Using different approaches to assess the reproducibility of a culturally sensitive quantified food frequency questionnaire
Bibliographic record
Abstract
Objective: To report on the use of different approaches to assess the reproducibility of a culturally sensitive quantified food frequency questionnaire (QFFQ) used for assessment of the habitual dietary intake of Setswana-speaking adults in the North West Province of South Africa.Method: A previously developed and validated QFFQ was completed by trained fieldworkers. Portion sizes were estimated using different methods. Food intake was coded and analysed for nutrient intake per day for each subject. The first interview (n = 1 888) took place during the baseline data collection period. For the second interview (n = 175), a convenient sample from the subjects who had completed the first interview was collected and the interview was conducted within four to six weeks of the first interview.Results: There were good correlations between the first and second QFFQ for all the nutrients (p < 0.0001). The Wilcoxon signed-rank test showed that there were no significant differences in the median intake between the two administrations, except for energy and total fat. The Bland-Altman plots showed good agreement. Between 41% and 58% of the subjects were correctly classified into the same quartile, with less than 3% grossly misclassified. The weighted κ statistics showed moderate agreement between the two applications.Conclusion: Our results show that more than one statistical approach is needed to assess the reproducibility of a QFFQ. The reproducibility of this culturally sensitive QFFQ was good.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".