Caffeine Use and Attentional Engagement in Everyday Life
Bibliographic record
Abstract
Caffeine is a common component of various beverages and foods with approximately 80% of the world's population consuming caffeinated products daily. Here we examined how caffeine consumption and different motivations for consuming caffeine (e.g., cognitive enhancement, negative affect relief, reinforcing effects, and weight control) relate to self-reported inattention, mind-wandering, and deep, effortless concentration (i.e., flow) in everyday life in a university student population via two online surveys (N = 224 and N = 234). Our results indicated that, contrary to what one might expect, the amount of caffeine consumed in a typical day (estimated in milligrams) was not related to attention-related experiences in everyday life. However, we found that those who are more likely to ingest caffeine to potentially enhance their cognition, or to experience the reinforcing effects of caffeine, or to help relieve negative affect showed higher levels of inattention in everyday life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".