Parent-adolescent interaction and risk of adolescent internet addiction: a population-based study in Shanghai
Bibliographic record
Abstract
BACKGROUND: Family-based intervention is essential for adolescents with behavioral problems. However, limited data are available on the relationship between family-based factors and adolescent internet addiction (AIA). We aimed to examine this relationship using a representative sample of Shanghai adolescents. METHODS: In October 2007, a total of 5122 adolescents were investigated from 16 high schools via stratified-random sampling in Shanghai. Self-reported and anonymous questionnaires were used to assess parent-adolescent interaction and family environments. AIA was assessed by DRM-52 Scale, developed from Young's Internet-addiction Scale, using seven subscales to evaluate psychological symptoms of AIA. RESULTS: Adjusting for adolescents' ages, genders, socio-economic status, school performances and levels of the consumption expenditure, strong parental disapproval of internet-use was associated with AIA (vs. parental approval, OR = 2.20, 95% CI: 1.24-3.91). Worse mother-adolescent relationships were more significantly associated with AIA (OR = 3.79, 95% CI: 2.22-6.48) than worse father-adolescent relationships (OR = 1.76, 95% CI: 1.10-2.80). Marital status of "married-but-separated" and family structure of "left-behind adolescents" were associated with symptoms of some subscales. When having high monthly allowance, resident students tended to develop AIA but commuter students did not. Family social-economic status was not associated with the development of AIA. CONCLUSIONS: The quality of parent-adolescent relationship/communication was closely associated with the development of AIA, and maternal factors were more significantly associated with development of AIA than paternal factors. Family social-economic status moderated adolescent internet-use levels but not the development of AIA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".