Accuracy of health‐related information regarding COVID‐19 on Twitter during a global pandemic

• Published date: 01 September 2021
• Author: Sarah B. Swetland,Ava N. Rothrock,Halle Andris,Bennett Davis,Linh Nguyen,Phil Davis,Steven G. Rothrock
• Date: 01 September 2021
• DOI: http://doi.org/10.1002/wmh3.468

World Med. & Health Policy. 2021;13:503–517. wileyonlinelibrary.com/journal/wmh3 © 2021 Policy Studies Organization

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503

Received: 26 June 2020

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Revised: 16 April 2021

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Accepted: 23 April 2021

DOI: 10.1002/wmh3.468

ORIGINAL ARTICLE

Accuracy of health‐related information

regarding COVID‐19 on Twitter during a global

pandemic

Sarah B. Swetland

1

|Ava N. Rothrock

2

|Halle Andris

3

|

Bennett Davis

4

|Linh Nguyen

5,6

|Phil Davis

6

|

Steven G. Rothrock

5,6

1

University of Florida, Gainesville,

Florida, USA

2

Duke University, Durham, North

Carolina, USA

3

Florida State University, Tallahassee,

Florida, USA

4

Department of Emergency Medicine,

Magnolia Regional Health Center, Corinth,

Mississippi, USA

5

College of Medicine, Florida State

University, Tallahassee, Florida, USA

6

Department of Emergency Medicine, Dr. P.

Phillips Hospital, Orlando, Florida, USA

Correspondence

Steven G. Rothrock, Emergency Physicians

of Central Florida, 3090 Caruso Court,

Suite 20, Orlando, FL 32806, USA.

Email: steve.rothrock@epcfonline.com

Abstract

This study was performed to analyze the accuracy of

health‐related information on Twitter during the cor-

onavirus disease 2019 (COVID‐19) pandemic. Au-

thors queried Twitter on three dates for information

regarding COVID‐19 and five terms (cure, emergency

or emergency room, prevent or prevention, treat or

treatments, vitamins or supplements) assessing the

first 25 results with health‐related information.

Tweets were authoritative if written by governments,

hospitals, or physicians. Two physicians assessed

each tweet for accuracy. Metrics were compared

between accurate and inaccurate tweets using χ

2

analysis and Mann–Whitney U. A total of 25.4% of

tweets were inaccurate. Accurate tweets were more

likely written by Twitter authenticated authors (49.8%

vs. 20.9%, 28.9% difference, 95% confidence interval

[CI]: 17.7–38.2) with accurate tweet authors having

more followers (19,491 vs. 7346; 3446 difference,

95% CI: 234–14,054) versus inaccurate tweet

authors. Likes, retweets, tweet length, botometer

scores, writing grade level, and rank order did not

differ between accurate and inaccurate tweets. We

found 1/4 of health‐related COVID‐19 tweets in-

accurate indicating that the public should not rely on

COVID‐19 health information written on Twitter.

Ideally, improved government regulatory authority,

public/private industry oversight, independent fact‐

checking, and artificial intelligence algorithms are

needed to ensure inaccurate information on Twitter is

removed.