“We have dealt with so much. There’s more coming?”: Improving Knowledge About Brain Health in Adults Living With Congenital Heart Disease
Bibliographic record
Abstract
Background: Significant advances in managing congenital heart disease (CHD) have occurred over the past few decades, resulting in a fast-growing adult patient population with distinct needs requiring urgent attention. Research has recently highlighted the prevalence of neurocognitive differences among adults living with CHD. Yet, there is a lack of knowledge about the perspectives of people living with CHD and family members/caregivers on brain health. We sought to explore their perspectives to guide future research and clinical endeavours. Methods: Using the principles of integrated knowledge translation and qualitative interpretive description, we conducted 2 focus groups with 7 individuals with CHD and their family members as part of a virtual forum on brain health in CHD. Data analysis followed the principles of interpretive description. Results: A lack of understanding about overall brain health and neurocognitive differences in adult CHD was identified. To increase overall knowledge about brain health, initiatives should (1) focus on the individual living with CHD, involving family members and peers; (2) use social media and health care encounters for knowledge exchange; and (3) ensure a "balancing act" in the information provided to avoid feelings of worry and uncertainty about the future while simultaneously empowering people living with CHD. Conclusions: There is a pressing need for better education about brain health among individuals living with CHD. Our findings can guide clinicians in developing programmes of care and (re)design health services that address the brain-heart axis and neurocognitive differences in CHD.
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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 | 0.025 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".