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Record W4400366784 · doi:10.26650/curare.2024.1447500

Validity and Reliability of the Turkish Version of the NutriSTEP Questionnaire

2024· article· en· W4400366784 on OpenAlexaboutno aff
Merve Azak, Duygu Gözen

Bibliographic record

VenueCURARE Journal of Nursing · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishReliability (semiconductor)PsychologyValidityReliability engineeringApplied psychologyClinical psychologyPsychometricsEngineeringPhilosophyPhysicsLinguistics

Abstract

fetched live from OpenAlex

Objective: This study aims to evaluate the validity and reliability of the Nutrition Screening Tool for Every Preschooler (NutriSTEP) questionnaire in Turkish, a measurement tool originating from Canada that is designed to assess the nutrition risk of preschool children.Materials and Methods: An online cross-cultural validation study was conducted with 196 parents of children aged 3-5 years in Istanbul, Türkiye. The NutriSTEP questionnaire is comprised of 17 items covering four categories and underwent translation into Turkish and subsequent evaluation for language, content, and face validity. Data collection occurred online, with statistical analyses being performed to gauge the reliability and validity of the tool.Results: A total of 196 parents participated in the study who yielded a mean NutriSTEP score of 27.30 ± 6.64, indicating a notable prevalence of medium to high nutrition risk among preschoolers. The content validity index was assessed at 0.99, underscoring the robustness of the tool’s content validity. The item-scale correlation analysis revealed a significant and consistent correlation between each item and the total score, affirming the coherence of the items within the NutriSTEP scale. Further scrutiny through item analysis unveiled predominantly positive correlations between most items and the total score, further bolstering the tool’s efficacy at gauging nutrition risk. A criterion-related validity analysis highlighted significant associations between NutriSTEP scores and various factors, illuminating the tool’s predictive capacity concerning nutrition risk. Moreover, the test-retest analysis demonstrated a robust correlation between the initial and repeated administrations of NutriSTEP (p < 0.01), reaffirming its reliability over time.Conclusion: In conclusion, the Turkish adaptation of NutriSTEP demonstrates strong validity and reliability for assessing nutrition risk among preschool children, making it a suitable tool for use in Türkiye. Its user-friendly nature that allows parents to complete the assessment swiftly in approximately 10 minutes provides valuable insights into various aspects of children’s nutritional status.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.070
GPT teacher head0.425
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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