Evidence map›Paper›PMID 36976597›Full record

Trial reportThe western journal of emergency medicine2023

Effects of an Online Community Peer-support Intervention on COVID-19 Vaccine Misinformation Among Essential Workers: Mixed-methods Analysis.

Dominic Arjuna Ugarte, Sean Young

Full text readRandomized Controlled Trial
In one paragraph

Trial report in The western journal of emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 4 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

11 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

2 authors.

Dominic Arjuna UgarteUniversity of California, Irvine, Department of Emergency Medicine, Orange, California.
Sean YoungUniversity of California, Irvine, Department of Emergency Medicine, Orange, California.

Funding

Mining real-time social media big data to monitor HIV: Development and Ethical IssuesR01AI132030 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YOUNG, SEAN · 2017 to 2020
$3.4M
NIAID NIH HHS R01 AI132030
6 · The paper itself

Abstract

introductionPublic health efforts to reduce the spread of coronavirus disease 2019 (COVID-19) have been plagued by vaccine hesitancy and misinformation. Social media has contributed to spreading misinformation by creating online environments where people find information or opinions that reinforce their own. Combating misinformation online will be essential to prevent and manage the spread of COVID-19. It is of particular urgency to understand and address misinformation and vaccine hesitancy among essential workers, such as healthcare workers, because of their frequent interactions with and influence upon the general population. Using data from an online community pilot randomized controlled trial designed to increase requests for COVID-19 vaccine information among frontline essential workers, we explored the topics discussed on the online community related to COVID-19 and COVID-19 vaccination to better understand current misinformation and vaccine hesitancy.

methodsFor the trial, 120 participants and 12 peer leaders were recruited through online advertisements to join a private, hidden Facebook group. The study consisted of an intervention and control arm, each with two groups of 30 randomized participants each. Peer leaders were only randomized into one of the intervention-arm groups. Peer leaders were tasked with engaging the participants throughout the study. Posts and comments of only participants were coded manually by the research team. Chi-squared tests assessed differences in the frequency and content of posts between intervention and control arms.

resultsWe found significant differences in the numbers of posts and comments focused on topics of general community, misinformation, and social support between intervention and control arms (6.88% vs 19.05% focused on misinformation, respectively, (P <0.001); 11.88% vs 1.90% focused on social support, respectively, (P <0.001); and 46.88% vs 62.86% focused on general community (P <0.001)).

conclusionResults suggest that peer-led online community groups may help to reduce the spread of misinformation and aid public health efforts in our fight against COVID-19.

Indexed as

COVID-19COVID-19 VaccinesHealth PersonnelHumansPeer GroupSocial SupportCOVID-19 Vaccines

Identifiers

PMID36976597
PMCPMC10047750

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read15
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.