Evidence map›Paper›PMID 38869840›Full record

ArticleInfectious diseases and therapy2024

Cross-Sectional Survey of Factors Contributing to COVID-19 Testing Hesitancy Among US Adults at Risk of Severe Outcomes from COVID-19.

Annlouise R Assaf, Gurinder S Sidhu, Apurv Soni, Joseph C Cappelleri, Florin Draica, Carly Herbert, Iqra Arham, Mehnaz Bader, Camille Jimenez, Michael Bois and 9 more

Abstract read
In one paragraph

Article in Infectious diseases and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Annlouise R AssafGlobal Medical Patient Impact Assessment, Worldwide Medical and Safety, Pfizer Inc, Groton, CT, USA.
Gurinder S SidhuUS Medical Affairs, Pfizer Inc, 537 Alandele Ave, Los Angeles, CA, 90036, USA. gurinder.sidhu@pfizer.com.
Apurv SoniProgram in Digital Medicine, University of Massachusetts, North Worcester, MA, USA.
Joseph C CappelleriBiostatistics, Pfizer Inc, Groton, CT, USA.ORCID http://orcid.org/0000-0001-9586-0748
Florin DraicaUS Medical Affairs, Pfizer Inc, New York, NY, USA.ORCID http://orcid.org/0000-0002-9489-5495
Carly HerbertProgram in Digital Medicine, University of Massachusetts, North Worcester, MA, USA.
Iqra ArhamUS Medical Affairs, Pfizer Inc, New York, NY, USA.
Mehnaz BaderGlobal Medical Patient Impact Assessment, Worldwide Medical and Safety, Pfizer Inc, New York, NY, USA.
Camille JimenezGlobal Medical Grants/Institute of Translational Equitable Medicine, Worldwide Medical and Safety, Pfizer Inc, New York, NY, USA.
Michael BoisUS Medical Affairs, Pfizer Inc, New York, NY, USA.
Eliza SilvesterStrategy Consulting, IQVIA, New York, NY, USA.
Jessica MeserveyStrategy Consulting, IQVIA, Boston, MA, USA.
Valerie EngStrategy Consulting, IQVIA, New York, NY, USA.
Megan NelsonStrategy Consulting, IQVIA, Boston, MA, USA.
Yong CaiAdvanced Analytics, IQVIA, Wayne, PA, USA.
Aakansha NangarliaStrategy Consulting, IQVIA, Boston, MA, USA.
Zhiyi TianAdvanced Analytics, IQVIA, Wayne, PA, USA.
Yanping LiuAdvanced Analytics, IQVIA, Wayne, PA, USA.
Stephen WattGlobal Medical Patient Impact Assessment, Worldwide Medical and Safety, Pfizer Inc, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe United States Centers for Disease Control and Prevention (CDC) advises testing individuals for COVID-19 after exposure or if they display symptoms. However, a deeper understanding of demographic factors associated with testing hesitancy is necessary.

methodsA US nationwide cross-sectional survey of adults with risk factors for developing severe COVID-19 ("high-risk" individuals) was conducted from August 18-September 5, 2023. Objectives included characterizing demographics and attitudes associated with COVID-19 testing. Inverse propensity weighting was used to weight the data to accurately reflect the high-risk adult US population as reflected in IQVIA medical claims data. We describe here the weighted results modeled to characterize demographic factors driving hesitancy.

resultsIn the weighted sample of 5019 respondents at high risk for severe COVID-19, 58.2% were female, 37.8% were ≥ 65 years old, 77.1% were White, and 13.9% had a postgraduate degree. Overall, 67% were Non-testers (who indicated that they were unlikely or unsure of their likelihood of being tested within the next 6 months); these respondents were significantly more likely than Testers (who indicated a higher probability of testing within 6 months) to be female (60.2 vs. 54.1%; odds ratio [OR] [95% confidence interval (CI)], 1.3 [1.1‒1.4]), aged ≥ 65 years old (41.5 vs. 30.3%; OR [95% CI] compared with ages 18‒34 years, 0.6 [0.5‒0.7]), White (82.1 vs. 66.8%; OR [95% CI], 1.4 [1.1‒1.8]), and to identify as politically conservative (40.9 vs. 18.1%; OR [95% CI], 2.6 [2.3‒2.9]). In contrast, Testers were significantly more likely than Non-testers to have previous experience with COVID-19 testing, infection, or vaccination; greater knowledge regarding COVID-19 and testing; greater healthcare engagement; and concerns about COVID-19.

conclusionsOlder, female, White, rural-dwelling, and politically conservative high-risk adults are the most likely individuals to experience COVID-19 testing hesitancy. Understanding these demographic factors will help guide strategies to improve US testing rates.

Indexed as

COVID-19Risk factorsSARS-CoV-2SurveyTesting

Identifiers

PMID38869840
PMCPMC11219613

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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.