Evidence map›Paper›PMID 37841671›Full record

ArticleJournal of cognition2023

Mixed News about the Bad News Game.

Megan E Graham, Brittany Skov, Zoë Gilson, Calvin Heise, Kaitlyn M Fallow, Eric Y Mah, D Stephen Lindsay

Abstract readNews
In one paragraph

Article in Journal of cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Megan E GrahamPsychology, Simon Fraser University, Burnaby, Canada.ORCID https://orcid.org/0009-0003-0194-5460
Brittany SkovPsychology, University of Victoria, Canada.ORCID https://orcid.org/0009-0007-0755-4259
Zoë GilsonPsychology, University of Victoria, Canada.ORCID https://orcid.org/0009-0001-3374-1687
Calvin HeisePsychology, University of Victoria, Canada.ORCID https://orcid.org/0000-0003-2385-6242
Kaitlyn M FallowPsychology, University of Victoria, Canada.ORCID https://orcid.org/0000-0002-7178-9403
Eric Y MahPsychology, University of Victoria, Canada.ORCID https://orcid.org/0000-0001-5730-6498
D Stephen LindsayPsychology, University of Victoria, Canada.ORCID https://orcid.org/0000-0002-6439-987X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Basol et al. (2020) tested the "the Bad News Game" (BNG), an app designed to improve ability to spot false claims on social media. Participants rated simulated Tweets, then played either the BNG or an unrelated game, then re-rated the Tweets. Playing the BNG lowered rated belief in false Tweets. Here, four teams of undergraduate psychology students each attempted an extended replication of Basol et al., using updated versions of the original Bad News game. The most important extension was that the replications included a larger number of true Tweets than the original study and planned analyses of responses to true Tweets. The four replications were loosely coordinated, with each team independently working out how to implement the agreed plan. Despite many departures from the Basol et al. method, all four teams replicated their key finding: Playing the BNG reduced belief in false Tweets. But playing the BNG also reduced belief in true Tweets to the same or almost the same extent. Exploratory signal detection theory analyses indicated that the BNG increased response bias but did not improve discrimination. This converges with findings reported by Modirrousta-Galian and Higham (2023).

Indexed as

Bad News GameFake newsgameified inoculationsocial media

Identifiers

PMID37841671
PMCPMC10573624

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.