Public Support for COVID-19 Test Allocation
7. Januar 2022 aktualisiert von: Alison Buttenheim, University of Pennsylvania
Race, Status, Vaccines, Tests, and Place: Public Attitudes and Support for Equitable COVID-19 Vaccine and Test Allocation
In a randomized survey experiment, investigators will assess public support or opposition towards one of three potential government plans for allocating at-home coronavirus disease 2019 (COVID-19) tests to United States residents: 1) first come, first served; 2) a random draw; or 3) a random draw with 20% of tests reserved for disadvantaged areas.
Investigators will also examine public attitudes surrounding other logistical and equity-related aspects of these allocation plans.
Studienübersicht
Status
Abgeschlossen
Bedingungen
Intervention / Behandlung
Detaillierte Beschreibung
Complementing other efforts to increase access to COVID-19 testing in the United States, the federal government recently announced the purchase of 500,000,000 at home COVID-19 to be distributed for free "to Americans that want them".
A central logistical element in matching supply with demand will be a website, on which people will register their interest in getting tests delivered to their home address.
However, it is still unclear how supply will be matched with demand.
Three main candidate options are first come, first served (FCFS), in which people are sent tests in the order in which they make requests; a random draw, such as a lottery; or a combination of a random draw with a guaranteed reserved amount for more disadvantaged populations.
FCFS is a widely known and practiced rationing principle, but it has shown to exacerbate inequities in, for example, the allocation of vaccine appointments.
Random draws can mitigate this impact, but, in the present context, might be insufficiently sensitive to the fact that not everyone has internet access, and that the need for testing is greater among more disadvantaged communities.
Combining a lottery with a disadvantage reserve system using measures such as the CDC's Social Vulnerability Index is a practical way of promoting equity, and it was already used by the majority of US states in allocating vaccines.
The main objective of this study is to assess public support for each of these three allocation plans and describe differences by demographic characteristics.
Investigators will also assess public attitudes toward specific details of these allocation plans.
The study, which is expected to take approximately 5 minutes to complete, will be administered as part of an omnibus online survey.
Studientyp
Interventionell
Einschreibung (Tatsächlich)
2019
Phase
- Unzutreffend
Kontakte und Standorte
Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.
Studienorte
-
-
District of Columbia
-
Washington, District of Columbia, Vereinigte Staaten, 20006
- Harris Insights & Analytics
-
-
Teilnahmekriterien
Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.
Zulassungskriterien
Studienberechtigtes Alter
18 Jahre und älter (Erwachsene, Älterer Erwachsener)
Akzeptiert gesunde Freiwillige
Ja
Studienberechtigte Geschlechter
Alle
Beschreibung
Inclusion Criteria:
- Aged 18 years old or older, United States resident
Exclusion Criteria:
- None
Studienplan
Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.
Wie ist die Studie aufgebaut?
Designdetails
- Hauptzweck: Versorgungsforschung
- Zuteilung: Zufällig
- Interventionsmodell: Parallele Zuordnung
- Maskierung: Single
Waffen und Interventionen
Teilnehmergruppe / Arm |
Intervention / Behandlung |
|---|---|
|
Experimental: First Come, First Served
Respondents will view the following description: "The US government will make 500 million COVID-19 home tests available for free. US residents can ask for tests by entering their home address in a website. It is likely that more people will want tests than will be available. How should the government decide who will receive tests, when there are not enough for all who want them? One plan that is being considered is this one:" Below this statement, respondents will view the "First Come, First Served" plan description. |
Respondents will view the following description of the plan: "Tests will be sent out in the order they are requested.
People who request tests the quickest will get them first, no matter where they live.
People who request tests later may not get any.
This strategy is also known as 'First Come, First Served.'"
|
|
Experimental: Random
Respondents will view the following description: "The US government will make 500 million COVID-19 home tests available for free. US residents can ask for tests by entering their home address in a website. It is likely that more people will want tests than will be available. How should the government decide who will receive tests, when there are not enough for all who want them? One plan that is being considered is this one:" Below this statement, respondents will view the "Random" plan description. |
Respondents will view the following description of the plan: "People who request tests will be entered into a random drawing, like a sweepstakes or lottery.
Everyone who is in the drawing has the same chance of getting tests, no matter where they live, but some people may not get any tests."
|
|
Experimental: Disadvantaged Priority & Random
Respondents will view the following description: "The US government will make 500 million COVID-19 home tests available for free. US residents can ask for tests by entering their home address in a website. It is likely that more people will want tests than will be available. How should the government decide who will receive tests, when there are not enough for all who want them? One plan that is being considered is this one:" Below this statement, respondents will view the "Disadvantaged Priority & Random" plan description. |
Respondents will view the following description of the plan: "Because COVID-19 has hit people living in disadvantaged areas of the country harder, a proportion of tests will be sent exclusively to people in these zip codes.
Planners will allocate 80% of the tests using a random drawing, like a sweepstakes or lottery.
Everyone who is in the drawing has the same chance of getting tests, no matter where they live.
The remaining 20% are set aside exclusively for the most disadvantaged areas, again allocated with a random drawing.
Some people may not get any tests.
But people living in disadvantaged areas are more likely to get them."
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Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Support for allocation plan
Zeitfenster: 5 minutes
|
Self-reported degree of support for the plan, measured on a 5-point Likert scale ("strongly oppose" to "strongly support") that will be collapsed into 3 response categories ("oppose," "neutral," and "support") for analysis.
|
5 minutes
|
Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Household-level test allocation preference
Zeitfenster: 5 minutes
|
Preferred way of sending tests to households, measured as a binary choice between a fixed or variable (based on household size) number of tests per household.
|
5 minutes
|
|
Tests allocated to disadvantaged areas
Zeitfenster: 5 minutes
|
Self-reported percentage of tests wanted to be sent to disadvantaged areas, measured as a continuous variable on a slider from 0% to 100% with increments of 0.1%.
This outcome will only be measured for respondents in the "Disadvantaged Priority & Random" condition.
|
5 minutes
|
Mitarbeiter und Ermittler
Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.
Sponsor
Ermittler
- Hauptermittler: Alison M Buttenheim, PhD, MBA, University of Pennsylvania
Studienaufzeichnungsdaten
Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.
Haupttermine studieren
Studienbeginn (Tatsächlich)
4. Januar 2022
Primärer Abschluss (Tatsächlich)
6. Januar 2022
Studienabschluss (Tatsächlich)
6. Januar 2022
Studienanmeldedaten
Zuerst eingereicht
7. Januar 2022
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
7. Januar 2022
Zuerst gepostet (Tatsächlich)
11. Januar 2022
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
11. Januar 2022
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
7. Januar 2022
Zuletzt verifiziert
1. Januar 2022
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Zusätzliche relevante MeSH-Bedingungen
Andere Studien-ID-Nummern
- 848725
- #84525 (Registrierungskennung: AsPredicted)
Plan für individuelle Teilnehmerdaten (IPD)
Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?
UNENTSCHIEDEN
Beschreibung des IPD-Plans
Only de-identified individual participant data will be shared by Harris Insights & Analytics to the research team.
Each participant will have a unique identifier to protect their confidentiality.
Only authorized research personnel will have access to the data which will be maintained on encrypted hard-drives.
Individual participant data may be made available to other researchers in an open-access repository.
Arzneimittel- und Geräteinformationen, Studienunterlagen
Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt
Nein
Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt
Nein
Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .