Bullying, Mental Health, and the Moderating Role of Supportive Adults: A Cross-National Analysis of Adolescents in 45 Countries
Bibliographic record
Abstract
Objectives: Relationships with supportive adults during adolescence may be a protective factor that lowers the risks associated with bullying. The current study aimed to examine the moderating role of supportive adults in the associations between bullying involvement (in-person and cyber) and mental health problems (psychological symptoms and low life satisfaction). Methods: Data from 45 countries and regions taking part in the 2017/18 Health Behaviour in School-Aged Children study ( N = 230,757) were used. Multivariable Poisson regression models were used to estimate relative risks of bullying on mental health. Effect estimates were compared across the number of supportive adults to examine a possible cumulative protective effect of relationships with supportive adults. Results: Bullying involvement was consistently associated with poor mental health across the 45 countries. Risk of mental health problems associated with bullying involvement was greatest among students reporting relationships with multiple supportive adults. This was true for all indicators of bullying involvement. Conclusion: Bullying remains a prevalent and harmful experience for youth worldwide. Merely having supportive adults is not sufficient in protecting youth from experiencing the mental health risks associated with bullying.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".