Targeting premeal anxiety in eating disordered clients and normal controls: A preliminary investigation into the use of mindful eating vs. distraction during food exposure
Bibliographic record
Abstract
OBJECTIVE: Studies have demonstrated that negative affect increases prior to food intake in individuals diagnosed with an eating disorder. Mindfulness has been supported empirically to treat experiential avoidance stemming from anxiety. Thus, the current objective in this study is to empirically compare mindfulness vs. thought suppression invention during a food exposure in both clinical and nonclinical samples. METHOD: In a 2 (Group: clinical vs. nonclinical) × 2 (INTERVENTION: mindfulness vs. distraction) counterbalanced within treatment design, the current investigation sought to determine the differential effectiveness of a brief mindfulness intervention vs. a brief distraction intervention in women diagnosed with AN and BN in a clinical and nonclinical sample during a food exposure. RESULTS: Results indicated that the eating disorder group reported a significant increase in negative affect after the mindfulness intervention as compared to the distraction intervention, whereas the nonclinical group reported a significant decrease in negative affect after the mindfulness intervention as compared to the distraction intervention. DISCUSSION: Preliminary findings suggest that clinicians may want to proceed cautiously when using mindful eating in those with severe eating disorders during the early stages of food exposure. Limitations and future directions are discussed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".