Proof of Concept for a Mindfulness-Informed Intervention for Eating Disorder Symptoms, Self-Efficacy, and Emotion Regulation among Bariatric Surgery Candidates
Bibliographic record
Abstract
Up to 64% of patients seeking bariatric (weight-loss) surgery report eating disorder (ED) symptoms (addictive-like eating, binge eating, emotional eating, grazing) that can interfere with post-surgical weight loss. This prospective proof-of-concept study aimed to evaluate the impact of a pre-surgical mindfulness-informed intervention (MII) on ED symptoms and potential mechanisms-of-action to inform optimization of the intervention. Surgery-seeking adults attended four, 2-hour, MII sessions held weekly. Participants completed validated questionnaires assessing ED symptoms, eating self-efficacy, emotion regulation, and mindful eating pre-MII, post-MII, and at a 12-week follow-up. The MII consisted of mindfulness training, with cognitive, behavioral, and psychoeducational components. Fifty-six patients (M = 47.41 years old, 89.3% female) participated. Improvements in addictive-like eating, binge eating, emotional eating, and grazing were observed from pre- to post-MII. ED symptom treatment gains were either maintained or improved further at 12-week follow-up. Eating self-efficacy and emotion regulation improved from pre-MII to follow-up. Scores on the mindful eating questionnaire deteriorated from pre-MII to follow-up. In mediation analyses, there was a combined indirect effect of emotion regulation, eating self-efficacy, and mindful eating on grazing and binge eating, and an indirect effect of emotion regulation on emotional eating and addictive-like eating. Participation in the MII was associated with improvements in ED symptoms and some mechanisms-of-action, establishing proof-of-concept for the intervention. Future work to establish the MII’s efficacy in a randomized controlled trial is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".