Exposure to Cues of Harsh or Safe Environmental Conditions Alters Food Preferences
Bibliographic record
Abstract
In humans, psychological stress is positively correlated with an increased desire for certain energy-dense food items, indicating that stress may trigger foraging behavior that adapts to perceived current and future resource availability. However, the extent to which such processes influence desire for different kinds of foods remains unclear. Here, we examine the effects of perceived environmental conditions on food preferences across the food spectrum of dairy, meats, vegetables, fruit, grains, and sweets. We first showed images of 30 different food items to participants and recorded their stated desire to eat each kind of food. We then repeated this procedure after exposing participants to cues of either a harsh or a safe environment. As predicted, we found cues of environmental harshness increased the desirability of energy-dense food items. However, there was also evidence for decreased desirability for energy-dense food items following exposure to cues of a relatively safe environment. Our findings indicate that simple manipulations of perceived environmental conditions may trigger changes in desire for different kinds of food. Our study has relevance for increasing efforts to understand eating behavior in order to promote uptake of healthier diets.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".