The Effects of Sex, Education and Marital Status on Alexithymia
Bibliographic record
Abstract
Background: Alexithymia is a sub-clinical condition characterized by an inability to identify and describe emotions, together with an externally oriented thinking style. The aim of this study was to investigate the effects of sex, education and marital status on alexithymia in African university students. \n \nMethods: A total of 368 Nigerian university students were involved in the study. Participants were 170 men and 198 women who were 17-27 years of age. Toronto Alexithymia Scale (TAS-20) was used to assess the points associated with alexithymia. Data were analyzed by applying student’s t-test (independent sample test) and one way ANOVA tests in SPSS for Windows (version 18) statistical program. \n \nResults: Alexithymia score was higher in female than in male subjects (t=2.83, p˂0.01). There was an inverse relationship between alexithymia scores and years of education (F=5.74, p˂0.001). Single subjects had the statistically higher alexithymia scores than the married subjects (t=2.18, p˂0.05). \n \nConclusions: According to these results, it can be stated that male gender, university education and marriage may be related to the lower alexithymia scores in university students. Also, these results suggested that university education individualize to students and improves their mental health by decreasing their alexithymia scores.
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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 | 0.000 | 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) | 0.005 | 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".