The Big Five Personality Traits and Dispositional Mindfulness as Predictors of Alexithymia in College Students.
Bibliographic record
Abstract
OBJECTIVE: The aim of this research was to measure the relationship between the Big Five personality traits, dispositional mindfulness and alexithymia, and to investigate personality traits and dispositional mindfulness as predictors of alexithymia in a group of college students. METHOD: In the present study, 150 college students at Tabriz University, aged between 18 and 26, were selected by convenient sampling method. NEO - Five Factor Inventory (NEO - FFI), Toronto Alexithymia Scale (TAS - 20), and Freiburg Mindfulness Inventory (FMI-SF) were used for data collection. RESULTS: The results showed that alexithymia was positively associated with neuroticism, and negatively associated with conscientiousness and openness to experiences. Neuroticism is the strongest predictor of alexithymia. After controlling for the effects of baseline characteristics and the Big Five personality traits, mindfulness did not remain a significant predictor of alexithymia. CONCLUSIONS: These results suggest that neuroticism, openness to experiences and conscientiousness have an essential role in alexithymia.
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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 | 0.000 |
| 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) | 0.001 | 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".