Development, reliability, and validity testing of Toddler NutriSTEP: a nutrition risk screening questionnaire for children 18–35 months of age
Bibliographic record
Abstract
Nutrition is vital for optimal growth and development of young children. Nutrition risk screening can facilitate early intervention when followed by nutritional assessment and treatment. NutriSTEP (Nutrition Screening Tool for Every Preschooler) is a valid and reliable nutrition risk screening questionnaire for preschoolers (aged 3-5 years). A need was identified for a similar questionnaire for toddlers (aged 18-35 months). The purpose was to develop a reliable and valid Toddler NutriSTEP. Toddler NutriSTEP was developed in 4 phases. Content and face validity were determined with a literature review, parent focus groups (n = 6; 48 participants), and experts (n = 13) (phase A). A draft questionnaire was refined with key intercept interviews of 107 parents/caregivers (phase B). Test-retest reliability (phase C), based on intra-class correlations (ICC), Kappa (κ) statistics, and Wilcoxon tests was assessed with 133 parents/caregivers. Criterion validity (phase D) was assessed using Receiver Operating Characteristic (ROC) curves by comparing scores on the Toddler NutriSTEP to a comprehensive nutritional assessment of 200 toddlers with a registered dietitian (RD). The Toddler NutriSTEP was reliable between 2 administrations (ICC = 0.951, F = 20.53, p < 0.001); most questions had moderate (κ ≥ 0.6) or excellent (κ ≥ 0.8) agreement. Scores on the RD nutrition risk rating and the Toddler NutriSTEP were correlated (r = 0.67, p < 0.000). The area under the ROC curve for moderate and high RD risk ratings were 84.6% and 82.7%, respectively. Cut-points of ≥21 (sensitivity 86%; specificity 61%) (moderate risk) and ≥26 (sensitivity 95%; specificity 63%) (high risk) were determined. The Toddler NutriSTEP questionnaire is both reliable and valid for screening for nutritional risk in toddlers.
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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 | 0.018 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".