Evidence map›Paper›PMID 38698715›Full record

ArticleThe Permanente journal2024

COVID-19 Vaccine Information and Infertility Posts on X: Insights on a Misinformation Pandemic.

Morgan S Levy, Kelby N Hunt, Sarah Rinehart, Alyssa D Brown, Amelia G Kelly, Padmaja Sundaram, Alisha Crump, Tiffany J Sinclair, Kally Dey, Alexander Zoroufy and 2 more

Abstract read
In one paragraph

Article in The Permanente journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

12 authors.

Morgan S LevyDepartment of Medical Education, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID 0000-0003-2022-8451
Kelby N HuntDepartment of Medical Education, University of Miami Miller School of Medicine, Miami, FL, USA.
Sarah RinehartDepartment of Medical Education, University of Miami Miller School of Medicine, Miami, FL, USA.
Alyssa D BrownDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Amelia G KellyDepartment of Obstetrics and Gynecology, New York University Grossman School of Medicine, New York, NY, USA.
Padmaja SundaramDepartment of Obstetrics and Gynecology, University of Massachusetts, Springfield, MA, USA.
Alisha CrumpDepartment of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Tiffany J SinclairDepartment of Surgery, Kaiser Panorama City, Panorama City, CA, USA.
Kally DeyChicago College of Osteopathic Medicine, Midwestern University, Downers Grove, IL, USA.
Alexander ZoroufySenior Statistical Programmer, Rho, Chapel Hill, NC, USA.
Alberto J Caban-MartinezDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA.
Torie Comeaux PlowdenDepartment of Gynecologic Surgery and Obstetrics, Uniformed Services University, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to evaluate misinformation surrounding infertility and the COVID-19 vaccine on X (formerly known as Twitter) by analyzing the prevalence and content of this misinformation across a sample of posts on X.

methodsThis study is a retrospective review of posts on X (formerly known as tweets) from the COVID-19-TweetIDs dataset from July 2021 and November 2021. Included posts were from crucial time points in the COVID-19 vaccine discourse and contained at least one word related to COVID-19 vaccination and fertility. Posts were analyzed and categorized based on factuality, common words, and hashtags. Descriptive statistics on total followers, account verification status, and engagement were obtained. Differences between posts on X classified as factual and misinformation were examined using analysis of variance or χ

resultsA total of 17,418 relevant posts on X were reviewed: 11,436 from timeframe 1 (July 2021) and 5982 from timeframe 2 (December 2021). Misinformation posts rose from 29.9% in July 2021 to 45.1% in November 2021. In both timeframes, accounts sharing factual information had more followers (p < 0.001), and verified users were more likely to share accurate posts (p ≤ 0.001). Factual and misinformation posts had similar engagement. Sentiment analysis identified that real posts were more positive and misinformation posts were more negative (p < 0.001). CONCLUSIONS AND RELEVANCE: Misinformation about the COVID-19 vaccine and fertility is highly prevalent on X and threatens vaccine uptake in patients desiring future fertility. Accounts sharing factual information were likely to have more followers and be verified; therefore, verifying more physicians sharing accurate information is critical.

Indexed as

CommunicationCOVID-19COVID-19 VaccinesInfertilitySocial MediaHumansPandemicsRetrospective StudiesSARS-CoV-2COVID-19 VaccinesCOVID-19FertilityMisinformationPregnancyTwitterVaccine Hesitancy

Identifiers

PMID38698715
PMCPMC11232903

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.