The primary goal of this project is to identify the best messaging and implementation strategies to maximize SARS-CoV-2 testing for children with intellectual and developmental disabilities (IDD) and their teachers to help ensure a safe school environment. Additionally, we will understand nationally the perceptions of COVID-19 and identify facilitators and barriers to help with the adoption of testing in other parts of the US and the necessary strategies to address other mitigation strategies including vaccination.
This research study will occur at six schools dedicated to children with IDD that are a part of the Special School Districts in St. Louis, MO. Additionally, surveys, focus groups, and fuzzy cognitive mapping sessions will be conducted at these six schools and at schools within the Kennedy Krieger School Programs in Baltimore, MD. Finally, a national survey will be administered to families, teachers, and staff of the 67 University Centers for Excellence in Developmental Disabilities (UCEDD) which is sponsored by the Association of University Centers for Disability (AUCD). The first aim will involve focus groups of parents/guardians, teachers, and school staff to identify the barriers and facilitators to frequent SARS-CoV-2 testing, impressions of COVID-19, and best messages and implementation strategies to promote increase testing and vaccination. A formal process for developing two types of messages (general versus focused) will be performed using focus group data and involving key stakeholders to test the messages. A cluster randomized adaptive clinical trial will then occur at the six special school district schools. In phase 1, the schools will be randomized initially to either the general or focused message to promote the adoption of weekly SARS-CoV-2 testing by the students and teachers. After 5 months, data analysis will be conducted to determine which strategy led to the highest percentage of testing. Phase 2 will begin at 7 months after the schools are randomized to either the best message determined from phase 1 or best message plus an augmented implementation strategy. Beginning in April 2021 the first aim was expanded to include weekly testing and message development at the Kennedy Krieger Institutes and Sheppard Pratt Schools in Baltimore, MD. In phase 1, these schools will be randomized initially to either the general or focused message to promote the adoption of weekly SARS-CoV-2 testing by the students and teachers. After 5 months, data analysis will be conducted to determine which strategy led to the highest percentage of testing. Phase 2 will begin at 7 months after these schools are randomized to either the best message determined from phase 1 or best message plus an augmented implementation strategy. The second aim will assess the national perspectives among parents of children with IDD and school staff regarding the impact of COVID-19 and importance of SARS-CoV-2 testing. Fuzzy cognitive mapping (FCM) and the administration of local and national surveys will be used to accomplish this aim. FCM will involve in-person sessions with parents from the schools in aim 1 and Kennedy Krieger Institute/Sheppard Pratt schools in Baltimore, MD for children with IDD. These sessions will help identify the facilitators and barriers SARS-CoV-2 testing and other mitigation strategies including COVID-19 vaccine. Since no accepted measures have been developed for understanding parent and school staff concerns for children with IDD around COVID-19, local (St. Louis and Baltimore) and national surveys will be conducted. Custom surveys will be deployed across two stakeholder groups: parent/guardians and school staff. We will administer the survey at baseline and during the trial across school settings (St. Louis and Baltimore). A national survey will also be administered across the UCEDDs. Psychometric analysis will be performed to help identify the questions for a national survey at the end of the study period. In addition to the custom surveys, NIH recommended parent-report surveys from the PhenX Toolkit will be used. The surveys to be used include the Psychological Stress Associated with the COVID-19 Crisis Scale and COVID-19 impact questionnaires.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
1,143
A messaging strategy will be developed from focus groups that generally describes COVID-19 and the importance of testing.
A messaging strategy that is developed from focus groups that is targeted to address specific concerns of the different communities. Messages may target groups being tested (staff versus students) or sociodemographic or race/ethnicity differences between schools depending on the focus groups input.
Weekly surveillance COVID-19 testing.
Focus groups to develop enhanced messaging.
FCMs to assess facilitators and barriers to COVID-19 testing.
Hugo W. Moser Research Institute at Kennedy Krieger, Inc.
Baltimore, Maryland, United States
University of Missouri
Kansas City, Missouri, United States
Special School District
St Louis, Missouri, United States
Enrollment Into Weekly Testing by Each Participant - Special School District
Assuming the binomial distribution for each primary outcome, generalized estimating equation (GEE) models with logit link function were utilized to investigate the primary outcome changes across the weeks. The denominators for the enrollment and test rate per school were the total number of staff and students; and the total number of consented participants for a specific week, respectively. For the weeks after randomization, the GEE model included the indicator of week, group indicator, and the interaction term between week and group indicator. P-values of the interaction term from type-3 test were used to test the difference between 2 groups across the weeks. At Kennedy, GEE models were conducted separately using participants with non-missing data and participants with missing data to assess the impact of missing data. The reported values reflect the percentage of participants enrolled per week.
Time frame: 22 months
Overall Testing Rate - Special School District
Assuming the binomial distribution for each primary outcome, generalized estimating equation (GEE) models with logit link function were utilized to investigate the primary outcome changes across the weeks. The denominators for the enrollment and test rate per school were the total number of staff and students; and the total number of consented participants for a specific week, respectively. For the weeks after randomization, the GEE model included the indicator of week, group indicator, and the interaction term between week and group indicator. P-values of the interaction term from type-3 test were used to test the difference between 2 groups across the weeks. At Kennedy, GEE models were conducted separately using participants with non-missing data and participants with missing data to assess the impact of missing data. The outcome measure reflects the percentage of participants tested per week.
Time frame: 22 months
Enrollment Into Weekly Testing by Each Participant - Kennedy Krieger Institute
Assuming the binomial distribution for each primary outcome, generalized estimating equation (GEE) models with logit link function were utilized to investigate the primary outcome changes across the weeks. The denominators for the enrollment and test rate per school were the total number of staff and students; and the total number of consented participants for a specific week, respectively. For the weeks after randomization, the GEE model included the indicator of week, group indicator, and the interaction term between week and group indicator. P-values of the interaction term from type-3 test were used to test the difference between 2 groups across the weeks. At Kennedy, GEE models were conducted separately using participants with non-missing data and participants with missing data to assess the impact of missing data. The outcome measure reflects the percentage of participants enrolled per week.
Time frame: 22 months
Overall Testing Rate - Kennedy Krieger Institute
Assuming the binomial distribution for each primary outcome, generalized estimating equation (GEE) models with logit link function were utilized to investigate the primary outcome changes across the weeks. The denominators for the enrollment and test rate per school were the total number of staff and students; and the total number of consented participants for a specific week, respectively. For the weeks after randomization, the GEE model included the indicator of week, group indicator, and the interaction term between week and group indicator. P-values of the interaction term from type-3 test were used to test the difference between 2 groups across the weeks. At Kennedy, GEE models were conducted separately using participants with non-missing data and participants with missing data to assess the impact of missing data. The outcome measure reflects the percentage of participants tested per week.
Time frame: 22 months
Key Themes and Subthemes: Perceptions of Returning to In-person Learning
Key themes and subthemes of participants' perceptions of returning to in-person learning
Time frame: 2 months
Key Themes and Subthemes: Facilitators to Participation in SARS-CoV-2 Screening Testing
Key Themes and Subthemes: Facilitators to Participation in SARS-CoV-2 Screening Testing
Time frame: 2 months
Key Themes and Subthemes: Communication (Messages)
Key Themes and Subthemes: Communication (messages)
Time frame: 2 months
Key Themes and Subthemes: Communication (Messengers)
Key themes and subthemes: Communication (messengers)
Time frame: 2 month
Structural Equation Modeling (SEM) for Effects of Facilitators and Barriers Related to a Successful SARS-COV-2 Test
Structural equation modeling (SEM) was used to confirm the results of the FCM analyses. SEM is a combination of confirmatory factor analysis (CFA) and multiple regression that identifies the relationships among latent constructs. For the purpose of the current study, SEM analyses examined the effects of facilitators and barriers related to a Successful SARS-COV-2 Test. The factor loadings in the tables can be interpreted on the following scale: 0.70+ -\> Strong 0.50 -\> Moderate 0.30 -\> Weak but acceptable
Time frame: up to 52 weeks
Structural Equation Modeling (SEM) for Successful SARS-COV-2 Test
In the one-factor model, Structural equation modeling (SEM) was used for pinpointing key items that loaded onto Successful SARS-COV-2 Test The factor loadings in the tables can be interpreted on the following scale: 0.70+ -\> Strong 0.50 -\> Moderate 0.30 -\> Weak but acceptable
Time frame: up to 52 weeks
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.