Study of Acute Effect of Caffeine on Cognition among Adults - A Cross Sectional Study from Puducherry, India
Bibliographic record
Abstract
BACKGROUND Information processing has substantial role in performing intellectual activities such as thinking, reasoning, remembering, imagining, or learning. Caffeine being a central nervous system (CNS) stimulant, improves mental performance, especially on alertness, attention, concentration and learning depending on the quantity of intake. In the present study, an attempt was made to study the effect of caffeine on cognitive processing in healthy individuals. METHODS This cross-sectional study was conducted on 50 subjects at Mahatma Gandhi Medical College & Research Institute. Montreal cognitive assessment (MoCA) questionnaire was utilized to assess the level of cognition of each subject. Visual reaction time (VRT), auditory reaction time (ART) and critical fusion frequency (CFF) prior and after consumption of 75 mg of caffeine in 200 ml of milk, pre and post reaction time measurement were taken from the subject to address the difference in reaction time. RESULTS Both visual and auditory reaction time were significantly reduced (P < 0.001) after intake of caffeine. The ability of the subject to appreciate the flickering light stimuli to be steady (critical flicker fusion frequency) had significantly improved to 15 % after caffeine intake. CONCLUSIONS Decrease in visual and auditory reaction and increase in critical flicker fusion frequency values indicate that caffeine increases alertness thereby it may enhance performance efficiency in reasoning, planning, judgment, organizing, concept formation, and problem solving. KEY WORDS Visual Reaction Time, Auditory Reaction Time, MoCA
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".