Cognitive and Motor Skill Performance Are Improved By Active Cooling Following Passive Hyperthermia
Bibliographic record
Abstract
Hyperthermia causes a number of deleterious effects including decreased exercise performance and mental acuity. Neck cooling and hand and forearm cooling are both effective in attenuating heat strain during exercise in hot environments. However, only limited research exists on the effectiveness of either cooling methods on cognitive and motor skill performance following whole-body hyperthermia. PURPOSE: To investigate the effect of two active cooling modalities on cognitive and motor skill performance following passive hyperthermia. METHODS: Eleven healthy participants (6 females and 5 males; 22±5 y; 173±10 cm; 71.8±15.1 kg) were passively heated to 39°C rectal temperature (Tre) by 40°C whole-body immersion. They were then removed from the water and sat quietly in a room (24.6±0.8°C and 49.8±6.3% rh) and used either a 2.6 m2 commercially available cooling towel wrapped against the surface of their neck (NT), hand and forearm immersion in 10.5±1.3°C water (H), or cooled passively (C) until Tre reached 38°C. Simple reaction time, Stroop word color, time to complete a trail-making task (TMT), and time to screw three nuts on three bolts (N&B) were measured pre and post whole-body immersion and every 15 min during the cooling phase. One and two-way repeated measures ANOVA were used to determine differences across time and between conditions. RESULTS: Reaction time was faster (p<0.05) with H (349±41 ms) compared to both NT (364±60 ms) and C (380±65 ms). Success in the Stroop word color test was improved (p<0.05) when using NT (31±3) but not H (31±4) compared to C (29±4). Neither hand and forearm cooling nor neck cooling improved TMT ability. Time to complete the N&B task trended towards an improvement (p=0.06) with H (39.4±11.4 s) but not NT (43.1±12.0 s) compared to C (45.5±12.4 s). CONCLUSION: Reaction time and color-word interference ability were found to improve with hand and forearm cooling and neck cooling, respectively.
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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) | 0.001 | 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".