Impact of nutritional labelling on 10-d energy intake, appetite perceptions and attitudes towards food
Bibliographic record
Abstract
The purpose of this study was to investigate the impact of nutritional labelling on energy intake, appetite perceptions and attitudes towards food. During a 10-d period, seventy normal-weight (BMI<25 kg/m2) and seventy-one obese women (BMI≥30 kg/m2) were given three meals per d under ad libitum conditions. Participants were randomly assigned to one of three experimental labelling groups in which the only difference was the label posted on lunch meal entrée: (1) low-fat label, (2) energy label (energy content of the entrée and average daily needs) and (3) no label (control). Average energy intake was calculated by weighing all foods before v. after daily consumption. Hunger and fullness perceptions were rated on visual analogue scales immediately before and after each meal. Satiety efficiency was assessed through the calculation of the satiety quotient (SQ). The appreciation and perceived healthiness of the lunch entrées were rated on eight-point Likert scales. There was no difference in energy intake, SQ and attitudes towards food between the three labelling groups. Fasting hunger perception was higher in the low-fat label group compared with the two others groups (P=0·0037). No interactions between labelling groups and BMI categories were observed. In conclusion, although labelling does not seem to influence energy intake, a low-fat label may increase women's fasting hunger perceptions compared with an energy label or no label.
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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 | 0.000 |
| 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 | 0.000 |
| 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".