Does Installing “Healthy Eating Information” in a University Dining Hall Change Students’ Food and Beverage Choices?
Bibliographic record
Abstract
The objective was to determine if the installation of “healthy eating information” in a University dining hall would influence students’ food and beverage choices. This was a pre‐post, population nutrition intervention conducted in a buffet‐style cafeteria between September 2014 and April 2015. The intervention encouraged students to “fill half their plate with fruits and vegetables” and illustrated the number of minutes of jogging it takes to burn the calories in each beverage option. The beverage choices, as well as visits to the vegetable and fruit bar, were recorded on twelve menu‐matched occasions before and after the intervention. Inventory data was collected to determine the total liters of each beverage taken and the number of fruit cases ordered. There was a significant decrease in the proportion of students selecting a sugar‐sweetened beverage before (49% of the population) versus after (41%) the intervention (p=0.004). There was also a significant increase in the proportion of students drinking water before (43%) versus after (54%) the intervention (p<0.001). There were no significant changes in the proportion of students selecting each individual type of beverage and there was no change in the volume (ml) of each beverage taken. There was a significant increase in the number of students taking fruit before (30% of the population) versus after (36%) the intervention (p<0.001). And the number of students visiting the vegetable bar significantly increased from 60% to 72% (p<0.001). Similar trends were seen in the inventory data. These results illustrate that providing healthy eating information in settings where food choices are made, such as cafeterias, could encourage healthier choices. Support or Funding Information Vanier Canada Graduate Scholarship (MS), McHenry Unrestricted Research Grant (ML)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".