<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04506268</url>
  </required_header>
  <id_info>
    <org_study_id>843565</org_study_id>
    <nct_id>NCT04506268</nct_id>
  </id_info>
  <brief_title>COVID-19 SAFE Enrollment</brief_title>
  <acronym>COVID SAFE</acronym>
  <official_title>Opt-In Versus Opt-Out for COVID Screening Assessment for Exposure</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Pennsylvania</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Pennsylvania</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      In order to safely and effectively reopen businesses and universities across the US,&#xD;
      institutions will need to develop approaches to rapidly identify COVID-19 cases and manage&#xD;
      their spread while balancing program effectiveness, feasibility, costs, and scalability.&#xD;
&#xD;
      The investigators will evaluate the implementation of a COVID-19 screening program that&#xD;
      coordinates several existing systems at the University of Pennsylvania including saliva-based&#xD;
      viral testing and test different outreach strategies (opt-in vs opt-out) to improve program&#xD;
      enrollment.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The coronavirus disease 2019 (COVID-19) pandemic has resulted in close to 10,000,000 reported&#xD;
      cases worldwide, including more than 2,000,000 aggregated reported cases and 120,000 deaths&#xD;
      in the United States. Initial efforts to address the COVID-19 pandemic were aimed at testing&#xD;
      symptomatic individuals, implementing stay-in-place orders, and at increasing hospital&#xD;
      capacity to meet surge demands. While the US continues to confront the current crisis, we&#xD;
      must plan for the future by putting in place tools to enhance our ability to conduct&#xD;
      effective screening, containment, and case management.&#xD;
&#xD;
      Widespread COVID-19 testing is needed to safely and effectively reopen schools and businesses&#xD;
      across the US. However, currently approved testing options require reagents that are limited&#xD;
      in supply, severely hindering scalability. Emerging evidence indicates that saliva testing&#xD;
      with the option of at-home sample collection can accurately identify COVID-19 viral&#xD;
      infection. Additional diagnostic testing options will continue to increase patient access.&#xD;
      Moreover, this approach provides an option for the easy, safe and convenient collection of&#xD;
      samples required for testing without traveling to a doctor's office, hospital, or testing&#xD;
      site. Collection by the patient also reduces exposure of health care workers to the virus and&#xD;
      preserves limited personal protective equipment.&#xD;
&#xD;
      With access to expanded testing, health systems and universities will need to test&#xD;
      alternative methods to manage COVID-19 spread while balancing program effectiveness,&#xD;
      feasibility, costs, and scalability. Insights from the field of behavioral economics offer&#xD;
      promise for designing and sustaining these kinds of policies. Specifically, research has&#xD;
      demonstrated that an opt-out framed recruitment strategy compared to a conventional opt-in&#xD;
      strategy can improve enrollment and adherence to behavioral interventions.&#xD;
&#xD;
      For these reasons, the investigators propose to evaluate the implementation of a COVID-19&#xD;
      screening program that uses saliva-based testing and to test approaches to improve program&#xD;
      enrollment.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">September 9, 2020</start_date>
  <completion_date type="Actual">October 30, 2020</completion_date>
  <primary_completion_date type="Actual">October 30, 2020</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Screening</primary_purpose>
    <masking>Double (Investigator, Outcomes Assessor)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Proportion Enrolled</measure>
    <time_frame>4 weeks</time_frame>
    <description>The proportion of those invited that enroll in the study</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Participant Age</measure>
    <time_frame>4 weeks</time_frame>
    <description>The average age of participants enrolled in the study</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Participant Sex</measure>
    <time_frame>4 weeks</time_frame>
    <description>The proportion of females enrolled in the study</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Participant Race/Ethnicity</measure>
    <time_frame>4 weeks</time_frame>
    <description>The proportion of enrolled participants belonging to specified categories of race (e.g., Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, White or Caucasian) and ethnicity (i.e., Hispanic or Latino, Non-Hispanic or Latino)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Participant Income</measure>
    <time_frame>4 weeks</time_frame>
    <description>The proportion of enrolled participants belonging to specified categories of income (e.g., Less than $10000, $10000 to $19999, $20000 to $29999, $150000 or more)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Participant Education</measure>
    <time_frame>4 weeks</time_frame>
    <description>The proportion of enrolled participants belonging to specified categories of education (e.g., less than high school, some high school, high school grad, college: 4 year degree, post-college education)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Test Completion</measure>
    <time_frame>8 weeks</time_frame>
    <description>The proportion of enrolled participants that submit a saliva sample</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">412</enrollment>
  <condition>Covid19</condition>
  <arm_group>
    <arm_group_label>Opt-in Recruitment Email</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Participants will receive a recruitment email that describes the objectives of a new COVID-19 voluntary screening program, and invites them to enroll.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Opt-out Recruitment Email</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Participants will receive a recruitment email that describes the objectives of a new COVID-19 voluntary screening program, and informs them that they have been conditionally enrolled.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Opt-out Recruitment Email</intervention_name>
    <description>Behaviorally informed, opt-out framed recruitment email</description>
    <arm_group_label>Opt-out Recruitment Email</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Opt-in Recruitment Email</intervention_name>
    <description>Standard, opt-in framed recruitment email</description>
    <arm_group_label>Opt-in Recruitment Email</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        •University of Pennsylvania staff, faculty, and trainees that have returned to work on&#xD;
        campus who have been identified by leadership at the University of Pennsylvania Perelman&#xD;
        School of Medicine.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        •Participants will not be eligible for the study if they identify any reason they are&#xD;
        unable to participate in the study.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Mitesh S Patel, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Pennsylvania</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Penn Medicine</name>
      <address>
        <city>Philadelphia</city>
        <state>Pennsylvania</state>
        <zip>19103</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>March 2021</verification_date>
  <study_first_submitted>August 7, 2020</study_first_submitted>
  <study_first_submitted_qc>August 7, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">August 10, 2020</study_first_posted>
  <last_update_submitted>March 10, 2021</last_update_submitted>
  <last_update_submitted_qc>March 10, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">March 11, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>COVID-19</keyword>
  <keyword>Coronavirus</keyword>
  <keyword>opt-in</keyword>
  <keyword>opt-out</keyword>
  <keyword>behavioral science</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>COVID-19</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04506268
org study id: 843565
nct id: NCT04506268
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
In order to safely and effectively reopen businesses and universities across the US,
      institutions will need to develop approaches to rapidly identify COVID-19 cases and manage
      their spread while balancing program effectiveness, feasibility, costs, and scalability.

      The investigators will evaluate the implementation of a COVID-19 screening program that
      coordinates several existing systems at the University of Pennsylvania including saliva-based
      viral testing and test different outreach strategies (opt-in vs opt-out) to improve program
      enrollment.
The coronavirus disease 2019 (COVID-19) pandemic has resulted in close to 10,000,000 reported
      cases worldwide, including more than 2,000,000 aggregated reported cases and 120,000 deaths
      in the United States. Initial efforts to address the COVID-19 pandemic were aimed at testing
      symptomatic individuals, implementing stay-in-place orders, and at increasing hospital
      capacity to meet surge demands. While the US continues to confront the current crisis, we
      must plan for the future by putting in place tools to enhance our ability to conduct
      effective screening, containment, and case management.

      Widespread COVID-19 testing is needed to safely and effectively reopen schools and businesses
      across the US. However, currently approved testing options require reagents that are limited
      in supply, severely hindering scalability. Emerging evidence indicates that saliva testing
      with the option of at-home sample collection can accurately identify COVID-19 viral
      infection. Additional diagnostic testing options will continue to increase patient access.
      Moreover, this approach provides an option for the easy, safe and convenient collection of
      samples required for testing without traveling to a doctor's office, hospital, or testing
      site. Collection by the patient also reduces exposure of health care workers to the virus and
      preserves limited personal protective equipment.

      With access to expanded testing, health systems and universities will need to test
      alternative methods to manage COVID-19 spread while balancing program effectiveness,
      feasibility, costs, and scalability. Insights from the field of behavioral economics offer
      promise for designing and sustaining these kinds of policies. Specifically, research has
      demonstrated that an opt-out framed recruitment strategy compared to a conventional opt-in
      strategy can improve enrollment and adherence to behavioral interventions.

      For these reasons, the investigators propose to evaluate the implementation of a COVID-19
      screening program that uses saliva-based testing and to test approaches to improve program
      enrollment.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Screening
masking: Double (Investigator, Outcomes Assessor)
measure: Proportion Enrolled
time frame: 4 weeks
description: The proportion of those invited that enroll in the study
measure: Participant Age
time frame: 4 weeks
description: The average age of participants enrolled in the study
measure: Participant Sex
time frame: 4 weeks
description: The proportion of females enrolled in the study
measure: Participant Race/Ethnicity
time frame: 4 weeks
description: The proportion of enrolled participants belonging to specified categories of race (e.g., Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, White or Caucasian) and ethnicity (i.e., Hispanic or Latino, Non-Hispanic or Latino)
measure: Participant Income
time frame: 4 weeks
description: The proportion of enrolled participants belonging to specified categories of income (e.g., Less than $10000, $10000 to $19999, $20000 to $29999, $150000 or more)
measure: Participant Education
time frame: 4 weeks
description: The proportion of enrolled participants belonging to specified categories of education (e.g., less than high school, some high school, high school grad, college: 4 year degree, post-college education)
measure: Test Completion
time frame: 8 weeks
description: The proportion of enrolled participants that submit a saliva sample
arm group label: Opt-in Recruitment Email
arm group type: Experimental
description: Participants will receive a recruitment email that describes the objectives of a new COVID-19 voluntary screening program, and invites them to enroll.
arm group label: Opt-out Recruitment Email
arm group type: Experimental
description: Participants will receive a recruitment email that describes the objectives of a new COVID-19 voluntary screening program, and informs them that they have been conditionally enrolled.
intervention type: Behavioral
intervention name: Opt-out Recruitment Email
description: Behaviorally informed, opt-out framed recruitment email
arm group label: Opt-out Recruitment Email
intervention type: Behavioral
intervention name: Opt-in Recruitment Email
description: Standard, opt-in framed recruitment email
arm group label: Opt-in Recruitment Email
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Mitesh S Patel, MD
role: Principal Investigator
affiliation: University of Pennsylvania
facility: 
country: United States
responsible party type: Sponsor
mesh term: COVID-19
sharing ipd: No