Contributing Roles of Depression, Anxiety, and Impulsivity Dimensions in Eating Behaviors Styles in Obese Individuals Seeking Bariatric Surgery
Bibliographic record
Abstract
Abstract BackgroundEven if bariatric surgery appears as the most effective therapeutic approach, it is not equally successful across individuals suffering from obesity. Among the factors that influence postsurgical outcomes, eating behaviors are known to play a key role in relapses. The aim of our study was to assess eating behaviors styles and several modulating psychopathological factors in patients suffering from obesity.MethodsPatients seeking bariatric surgery (N = 127) completed a set of standardized tools assessing eating behaviors (DEBQ), psychiatric comorbid conditions (MINI), mood (BDI-13, STAI), and impulsivity (UPPS-P).ResultsWe found significant correlations between DEBQ Emotional Eating (EmoE) and depression, state and trait anxiety and all dimensions of impulsivity. Significant correlations also occurred between DEBQ External Eating (ExtE) and depression, state and trait anxiety and UPPS-P positive urgency, lack of perseverance and sensation seeking. Regression analyses showed female gender, trait anxiety, and lack of perseverance as explanatory factors in EmoE, and depression severity score and positive urgency in ExtE.ConclusionsEmoE might be a means of dealing with negative emotions and/or intrusive thoughts, while ExtE may result from a mechanism associated with depression. These results may help to improve patients’ outcome by defining specific therapeutic targets in psychological interventions.
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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 | 0.002 |
| 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) | 0.002 | 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".