Effects of snack portion size on anticipated and experienced hunger, eating enjoyment, and perceived healthiness among children
Bibliographic record
Abstract
BACKGROUND: Large portion sizes encourage overconsumption. Prior studies suggest that this may be due to errors in anticipating the effects of portion size, although the studies were limited to adults and energy-dense foods. OBJECTIVE: Our aim was to investigate potential anticipation errors related to the effects of portion size on hunger, eating enjoyment, and healthiness ratings among 8-to-11-year-old children, for snacks differing in energy density and healthiness perception, and as a function of initial hunger. METHODS: In a within-subject design, 83 children aged 8 to 11 years old were first asked to anticipate how much they would enjoy, how hungry they would feel after eating, and how healthy it would be to eat a recommended serving size, a 50% larger portion, and a 125% larger portion of brownie or applesauce. Over six subsequent sessions, the children were asked to eat all of each of these portions and then rate their post-intake enjoyment, residual hunger, and healthiness perceptions. We also measured hunger at the beginning of each session. RESULTS: For both snacks, larger portions reduced anticipated and experienced residual hunger similarly. In contrast, larger portions increased anticipated but not experienced eating enjoyment for both snacks; although larger portions increased anticipated and experienced enjoyment ratings among extremely hungry children. All children under-anticipated how much they would enjoy the smaller portion sizes. Healthiness ratings were unaffected by portion size for both snacks but differed across foods (applesauce vs. brownie). CONCLUSIONS: Children anticipate the effects of portion size on hunger change accurately, overestimate the effects of portion size on eating enjoyment, and rate food healthiness on food type and not portion size. Helping children better anticipate the enjoyment from smaller (recommended) portion sizes and understand that food quantity, not just quality, matters for healthy eating may be a solution to improve portion control.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".