Emotional Reactivity and Appraisal of Food in Relation to Eating Disorder Cognitions and Behaviours: Evidence to Support the Motivational Conflict Hypothesis
Bibliographic record
Abstract
Eating disorders are associated with both negative and positive emotional reactions towards food. Individual eating disorder symptoms may relate to distinct emotional responses to food, which could necessitate tailored treatments based on symptom presentation. We examined associations between eating disorder symptoms and psychophysiological responses to food versus neutral images in 87 college students [mean (SD) age = 19.70 (2.09); mean (SD) body mass index = 23.25(2.77)]. Reflexive and facial electromyography measures tapping negative emotional reactivity (startle blink reflex) and appraisal (corrugator muscle response) as well as positive emotional reactivity (postauricular reflex) and appraisal (zygomaticus muscle response) were collected. Eating disorder cognitions correlated with more corrugator activity to food versus neutral images, indicating negative appraisals of food. Binge eating was associated with increased postauricular reflex reactivity to food versus neutral images, suggesting enhanced appetitive motivation to food. The combination of cognitive eating disorder symptoms and binge eating may result in motivational conflict towards food. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".