A cohort study examining the association between children’s symptoms of inattention and hyperactivity, internalizing symptoms, and mindful parenting during the COVID-19 pandemic
Bibliographic record
Abstract
Objectives: Increased mental health difficulties have been reported in Canadian children as a result of the COVID-19 pandemic, and emerging research suggests that children with high levels of symptoms of inattention and hyperactivity have been disproportionately impacted. Accordingly, the pandemic has impacted families as well. The purpose of this study was the following: (1) to examine whether children's symptoms of inattention and hyperactivity at the beginning of the 2020 and 2021 academic year were associated with mindful parenting at the end of the academic year and (2) to examine whether children's depressive and anxiety symptoms at the end of the year moderated this relationship. Methods: Parents of 114 young children in a large Canadian city participated in this study in the Winter of 2020 and the Spring of 2021. Parents completed several self-report scales used to measure children's mental health symptomatology and mindfulness in parenting. Results: Children's symptoms of inattention and hyperactivity were significantly, negatively associated with mindful parenting across the pandemic year, and children's depressive symptoms moderated this relationship. Specifically, when children's depressive symptoms were low or average it was found that higher symptoms of inattention and hyperactivity were associated with lower levels of mindful parenting. However, when children's depressive symptoms were high their symptoms of inattention and hyperactivity were not predictive of mindful parenting. Conclusions: Children's mental health, namely symptoms of inattention/hyperactivity and depression, are related to challenges in mindful parenting during COVID-19. These results may inform practitioners about which families require additional support during the 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".