Biochemical Changes in Adult Male Gamers During Prolonged Gaming: Pilot Study
Bibliographic record
Abstract
BACKGROUND: Gaming has become an integrated part of life for children and adults worldwide. Previous studies on the impact of gaming on biochemical parameters have primarily addressed the acute effects of gaming. The literature is limited, and the study designs are very diverse. The parameters that have been investigated most thoroughly are blood glucose and cortisol. OBJECTIVE: This exploratory study is the first to investigate the effects of long gaming sessions on the biochemical parameters of healthy male adults. The extensive testing allowed us to observe short-term changes (within 6 hours), long-term changes during the duration of the gaming sessions, and follow-up after 1 week to determine whether any changes were longer lasting. METHODS: In total, 9 experienced gamers completed 2 back-to-back 18-hour gaming sessions interspersed with a 6-hour rest period. All participants adhered to a structured sleep pattern due to daytime employment or attending university. Blood, saliva, and urine samples were collected from the participants every 6 hours. Linear mixed-effect models were used to analyze the repeated-measures data accumulated during the study. A total of 51 biochemical parameters were investigated. RESULTS: In total, 12 of the 51 biochemical parameters significantly changed during the study: alkaline phosphatase, aspartate aminotransferase, bilirubin, chloride, creatinine, glucose, hemoglobin, immature reticulocyte fraction, lactate, methemoglobin, sodium, and thrombocytes. All changes were within the normal range. The mean glucose level of the participants was 4.39 (SD 0.07) mmol/L at baseline, which increased significantly by 0.24 (SD 0.07) mmol/L per 6 hours during the first period and by 0.38 (SD 0.07) mmol/L per 6 hours in the second period (P<.001). The glucose levels during the second session increased even though the participants had little energy intake. Cortisol levels did not change significantly, although the cortisol pattern deviated from the typical circadian rhythm. During both gaming sessions, we observed increasing cortisol levels from 6 AM until noon. The participants were relatively dehydrated at the start of the study. The patients were asked to fast before the first blood sampling. Within the first 6 hours of the study, the participants rehydrated, followed by relative dehydration during the remainder of the study. This pattern was identified using the following parameters: albumin, creatinine, hemoglobin, erythrocytes, potassium, and platelets. CONCLUSIONS: This study is the first of its kind, and many of the analyses in the study yielded novel results. The study was designed to emulate the behavior of gamers during the weekend and other long gaming sessions. At this point, we are not able to determine the difference between the effects of gaming and behavior during gaming. Regardless, the results of this study suggest that healthy gamers can partake in long gaming sessions, with ample amounts of unhealthy foods and little rest, without acute impacts on health.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".