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. 2025 Aug 3:11:20552076251365004.
doi: 10.1177/20552076251365004. eCollection 2025 Jan-Dec.

Fact-checking of health information on social networking sites: The moderating role of gender

Jiabei Xia  1 , Tailai Wu  1 , Zhuo Chen  2   3 , Liqin Zhou  1
Affiliations

Fact-checking of health information on social networking sites: The moderating role of gender

Jiabei Xia et al. Digit Health. .

Abstract

Background: This study aims to explore the factors related to fact-checking health information and the moderating role of gender on the effects of explored factors. Based on social cognitive theory (SCT) and social role theory (SRT), we established a research model to explore the factors of fact-checking on health information and the role of gender.

Methods: To validate the research model, data were collected by survey method and analyzed by partial least squares technique.

Results: The analysis results present that personal factors (self-efficacy and outcome expectancy), and environmental factors (perceived skepticism and perceived ambiguity) have significant impacts on fact-checking about health information. Meanwhile, our results reveal that gender moderates the effects of outcome expectancy, perceived skepticism, and perceived ambiguity on users' fact-checking.

Conclusion: Our study uses SCT to explore the factors impacting fact-checking, while we combine it with SRT to understand the gender differences in the process of fact-checking health information in social networking sites.

Keywords: Fact-checking; gender differences; social cognitive theory; social networking sites; social role theory.

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Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Research model and hypothesized relationships.
Figure 2.
Figure 2.
Structural results. Note: *=0.05 significance; **=0.01 significance; ***=0.001 significance.
Figure 3.
Figure 3.
(a) PLS analysis for the male sample (N1 = 133). Note: *=0.05 significance; **=0.01 significance; ***=0.001 significance; ns = statistically not significant. (b) PLS analysis for the female sample (N2 = 168). Note: *=0.05 significance; **=0.01 significance; ***=0.001 significance; ns = statistically not significant. PLS: partial least square.
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