The power of product: how food advertising affects children’s perceptions of child and non-child targeted food advertising?
Bibliographic record
Abstract
BACKGROUND: Food advertising shapes children’s preferences for unhealthy foods, contributing to poor diets and increased risk of obesity and non communicable diseases. This study explored children’s perceptions of child and non-child-targeted food advertising. METHODS: Open-ended online interviews with 17 participants, recruited through convenience sampling, were conducted where children were prompted with four advertisements (ads): a child-targeted and non-child-targeted ad for both healthy (plain milk) and unhealthy (chocolate) foods. A thematic analysis was conducted. RESULTS: Most children expressed positive perceptions of the ads, and the reasons children described liking the ads included: (i) people in the ad eating the product, (ii) positive emotional appeal, (iii) pre-existing affinity with the product, and (iv) visibility of the product. However, most children expressed “negative purchase intent” to all ads due to a pre-existing aversion to the product. Many children who expressed pre-existing affinity with the product still expressed negative purchase intent because they preferred other brands or flavours of the product. Most children considered the type of product over the marketing techniques when asked about perceived targeted audience. The main themes found were: (i) product for everyone, and (ii) product for people that like the product. CONCLUSIONS: Children’s perceptions, purchase intent and perceived targeted audience did not change between child-targeted and non-child-targeted ads. This study underscores the critical role of the product itself in influencing children’s responses to ads. It highlights the need for public policies and advertising regulations to focus on restricting promotions of unhealthy products rather than solely addressing marketing techniques or target audiences.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".