The role of depressive symptoms and social support in the association of internet addiction with non-suicidal self-injury among adolescents: a cohort study in China
Bibliographic record
Abstract
BACKGROUND: Both internet addiction (IA) and non-suicidal self-injury (NSSI) are major public health concerns among adolescents, however, the association between IA and NSSI was not well understood. We aimed to investigate the association between IA and NSSI within a cohort study, and explore the mediated effect of depressive symptoms and the moderating effect of social support in the association. METHODS: A total of 1530 adolescents aged 11-14 years who completed both the baseline (T1) and 14-month follow-up (T2) survey of the Chinese Adolescent Health Growth Cohort were included for the current analysis. IA, NSSI, depressive symptoms and social support were measured at T1; depressive symptoms and NSSI were measured again at T2. Structural equation models were employed to estimate the mediated effect of depressive symptoms and the moderating effect of social support in the association between IA and NSSI at T2. RESULTS: IA was independently associated with an increased risk of NSSI at T2, with the total effect of 0.113 (95%CI 0.055-0.174). Depressive symptoms mediated the association between IA and NSSI at T2, and social support moderated the indirect but not the direct effect of IA on NSSI at T2. Sex differences were found on the mediated effect of depressive symptoms and the moderated mediation effect of social support. CONCLUSIONS: Interventions that target adolescents' NSSI who also struggle with IA may need to focus on reducing depressive symptoms and elevating social support.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".