The impact of post-prandial delay periods on ad libitum consumption of a laboratory breakfast meal
Bibliographic record
Abstract
This study examined the impact of varying the holding time following an ad libitum laboratory breakfast on acute dietary behaviour and subsequent intake. Twenty-four participants (20 females (age: 23.4 ± 6.3 years; body mass index: 23.9 ± 3.9 kg·m–2, mean ± SD)) completed 3 trials following a quasi-randomised, crossover design. Each trial (7-day separation) incorporated a defined post-prandial delay (DPD) period of either zero (no delay), 1 or 3 hours following a buffet breakfast consumed over 30 minutes. Dietary intake outcomes included energy, macronutrient and core food group intakes. On completion of the DPD period, participants left the laboratory and recorded all food/beverages consumed for the remainder of the day. One-way repeated-measures ANOVA assessed all outcomes, with post hoc analysis conducted on significant main effects. Energy and carbohydrate intakes were significantly lower on no delay vs. 1-hour (p = 0.014) and 3-hour (p = 0.06) DPD trials (energy intake: 1853 ± 814 kJ vs. 2250 ± 1345 kJ vs. 1948 ± 1289 kJ; carbohydrates: 68 ± 34 g vs. 77 ± 44 vs. 69 ± 43 g; respectively). DPD periods did not influence the time to consume next meal or energy, macronutrient and core food group intakes for the remainder of the day. Delaying participants from leaving a laboratory alters dietary intake at an ad libitum test meal. The post-meal holding period is an important methodological consideration when planning laboratory studies to assess appetite. Novelty: Delaying participants from leaving a laboratory alters dietary intake at ad libitum breakfast meals. The length of the delay period did not affect dietary intake at ad libitum breakfast meals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".