Mental health trajectories of children and adolescents up to five years after the onset of the COVID-19 pandemic: a longitudinal study
Bibliographic record
Abstract
ABSTRACT Background The COVID-19 pandemic had heterogeneous effects on the mental health of children and adolescents according to individual experiences, with some consequences persisting beyond the lifting of restrictions. We aimed to examine whether the perceived impact of the COVID-19 pandemic was associated with 2022-2025 trajectories of mental health difficulties in children and adolescents, and to identify associated risk and protective factors. Methods Data was drawn from the population-based SEROCoV-KIDS cohort study conducted in Geneva, Switzerland. The multidimensional perceived impact of the pandemic, as well as potential socio-demographic, health, family, social, and behavioral risk and protective factors were parent-reported at baseline, in 2022. Mental health difficulties were collected annually between 2022 and 2025. Generalized mixed effects models were used to estimate mental health trajectories by pandemic impact, and to assess risk and protective factors. Results Of 1907 children aged 2-17 years, 9.3% and 7.9% had experienced a negative and positive pandemic impact, respectively. Compared to their unaffected peers, negatively impacted children had more mental health difficulties in 2022 (incidence rate ratio [IRR]: 1.51; 95% confidence interval [CI]: 1.34-1.70) and improving trends between 2022 and 2025 (IRR: 0.97; 95% CI: 0.95-1.01). An average-to-poor financial situation was related to a milder mental health response to a negative impact in 2022 (IRR: 0.64; 95% CI: 0.46-0.89). A positive pandemic impact tended to be associated with higher difficulties in 7-12 years old children only (IRR: 1.36; 95% CI: 0.98-1.89) in 2022, with stable trends over time. Conclusion About five years after the onset of COVID-19, the lasting mental health difficulties presented by negatively impacted children had largely improved. Although globally reassuring, these findings call for proactive measures to prevent such long-term consequences on youth mental health in the event of future crises.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".