The effect of stress on delay discounting in bulimia nervosa and alcohol use disorder: a functional magnetic resonance imaging study.
Bibliographic record
Abstract
Background:Stress could induce neurobiological changes in patients with bulimia nervosa (BN) and alcohol use disorder (AUD) that increase delay discounting (DD), making the short-term benefits of coping through eating or drinking outweigh long-term negative consequences. Therefore, this study explores differences in DD between patients (BN or AUD) and healthy controls (HC), the impact of stress on food and alcohol DD, and the associated changes in brain activity.Methods:A total of 102 female participants (AUD: 27, BN: 25, HC: 50; age range: 18-38 years) underwent repeated fMRI scanning while performing three DD tasks (DDT). Initially, all participants performed a monetary DDT. Then, participants performed a food or alcohol DDT before and after stress induction with the Montreal Imaging Stress Task (MIST). Specifically, patients with BN completed a food DDT,patients with AUD completed an alcohol DDT and HC were randomly allocated to either DDT.Results:No differences were found in the DD of money, food or alcohol between patients and controls before stress. However, stress increased the DD of alcohol in patients with AUD, but not in HC. Stress also increased the DD of food in HC, but not in patients with BN. Furthermore, stress caused patients with AUD to display a lower activity of the right supplementary motor area while discounting alcohol. Stress also caused HC to display a lower activity of the middle/super frontalcortex and a higher activity of the motor cortex while discounting food, but caused patients with BN to display a higher activity of the occipital cortex.Conclusion:The results suggest that stress induces neurobiological changes in patients with AUD which cause them to prefer more immediately available alcohol. However, the results observed in patients with BN suggest a more complex relation between stress and food.
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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 | 0.000 |
| 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) | 0.001 | 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".