Prevalence of Eating Disorders: Its Relationship with Alexithymia and Mental Complaints
Bibliographic record
Abstract
The aim of this study is to investigate the prevalence of eating disorders (ED) among university students who are considered to be at high risk in terms of ED, where productivity in life is more important, and also to examine alexithymia and other mental symptoms that ED may be associated with.This is a descriptive relational study.Four hundred twenty one university students with appropriate participation conditions were included in the research.Sociodemographic information form, Eating Attitude Test (EAT-40), Toronto Alexithymia Scale (TAS-20) and Symptom Check List (SCL-90-R) scales were applied to the participants.The data were evaluated with the SPSS 25.0 statistics program.Participants with an average age of 19,82 ± 10,11; 58,2% were women, 97% were single, 71,7% were living with their families.Eating disorder prevalence was 20,9% and it was found that eating attitude disorder was more common among women.Among individuals with eating disorders, alexithymia total score and two alexithymia subscale scores, difficulty recognizing emotions and expressive thought, were significantly higher.At the same time, the anxiety, hostile attitude and psychoticism score indexes of the individuals with ED were found to be significantly higher.It is very important in terms of social functionality to recognize ED, whose incidence is gradually increasing, and to direct patients to effective treatment.Alexithymic complaints can cause ED or increase the severity of the existing disorder.Comorbidity of mental complaints with ED is common.A detailed evaluation of the factors that cause ED and affect symptom severity will increase treatment success.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".