Can a tDCS treatment enhance subjective and objective sleep among student-athletes?
Bibliographic record
Abstract
Introduction Previous studies have shown that student-athletes suffer from sleep difficulties. This study explored the impact of tDCS on sleep parameters among student-athletes.Method Thirty student-athletes (15 females, 15 males, age 21.1 ± 2.1 years) were recruited. All participants underwent a series of questions to rule out depressive and anxiety disorders or any specific tDCS exclusion criteria. All participants were advised to maintain their usual sleep schedule.Results Compared polysomnographic and Psychomotor Vigilance Task data analyses did not show any improvement after experimental tDCS. Regardless of groups, PVT mean reaction time was decreased. Regarding the questionnaires, data analyses showed improvement on the PSQI (p < .001), ISI (p < .001) and ASSQ (p < .007) scores after tDCS.Discussion tDCS appears to increase total sleep time and should be further explored. Improvements in subjective sleep suggest that tDCS bears interesting possibilities into the enhancement of sleep among student-athletes.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".