The role of colour and summary indicators in influencing front-of-pack food label effectiveness across seven countries
Bibliographic record
Abstract
OBJECTIVE: Many countries are considering the implementation of front-of-pack nutrition labels as a strategy to address high and increasing levels of overweight and obesity. A growing body of work demonstrates the superiority of labels that use colour and/or provide a summary indicator of product healthiness to enhance comprehension. However, previous studies have been confounded in determining the relative effectiveness of these two attributes by comparing labels that also differ in other ways. The present study tested labels that varied only on use of colour and/or reliance on a summary indicator across an international sample to provide unique insights into the relative importance of these attributes. DESIGN: Participants were randomised to see one of four variations of the Health Star Rating label that differed on the basis of use of colour and sole provision of a summary indicator. SETTING: Australia, Canada, China, India, New Zealand, the UK and the USA. PARTICIPANTS: Adults (n 7545) in seven countries were exposed to online choice tasks requiring them to select a preferred breakfast cereal and then nominate the healthiest cereal. RESULTS: Overall, the coloured versions, and particularly the one with just a summary indicator, outperformed the monochrome version that included nutrient-specific information. However, there were some differences by country, with results from Canada and China indicating superior outcomes for monochrome labels and those providing nutrient-specific information. CONCLUSIONS: The results highlight the importance of colour, but suggest that the introduction of front-of-pack nutrition labels should be preceded by country-specific formative testing to identify potential differences in outcomes.
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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 | 0.001 | 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".