How Mediterranean Diet Adherence and Eating Disorders Shape Alexithymia Status?
Bibliographic record
Abstract
Understanding the relationship of alexithymia with eating disorders is significant because alexithymia is a risk factor for eating disorders. The importance of the Mediterranean diet has been rising because it provides a sustainable eating model. This study aims to examine alexithymia in the light of eating disorders and adherence to a Mediterranean diet. The study was carried out online in March-June 2022 via social networks. The population of the study consists of 501 adults (72,6% females) aged 18-65. The questionnaires administered to the participants included the REZZY Eating Disorder Scale, Eating Attitude Test (EAT-26), Mediterranean Diet Adherence Scale (MEDAS), and Toronto Alexithymia Scale (TAS-20). Participants at risk for an eating disorder were more likely to have scores in the borderline or clinically significant range with respect to alexithymia compared to participants who were not at risk for an eating disorder. The frequency of alexithymia increased as adherence to a Mediterranean diet decreased and MEDAS scores were higher among individuals who were not alexithymic. It is foreseen that adherence to Mediterranean diet can cause positive effects on psychiatric disorders, and people are suggested to adhere to the Mediterranean diet. Moreover, it is thought that alexithymia and eating disorders might be related to each other.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".