How Exergaming with Virtual Reality Enhances Specific Cognitive and Visuo‐Motor Abilities: An Explorative Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Virtual reality (VR) is the computer simulation of a three-dimensional environment that a person can interact with using special electronic equipment, such as a headset with an integrated display. Often coupled with VR, exergames are video games that involve physical exercise. Little is known regarding the chronic effects of exergaming through VR chon cognitive functions. Eleven young participants were enrolled in this crossover exploratory study. They had to follow two trainings of 5 consecutive days, 15 min per day, interspaced by a 1-month washout period. Trainings were performed in a random order: (1) a video training using shadow boxing fitness videos (SBV) and (2) a VR training using a three-dimensional game where the aim is to cut moving cubes with a sword in each hand. Before and after each training period, a battery of cognitive tests was performed to assess executive functions, such as attention (change blindness), reaction time, response inhibition (go/no-go, Stroop task), or flexibility (trail making test). Fine motor skills were also evaluated through a Fitt's task. No effect of the SBV training was observed on any of the cognitive functions tested. On the contrary, a significant increased performance in selective attention and observation tests was found after VR training, as well as in inhibitory processes (Stroop and go/no-go). Other performances were unaffected by either VR or SBV training. The present study argues that VR exergaming is a promising tool to promote cognitive enhancement but targets specific functions according to the type of interface/game that is used.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it