Development and validation of the Pediatric Asthma kNowleDge and mAnagement (P.A.N.D.A) questionnaires
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to assess the validity, feasibility and reliability of the Pediatric Asthma kNowleDge and mAnagement (PANDA) questionnaires that we developed. METHODS: We developed 3 questionnaires aimed for Children, Teenagers and Parents of children living with asthma. Experts in childhood asthma reviewed the questionnaires to evaluate face and content validity with a measure of the Scale-Content Validity Index (S-CVI). Children age 7 and up and their parents participated in the feasibility and reliability assessment. Reliability was assessed by doing a test re-test, using the Intraclass Correlation Coefficient (ICC), for each questionnaire topic. RESULTS: Face validity was validated for the three PANDA questionnaires with a satisfactory length and comprehension level. Content validity, with a total S-CVI of 0.91, was found for the Children and Parents questionnaires. With 84 participants, the ICC were found to be higher than 0.7 with a 95%CI [0.5-0.9] for the total scores and higher than 0.5 for each topic for each questionnaire, indicating reliability. CONCLUSION: Face and content validity and reliability of the PANDA questionnaires was established, with an appropriate comprehension level and length. Other types of validation like construct validity and responsiveness would need to be assessed to complete the validation of the questionnaires. The PANDA questionnaires could be used for research and in everyday practice.
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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 | 0.034 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".