Reliability and Validity of Simple Stroke Food Frequency Questionnaire (SS-FFQ) for Nutrition Monitoring in Patients with Acute Ischemic Stroke
Bibliographic record
Abstract
Abstract Objectives Standard dietary questionnaires may have some limitations in cases with stroke, particularly in those suffering from language and communication difficulties. The present study aimed to develop a dietary questionnaire appropriate for patients with acute ischemic stroke (AIS). Materials and Methods Major food groups ( n = 19) were first identified using the dietary questionnaire of the INTERHEART study. Using the Food Frequency Questionnaire (FFQ), an expert dietitian and a vascular neurologist then selected a total number of 68 corresponding food items from 168 available FFQ items. In the next phase, a panel of expert dietitians ( n = 10) assessed the face validity and the content validity of these 68 items and approved a total number of 62 items for the final questionnaire, namely, the Simple Stroke FFQ (SS-FFQ). Employing test-retest method, the intraclass correlation (ICC) of the SS-FFQ was subsequently calculated in 30 randomly selected cases affected with AIS. Ultimately, principal component analysis (PCA) was utilized for 153 cases with AIS to assess the construct validity of the questionnaire concerned. The SPSS Statistics software (version 18: SPSS Inc., Chicago, Illinois, United States) as well as descriptive tests including mean and percentage were additionally used to account for the baseline characteristics of the study participants. Results The results revealed that the reliability of the newly developed form of the SS-FFQ was perfect (ICC = 0.86). Dietary conditions were further assessed administering the SS-FFQ on 153 cases of AIS with the mean age of 63.76 ± 15.93 years. The PCA results also showed that 15 extracted items of the given questionnaire could explain 73.10% of total item variance. Conclusions It was concluded that the SS-FFQ was a valid and reliable questionnaire to assess nutrient intakes among patients with AIS.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".