Adaptation and reliability of ‘Nutrition Screening Tool for Every Preschooler’ (<scp>NutriSTEP</scp>) for use as a parent administered questionnaire in New Zealand
Bibliographic record
Abstract
Aim To adapt the validated Canadian Nutrition Screening Tool for Every Pre‐schooler (NutriSTEP), for use in New Zealand and test its reliability to identify nutrition risk in pre‐school children aged 2–5 years, as a parent administered questionnaire. Methods Adaptations to the Canadian NutriSTEP were undertaken by three registered dietitians (expert review), followed by intercept interviews with pre‐schooler parents (n = 26). A second expert review was conducted to finalise the adaptions for online reliability testing. A further 79 pre‐schooler parents completed online administrations of the Canadian and adapted NutriSTEP tools, 4 weeks apart in a blinded manner. Intraclass correlation coefficients (ICCs) were used to verify test–retest reliability between the administrations. Individual questionnaire items were verified for reliability between administrations through Cohen's κ statistic (κ), Pearson's χ2 value and Fisher's exact test. Results Online administrations of the Canadian and adapted NutriSTEP tools were determined to be reliable (ICC = 0.91; P < 0.001). Between NutriSTEP administrations, 13 out of 17 questionnaire items had adequate (κ > 0.5) agreement, one item had excellent agreement (κ > 0.75) with a significant relationship (P < 0.05) between all items. Sensitivity for the adapted NutriSTEP was higher for pre‐schoolers at nutrition risk (31.6%) versus the Canadian version (20.3%). Risk items were highest for low intake of breads and cereals (58.2%), milk and milk products (51.9%), meat and meat alternatives (40.5%), child controlling the amount consumed (35.4%) and vegetable intake (34.2%). Conclusion The Canadian NutriSTEP and the adapted NutriSTEP were reliable between online administrations when completed by parents in the community. The adapted NutriSTEP identified an additional nine preschoolers at increased nutrition risk, demonstrating increased sensitivity in comparison to the Canadian NutriSTEP. Nutrition risk can be identified in early childhood to prevent the development of chronic disease. The adapted NutriSTEP should be considered for future use to identify preschoolers at increased nutrition risk and guide appropriate nutrition intervention.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".