Slow walking leads to slower reaction time in young adults
Bibliographic record
Abstract
It has been established that walking is an attentionally demanding task. However, few studies have examined attentional demands of walking at various speeds and their findings need to be reinforced. Therefore, the aim of the present study was to compare reaction time (RT) at various walking speeds. Fifteen healthy young adults (2 males and 13 females; 20.5 ± 2.59 years) were asked to walk along a 10 meter path at three different walking speeds: preferred, 30% faster and 30% slower. Participants verbally responded to random auditory stimuli as fast as possible while maintaining the requested walking speed. Results demonstrated a significant main effect of Walking Speed on RT (p<0.001). Walking slowly exhibited significantly longer RTs (0.471 ms) than preferred (0.436 ms) and fast (0.401 ms) walking speeds. No difference was found between preferred and fast speeds. Results suggest the longer RTs observed in slow walking could be due to increases in task difficulty, energy requirements and equilibrium demands observed when walking slowly. Since walking fast occurs more frequently than walking slow in daily situations, faster RT in the fast speed condition can be attributed to the fact that it is a more practiced task. The lack of differences in RT between preferred and fast speeds may stem from the similar equilibrium demands. Furthermore, the increase in attentional demand in the non-preferred fast pace may have counterbalanced the heightened arousal levels during fast walking, which could explain the similarity in RT between preferred and fast conditions.
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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 | 0.002 |
| 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) | 0.004 | 0.001 |
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".