Characterizing and predicting Canadian adolescents’ internalizing symptoms in the first year of the COVID-19 pandemic.
Bibliographic record
Abstract
Most studies of adolescents’ internalizing symptoms during the COVID-19 pandemic have included few data waves, limiting long-term conclusions about adolescents’ mental health during the pandemic. Collecting only a few waves of data precludes examination of intraindividual symptom variability, which may have implications for adjustment beyond mean symptoms. We characterized mean n = 192 adolescents’ internalizing symptoms from March 2020-April 2021 and used mixed effect location scale models to examine established risk factors as predictors of mean trends and intraindividual variability in adolescents’ internalizing symptoms. Adolescents’ symptoms were relatively stable and low over the first year of the pandemic; severity peaked in February and April 2021. Girls showed greater symptoms and greater intraindividual variability in symptoms. Adolescents’ internalizing symptoms and intraindividual variability in symptoms increased as parents’ depressive symptoms increased, while intraindividual variability in adolescents’ internalizing symptoms decreased as parents’ anxious symptoms increased. Implications for intervention and prevention are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".