Developing and evaluating the validity and reliability of the Iranian preschool food frequency questionnaire (IP-FFQ)
Bibliographic record
Abstract
Introduction This study aimed to assess the relative validity and reliability of a semi-quantitative food-frequency questionnaire (FFQ) among preschool children in Iran. Methods A total of 161 children aged 4–6 years were enrolled in the validation phase, with a subsample of 120 subjects participating in the reliability study. A two-round Delphi study was conducted to assess content validity, and 24-hours dietary recall (24-HR) was used as reference for the criterion validity of the FFQ. Reliability was evaluated by intra-class correlation coefficients (ICCs) between results of two FFQs administered with eight weeks intervals. The Bland–Altman plot was used to examine the agreement between the FFQ-1 vs 24-HRs and FFQ-1 vs FFQ-2 for energy and nutrient intakes. Results The Delphi showed satisfactory levels of Content Validity Ratio (0.84) and Content Validity Index (0.88), respectively. The Pearson’s correlation coefficients between FFQ-1 and 24-HRs showed low to moderate agreement, ranging from 0.06 for vitamin B12 to 0.45 for vitamin D. As for reliability, ICCs showed excellent agreement (>0.75) for all nutrients between repeated FFQs. Findings of the Bland–Altman plots showed that most data points fell within the 95 % limits of agreement (LOA) for all nutrients. The results confirm that the IP-FFQ has acceptable validity and good reliability to assess preschool children’s food intake . Conclusion This questionnaire could be used in epidemiological studies and health sciences research, to implement evidence-based strategies and policies for optimal growth and heath amongst children.
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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 | 0.028 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".