Family Violence Against Children and Parents’ Social Support during the COVID-19 Pandemic: A Cohort Study
Bibliographic record
Abstract
Amid the COVID-19 pandemic, several experts have raised concerns over an increased risk of family violence. The proximity between confined family members and social isolation fostered tensions, making families more vulnerable. The first objective of this study was to describe the evolution of family violence against children (psychological aggression and corporal punishment) and parents' social support during the COVID-19 pandemic. The second objective was to determine the contribution of parents’ social support to the evolution of family violence against children between two measurement times. Participants included parents living with at least one child between 0 and 17 years old (N = 514) from the broader longitudinal prospective cohort study, My Life and the Pandemic in Quebec (MAVIPAN) from Quebec, Canada. Family violence against children and social support were measured twice (2020 and 2021) with a web-based survey. Most parents reported no family violence against children. Psychological aggression significantly decreased between the two measurement times (p = .003). Corporal punishment and social support remained stable. Social support was a significant predictor of the evolution of psychological aggression. Participants reporting a lower level of perceived social support at baseline were more likely to report psychological aggression at both measurement times, compared to the reference group of parents reporting none (p = .002; OR = 0.914). Social support emerged as a protective factor when psychological aggression towards children is chronic in a family. This study contributes to the growing literature documenting the experience of parents during the COVID-19 pandemic.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".