<i>Impact of Nutrition Education</i> On University Students’ Fat Consumption
Bibliographic record
Abstract
PURPOSE: University science students who have taken a nutrition course possess greater knowledge of fats than do those who have not; whether students apply this knowledge to their diet is unknown. We measured and compared science students' total and saturated fat intake in the first and fourth years, and evaluated whether taking a nutrition course influenced fat consumption. METHODS: A sample of 269 first- and fourth-year science students at a small undergraduate university completed a survey with both demographic questions and a semi-quantitative food frequency questionnaire about fats in the diet. Data were analyzed using chi-square tests and independent-sample t-tests. RESULTS: Fourth-year science students consumed fewer grams of total and saturated fat than did first-year science students (p<0.001). Science students who had taken a nutrition course consumed fewer grams of total and saturated fat than did those who had not (p<0.001). CONCLUSIONS: Taking a nutrition course may decrease first-year students' fat consumption, which may improve diet quality and decrease the risk of chronic disease related to fat consumption.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".