Association between family contextual factors and child mental health during the third wave of the pandemic in Ontario: A cross-sectional analysis
Notice bibliographique
Résumé
BACKGROUND: In Ontario, school closures due to the pandemic lasted 20 weeks at various times throughout March 2020 to June 2021; longer than any Canadian province or territory. School closures may have had a detrimental impact on school-aged children’s academic and psychological functioning. OBJECTIVES: The objective was to examine the variability in child mental/emotional mental health in association with family factors (caregiver depression, caregiver anxiety, overreactive parenting, partner conflict, work-family conflict) and COVID-19 experiences (health-related stressors, resource-related stressors, positive experiences) among children from two-caregiver working households in Ontario METHODS: Data came from the second iteration of the Ontario Parent Survey. The cross-sectional analysis (n=5787) was restricted to working adults, part of a two-caregiver household, with a child aged 4 to 17 years. Sample selection reflected the focus on work-family conflict and partner-conflict as important predictors of interest. Parent-reported, child negative affect and the negative impact on child functioning since the pandemic started, were the main outcomes of interest. Hierarchal linear regression models were constructed, and each group of predictors (covariates, family factors and COVID-19 experiences) were added in a step-wise fashion. Findings were also stratified by child age and child gender. Missing data were handled via multiple imputations. RESULTS: The final model accounted for 38.7% of the variability in negative affect scores, and 24.1% of the variability in COVID-19 negative impact scores. Negative affect was significantly associated with all family factors, resource-related COVID-19 stressors and positive COVID-19 experiences. The negative impact of COVID-19 on child functioning was significantly associated with all COVID-19 experiences and all family factors except overreactive parenting. Caregiver depression was the strongest predictor of worsening child mental/emotional health in all models. Upon stratifying the analyses by child gender and age, partner-conflict was only a predictor of child mental/emotional health for females and child adolescents. Additionally, health-related COVID-19 stress was a significant predictor for males/other only and caregiver anxiety, overreactive parenting and health-related COVID-19 stressors were significant predictors for children, but not for adolescents. CONCLUSIONS: The pandemic recovery period in Ontario should consist of significant efforts to provide preventative family-based programming and interventions to address the growing mental health crisis in children. Future research efforts should aim to explore the mechanisms by which family factors and COVID-19 specific experiences interact to produce various family dynamics and psychological presentations in children. Further research should also replicate the present study in marginalized and culturally diverse populations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».