The role of alexithymia in attachment and binge eating
Bibliographic record
Abstract
Introduction: Binge eating is characterized by eating large quantities of food and experiencing lack of control in a discrete time period. Obesity is widespread and causes health and psychosocial problems and is costly to the health care system and society. A possible predisposing factor is early attachment style and its relationship to emotion regulation later in life. When a child is insecurely attached, they may be at risk for developing maladaptive coping strategies such as eating pathology. A possible mechanism related to emotion regulation is alexithymia, a personality trait which co-occurs with insecure attachment and binge eating. To develop a more effective treatment for binge eating in obese individuals, it is important to learn more about relevant psychological factors, thereby improving long-term treatment outcomes. Methods: This study utilized a cross-sectional cohort design. Data collected from 92 individuals who completed three self-report questionnaires—Toronto Alexithymia Scale-20 (TAS-20), Binge Eating Scale (BES), and Experiences in Close Relationships-Revised questionnaire (ECR-R)—which were analyzed using SPSS. Results: Results show a significant relationship between insecure attachment and binge eating, and this relationship is mediated by alexithymia in both anxious and avoidant attachment styles. Simple mediator model analyses display that the total indirect effect of the mediator was significant, indicating that alexithymia is a significant partial mediator in the relationship between attachment style and binge eating behaviours. Conclusions: This study extends the existing literature on possible predisposing factors and mechanisms in binge eating symptomatology among obese individuals and examined the possible role of alexithymia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".