerican Journal of Health Education · 2025
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInclusion (mineral)Identity (music)Heart diseasePsychologyDiseaseCoronary heart diseaseDevelopmental psychologyMedicineGerontologySocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

Background This study explores the experiences and perceptions of adults with congenital heart disease (ACHD) who participated in the Fearless Physical Activity program, a community-based initiative aimed at promoting physical activity in CHD patients.Methods Using a qualitative research design, 27 participants were recruited and participated in semi-structured interviews.Results Thematic analysis revealed key factors influencing participation, including identity, social inclusion and program design.Discussion The study concludes that future ACHD-specific programs must address the diverse needs of ACHD patients, offering adaptable activities, consistent scheduling and clearer communication.Translation to Health Education Practice This study informs several Areas of Responsibility for health education specialists. Area I (Assessment) is addressed by identifying identity-related barriers to participation. Area II (Planning) highlights the need to co-design inclusive programs with ACHD patients. Area IV (Evaluation and Research) is supported through the use of qualitative methods to assess program impact. Lastly, Areas VI (Advocacy) and VII (Communication) emphasize the importance of clear messaging and advocating for inclusive, sustainable program funding.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.429

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 studies0.0010.000
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 head0.020
GPT teacher head0.401
Teacher spread0.381 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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