The Effects of Physical and Mental Fatigue on Time Perception
Bibliographic record
Abstract
Abstract The subjective perception of time holds a foundational significance within the realm of human psychology and our conceptualizations of reality and how we elucidate the chronological progression of events within our lives. While there have been some studies examining the effects of exercise on time perception during the exercise period, there are no studies investigating the effects of fatiguing exercise on time perception after the exercise intervention. This study aimed to investigate the effects of physical and mental fatigue on time estimates over 30-seconds (5-, 10-, 20-, and 30-seconds) immediately after exercise and 6-minutes after the post-test. Seventeen healthy and recreationally active volunteers (14 males, 3 females) were subjected to three conditions: physical fatigue, mental fatigue, and control. All participants completed a familiarization and three 30-minute experimental conditions (control, physical fatigue (cycling at 65% peak power output), and mental fatigue (Stroop task for 1100 trials) on separate days. Heart rate and body temperature were recorded at the pre-test, start, 5-, 10-, 20-, 30-seconds of the interventions, post-test, and 6-min follow-up. Rating of perceived exertion (RPE) was recorded four times during the intervention. Time perception was measured prospectively (at 5-, 10-, 20-, and 30-seconds) at the pre-test, post-test, and 6-minute follow-up. Physical fatigue significantly (p=0.001) underestimated time compared to mental fatigue and control conditions at the post-test and follow-up, with no significant differences between mental fatigue and control conditions. Heart rate, body temperature, and RPE were significantly (all p=0.001) higher with physical fatigue compared to mental fatigue and control conditions during the intervention and at the post-test. This study demonstrated that cycling-induced fatigue led to time underestimation compared to mental fatigue and control conditions. It is crucial to consider that physical fatigue has the potential to lengthen an individual’s perception of time estimates in sports or work environments.
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 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 | 0.001 | 0.004 |
| 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) | 0.002 | 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".