139 Understanding the Psychosocial Impact of the Novel Coronavirus Pandemic – A Focus on Children and Families
Bibliographic record
Abstract
Abstract Primary Subject area Social Paediatrics Background The novel coronavirus (COVID-19) pandemic is a major global threat that emerged in 2020. Many countries have enacted policies such as mandatory school closures, business closures, and self-quarantining to keep people at home and prevent further spread of the virus. Previous research has shown that pandemics and subsequent disease containment measures negatively affect children and families, both psychosocially and economically. Objectives The current study explores the potential psychosocial impacts of the COVID-19 pandemic and subsequent disease containment measures on a number of domains (employment/business, education, finances, medical care, access to medication, technology, children/family, access to community services) through an online survey. The current abstract focuses on the emotional well-being of children and how families have been affected by the restrictions and changes related to the COVID-19 pandemic. Design/Methods Participants were asked to complete an online survey through a secure portal. The survey consisted of questions about household demographics and socio-economic status (SES), as well as five psychometric scales measuring satisfaction with life, psychological well-being, anxiety, depression, and substance use, and specific questions about how the COVID-19 pandemic has impacted respondents’ daily lives in the previously identified domains. This is the first of four longitudinal surveys that will be conducted throughout this study. Results A total of 571 participants completed the survey. Of these participants, 41.3% identified as being a parent or guardian with children under 18. The focus of this abstract is the subset of respondents with children. Roughly three quarters of participants identified that their children were emotionally impacted by COVID-19, the school closures, or missing friends or family (Yes = 46.6%; Somewhat = 30.5%). Parents also reported loss of access to childcare, disruptions to their visits with their children living outside the home, and feeling like they could not access timely medical care for their children. Demographic information and other relevant responses and information can be found in Tables 1 and 2, respectively. Conclusion The impacts of the COVID-19 pandemic will be felt for years to come and will shape an entire generation of children. Even in the current sample, which consisted largely of individuals from medium-high SES households, most reported that children had been impacted emotionally. Understanding and mitigating the impact on children and adapting resources in the short term and the long-term to meet the growing needs of our communities must be top priorities for pediatricians and community service providers.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".