Evidence map›Paper›PMID 35030089›Full record

ArticleJournal of medical Internet research2022

A Stanford Conference on Social Media, Ethics, and COVID-19 Misinformation (INFODEMIC): Qualitative Thematic Analysis.

Michael A Gisondi, Daniel Chambers, Tatum Minh La, Alexa Ryan, Adyant Shankar, Athena Xue, Rachel Anne Barber

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
11.4field-weighted citation impact, top 2% 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

17 citing papers in PubMed, 29 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Michael A Gisondi *Department of Emergency Medicine, Stanford School of Medicine, Palo Alto, CA, United States.ORCID 0000-0002-6800-3932
Daniel Chambers *Stanford University, Palo Alto, CA, United States.ORCID 0000-0001-7129-8340
Tatum Minh La *Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-2364-5042
Alexa Ryan *Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-0333-7106
Adyant Shankar *Stanford University, Palo Alto, CA, United States.ORCID 0000-0003-2683-8218
Athena Xue *Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-9958-5306
Rachel Anne Barber *Stanford University, Palo Alto, CA, United States.ORCID 0000-0003-4290-7041
Palo Alto University · USStanford Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic continues to challenge the world's population, with approximately 266 million cases and 5 million deaths to date. COVID-19 misinformation and disinformation led to vaccine hesitancy among the public, particularly in vulnerable communities, which persists today. Social media companies are attempting to curb the ongoing spread of an overwhelming amount of COVID-19 misinformation on their platforms. In response to this problem, the authors hosted INFODEMIC: A Stanford Conference on Social Media and COVID-19 Misinformation (INFODEMIC) to develop best practices for social media companies to mitigate online misinformation and disinformation.

objectiveThe primary aim of this study was to develop recommendations for social media companies to address the COVID-19 infodemic. We report the methods used to execute the INFODEMIC conference, conference attendee engagement and analytics, and a qualitative thematic analysis of the conference presentations. The primary study outcomes were the identified themes and corresponding recommendations.

methodsUsing a constructivist paradigm, we conducted a thematic analysis of the 6-hour conference transcript to develop best practice recommendations. The INFODEMIC conference was the study intervention, the conference speakers were the study participants, and transcripts of their presentations were the data for this study. We followed the 6-step framework for thematic analysis described by Braun and Clarke. We also used descriptive statistics to report measures of conference engagement including registrations, viewership, post-conference asynchronous participation, and conference evaluations.

resultsA total of 26 participants spoke at the virtual conference and represented a wide array of occupations, expertise, and countries of origin. From their remarks, we identified 18 response categories and 4 themes: trust, equity, social media practices, and interorganizational partnerships. From these, a total of 16 best practice recommendations were formulated for social media companies, health care organizations, and the general public. These recommendations focused on rebuilding trust in science and medicine among certain communities, redesigning social media platforms and algorithms to reduce the spread of misinformation, improving partnerships between key stakeholders, and educating the public to critically analyze online information. Of the 1090 conference registrants, 587 (53.9%) attended the live conference, and another 9996 individuals viewed or listened to the conference recordings asynchronously. Conference evaluations averaged 8.9 (best=10).

conclusionsSocial media companies play a significant role in the COVID-19 infodemic and should adopt evidence-based measures to mitigate misinformation on their platforms.

Indexed as

COVID-19Social MediaCommunicationHumansInfodemicPandemicsSARS-CoV-2COVID-19disinformationinfodemicmisinformationqualitativesocial mediathematic analysisvaccine

Identifiers

PMID35030089
PMCPMC8849255
OpenAlexW4206062377

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.