The Mediating Effect of Alexithymia on the Relationship Between Schizotypal Traits and Sleep Problems Among College Students
Bibliographic record
Abstract
A body of research has investigated the relationship between alexithymia and sleep problems, as well as the relationship between schizophrenia and alexithymia. However, there have been few studies on the relationships between the three. The current study aimed to explore the relationship between schizotypal traits and sleep problems among college students, and the potential role of alexithymia as a mediator of this relationship. The participants were all first-year students at a medical university in Guangdong province, China. A total of 2626 college students participated. They were asked to complete a questionnaire that incorporated the Schizotypal Personality Questionnaire (SPQ), the Toronto Alexithymia Scale (TAS-20), and the Insomnia Severity Index (ISI). The results revealed a relatively high percentage of students with mild insomnia (74.8%) and a smaller percentage with moderate to severe insomnia (7.9%). Correlation analysis revealed that both the TAS-20 and ISI scores had significant positive correlations with the SPQ score (p<0.01). There was also a significant positive correlation between the TAS-20 and ISI scores (p<0.01). The ISI score was significantly influenced by the SPQ score in a direct way, and increased considerably with increases in the TAS-20 score, indicating the importance of alexithymia as a mediator. The mediation model was tested via regression analysis and the bias-corrected bootstrap method, and the results further confirmed the role of alexithymia as a mediator.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".