Caffeine Use and Alexithymia in University Students
Bibliographic record
Abstract
Abstract Alexithymia refers to difficulties with identifying, describing, and regulating one's own emotions. This trait dimension has been linked to risky or harmful use of alcohol and illicit drugs; however, the most widely used psychoactive drug in the world, caffeine, has not been examined previously in relation to alexithymia. The present study assessed 106 male and female university students aged 18-30 years on their caffeine use in relation to several traits, including alexithymia. The 18 participants defined as alexithymic based on their Toronto Alexithymia Scale (TAS-20) scores reported consuming nearly twice as much caffeine per day as did non-alexithymic or borderline alexithymic participants. They also scored significantly higher than controls on indices of frontal lobe dysfunction as well as anxiety symptoms and sensitivity to punishment. In a hierarchical linear regression model, sensitivity to punishment negatively predicted daily caffeine intake, suggesting caffeine avoidance by trait-anxious individuals. Surprisingly, however, TAS-20 alexithymia scores positively predicted caffeine consumption. Possible reasons for the positive relationship between caffeine use and alexithymia are discussed, concluding that this outcome is tentatively consistent with the hypo-arousal model of 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 | 0.001 |
| 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 | 0.000 |
| 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".