Youth mental health in a Canadian community sample during COVID‐19: Exploring the role of perceived sense of belonging
Bibliographic record
Abstract
Research has linked broad societal changes related to the COVID-19 pandemic and poorer mental health in young people. There remains a pressing need for studies examining the factors that are associated with better mental health and well-being. The current study addresses this gap using a community-based survey called the Waterloo Region Youth Impact Survey. It was designed in partnership with local youth and the Canadian Index of Well-Being in accordance with United Nations International Children's Emergency Fund guidelines. Using a convenience sampling methodology, this survey was developed to explore the domains, rates, and correlates of well-being and mental health among youth during the pandemic (N = 297). Confirmatory factor analysis was used to identify dimensions related to children's social environment (friends, school, family), sense of belonging, mental health, and well-being. Subsequently, a mediation model was tested. The relationship between children's environments and mental health and well-being operated via perceived sense of belonging. Findings shed light on patterns of youth mental health and well-being during the pandemic, illustrating the role of belonging as a promotive factor with public health relevance.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".