Mental health, coping and related risk factors during the first 2 years of the COVID-19 pandemic in children: Nationally representative, multi-wave, cross-sectional results from 12 countries from the global COH-FIT study
Bibliographic record
Abstract
Few multinational studies have assessed risk factors and coping strategies associated with the impact of the COVID-19 pandemic on children’s mental health over time. The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) is the largest transcontinental, multi-wave, cross-sectional survey collecting multi-nation data on well-being and psychopathology during the pandemic. We analyzed country-specific, general-population-based, representative COH-FIT data of 6067 children aged 6–13 years from 12 countries across repeated cross-sectional waves over a period of >2 years (Apr/2020–May/2022), addressing through current and retrospective assessment pre- to intra-pandemic changes in well-being (WHO-5) and general psychopathology scores (P c ) (0–100) in relation to COVID-related deaths, stringency index, eight a priori risk factors, and 16 coping strategies in different responders at each wave. From pre- to intra-pandemic, WHO-5 scores decreased (−4.59, 95 %CI=−6.18 to −2.99, p < 0.001), while PC-scores increased (+6.68, 95 %CI=4.48–8.88, p < 0.001) significantly, following distinct time patterns but both returning to near pre-pandemic levels. Changes in both scores varied by country. WHO-5 scores correlated strongly with P C and subdomain scores. Both score changes were significantly but minimally associated to COVID-19 deaths/stringency index. The proportion of children screening positive for depression increased from 3.9 % to 8.3 % (χ²=145.70, p < 0.001) and for major depression from 0.6 % to 2.2 % (χ²=68.64, p < 0.001) intrapandemic. WHO-5 and P C -score changes were significantly associated with female gender, school closure, and pre-existing physical and mental conditions, with cumulative effects. The five most frequently endorsed coping strategies were family contact (85.2 %), friends (67.3 %), outdoor play (54.0 %), pet interaction (51.5 %), and internet use (50.9 %). Identified risk groups and coping strategies can inform targeted interventions and global public health policy. Trial Registration: ClinicalTrials.gov; Identifier: NCT04383470
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".