The Effects of Circadian Rhythm in Adolescents on Optimal Performance in Cognitive Tasks
Bibliographic record
Abstract
Introduction: The circadian rhythm is a sleep-wake cycle determined by differences in serum melatonin and cortisol levels, and affects cognition and behaviour. Past research suggests that young adults tend to perform better on cognitive tasks during the afternoon and evening, which may be the optimal time of day in this population. This research protocol seeks to determine whether cognitive performance is affected at times assumed to be optimal for both populations (evening) compared with suboptimal times (morning). Methods: Individuals would be recruited and divided into two groups: adolescents 13–17 and younger adults aged ages 18–25, with all participants of the afternoon/evening chronotype. Saliva is collected directly preceding test-taking. Each group completes a standard computerized test of simple math, logical reasoning, and executive function at both their optimal time of day (TOD) (3:00 to 6:00 PM) and at their non-optimal time of day (8:00 to 11:00 AM). Neuroelectric activity is recorded using electroencephalography (EEG). Results: We hypothesize that adolescents and younger adults will be at their optimal performance level (measured by EEG and behavioural measures) between 3 to 6 P.M. rather than from 8 to 11 AM, due to their circadian rhythm. We expect TOD to influence reaction times and accuracy during task completion. A difference will be seen across many neural indices such as event-related potentials (ERPs) and alpha and theta power demonstrating optimal performance in the evening. Discussion: Higher cortisol levels and changes in amplitude and latency of P3, N2Pc, N450, and PD ERP indices and differences in alpha and theta frequencies may be associated with optimal cognitive performance. This is related to faster response time, focus, and overall higher accuracy. Based on the anticipated results, one could alter the timing of task completion to fit different age groups’ peak mental ability. Conclusion: Continuously working at non-optimal times could lead to chronic circadian rhythm disruption, which could result in the deterioration of physical and mental health. Aspects of everyday life, such as student test-taking times, can be improved to benefit both individuals and institutions by catering to an individual’s optimal TOD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".