The relationship between daily caffeine consumption and withdrawal symptoms: a questionnaire-based study
Bibliographic record
Abstract
To estimate daily caffeine intake among a group of university students at the Kocaeli Vocational School of Health Services in Turkey, and to determine the relationship between daily caffeine consumption and withdrawal symptoms. Materials and methods: This survey study was conducted using a questionnaire that was administered to 156 university students (129 females, 27 males) at the Kocaeli Vocational School of Health Services in Kocaeli, Turkey. The quantity of caffeine-containing products consumed was recorded on a daily basis, depending on the dietary habits of the consumer. The t test for differences between 2 proportions (using the normal approximation) was used for comparison of the frequency of complaints that began within 12-24 h of the cessation of caffeine consumption in relation to the quantities of daily caffeine consumption at P < 0.05. Results: Daily caffeine intake was estimated to range from 0 to 500 mg day_{-1} A significant increase in headache, fatigue, irritability, and sleepiness/drowsiness (P < 0.05) was reported by student's whose daily caffeine consumption was > 200 mg than by those whose daily caffeine consumption was < 200 mg. Conclusion: The data obtained show that Turkish university students consume similar amounts of caffeine as American, Canadian, Swedish, and British university students. The survey results show that there was a relationship between daily caffeine consumption and withdrawal symptoms (headache, fatigue, irritability, and sleepiness/drowsiness).
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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 | 0.000 | 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".