The trajectory of depression and anxiety among children and adolescents over two years of the COVID-19 pandemic
Bibliographic record
Abstract
Longitudinal research examining children's mental health (MH) over the course of the COVID-19 pandemic is scarce. We examined trajectories of depression and anxiety over two pandemic years among children with and without MH disorders. Parents and children 2-18 years completed surveys at seven timepoints (April 2020 to June 2022). Parents completed validated measures of depression and anxiety for children 8-18 years, and validated measures of emotional/behavioural symptoms for children 2-7 years old; children ≥10 years completed validated measures of depression and anxiety. Latent growth curve analysis determined depression and anxiety trajectories, accounting for demographics, child and parent MH. Data were available on 1315 unique children (1259 parent-reports; 550 child-reports). Trajectories were stable across the study period, however individual variation in trajectories was statistically significant. Of included covariates, only initial symptom level predicted symptom trajectories. Among participants with pre-COVID data, a significant increase in depression symptoms relative to pre-pandemic levels was observed; children and adolescents experienced elevated and sustained levels of depression and anxiety during the two-year period. Findings have direct policy implications in the prioritization and of maintenance of educational, recreational, and social activities with added MH supports in the face of future events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".