Bullying victimization and mental health before and during the COVID-19 pandemic
Bibliographic record
Abstract
Introduction: Bullying victimization is associated with numerous mental health difficulties yet studies from early in the COVID-19 pandemic revealed significant decreases in bullying victimization but significant increases in mental health difficulties for many children and adolescents. It is unclear whether the decrease in bullying victimization early in the pandemic translated to weaker associations between bullying victimization and mental health difficulties. Methods: Using a population-based design, we examined whether the correlations between bullying victimization and mental health difficulties were significantly weaker in magnitude during the COVID-19 pandemic compared to before the pandemic in a sample of 6,578 Canadian students in grades 4-12. Students were randomly assigned to report on their bullying and mental health experiences either during the school year before the pandemic or the school year during the pandemic. Only students who reported experiences of victimization were included in the present study as questions on mental health were specifically on difficulties experienced due to victimization. Results: As expected, overall bullying victimization and mental health difficulties were significantly correlated before and during the pandemic, but correlations were significantly weaker in magnitude during the pandemic for girls and secondary students. Significant decreases in correlation magnitude were also found predominately for general, verbal, and social forms of bullying victimization, but not for physical and cyber victimization. Among students who reported victimization, we also found significantly lower means for mental health difficulties and most forms of bullying victimization during the pandemic compared to pre-pandemic. Discussion: Findings indicate a strong coupling of bullying victimization and mental health difficulties, particularly before the pandemic, and the need to reduce these associations to improve the well-being of children and 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".