Psychosocial impact of respiratory infectious disease pandemics on children: a systematic review
Bibliographic record
Abstract
Abstract Objective To examine the impact of respiratory infectious disease pandemics in the new millennium on mental health, behavioral responses, and parenting practices in children, and provide further intervention directions to mitigate negative effects of the 2019 novel coronavirus disease (COVID-19). Methods We conducted a systemic literature review of researches from January 2003 to May 2020 with three mainstream electronic databases including PubMed, Web of Science, and China National Knowledge Infrastructure. Quality of included studies were assessed using Agency for Healthcare Research and Quality (AHRQ), Newcastle-Ottawa Scale (NOS), and Critical Appraisal Skills Programme (CASP) according to different study design. Further directions were identified for developing appropriate interventions. Results Twenty-four studies conducted in the context of severe acute respiratory syndrome (SARS) (n = 10), influenza A (H1N1) (n = 3), and COVID-19 (n = 11) pandemics met the inclusion criteria. Children showed emotional conditions such as anxiety, fear, and depression, while psychological responses varied across age and gender groups. Children with mental illness history experienced an exacerbation of psychological symptoms. The pandemics changed hygiene habits and learning styles, and led to the increased participation in unfavorable lifestyles. For families with pediatric patients, the pandemic decreased parents’ participation in providing family-centered care and threatened to supportive family relationship and effective parents-child communication. Conclusion The emerging virus outbreaks and subsequent disease-control measures have impacts on mental health status, behavioral responses, and parenting practices in children. In response to COVID-19, greater efforts taking into account children’s developmental stage should be made to implement evidence-based psychological interventions, enhance effective communication, and encourage collaboration.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".