ABSTRACT
HPV has long been constructed as a sex-specific virus. Boys and men largely perceive the virus as not related to themselves and thus develop a female-specific schema on HPV. The present study investigates message strategies for promoting HPV vaccination among heterosexual young men in the United States. Through an online experiment, this study examined the effects of reference point (self, other, vs. self-other) and message framing (gain vs. loss) on processing fluency, optimistic bias, and behavioral intentions. The findings showed a schema-matching pattern in facilitating information processing, and a schema-mismatching pattern in attenuating optimistic bias. Specifically, other-referencing messages that related the outcomes of getting vaccinated for HPV to the message recipients’ sexual partners promoted processing fluency and widened the self-other gap in perceived susceptibility to HPV, regardless of the message frame. By contrast, self-other-referencing messages that highlighted the outcomes regarding themselves and their sex partners enhanced processing fluency and mitigated optimistic bias. Moreover, the attenuation in optimistic bias increased the participants’ information seeking intentions and the likelihood that they would share the messages on social media. The implications for health message design are discussed from a schema-based, message-tailoring perspective.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. A previous study conducted by the authors revealed a significant interaction effect between message framing and reference point with a small to medium effect size Cohen’s d = 0.43 (Huang et al., Citation2019). Therefore, we adopted this as the benchmark for calculating the required sample size for this study.
2. We conducted an exploratory factor analysis to explore whether there were any underlying dimensions within the items. The results revealed two potential factors with eigenvalues greater than 1 (Factor 1: Eigenvalue = 4.520; Factor 2: Eigenvalue = 1.019), but almost all items have large cross-loading values on both factors. Besides, the two factors are not theoretically meaningful or interpretable. Therefore, we decided to divide behavioral intentions into multiple items, each item corresponding to one unique behavior.