The mental well-being of children and adolescents during the COVID-19 pandemic: A systematic review of qualitative literature
Bibliographic record
Abstract
COVID-19 has led to significant isolation resulting in a rise in educational inequity and mental illness among youth. A systematic literature review of qualitative studies was conducted adhering to PRISMA 2020 guidelines, to describe the mental wellbeing of children and adolescents during the COVID-19 pandemic. The protocol has been registered in the PROSPERO International Prospective Register of Systematic Reviews. Three Electronic databases were searched for original, qualitative, peer-reviewed, full text, English journal articles published from December 2019- to May 2020, conducted among children and their parents. We extracted the results that describe the psychological impact on children and their parents amidst COVID-19. Thirteen studies were included in the final review. Four major themes (1. Negative and maladaptive behavior 2. Social and psychological disruption 3. Emotion regulation 4. Value of family time) were identified through Inductive Thematic Synthesis. Although children regulate their emotions effectively, most of the children seem to experience maladaptive behaviors which may have a devastating effect on their development. Health care professionals, caregivers, school officials, and social workers should address these aspects of childcare during a pandemic and in the post-pandemic period.
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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 | 0.024 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".