The effect of performing mental exertion during cycling endurance exercise on fatigue indices: sex dependent differences
Bibliographic record
Abstract
Introduction: Men and women have different performance abilities, where women have greater tolerance for fatigue in long-distance exercise. Part of this greater tolerance may be due, in part, differences in men's and women's mental fatigue capacity during exercise. Thus, the aim of this study was to examine the effect of cycling endurance exercise, along with mental fatigue, on the sex dependent differences in exercise tolerance. Methods: Twenty-five (15 women and 10 men) cyclists in a randomized, controlled, and crossover protocol performed three experimental sessions. In the first session, the cycling peak power output (PPO) was determined and 65% of PPO was used for intensity of the experimental sessions. In sessions 2 and 3, participants performed Cycling + Mental Exertion (ME) (cycling endurance exercise with a ME-stroop task) and Cycling + Movie (cycling endurance exercise while watching a movie). Serum cortisol concentration and a psychomotor vigilance task (PVT) were measured pre- and post-sessions. During the experimental sessions rate of perceived exertion (RPE) and heart rate (HR) were recorded every 10 min and participants completed the NASA-TLX questionnaire directly following the post- PVT. Results: Performing Cycling + ME was associated with a longer time to exhaustion (p < 0.05) and higher RPE following 40-70 min in women than men (p < 0.05). Cycling + ME increased HR following 40-70 min in women (p < 0.05). For both men and women cortisol concentration level was higher pre- to post-Cycling + ME with no difference between sexes. Women exhibited faster reaction times compared to men in both pre- and post-sessions. Discussion: Performing mental exertion with cycling endurance exercise impairs endurance performance. While our findings align with some previous research, we suggest that men may be more prone to mental fatigue; however, further research needed to confirm this.
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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 | 0.000 | 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".