The association between positive parent–child interaction and mental health outcomes in children aged 1–11 years in Canada
Bibliographic record
Abstract
OBJECTIVES: The prevalence of mental health disorders in Canada has increased over the past 10 years. Positive parent-child interaction (PCI) is a potential protective factor for child mental health, but has not been explored in a Canadian context. This study aimed to determine the association between positive PCI and mental health outcomes in children ages 1-11 years in Canada. METHODS: Participants were included from the 2019 Canadian Health Survey on Children and Youth (CHSCY) (N = 28,874). PCI was assessed using five items, reported by the parents. The combined PCI score was also derived. Parent-reported general child mental health was the main outcome. Multivariable logistic regression models, adjusting for confounders, were performed. RESULTS: Only 2.8% of parents reported their child's mental health to be "fair/poor". The adjusted analysis did not show an association between combined PCI score and parent-reported general child mental health (OR = 0.96; 95%CI 0.91-1.01). Models assessing individual PCI items did not show significant associations with general child mental health, except for the "laughs with child" item. CONCLUSION: While it is theorized that positive PCI is predictive of child mental health, this study did not find a consistent association, except for the frequency at which the parent laughs with the child. This suggests that PCI, as measured in CHSCY, is not a strong indicator of child mental health. Yet, as PCI is an important parenting concept, the PCI items in the CHSCY may not adequately capture the intended construct. Future studies should consider assessing the construct validity of these items.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".