Regional contextual determinants of internet addiction among college students: a representative nationwide study of China
Bibliographic record
Abstract
Background: Many studies have reported factors associated with internet addiction (IA) but little attention has been paid to contextual influences. The present study examined the association between regional contextual determinants of IA among college students in China. Methods: Participants comprised 6929 college students, who were identified through a multistage survey sampling process conducted in 28 university/colleges in China. Individual data was obtained through a self-administered questionnaire, and regional variables were retrieved from a national database. Multilevel logistic regression models were used to examine individual and regional influences on IA. Results: The overall IA prevalence was 13.6%. The final multiple level logistic models showed that higher frequent air pollution and PM2.5 level had 4.34 and 1.56 times the likelihood of suffering from IA, respectively; but higher regional per capita area of paved roads had lower likelihood of IA, ORs were from 0.66 to 0.39. Conclusions: The results of this study add important insights about the role of contextual regional factors, especially air pollution, affecting IA among college students in China, and demonstrates the need to account for environmental influences in addressing IA.
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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 | 0.015 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".