“I really like playing games together”: Understanding what influences children with congenital heart disease to participate in physical activity
Bibliographic record
Abstract
BACKGROUND: Participation in physical activity is essential to the long-term health and development of all children. However, children living with cardiac conditions are typically not active enough to sustain positive health outcomes. Understanding the experiences of children living with congenital heart disease in community-based settings could help inform the physical activity counselling practices of clinicians. The current study explored the perceptions of 7- to 10-year-old children with moderate or complex congenital heart disease as they participated in a 10-week multisport programme. METHODS: Detailed field notes recorded the discussions and behaviours of 11 participants (45% female participants) each week during the programme sessions. Among those, four participants (50% female participants) were purposively selected to participate in preprogramme and postprogramme focus groups to gather more detailed accounts of their experiences. RESULTS: Four main themes surrounding physical activity were identified: (a) motivation, (b) self-efficacy, (c) peer influences, and (d) family influences. Although feelings of excitement and enjoyment towards physical activity were prevalent throughout the data ("I'm really excited … because I really like those sports"), participants also often felt frustrated, nervous, and fatigued ("I'm not very good at the skills"). Social inclusion with peers and family influences were meaningful reasons to engage in physical activity ("I really like playing games together"). Following the completion of the programme, participants emphasized their enjoyment of physical activity as a primary source of motivation, demonstrating an important shift from recognizing positive health outcomes ( "… it's good for you") towards more intrinsic sources of motivation ("… because it's fun"). CONCLUSION: Opportunities for physical activity that enhance positive experiences and build intrinsic motivation should be identified and promoted to children with congenital heart disease. Community-based programmes may also be an appropriate context for children with cardiac conditions to engage and maintain participation in physical activity through adolescence.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".