Implementing the Nutrition Screening Tool For Every Preschooler (NutriSTEP<sup>®</sup>): In Community Health Centres
Bibliographic record
Abstract
PURPOSE: Identifying nutrition-related problems during the early years may provide an opportunity to enhance parents' abilities to support healthy growth and development. The Nutrition Screening Tool for Every Preschooler (NutriSTEP®) is a validated, parent-administered questionnaire designed to identify preschool children at nutritional risk. Parents can complete NutriSTEP® in under five minutes. Parents' and staff's views of NutriSTEP® implementation feasibility were assessed in two community health centres. METHODS: Parents attending preschool immunization clinics were recruited. Parents, staff, and physicians were asked for their opinions on screening. RESULTS: The 412 (34%) parent questionnaires completed indicated that parents found NutriSTEP® easy to complete and helpful for identifying areas of nutrition concern. Staff estimated screening distribution took one to three minutes. Clerks and nurses expressed concern about additional workload and demands on parents. Managers believed NutriSTEP® was easy to implement. Physicians considered nutrition screening of preschoolers important, and felt that health centres were the best location for screening. CONCLUSIONS: NutriSTEP® was relatively easy to implement in two community health clinics. While staff expressed concern about increased workload, parents found it easy to complete and helpful.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".