Effects of prolonged engagement in alternating video games and smartphone use on muscle endurance and physical activity intentions in young healthy adults
Bibliographic record
Abstract
Recent studies suggest a negative effect of acute and prolonged use of smartphones or video games on physical performance. This study examined the effect of alternating between video gaming and smartphone scrolling on subsequent muscle endurance performance and physical activity intention in young adults. Thirty-eight young adults (19 ± 1 y.o.; 13 female) participated in this within-subjects crossover pre–post-test comparison design study. Participants engaged either in 90 min alternating between video gaming and smartphone scrolling (VGSS condition) or watching documentaries (control condition). Perceived workload, mental fatigue, motivation and boredom in each condition were assessed. Cognitive performance and physical activity intention were measured pre–post VGSS and control condition through a working memory 2-Back task and the Borg 6–20 scale, respectively. Then, participants performed a knee extensors endurance task until exhaustion at 20% of their maximal voluntary peak force. Participants perceived the VGSS as more demanding than watching documentaries (p < .001, rank-biserial correlation = 0.640), but only a slight increase in mental fatigue (9/100) and no difference between conditions in cognitive performance (p = .107, η2p = 0.069) were observed. Regardless of the condition, motivation decreased, and boredom increased over time. Muscle endurance performance did not differ after VGSS or documentaries watching (p = .239, d = 0.116), and physical activity intention decreased (p < .001, η2p = 0.446) regardless of condition. Engaging in VGSS did not induce a specific state of mental fatigue, which may explain the absence of impaired muscle endurance performance. Both conditions negatively impacted physical activity intentions, suggesting that sitting in front of a screen impairs intentions to be active.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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; 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".