Evidence map›Paper›PMID 42577378›Full record

ArticleFrontiers in psychology2026

Hedging, ambiguity, and the rejection of misinformation: evidence from Chinese readers.

Ruihong Li, Cun Fu

Abstract read
In one paragraph

Article in Frontiers in psychology, 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

2 authors.

Ruihong LiSchool of Foreign Languages and Cultures, Chongqing University, Chongqing, China.
Cun FuSchool of Foreign Languages and Cultures, Chongqing University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Misinformation poses a challenge not only because false claims circulate widely, but also because readers must make judgments about whether such claims are credible and whether they should be shared. While hedging is frequently observed in misinformation, its effects on audience evaluation remain insufficiently differentiated, particularly outside Western linguistic settings. This study examines whether two ambiguity-based hedging cues, source ambiguity and numerical ambiguity, shape readers' responses to Chinese misinformation in distinct ways. A total of 182 participants evaluated a set of Chinese misinformation claims that had previously been debunked by authoritative fact-checking sources. The statements were presented in one of four versions generated through the presence or absence of source ambiguity and numerical ambiguity. Participants' rejection of debunked misinformation claims, sharing intentions, and reaction times were analyzed using mixed-effects models. The results showed that both source ambiguity and numerical ambiguity were associated with greater rejection of debunked misinformation claims. Neither cue directly predicted sharing intention; however, greater rejection of debunked misinformation claims was associated with lower willingness to share it. Numerical ambiguity, but not source ambiguity, was additionally associated with shorter reaction times. These findings suggest that ambiguity-based hedging cues may function as cues of unreliability rather than persuasive devices, highlighting the importance of source traceability and numerical specificity in misinformation literacy interventions.

Indexed as

ambiguity cueshedgingmisinformation evaluationmisinformation rejectionnumerical ambiguityreaction timesharing intentionsource ambiguity

Identifiers

PMID42577378
PMCPMC13454060

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.