Prevalence of Alexithymia and Its Association with Demographic Variables in Students
Bibliographic record
Abstract
Background: Emotional strengthening, facilitates being faced with life challenges and improves the level of peoples' mental health. In the present study, prevalence of alexithymia and its relationship with demographic variables has been investigated. Methods: A sample of 571 undergraduate students of Kharazmi university of Tehran (Karaj campus), 202 boys and 369 girls, aged 18-25 were chosen with Stratified sampling method and completed Toronto Alexithymia Scale-20 (TAS-20) and Edinburgh Handedness Inventory. Data were analyzed by descriptive indices, independent sample T-test and Pearson’s correlation. Results: The overall prevalence of alexithymia was 15.1% (17.3% boys, 13.8% girls). Result of independent sample T-test showed that alexithymia was associated with male gender, language (monolingual and bilingual) and handedness. As to the three factors of the TAS-20, boys scored higher in externally oriented thinking (EOT), but there was no gender difference in difficulty in identifying feelings (DIF) and difficulty in describing feelings (DDF). Conclusion: Based on this finding male gender, bilingualism and right handing has important indicator for became alexithymic in the individual.
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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 | 0.000 |
| 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".