Evidence map›Paper›PMID 42371971›Full record

ArticlePloS one2026

Ad-based social media interventions increase belief accuracy and generate pro-social opinions among non-news readers.

Erin Wertz, Maria Babińska, Dominik Batorski, Debra Louison-Lavoy, Nicholas Blazer, Nancy S Noble, Magdalena Wojcieszak

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Erin WertzCenter for Excellence in Social Science, University of Warsaw, Warsaw, Poland.ORCID https://orcid.org/0000-0003-0293-2840
Maria BabińskaCenter for Social and Cultural Psychology, Université Libre de Bruxelles, Brussels, Belgium.
Dominik BatorskiInterdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Warsaw, Poland.ORCID https://orcid.org/0000-0003-1112-7114
Debra Louison-LavoyReality Team, New York City, New York, United States of America.
Nicholas BlazerReality Team, New York City, New York, United States of America.
Nancy S NobleReality Team, New York City, New York, United States of America.
Magdalena WojcieszakCenter for Excellence in Social Science, University of Warsaw, Warsaw, Poland.ORCID https://orcid.org/0000-0001-5456-4483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Democratic challenges are often attributed to the spread of misleading, untrustworthy, or biased information, leading scholars to focus on minimizing exposure to such "bad" content online. Instead, we introduce a scalable intervention to put factual and verified public affairs information in users' social media feeds to make them better informed and more resilient to various online threats. We conducted 48 field quasi-experiments using Instagram ads targeting news non-users to enhance their belief accuracy, democratic attitudes, and behavioral intentions related to climate change, COVID-19 vaccines, media literacy, and election integrity. The treatment videos reached 2,496,878 Instagram accounts, 690,470 users watched at least 50% of the video, and 40,584 of those users completed post-test assessment. The intervention was effective: 46 out of 48 of the quasi-experiments had positive effect sizes and 40 out of 48 achieved statistical significance. The intervention predicted not only belief accuracy but also attitudes, media literacy, and - to some extent - behavioral intentions related to vaccination. These patterns emerged across topics, did not dissipate with time (two of three climate change quasi-experiments show continued effects), and were not contingent on persuasive appeals and format features presented in the ads.

Indexed as

AdvertisingCOVID-19Public OpinionSocial MediaAttitudeClimate ChangeCOVID-19 VaccinesHumansMedia ExposurePoliticsSARS-CoV-2COVID-19 Vaccines

Identifiers

PMID42371971
PMCPMC13313353

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.