Evidence map›Paper›PMID 33863574›Full record

ArticleVaccine2021

#DoctorsSpeakUp: Lessons learned from a pro-vaccine Twitter event.

Beth L Hoffman, Jason B Colditz, Ariel Shensa, Riley Wolynn, Sanya Bathla Taneja, Elizabeth M Felter, Todd Wolynn, Jaime E Sidani

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 9% of its field
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, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

8 authors at 2 institutions in 1 country.

Beth L HoffmanDepartment of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 130 De Sotto Street, Pittsburgh, PA 15261, United States; Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, School of Medicine, 1218 Scaife Hall, 35505 Terrace Street, Pittsburgh, PA 15261, United States; Center for Behavioral Health, Media, and Technology, University of Pittsburgh, School of Medicine, 230 McKee Place, Suite 600, Pittsburgh, PA 15213, United States. Electronic address: beth.hoffman@pitt.edu.
Jason B ColditzDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh, School of Medicine, 1218 Scaife Hall, 35505 Terrace Street, Pittsburgh, PA 15261, United States; Center for Behavioral Health, Media, and Technology, University of Pittsburgh, School of Medicine, 230 McKee Place, Suite 600, Pittsburgh, PA 15213, United States. Electronic address: colditzjb@pitt.edu.
Ariel ShensaDepartment of Physical Therapy, University of Pittsburgh School of Health and Rehabilitation Sciences, 4028 Forbes Tower, Pittsburgh, PA 15260, United States. Electronic address: ariel.shensa@pitt.edu.
Riley WolynnDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh, School of Medicine, 1218 Scaife Hall, 35505 Terrace Street, Pittsburgh, PA 15261, United States; Center for Behavioral Health, Media, and Technology, University of Pittsburgh, School of Medicine, 230 McKee Place, Suite 600, Pittsburgh, PA 15213, United States. Electronic address: RIW22@pitt.edu.
Sanya Bathla TanejaDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh, School of Medicine, 1218 Scaife Hall, 35505 Terrace Street, Pittsburgh, PA 15261, United States; Center for Behavioral Health, Media, and Technology, University of Pittsburgh, School of Medicine, 230 McKee Place, Suite 600, Pittsburgh, PA 15213, United States. Electronic address: SBT12@pitt.edu.
Elizabeth M FelterDepartment of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 130 De Sotto Street, Pittsburgh, PA 15261, United States. Electronic address: emfelter@pitt.edu.
Todd WolynnKids Plus Pediatrics, 4070 Beechwood Blvd, Pittsburgh, PA 15217, United States. Electronic address: todd@kidspluspgh.com.
Jaime E SidaniDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh, School of Medicine, 1218 Scaife Hall, 35505 Terrace Street, Pittsburgh, PA 15261, United States; Center for Behavioral Health, Media, and Technology, University of Pittsburgh, School of Medicine, 230 McKee Place, Suite 600, Pittsburgh, PA 15213, United States. Electronic address: jaime.sidani@pitt.edu.
University of Pittsburgh · USPlus Designs (United States) · US

Funding

Leveraging Twitter to monitor nicotine and tobacco-related cancer communicationR01CA225773 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PRIMACK, BRIAN A. · 2018 to 2022
$1.9M
NCI NIH HHS R01 CA225773
6 · The paper itself

Abstract

backgroundIn response to growing anti-vaccine activism on social media, the #DoctorsSpeakUp event was designed to promote pro-vaccine advocacy. This study aimed to analyze Twitter content related to the event to determine (1) characteristics of the Twitter users who authored these tweets, (2) the proportion of tweets expressing pro-vaccine compared to anti-vaccine sentiment, and (3) the content of these tweets.

methodsData were collected using Twitter's Filtered Streams Interface, and included all publicly available tweets with the "#DoctorsSpeakUp" hashtag on March 5, 2020, the day of the event. Two independent coders assessed a 5% subsample of original tweets (n = 966) using a thematic content analysis approach. Cohen's κ ranged 0.71-1.00 for all categories. Chi-square and Fisher's exact tests were used to examine associations between tweet sentiment, type of account, and tweet content (personal narrative and/or statement about research or science). Accounts were analyzed for likelihood of being a bot (i.e. automated account) using Botometer.

resultsOf 847 (87.7%) relevant tweets, 244 (28.8%) were authored by a Twitter user that identified as a parent and 68 (8.0%) by a user that identified as a health professional. With regard to sentiment, 167 (19.7%) were coded as pro-vaccine and 668 (78.9%) were coded as anti-vaccine. Tweet sentiment was significantly associated with type of account (p < 0.001) and tweet content (p = 0.001). Of the 575 unique users in our dataset, 31 (5.4%) were classified as bots using Botometer.

conclusionsOur results suggest a highly coordinated response of devoted anti-vaccine antagonists in response to the #DoctorsSpeakUp event. These findings can be used to help vaccine advocates leverage social media more effectively to promote vaccines. Specifically, it would be valuable to ensure that pro-vaccine messages consider hashtag use and pre-develop messages that can be launched and promoted by pro-vaccine advocates.

Indexed as

Social MediaVaccinesHumansVaccinesAnti-vaccineHealth communicationSocial mediaTwitter

Identifiers

PMID33863574
PMCPMC9351384
OpenAlexW3152933724

What OpenQuestion holds

Textmetadata
LicenceTDM
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.