Dataset Information

Factors affecting the behavior of children with ASD during the first outbreak of the COVID-19 pandemic.

ABSTRACT:

Aim and methods

Cross-sectional data from 118 Chilean children with ASD collected during the pandemic outbreak of COVID-19 in 2020 were evaluated to analyze predictors of behavioral problem impairment.

Results

Forty-five percent of parents stated that their children's behavioral difficulties increased in intensity or frequency. The adjusted predictors were having a family member hospitalized with COVID-19 (OR = 4.11; 95% CI = 1.53-11.1) and parents' mental health disorders during the pandemic (OR = 2.43; 95% CI = 1.01-5.83).

Conclusion

Potentially modifiable psychosocial factors affecting children's behavior should be considered in a possible second outbreak.

SUBMITTER: Nunez A

PROVIDER: S-EPMC7914113 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Factors affecting the behavior of children with ASD during the first outbreak of the COVID-19 pandemic.

Nuñez Alicia A Le Roy Catalina C Coelho-Medeiros María Elisa ME López-Espejo Mauricio M

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology 20210228 5

<h4>Aim and methods</h4>Cross-sectional data from 118 Chilean children with ASD collected during the pandemic outbreak of COVID-19 in 2020 were evaluated to analyze predictors of behavioral problem impairment.<h4>Results</h4>Forty-five percent of parents stated that their children's behavioral difficulties increased in intensity or frequency. The adjusted predictors were having a family member hospitalized with COVID-19 (OR = 4.11; 95% CI = 1.53-11.1) and parents' mental health disorders during ...[more]

PMID: 33641028

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Project description:BackgroundA large portion of COVID-19 cases and deaths in the United States have occurred in nursing homes; however, current literature including the frontline perspective of staff working in nursing homes is limited. The objective of this qualitative assessment was to better understand what individual and facility level factors may have contributed to the impact of COVID-19 on Certified Nursing Assistants (CNAs) and Environmental Services (EVS) staff working in nursing homes.MethodsBased on a simple random sample from the National Healthcare Safety Network (NHSN), 7,520 facilities were emailed invitations requesting one CNA and/or one EVS staff member for participation in a voluntary focus group over Zoom. Facility characteristics were obtained via NHSN and publicly available sources; participant demographics were collected via SurveyMonkey during registration and polling during focus groups. Qualitative information was coded using NVIVO and Excel.ResultsThroughout April 2021, 23 focus groups including 110 participants from 84 facilities were conducted homogenous by participant role. Staffing problems were a recurring theme reported. Participants often cited the toll the pandemic took on their emotional well-being, describing increased stress, responsibilities, and time needed to complete their jobs. The lack of consistent and systematic guidance resulting in frequently changing infection prevention protocols was also reported across focus groups.ConclusionsAddressing concerns of low wages and lack of financial incentives may have the potential to attract and retain employees to help alleviate nursing home staff shortages. Additionally, access to mental health resources could help nursing home staff cope with the emotional burden of the COVID-19 pandemic. These frontline staff members provided invaluable insight and should be included in improvement efforts to support nursing homes recovering from the impact of COVID-19 as well as future pandemic planning.

Dataset Information

Factors affecting the behavior of children with ASD during the first outbreak of the COVID-19 pandemic.

Aim and methods

Results

Conclusion

Publications

Factors affecting the behavior of children with ASD during the first outbreak of the COVID-19 pandemic.

Similar Datasets

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