Validation of a Revised Knowledge Assessment Tool for Children with Inflammatory Bowel Disease (IBD-KID2)
Bibliographic record
Abstract
Introduction: For children with inflammatory bowel disease (IBD), acquired knowledge of their condition and treatment is integral to their adherence and self-management. Assessing their knowledge is vital to identify deficits that may affect disease management. IBD-KID2 is a knowledge assessment tool written for children aged 8 years and over with IBD. Objectives: In order to examine validity and reliability, a study was carried out using IBD-KID2 in a paediatric IBD population and a number of comparator groups with established levels of IBD knowledge. Methods: IBD-KID2 was administered to 4 participant groups in Christchurch Hospital, New Zealand: children with IBD (n = 22), children without IBD (n = 20), medical staff (n = 15), and administration staff (n = 15). Between-group differences were tested using ANOVA and pairwise comparisons made with the IBD group. Repeat assessments by the IBD group determined test-retest reliability (n = 21). Results: The mean age (range) of the paediatric groups were: IBD 13.3 years (8–18), without IBD 11.9 years (8–15). Group mean scores (SD) were: IBD 8.5 (±2.3), without IBD 3.7 (±2.2), medical staff 13.5 (±1.3), administration staff 6.3 (±2.5). Group means were all significantly different to the IBD group. Test-retest mean at baseline (8.4, CI ±2.4) and repeat (9.0, CI ±2.4) were not significant. Intraclass correlationcoefficient was 0.82. Internal reliability was 0.85, and item-total statistics showed no improvement by specific item removal. Conclusions: IBD-KID2 could distinguish between groups with different knowledge levels. Repeat assessment shows comparable scores on retest and good reproducibility. IBD-KID2 is a valid and reliable tool for use in the paediatric IBD population.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.002 |
| 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".