From Diagnoses to Ongoing Journey: Parent Experiences Following Congenital Heart Disease Diagnoses
Bibliographic record
Abstract
OBJECTIVE: Using qualitative and quantitative methods, the current cross-sectional study examined parents' experiences at the time of their child's diagnosis, what they thought helped their child recover, barriers to support, and identified needs for future models of care. METHOD: The sample included 26 parents (22 mothers, 3 fathers, and 1 mother/father pair) of children with CHD, ranging in age between 6 months and 4 years with a mean age of 2 years. RESULTS: Qualitative results were organized around five themes: (a) They (medical team) saved my child's life, (b) My child is going to be okay, (c) Not out of the woods, (d) Optimizing support for my child and myself, and (e) What still gets in the way. Parents uniformly expressed a need for greater mental health support for their children as well as programs to improve parents' skill and confidence, with no difference between age groups (< 2 years and > 2 years of age). Common barriers to service included distance and time off work. CONCLUSION: Parents' experiences informed both acute and long term implications following CHD diagnoses, and highlight current gaps in mental health care. Direction for clinical care and improved intervention opportunities are discussed.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".