ClinicalTrials.gov
public full text
Public Domain
Brief Informational Intervention for COVID-19 Misinformation Prophylaxis
As the coronavirus disease 2019 (COVID-19) pandemic has continued to affect life in the United States, the important role of non-pharmaceutical preventive behaviors (such as wearing a face mask) in reducing harm has become clear. In parallel to the pandemic, researchers have observed an "infodemic" of misinformed or inconsistent narratives about COVID-19. There is growing evidence that misinformed COVID-19 narratives are associated with a wide variety of undesirable behavior (e.g., burning down cell towers). Further, individuals' adherence to recommended COVID-19 preventive guidelines has been inconsistent, and such mandates have engendered opposition and controversy. Recent research suggests the possibility that trust in science and scientists may be an important thread to weave throughout these seemingly disparate components of the modern public health landscape. Thus, this paper describes the protocol for a randomized trial of a brief, digital intervention to increase trust in science. The objective of this trial is to examine if exposure to a curated infographic can increase trust in science, reduce believability of misinformed narratives, and increase likelihood to engage in preventive behaviors.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Anatomy of a Conspiracy Theory: Law, Politics, and Science Denialism in the Era of COVID-19#1021957
- Mechanical Complications of Acute Myocardial Infarction During COVID-19 Pandemics#839704
- Following the Science: Pandemic Policy Making and Reasonable Worst-Case Scenarios#702792
- SALGINTR: Development and Evaluation of a Digital Participatory Surveillance System to Monitor Influenza-like Illness in Türkiye Based on Self-Reported Data from A Physician Cohort#923956
- johntaz/COVID-Collateral#1079800
Record · ID 838982
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive