Examining maladaptive eating behaviors and psychological difficulties among women with compulsive eating and obesity: a latent profile analysis
Bibliographic record
Abstract
BACKGROUND: Maladaptive eating behaviors are central to weight gain and are influenced by various psychological determinants associated with obesity. While some studies have established profiles based on different maladaptive eating behaviors using medical samples of individuals with obesity, no studies have focused on all patients with overweight or obesity seeking psychological help for compulsive eating. The objective was to identify eating behaviors profiles using maladaptive eating behaviors (disinhibition, susceptibility to hunger, and restraint) among women patients with compulsive eating and overweight or obesity, and to compare those profiles with each other on socio-demographic, clinical, psychological, and eating-related variables. METHODS: ) completed online questionnaires and participated in an eating disorders diagnosis interview. Profiles were created using latent profile analysis and compared with a MANOVA with Tukey adjusted post-hoc comparisons and a chi-square analysis. RESULTS: Three profiles emerged from the latent profile analysis. The Highly disinhibited profile includes women with high scores for disinhibition and susceptibility to hunger and a low score of restraint. The Moderate sensitivity to eating cues profile includes women with moderate scores of disinhibition, susceptibility to hunger, and restraint. The Perceived control over food profile includes women with the highest restraint score and the lowest levels of disinhibition and susceptibility to hunger. Group comparisons showed significant differences between profiles. The Highly disinhibited profile included women with higher levels of depressive symptoms and impulsivity as well as lower scores of self-directedness and cooperation. This profile also showed the highest level of binge eating, food craving, and food addiction symptoms. The Moderate sensitivity to eating cues profile showed more body esteem and greater cooperation. The Perceived control over food profile had less impulsivity and depressive symptoms as well as a higher level of self-directedness. CONCLUSION: These results highlighted mechanisms that seem to prevail in different profiles of patients with compulsive eating which offer intervention targets that should be prioritized when offering psychotherapeutic treatment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".