A Match Made in Language: Examining the Role of Linguistic Similarity in Adolescents’ Preference for Persuasive Health Messages

Engaging adolescents in digital environments is notoriously difficult. A common strategy is message personalization, yet most efforts focus on personalizing what is said rather than how it is expressed. This is a missed opportunity, as youth communication that truly speaks their language requires attention to style as well as content. Digital communication environments enable such stylistic adaptation by revealing users’ expression patterns that can be leveraged for personalization. Yet little is known about how adolescents respond to persuasive messages written in a similar linguistic style, or how such similarity is best operationalized. Addressing these gaps, this preregistered study tests whether adolescents prefer social media health messages that are more similar to their linguistic style and identifies which linguistic categories are most effective in eliciting positive responses. We analyzed donated WhatsApp conversation data from 191 Dutch adolescents (aged 13–15) to calculate individual linguistic profiles and design Instagram-style health messages that varied in linguistic similarity. Participants then evaluated 22 message pairs, each manipulating one linguistic category. Bayesian analyses yielded inconclusive evidence that linguistic similarity influenced message preference or personalization, and moderate evidence against effects on perceived effectiveness. However, adolescents consistently preferred messages that were positively valenced and low in complexity, regardless of linguistic similarity. These findings suggest that positive, easy-to-read messages may be an effective strategy for digital youth engagement. Furthermore, we discuss the implications for computer-mediated style matching, including algorithmic approaches, large language models, and future theoretical development.