School Closures on Bullying Experiences of Treatment-Seeking Children and Youth: The Influence of the COVID-19 Pandemic Within Ontario, Canada
Bibliographic record
Abstract
Amongst school-aged children and youth, bullying is a significant problem warranting further investigation. The current study sought to investigate the influence of the COVID-19 pandemic waves and school closures on the bullying experiences of 22,012 children aged 4-18-years-old who were referred and assessed at mental health agencies in Ontario, Canada. Individual, familial, and mental health variables related to bullying experiences were also investigated. Data were collected from January 2017 to February 2022. The pre-pandemic period of study included January to June 2017, September 2018/2019 to June 2019/2020. The pandemic period was divided into categories of remote learning (17 March 2020 to 30 June 2020, 8 January 2021 to 16 February 2021, 12 April 2021 to 30 June 2021) and in-person learning (remaining pandemic dates). The summer holidays pre-pandemic were in July-August 2017, 2018, 2019 and during the pandemic they were in July-August 2020 and 2021. Logistic regressions were conducted to analyze data. Findings related to COVID-19 showed bullying rates to be lower during the pandemic when compared to pre-pandemic levels (bullied others during pandemic in school: OR = 0.44, CI = 0.34-0.57; victim of bullying during pandemic in school: OR = 0.41, CI = 0.33-0.5). Furthermore, bullying rates were lower during the pandemic periods when schools were closed for in-person learning (bullied others during pandemic remote: OR = 0.62, CI = 0.45-0.85; victim of bullying during pandemic remote: OR = 0.24, CI = 0.17-0.34). Children who lived in lower income areas, experienced home life challenges, exhibited mental health difficulties, or had behavioural concerns were more likely to be involved in bullying experiences. Finally, classroom type and school program impacted the child's likelihood of bullying others or being bullied. These findings further our understanding of the impact of school closures on children's mental health and behaviour during the pandemic. Public health and policy implications such as bullying prevention, supervision, and conflict management are discussed.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".