<i>Zinc-specific Food Frequency Questionnaire</i>To Assess College Women’s Eating Habits
Bibliographic record
Abstract
Zinc deficiency has been reported in individuals with eating disorders, the risks of which increase during the adolescent and early adult years. A food frequency questionnaire (FFQ) specific for zinc-rich foods was tested for its usefulness in identifying problematic eating behaviour tendencies in college-age women. Ninety-two female students enrolled in a university introductory psychology course volunteered to complete demographic information, the Eating Attitudes Test (EAT-26), and a zinc-specific FFQ (ZnFFQ). Relationships among estimated zinc intakes, food/lifestyle habits, and eating attitude variables were examined. Twenty-five women had estimated intakes below the Recommended Dietary Allowance (RDA) for zinc. Individuals in the highest zinc intake group (over twice the RDA) had a tendency to score higher on the EAT-26 and the bulimia subscale. Vegetarians also scored high on the EAT-26. Although our data are limited, the ZnFFQ should be studied further to determine whether it could play a useful role in identifying individuals at risk for bulimia. The ZnFFQ is a simple, non-confrontational assessment tool and may be a helpful starting point for identifying women with unhealthy eating habits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".