A Parent Reported Quality of Life Measure for Young Children with Primary Ciliary Dyskinesia: QOL-PCDPR
Bibliographic record
Abstract
Background: Monitoring disease progression and evaluating new treatments in PCD is hampered by the lack of sensitive physiological measures, particularly for preschool children. Patient-reported outcome measures including quality of life (QoL) questionnaires are recognised as valid and informative indices of symptoms and functioning. We aim to develop a questionnaire assessing QoL in preschool children (parent-proxy) and parental burden associated with having a child with PCD: QOL-PCDPR. Methods: Following FDA and EMA guidelines, twenty-four semi-structured interviews were conducted with parents (mothers: 73%) of 20 children (males n=14; mean age 3 years) from Europe and North America. This was followed by transcription and content-analysis. Items were rated for relevance and importance by patients and PCD specialists. Qualitative and quantitative data were used to develop QOL-PCDPR that was refined after cognitive testing. Results: Saturation grids generated from analysis of the qualitative data (Nvivo) confirmed comprehensive coverage of content. The data were used to generate items covering a range of domains. Domains affecting both child and parent included emotional functioning, social functioning and treatment burden. Domains unique to the child included respiratory and ear symptoms, while for parents’ role/career functioning, coping, vitality and health concerns were impacted. Conclusions: QOL-PCDPR was developed using rigorous, protocol-driven methods, has demonstrated face validity and cross-cultural equivalence for implementation in English-speaking populations. Psychometric testing is underway to determine the measure’s properties for evaluating clinical interventions.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".