Diagnosticity of perceived message effectiveness in campaign message pretesting: multilevel analysis of the between-message correlation and message-pair standing comparisons

Abstract Whether perceived message effectiveness (PME) can be diagnostic for the differences of actual message effect (AME) in campaign message pretesting and how the diagnosticity of PME should be tested have been controversial. To address these issues, we conducted a survey involving 19 campaign messages (N = 760) and statistically analyzed the multilevel relationships among the between-message, within-message, and disaggregated across-message PME–AME correlations. From our analysis, we advocate for a multilevel analysis of between-message PME–AME correlation as the optimal method for testing PME’s diagnosticity. We also evaluated O’Keefe’s (2018) message-pair standing comparison method and suggested using statistical significance tests to examine PME differences between messages. The between-message PME–AME correlations were strongly positive (greater than 0.824), and PME standing corresponded with AME standing in 94.5% of the message-pairs. Our findings confirm that PME is diagnostic for AME.

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Publication Details

Journal
Journal of Communication
Published
2025-03-06
DOI
https://doi.org/10.1093/joc/jqaf006
Primary Topic
Media Influence and Health
Type
article
Field-Weighted Citation Impact
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article

Diagnosticity of perceived message effectiveness in campaign message pretesting: multilevel analysis of the between-message correlation and message-pair standing comparisons

Sungeun Chung, Youllee Kim, Byeong-Hyeon Lee
Journal of Communication
Media Influence and Health
article

Diagnosticity of perceived message effectiveness in campaign message pretesting: multilevel analysis of the between-message correlation and message-pair standing comparisons

Sungeun Chung, Youllee Kim, Byeong-Hyeon Lee
article en

Abstract

Abstract Whether perceived message effectiveness (PME) can be diagnostic for the differences of actual message effect (AME) in campaign message pretesting and how the diagnosticity of PME should be tested have been controversial. To address these issues, we conducted a survey involving 19 campaign messages (N = 760) and statistically analyzed the multilevel relationships among the between-message, within-message, and disaggregated across-message PME–AME correlations. From our analysis, we advocate for a multilevel analysis of between-message PME–AME correlation as the optimal method for testing PME’s diagnosticity. We also evaluated O’Keefe’s (2018) message-pair standing comparison method and suggested using statistical significance tests to examine PME differences between messages. The between-message PME–AME correlations were strongly positive (greater than 0.824), and PME standing corresponded with AME standing in 94.5% of the message-pairs. Our findings confirm that PME is diagnostic for AME.

Journal of CommunicationVol. 75(5)
University of Denver (US), University at Buffalo, State University of New York (US), Sungkyunkwan University (KR)
Openalex Percentile: Top 95%
Media Influence and Health
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