Evidence map›Paper›PMID 35131808›Full record

ArticleBMJ global health2022

Finding the facts in an infodemic: framing effective COVID-19 messages to connect people to authoritative content.

Andrew B Pattison, Monta Reinfelde, Hyunsoo Chang, Mayukh Chowdhury, Emma Cohen, Sean Malahy, Katie O'Connor, Mehdi Sellami, Karen L Smith, Charlotte Y Stanton and 2 more

Abstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. A scoping review of digital health interventions for combating COVID-19 misinformation and disinformation.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  7. Article
  8. Article
  9. 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

12 authors.

Andrew B PattisonDigital Health and Innovation, World Health Organization, Geneve, Switzerland pattisona@who.int.
Monta ReinfeldeDigital Health and Innovation, World Health Organization, Geneve, Switzerland.
Hyunsoo ChangGoogle, Mountain View, California, USA.
Mayukh ChowdhuryGoogle, Mountain View, California, USA.
Emma CohenGoogle, Mountain View, California, USA.
Sean MalahyGoogle, Mountain View, California, USA.
Katie O'ConnorGoogle, Mountain View, California, USA.
Mehdi SellamiGoogle, Mountain View, California, USA.
Karen L SmithGoogle, Mountain View, California, USA.
Charlotte Y StantonGoogle, Mountain View, California, USA.
Bram VoetsGoogle, Mountain View, California, USA.
Henry G WeiGoogle, Mountain View, California, USA.

Funding

World Health Organization 001
6 · The paper itself

Abstract

The public's need for timely and trusted COVID-19 information remains high. Governments and global health agencies such as the WHO have sought to disseminate accurate and timely information to counteract misinformation and disinformation that has arisen as part of an 'infodemic'-the overabundance of information on COVID-19-some accurate and some not. In early 2020, WHO began a collaboration with Google to run online public service announcements on COVID-19, in the form of search ads displayed above results of Google Search queries. Web-based text ads can drive online searchers of COVID-19 information to authoritative COVID-19 content but determining what message is most effective is a challenge. WHO wanted to understand which message framing, that is, the way in which ad information is worded for the public, leads searchers to click through to WHO content. WHO tested 71 text ads in English across four COVID-19 topics using a mix of message frames: descriptive, collective, gain, loss, appeals to values and emphasising reasons. Between 11 September 2020 and 23 November 2020, there were 13 million views of the experimental WHO text ads leading to 1.4 million click-throughs to the WHO website. Within the set of 71 ads, there was a large spread between the most effective and least effective messages; for messages on COVID-19, the best performing framings were more than twice as effective as the worst performing framings (18.7% vs 8.5% engagement rate). Health practitioners can apply the messaging tactics WHO found to be successful to rapidly optimise messages for their own public health campaigns and better reach the public with authoritative information. Similar collaboration between big technology companies and governments and global health agencies has the potential to advance public health.

Indexed as

COVID-19Health PromotionHumansInfodemicPublic HealthSARS-CoV-2COVID-19health education and promotionpublic health

Identifiers

PMID35131808
PMCPMC8829835

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.