Gist Knowledge and Misinformation Acceptance: An Application of Fuzzy Trace Theory

ABSTRACT

Applying fuzzy trace theory to misinformation related to COVID-19, the present study (a) examines the roles of gist knowledge in predicting misinformation acceptance, and (b) further examines whether a gist cue in fact checking scales affects the level of gist knowledge. Study 1 (a survey) showed that categorical gist knowledge was negatively related to misinformation acceptance, whereas ordinal gist knowledge was not, when both types of knowledge were included in the model. In addition, Study 2 (an experiment) showed that fact checking scales containing a categorical gist cue resulted in greater categorical gist knowledge.

Acknowledgment

This research was supported by the School of Media and Communication at Korea University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10410236.2023.2197306.

Notes

1. The original fact checking scale used by the SNU factcheck was as follows: (1) “not true at all,” (2) “mostly not true,” (3) “half true,” (4) “mostly true,” and (5) “true.” We renamed the five categories into four categories: (1) “very false,” (2) “mostly false,” (3) “mostly true,” and (4) “very true.” We did not use the “half true” statements in SNU factcheck because we had to measure gist knowledge (either “true” or “false”). In addition, we used two statements with a definite conclusion from WHO advice (“Antibiotics cannot prevent COVID-19,” “An alcohol-based hand sanitizer does not create antibiotic resistance”). We concluded that both statements are “very true” based on the WHO advice, although WHO did not use fact checking scales.

Additional information

Funding

The work was supported by the Korea University.