Validation and Acceptability of the Mobile App Version of the Control of Allergic Rhinitis and Asthma Test for Children (CARATKids): Cross-Sectional Study
Bibliographic record
Abstract
Background: The electronic version of the Control of Allergic Rhinitis and Asthma Test for Children (CARATKids) has the potential to enhance pediatric telemonitoring but has not yet been validated. Objective: This study aimed to validate the electronic version of CARATKids against the paper-based version. Methods: A cross-sectional study was conducted between April and December 2024 in a tertiary hospital in northern Portugal. Children with asthma or allergic rhinitis and their caregivers were recruited during pulmonology outpatient appointments. CARATKids comprises 13 yes or no questions, 8 addressed to the child and 5 to the caregiver, and the total score ranges from 0 to 13. The electronic CARATKids was made available through a mobile app. Both paper and electronic versions were administered in a randomized order before and after the appointment. In addition, participants' preferences between the two administration versions were assessed. Internal consistency (Cronbach α), reliability (intraclass correlation coefficient [ICC], Bland-Altman analysis), and convergent validity (Spearman coefficient) were analyzed following COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines. Results: A total of 51 children (median 9, IQR 8-11 years; n=29, 57% male) and respective caregivers (median 41, IQR 7-45) years were included. The CARATKids total score was similar across the paper (median 5, IQR 3-8) and electronic (median 5, IQR 3-7) versions. The internal consistency was 0.79 for the paper version and 0.83 for the electronic version. The reliability between the two versions was excellent (ICC 0.95, 95% CI 0.91-0.97). The Bland-Altman analysis showed strong agreement between the two versions, with a mean difference of 0.04 (95% CI -1.99 to 2.07). The Spearman correlation between the two versions was 0.95 (P<.001). In total, 63% (n=32) of children and 61% (n=31) of caregivers were indifferent to the version used, while 33% (n=17) and 35% (n=18), respectively, preferred the electronic version. Conclusions: The electronic version of CARATKids appears to be equivalent to the paper-based version of the questionnaire, with good acceptance by children and caregivers. CARATKids implementation in mobile health technologies has the potential to enhance remote child monitoring and optimize the management of asthma and allergic rhinitis.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".