The Use of Compression Stockings to Reduce Water Retention in the Legs During Gaming and Esports: Randomized Controlled Field Study
Bibliographic record
Abstract
BACKGROUND: With the increasing digitalization of daily life, internet-based entertainment such as gaming and streaming has advanced to one of the megatrends of the 21st century. Besides offering a multitude of controversially discussed opportunities for entertainment and social interaction, there is reasonable concern about health issues caused by the absence of physical activity among activities linked to gaming and streaming. OBJECTIVE: The aim of this study is to compare the water balance of recreational gamers with and those without compression stockings during a gaming event. METHODS: We measured body composition and water balance with 8-electrode bioelectrical impedance analysis among 46 recreational gamers with an average age of 27.1 (SD 6.5) years (5/46, 11% women and 41/46, 89% men) before and after 24 hours at a gaming event. Of the 46 gamers, 23 (50%) gamers wore compression stockings for the duration of the study. RESULTS: Our study shows that prolonged gaming and associated behaviors during a 24-hour time frame lead to an increase in total body water (+0.76 L; P<.001) and a decrease of phase angle in the lower extremities (-0.47°; P<.001) but not in the upper extremities (+0.09°; P=.80), when no compression is used. Gamers using compression socks did not show any significant negative effects on their body composition. CONCLUSIONS: Prolonged gaming and streaming are serious risk factors for diseases associated with water retention in the legs, and these risks can be measured by bioelectrical impedance and reduced by wearing compression stockings. We conclude that these findings should be discussed and replicated in larger studies and that there is a considerably large market for compression stockings among gamers and live streamers.
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How this classification was reachedexpand
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 | 0.029 | 0.012 |
| 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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".