Internet and Video Game Use in Relation to Overweight in Young Adults
Bibliographic record
Abstract
PURPOSE: To examine the relationship between interactive media use (Internet and video games) and overweight risk in young adults. DESIGN: Prospective cohort study. SETTING: France (TEMPO study). SUBJECTS: Community sample of 674 young adults aged 22 to 35 in 2009 (response rate to the original mail out: 44.3%). MEASURES: Data were collected through mail-based questionnaires from study participants in 1999 (juvenile overweight, juvenile TV use) and 2009 (overweight, Internet and video game use, regular physical activity), and from their parents who participated in the GAZEL study from 1989 to 2009 (parental overweight). ANALYSIS: Logistic regression. RESULTS: Participants who engaged in regular video game use (>1 time/wk) were more likely to be overweight than those who did not (odds ratio [OR] 2.20, 95% confidence interval [CI] 1.42-3.42). Adjusting for sex, regular athletic activity, juvenile overweight, juvenile TV use, and parental overweight, the OR associated with video game use decreased but remained statistically significant (OR 1.94, 95% CI 1.15-3.28). We found no significant association between Internet use and overweight. CONCLUSION: Video game use may be a relevant target for interventions aiming to decrease the burden of overweight and associated consequences in young adults.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".