Evidence map›Paper›PMID 36753464›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

The political polarization of COVID-19 treatments among physicians and laypeople in the United States.

Joel M Levin, Leigh A Bukowski, Julia A Minson, Jeremy M Kahn

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
23.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Political polarization and health.Nature medicine · 2024
    Review
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Joel M LevinKatz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260.ORCID 0000-0002-4095-4840
Leigh A BukowskiDepartment of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA 15213.ORCID 0000-0001-7889-3062
Julia A MinsonKennedy School of Government, Harvard University, Cambridge, MA 02138.ORCID 0000-0002-9150-8509
Jeremy M KahnDepartment of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA 15213.
University of Pittsburgh · USHarvard University · US

Funding

Organizational strategies for improving evidence-uptake in intensive careR35HL144804 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KAHN, JEREMY M · 2019 to 2025
$6.6M
NHLBI NIH HHS R35 HL144804
6 · The paper itself

Abstract

In the United States, liberals and conservatives disagree about facts. To what extent does expertise attenuate these disagreements? To study this question, we compare the polarization of beliefs about COVID-19 treatments among laypeople and critical care physicians. We find that political ideology predicts both groups' beliefs about a range of COVID-19 treatments. These associations persist after controlling for a rich set of covariates, including local politics. We study two potential explanations: a) that partisans are exposed to different information and b) that they interpret the same information in different ways, finding evidence for both. Polarization is driven by preferences for partisan cable news but not by exposure to scientific research. Using a set of embedded experiments, we demonstrate that partisans perceive scientific evidence differently when it pertains to a politicized treatment (ivermectin), relative to when the treatment is not identified. These results highlight the extent to which political ideology is increasingly relevant for understanding beliefs, even among expert decision makers such as physicians.

Indexed as

COVID-19COVID-19 Drug TreatmentCritical CareHumansIvermectinPoliticsUnited StatesIvermectinbelief polarizationCOVID-19expert judgmentmedical decision-making

Identifiers

PMID36753464
PMCPMC9963903
OpenAlexW4319461041

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.