Identifying Message "Recipes" for High Perceived Effectiveness: Cognitive, Social, and Emotional Profiles of Vaping Public Education Messages Among Young Adults Who Vape
- 1University of California, Santa Barbara
Abstract
IntroductionVaping public education campaigns are a central prevention strategy for young adults (YAs), but message effectiveness varies widely and formative testing typically evaluates one message attribute at a time. This study examined how four perceptual dimensions--cognitive engagement, social relevance, emotional arousal, and emotional valence--relate to perceived message effectiveness (PME), and whether multiple combinations of these dimensions correspond to similarly high PME.
MethodsIn a cross-sectional online message-testing study conducted from March to April 2025, 540 U.S. YAs who vape each evaluated 15 messages randomly sampled from a corpus of 229 text-image vaping public education messages, yielding 8,100 message evaluations. Cross-classified multilevel models estimated associations between each perceptual dimension and PME. An Explainable Boosting Machine probed nonlinear associations, and k-means clustering of high-predicted-PME perceptual configurations identified distinct profiles. Analyses were conducted in 2026.
ResultsCognitive engagement (b = 0.20, 95% CI [0.18, 0.22]) and social relevance (b = 0.15, 95% CI [0.13, 0.17]) showed the strongest associations with PME, followed by emotional arousal (b = 0.06, 95% CI [0.04, 0.08]); emotional valence showed no linear association (b = 0.00, 95% CI [-0.02, 0.02]). The Explainable Boosting Machine revealed a U-shaped valence pattern, with higher predicted PME at both the negative and positive ends of the scale. Clustering yielded five distinct perceptual profiles with similarly high predicted PME (4.10-4.25).
ConclusionsMultiple perceptual configurations correspond to similarly high PME, supporting a configurational approach to formative message testing rather than a single optimal message formula.
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BibTeX
@misc{liu2026identifying,
title = {{Identifying Message "Recipes" for High Perceived Effectiveness: Cognitive, Social, and Emotional Profiles of Vaping Public Education Messages Among Young Adults Who Vape}},
author = {J. Liu and Q. Peng and M. Malik and Y. Wang and E. Norton and T. Ye and C. Markey and A. Worsdale and L. H. Sweet},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.04.26364669},
url = {https://www.medrxiv.org/content/10.64898/2026.10.04.26364669v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Identifying Message "Recipes" for High Perceived Effectiveness: Cognitive, Social, and Emotional Profiles of Vaping Public Education Messages Among Young Adults Who Vape
AU - J. Liu
AU - Q. Peng
AU - M. Malik
AU - Y. Wang
AU - E. Norton
AU - T. Ye
AU - C. Markey
AU - A. Worsdale
AU - L. H. Sweet
PY - 2026
DA - 2026/10/04
PB - medRxiv
DO - 10.64898/2026.10.04.26364669
UR - https://www.medrxiv.org/content/10.64898/2026.10.04.26364669v1
AB - IntroductionVaping public education campaigns are a central prevention strategy for young adults (YAs), but message effectiveness varies widely and formative testing typically evaluates one message attribute at a time. This study examined how four perceptual dimensions--cognitive engagement, social relevance, emotional arousal, and emotional valence--relate to perceived message effectiveness (PME), and whether multiple combinations of these dimensions correspond to similarly high PME. MethodsIn a cross-sectional online message-testing study conducted from March to April 2025, 540 U.S. YAs who vape each evaluated 15 messages randomly sampled from a corpus of 229 text-image vaping public education messages, yielding 8,100 message evaluations. Cross-classified multilevel models estimated associations between each perceptual dimension and PME. An Explainable Boosting Machine probed nonlinear associations, and k-means clustering of high-predicted-PME perceptual configurations identified distinct profiles. Analyses were conducted in 2026. ResultsCognitive engagement (b = 0.20, 95% CI [0.18, 0.22]) and social relevance (b = 0.15, 95% CI [0.13, 0.17]) showed the strongest associations with PME, followed by emotional arousal (b = 0.06, 95% CI [0.04, 0.08]); emotional valence showed no linear association (b = 0.00, 95% CI [-0.02, 0.02]). The Explainable Boosting Machine revealed a U-shaped valence pattern, with higher predicted PME at both the negative and positive ends of the scale. Clustering yielded five distinct perceptual profiles with similarly high predicted PME (4.10-4.25). ConclusionsMultiple perceptual configurations correspond to similarly high PME, supporting a configurational approach to formative message testing rather than a single optimal message formula.
ER -