Eight Weeks Of Passive Heating And Exercise, Alone Or In Combination, Does Not Improve Cognition
Bibliographic record
Abstract
PURPOSE: Exercise and heat stress have been reported to independently provide benefits to brain health. We tested the hypothesis that eight weeks of a combined intervention of passive heating and exercise improves cognitive performance compared to a control group. METHODS: Sixty young, healthy participants (n = 30 female, age: 23 [3] years, BMI: 24.0 [3.6] kg/m2) were randomized into one of four groups: control (CON), exercise (EX), passive heating (HEAT), or combined heat and exercise (HEATEX). Participants completed supervised sessions three times per week for eight weeks. Exercise sessions were completed at 70-75% of maximum heart rate on a cycle ergometer and passive heating sessions involved hot water immersion (42 °C) of the feet (both 45 min duration). The HEATEX group performed both the EX and HEAT components sequentially on the same days (90 min total duration). Cognitive performance was measured at baseline and at the end of the 8-week intervention using the digit symbol substitution task (DSST) and the Stroop test. The primary endpoints were the number of correct responses processed in 120 sec (DSST) and Stroop cost (incongruent stimuli reaction time minus congruent reaction time). The data were analyzed using linear mixed models with fixed effects of time (repeated) and condition, time by condition interaction, and participants as a random effect. As an exploratory analysis, biological sex was included as a covariate in the model to identify a possible influence of sex on the outcomes. RESULTS: There was a main effect of time (P < 0.001) where DSST performance improved by an average of 6% post-intervention; however, there was no main effect of group (P = 0.116) or time by group interaction (P = 0.068). There was no effect (time by condition interaction P = 0.205) of the interventions on Stroop cost (baseline: 90 [70] ms; post-intervention: 84 [70] ms), and biological sex was not a significant covariate in the models (P = 0.320 and P = 0.083 for DSST and Stroop, respectively). CONCLUSIONS: Eight weeks of EX, HEAT, or HEATEX had no effect on cognitive performance compared to CON, as assessed by the DSST and Stroop test. Therefore, eight weeks of exercise training and/or passive heating is not a sufficient stimulus to improve cognitive performance in young, moderately fit individuals. Supported by NSERC (#20011033, 202103522).
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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) | 0.001 | 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".