Evidence map›Paper›PMID 36271079›Full record

ArticleScientific reports2022

Web and social media searches highlight menstrual irregularities as a global concern in COVID-19 vaccinations.

Ariel Katz, Yoav Tepper, Ohad Birk, Alal Eran

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
–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

8 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ariel KatzDepartment of Life Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. katzari@post.bgu.ac.il.
Yoav Tepper, Tel Aviv, Israel.
Ohad Birk *Genetics Institute at Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Alal Eran *Department of Life Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. alal_eran@hms.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Delineation of public concerns that prevent vaccine compliance is a major step in generating assurances and enhancing the success of COVID-19 prevention programs. We therefore sought to identify public concerns associated with COVID-19 vaccines, as reflected by web and social media searches, with a focus on menstrual irregularities. We used trajectory analyses of web and social media search data in combination with global COVID-19 data to reveal time-dependent correlations between vaccination rates and the relative volume of vaccine and period related searches. A surge of period and vaccine related Google searches followed the introduction of Covid vaccines around the world, and the commencement of vaccination programs in English speaking countries and across the United States. The relative volume of searches such as "Covid vaccine menstrual irregularities", "Covid vaccine menstrual period", "Pfizer vaccine menstruation", and "Moderna vaccine menstruation" was each significantly correlated with vaccination rates (Spearman r = 0.42-0.88, P = 4.33 × 10

Indexed as

COVID-19Social MediaVaccinesCOVID-19 VaccinesFemaleHumansMenstruation DisturbancesUnited StatesVaccinationCOVID-19 VaccinesVaccines

Identifiers

PMID36271079
PMCPMC9587257

What OpenQuestion holds

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LicenceCC BY
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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.