- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04565509
Supporting the Health and Well-being of Children With Intellectual and Developmental Disability During COVID-19 Pandemic
Study Overview
Status
Detailed Description
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
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Maryland
-
Baltimore, Maryland, United States, 21205
- Hugo W. Moser Research Institute at Kennedy Krieger, Inc.
-
-
Missouri
-
Kansas City, Missouri, United States, 64110
- University of Missouri
-
St Louis, Missouri, United States, 63131
- Special School District
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Students enrolled in the St. Louis Special School District or the Kennedy Krieger Institutes/Sheppard Pratt Schools in Maryland.
- Teachers/Staff working at the St. Louis Special Schools or the Kennedy Krieger Institutes/Sheppard Pratt Schools in Maryland dedicated to teaching children with IDD.
or
- Parents/ of students, teachers and/or staff employed by the St. Louis Special School District or Kennedy Krieger Institute/Sheppard Pratt schools in Maryland or
- 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).
Exclusion Criteria:
- Members of the research team will not be eligible to participate in the focus groups.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Active Comparator: SSD: Standard Messaging - Standard Messaging
In phase 1, all schools received standard messaging.
In phase 2, three schools were randomized to standard messaging.
|
A messaging strategy will be developed from focus groups that generally describes COVID-19 and the importance of testing.
Weekly surveillance COVID-19 testing.
|
|
Active Comparator: SSD: Standard Messaging - Enhanced Messaging
In phase 1, all schools received standard messaging.
In phase 2, three schools were randomized to a messaging strategy that was developed from focus groups that were targeted to address specific concerns of the different communities.
|
A messaging strategy will be developed from focus groups that generally describes COVID-19 and the importance of testing.
Weekly surveillance COVID-19 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.
|
|
Active Comparator: KKI: Standard Messaging - Standard Messaging
In phase 1, all schools received standard messaging.
In phase 2, two schools were randomized to standard messaging.
|
A messaging strategy will be developed from focus groups that generally describes COVID-19 and the importance of testing.
Weekly surveillance COVID-19 testing.
|
|
Active Comparator: KKI: Standard Messaging - Enhanced Messaging
In phase 1, all schools received standard messaging.
In phase 2, two schools were randomized to a messaging strategy that was developed from focus groups that were targeted to address specific concerns of the different communities.
|
A messaging strategy will be developed from focus groups that generally describes COVID-19 and the importance of testing.
Weekly surveillance COVID-19 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.
|
|
Experimental: Focus Groups
Focus group were completed in Phase 1 to develop enhanced messaging.
Focus group participants were not required to be enrolled in testing.
|
Focus groups to develop enhanced messaging.
|
|
Experimental: Fuzzy Cognitive Mapping
FCMs were completed to assess the facilitators and barriers to testing.
FCM participants were not required to be enrolled testing.
|
FCMs to assess facilitators and barriers to COVID-19 testing.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Enrollment Into Weekly Testing by Each Participant - Special School District
Time Frame: 22 months
|
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.
|
22 months
|
|
Overall Testing Rate - Special School District
Time Frame: 22 months
|
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.
|
22 months
|
|
Enrollment Into Weekly Testing by Each Participant - Kennedy Krieger Institute
Time Frame: 22 months
|
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.
|
22 months
|
|
Overall Testing Rate - Kennedy Krieger Institute
Time Frame: 22 months
|
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.
|
22 months
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Key Themes and Subthemes: Perceptions of Returning to In-person Learning
Time Frame: 2 months
|
Key themes and subthemes of participants' perceptions of returning to in-person learning
|
2 months
|
|
Key Themes and Subthemes: Facilitators to Participation in SARS-CoV-2 Screening Testing
Time Frame: 2 months
|
Key Themes and Subthemes: Facilitators to Participation in SARS-CoV-2 Screening Testing
|
2 months
|
|
Key Themes and Subthemes: Communication (Messages)
Time Frame: 2 months
|
Key Themes and Subthemes: Communication (messages)
|
2 months
|
|
Key Themes and Subthemes: Communication (Messengers)
Time Frame: 2 month
|
Key themes and subthemes: Communication (messengers)
|
2 month
|
|
Structural Equation Modeling (SEM) for Effects of Facilitators and Barriers Related to a Successful SARS-COV-2 Test
Time Frame: up to 52 weeks
|
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 |
up to 52 weeks
|
|
Structural Equation Modeling (SEM) for Successful SARS-COV-2 Test
Time Frame: up to 52 weeks
|
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 |
up to 52 weeks
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Jason G. Newland, MD, Washington University School of Medicine
Publications and helpful links
General Publications
- Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Aug 7;4:50. doi: 10.1186/1748-5908-4-50.
- Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, Boynton MH, Halko H. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017 Aug 29;12(1):108. doi: 10.1186/s13012-017-0635-3.
- Lalli MA, Langmade JS, Chen X, Fronick CC, Sawyer CS, Burcea LC, Wilkinson MN, Fulton RS, Heinz M, Buchser WJ, Head RD, Mitra RD, Milbrandt J. Rapid and Extraction-Free Detection of SARS-CoV-2 from Saliva by Colorimetric Reverse-Transcription Loop-Mediated Isothermal Amplification. Clin Chem. 2021 Jan 30;67(2):415-424. doi: 10.1093/clinchem/hvaa267.
- Wylie AL, Fourneir J, Casanovas-Massana A, et al. Saliva is more sensitive for SARS-CoV-2 detection in COVID-19 patients than nasopharyngeal swabs. medRxiv. 2020.
- Rader B, Astley CM, Sy KTL, Sewalk K, Hswen Y, Brownstein JS, Kraemer MUG. Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates. J Travel Med. 2020 Nov 9;27(7):taaa076. doi: 10.1093/jtm/taaa076. No abstract available.
- Silliman Cohen RI, Bosk EA. Vulnerable Youth and the COVID-19 Pandemic. Pediatrics. 2020 Jul;146(1):e20201306. doi: 10.1542/peds.2020-1306. Epub 2020 Apr 28. No abstract available.
- Landes SD, Turk MA, Formica MK, McDonald KE, Stevens JD. COVID-19 outcomes among people with intellectual and developmental disability living in residential group homes in New York State. Disabil Health J. 2020 Oct;13(4):100969. doi: 10.1016/j.dhjo.2020.100969. Epub 2020 Jun 24.
- Ross LF, Loup A, Nelson RM, Botkin JR, Kost R, Smith GR, Gehlert S. Nine key functions for a human subjects protection program for community-engaged research: points to consider. J Empir Res Hum Res Ethics. 2010 Mar;5(1):33-47. doi: 10.1525/jer.2010.5.1.33.
- Waltz TJ, Powell BJ, Fernandez ME, Abadie B, Damschroder LJ. Choosing implementation strategies to address contextual barriers: diversity in recommendations and future directions. Implement Sci. 2019 Apr 29;14(1):42. doi: 10.1186/s13012-019-0892-4.
- Zhou G, Lee MC, Atieli HE, Githure JI, Githeko AK, Kazura JW, Yan G. Adaptive interventions for optimizing malaria control: an implementation study protocol for a block-cluster randomized, sequential multiple assignment trial. Trials. 2020 Jul 20;21(1):665. doi: 10.1186/s13063-020-04573-y.
- Steiner JF. Using stories to disseminate research: the attributes of representative stories. J Gen Intern Med. 2007 Nov;22(11):1603-7. doi: 10.1007/s11606-007-0335-9. Epub 2007 Sep 1.
- Jetter AJ, Schweinfort W. Building scenarios with Fuzzy Cognitive Mapping: An exploratory study of solar energy. Futures. 2011;43(1):52-66.
- Sherby MR, Walsh TJ, Lai AM, Neidich JA, Balls-Berry JE, Morris SM, Head R, Prener CG, Newland JG, Gurnett CA; COMPASS-T Study Group. SARS-CoV-2 screening testing in schools for children with intellectual and developmental disabilities. J Neurodev Disord. 2021 Sep 1;13(1):31. doi: 10.1186/s11689-021-09376-z.
- Sherby MR, Walsh T, Lai AM, Neidich JA, Balls-Berry JE, Morris SM, Head R, Prener C, Newland JG, Gurnett CA; COMPASS-T Study Group. SARS-CoV-2 Screening Testing in Schools for Children with Intellectual and Developmental Disabilities. Res Sq [Preprint]. 2021 Jul 20:rs.3.rs-700296. doi: 10.21203/rs.3.rs-700296/v1.
- Vestal LE, Schmidt AM, Dougherty NL, Rolf L, Newland JG, Mueller NB; COMPASS-T Study Group. COVID-19 Related Facilitators and Barriers to In-Person Learning for Children With Intellectual and Development Disabilities: A Follow-Up. J Sch Health. 2024 Feb;94(2):105-116. doi: 10.1111/josh.13404. Epub 2023 Oct 18.
- Gemmell M, Walsh T, Sherby M, Imbeah A, Bono K, Baldenweck M, Gurnett C, Newland JG. Clusters of SARS-CoV-2 Infection Across Six Schools for Students with Intellectual and Developmental Disabilities. Infect Dis Ther. 2023 Sep;12(9):2289-2294. doi: 10.1007/s40121-023-00855-5. Epub 2023 Sep 13.
- Vestal LE, Schmidt AM, Dougherty NL, Sherby MR, Newland JG, Mueller NB; COMPASS-T Study Group. COVID-19-Related Facilitators and Barriers to In-Person Learning for Children With Intellectual and Development Disabilities. J Sch Health. 2023 Mar;93(3):176-185. doi: 10.1111/josh.13262. Epub 2022 Nov 20.
Helpful Links
- Brown School Evaluation Center at Washington University in St. Louis
- Health Communication Research Laboratory at Washington University in St. Louis
- Intellectual and Developmental Disabilities Research Center at Washington University in St. Louis
- Kennedy Krieger Institute Intellectual and Developmental Disabilities Research Center
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Neurologic Manifestations
- Nervous System Diseases
- Mental Disorders
- Respiratory Tract Infections
- Infections
- RNA Virus Infections
- Virus Diseases
- Respiratory Tract Diseases
- Neurobehavioral Manifestations
- Lung Diseases
- Pneumonia, Viral
- Pneumonia
- Coronavirus Infections
- Coronaviridae Infections
- Nidovirales Infections
- Neurodevelopmental Disorders
- Pathological Conditions, Signs and Symptoms
- Signs and Symptoms
- COVID-19
- Developmental Disabilities
- Intellectual Disability
- Health Care Quality, Access, and Evaluation
- Investigative Techniques
- Epidemiologic Methods
- Clinical Laboratory Techniques
- Diagnostic Techniques and Procedures
- Diagnosis
- Data Collection
- Health Care Evaluation Mechanisms
- Quality of Health Care
- Public Health
- Environment and Public Health
- Focus Groups
- COVID-19 Testing
Other Study ID Numbers
- 202009060
- 3P50HD103525-01S1 (U.S. NIH Grant/Contract)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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