The Impact on Parents of Diagnosing PCD in Young Children
Bibliographic record
Abstract
Primary ciliary dyskinesia (PCD) is an incurable, rare, inherited, chronic condition. Treatment includes the regular clearing of airway mucus, aggressive treatment of infections and management of hearing loss. Caregiver burden has not been explored, hence we interviewed 18 mothers and 6 fathers of children under 6 years to understand the impact of diagnostic testing and implications of a positive diagnosis. Interviews were transcribed and thematically analysed and five key themes were identified. These included the parents' experiences following child's diagnosis, impact of child's treatment regimen on parent, impact of child's health status on parent, parent's coping strategies, and parental concerns for the future. Parents described their diagnostic journey, with the findings revealing how a lack of awareness among clinicians of the PCD symptom pattern can lead to a delayed diagnosis. Parents discussed the emotional and practical impact of a PCD diagnosis and the coping strategies employed to deal with challenges arising following a diagnosis. Parents use a variety of different lifestyle changes to accommodate their child's treatment regimen and to cope with disruptive life events such as the COVID-19 pandemic. This study provides valuable insights into parental adjustment and adaptation to a PCD diagnosis and management regimen. Going forward, this research highlights the need for integrated social care for PCD patients and their families.
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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 | 0.023 |
| 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 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".