A muti-informant national survey on the impact of COVID-19 on mental health symptoms of parent–child dyads in Canada
Bibliographic record
Abstract
The COVID-19 pandemic negatively impacted the mental health of children, youth, and their families which must be addressed and prevented in future public health crises. Our objective was to measure how self-reported mental health symptoms of children/youth and their parents evolved during COVID-19 and to identify associated factors for children/youth and their parents including sources accessed for information on mental health. We conducted a nationally representative, multi-informant cross-sectional survey administered online to collect data from April to May 2022 across 10 Canadian provinces among dyads of children (11-14 years) or youth (15-18 years) and a parent (> 18 years). Self-report questions on mental health were based on The Partnership for Maternal, Newborn & Child Health and the World Health Organization of the United Nations H6+ Technical Working Group on Adolescent Health and Well-Being consensus framework and the Coronavirus Health and Impact Survey. McNemar's test and the test of homogeneity of stratum effects were used to assess differences between children-parent and youth-parent dyads, and interaction by stratification factors, respectively. Among 933 dyads (N = 1866), 349 (37.4%) parents were aged 35-44 years and 485 (52.0%) parents were women; 227 (47.0%) children and 204 (45.3%) youth were girls; 174 (18.6%) dyads had resided in Canada < 10 years. Anxiety and irritability were reported most frequently among child (44, 9.1%; 37, 7.7%) and parent (82, 17.0%; 67, 13.9%) dyads, as well as among youth (44, 9.8%; 35, 7.8%) and parent (68, 15.1%; 49, 10.9%) dyads; children and youth were significantly less likely to report worsened anxiety (p < 0.001, p = 0.006, respectively) or inattention (p < 0.001, p = 0.028, respectively) compared to parents. Dyads who reported financial or housing instability or identified as living with a disability more frequently reported worsened mental health. Children (96, 57.1%), youth (113, 62.5%), and their parents (253, 62.5%; 239, 62.6%, respectively) most frequently accessed the internet for mental health information. This cross-national survey contextualizes pandemic-related changes to self-reported mental health symptoms of children, youth, and families.
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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) | 0.002 | 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".