Prevalence of Eating Disorders and Alexithymia among a sample of Egyptian Medical Students Not Attending Psychiatric Clinics
Bibliographic record
Abstract
Abstract Background Eating disorders are prevalent psychiatric disorders and a major Public health burden worldwide, having huge impact on physical and mental health, The student population seems to be vulnerable to eating disorders, but is this in relation to their ability to express their emotions or alexithymia? Aim of the work To evaluate the relationship between alexithymia and eating disorders. Subjects and methods this is a cross sectional study done on a stratified random sample of 575 medical students in Ain- Shams University, started from 2018 till July 2019, those with history of chronic physical or mental illness were excluded, all students were subjected to Designed clinical sheet for demographic data, Arabic version of Eating Attitude Test -26 (EAT-26) as screening tool for eating disturbances in non-clinical populations and Arabic version of Toronto scale 20 to measure alexithymia. Results our study revealed disordered eating 12.3% among the study sample, alexithymia 24.4% and significant variation in scores of eating disorder according to alexithymia scores. Conclusion our study revealed positive correlation between eating disorders and alexithymia consistently with hypothesis of emotional regulation deficits in eating disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".