The Association between Family Environment and Subsequent Risk of Cyberbullying Victimization in Adolescents
Bibliographic record
Abstract
BACKGROUND: Family environment and parental monitoring have long been recognized as two important factors associated with adolescents' psychological development. Studies have suggested a potential link between parenting style/parental engagement and the likelihood of bullying victimization among adolescents. Nonetheless, no studies to date have investigated the association between family environment and the subsequent risk of cyberbullying victimization among adolescents. In this study, we assessed the association between family environment (eg, parental monitoring and family conflict) and subsequent risk of cyberbullying victimization using data from the Adolescent Brain Cognitive Development (ABCD). METHODS: We used multivariable logistic regressions to assess the association between parental monitoring and family conflict at year 1 and the subsequent risk of cyberbullying victimization at year 2 in 10,410 eligible ABCD study participants. RESULTS: Adjusting for sociodemographic characteristics, study sampling weights and study site, higher levels of parental monitoring at year 1 were associated with a lower reported past 12-month (OR: 0.61, 95% CI: 0.50-0.75) history of cyberbullying victimization at year 2. Higher levels of family conflict at year 1 were associated with a higher risk of reported past 12-month history (OR: 1.10, 95% CI: 1.04-1.16) of cyberbullying victimization one year later. CONCLUSION: Higher levels of parental monitoring and lower levels of family conflict are associated with a subsequent lower risk of cyberbullying victimization among adolescents. Cyberbullying victimization preventive programs should advocate for increased parental monitoring and minimize family conflict at home to reduce the risks of cyberbullying victimization among adolescents.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".