Predictors of harsh parenting practices and inter-partner conflict during the COVID-19 pandemic in Ontario, Canada: a cross-sectional analysis from the Ontario Parent Survey
Bibliographic record
Abstract
OBJECTIVES: Guided by the bioecological model, the purpose of this study was to examine the associations of (1) individual level factors (sociodemographic, health behaviour and mental health), (2) family (micro) level COVID-19 experiences (difficulty with household management, managing child mood and behaviour, and pandemic-related positive experiences) and (3) community (macro) level factors (residential instability, ethnic concentration, material deprivation and dependency, an indicator of age and labour force) with harsh parenting practices and inter-partner conflict during the early lockdown of the COVID-19 pandemic in Ontario, Canada. DESIGN: A cross-sectional analysis of data from the Ontario Parent Survey. SETTING: A convenience sample of 7451 caregivers living in Ontario, Canada, at the time of baseline data collection (May-June 2020). PARTICIPANTS: Caregivers aged 18 years and older with children 17 years or younger. OUTCOME MEASURES: Parenting practices over the past 2 months was assessed using a published modification of the Parenting Scale. The frequency of inter-partner conflict over the past month was assessed using the Marital Conflict scale. RESULTS: Individual (sociodemographic factors, alcohol use, and higher depressive and anxiety symptoms) and family (difficulties with managing the household and child mood and behaviour) level factors were positively associated with inter-partner conflict and harsh parenting practices. Having fewer positive experiences (eg, performing activities with children), and economic adversity at the family level were positively associated with inter-partner conflict but inversely associated with harsh parenting. At the community level, residential instability was negatively associated with harsh parenting practices. CONCLUSIONS: Individual and family level factors were associated with harsh parenting and inter-partner conflict. The associations of fewer positive experiences and economic hardship with harsh parenting practices may be more complex than initially thought. Efforts that raise awareness and address caregiver mental health concerns are needed as part of the pandemic response to promote positive inter-partner and parent-child interactions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".