Personal characteristics related to the risk of adolescent internet addiction: a survey in Shanghai, China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Paralleling the rapid growth in computers and internet connections, adolescent internet addiction (AIA) is becoming an increasingly serious problem, especially in developing countries. This study aims to explore the prevalence of AIA and associated symptoms in a large population-based sample in Shanghai and identify potential predictors related to personal characteristics. METHODS: In 2007, 5,122 adolescents were randomly chosen from 16 high schools of different school types (junior, senior key, senior ordinary and senior vocational) in Shanghai with stratified-random sampling. Each student completed a self-administered and anonymous questionnaire that included DRM 52 Scale of Internet-use. The DRM 52 Scale was adapted for use in Shanghai from Young's Internet Addiction Scale and contained 7 subscales related to psychological symptoms of AIA. Multiple linear regression and logistic regression were both used to analyze the data. RESULTS: Of the 5,122 students, 449 (8.8%) were identified as internet addicts. Although adolescents who had bad (vs. good) academic achievement had lower levels of internet-use (p < 0.0001), they were more likely to develop AIA (odds ratio 4.79, 95% CI: 2.51-9.73, p < 0.0001) and have psychological symptoms in 6 of the 7 subscales (not in Time-consuming subscale). The likelihood of AIA was higher among those adolescents who were male, senior high school students, or had monthly spending >100 RMB (all p-values <0.05). Adolescents tended to develop AIA and show symptoms in all subscales when they spent more hours online weekly (however, more internet addicts overused internet on weekends than on weekdays, p < 0.0001) or when they used the internet mainly for playing games or real-time chatting. CONCLUSIONS: This study provides evidence that adolescent personal factors play key roles in inducing AIA. Adolescents having aforementioned personal characteristics and online behaviors are at high-risk of developing AIA that may compound different psychological symptoms associated with AIA. Spending excessive time online is not in itself a defining symptom of AIA. More attention is needed on adolescent excessive weekend internet-use in prevention of potential internet addicts.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it