Impact of frequency of internet use on development of brain structures and verbal intelligence: Longitudinal analyses
Bibliographic record
Abstract
Excessive internet use is shown to be cross sectionally associated with lower cognitive functioning and reduced volume of several brain areas. However, the effects of daily internet use on the development of verbal intelligence and brain structures have not been investigated. Here, we cross sectionally examined the effects of the frequency of internet use on regional gray/white matter volume (rGMV/rWMV) and verbal intelligence as well as their longitudinal changes after 3.0 ± 0.3 (standard deviation) years in a large sample of children recruited from the general population (mean age, 11.2 ± 3.1 years; range, 5.7-18.4 years). Although there were no significant associations in cross sectional analyses, a higher frequency of internet use was found to be associated with decrease of verbal intelligence and smaller increase in rGMV and rWMV of widespread brain areas after a few years in longitudinal analyses. These areas involve areas related to language processing, attention and executive functions, emotion, and reward. In conclusion, frequent internet use is directly or indirectly associated with decrease of verbal intelligence and development to smaller gray matter volume at later stages.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".