A Multilevel Analysis of Antimarijuana Public Service Announcement Effectiveness

René Weber, Amber Westcott-Baker, Grace Anderson

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


In public-health campaign research, 3 prominent theories of persuasion and media effects-elaboration likelihood model (ELM), activation model of information exposure (AMIE), and limited capacity model of motivated mediated message processing (LC4MP)-have been used to predict message effectiveness. Although conceptually overlapping, these theories suggest contradictory predictions about individual-level and message-level factors on persuasion outcomes. In this study, we contrast and test competing predictions of antidrug message effectiveness from 3 recent publications that draw on ELM, AMIE, and LC4MP. We use televised antimarijuana messages, young-adult samples, and a multilevel modeling approach. Significant interactions between individual- and message-level factors were found predicting message effectiveness as theory dictates; these results replicate some, but not all of the findings from the aforementioned publications.

Original languageEnglish
Pages (from-to)302-330
Number of pages29
JournalCommunication Monographs
Issue number3
StatePublished - Sep 2013


  • Antidrug Public Service Announcements
  • Elaboration Likelihood Model
  • Health Communication
  • Multilevel Analysis
  • Persuasion


Dive into the research topics of 'A Multilevel Analysis of Antimarijuana Public Service Announcement Effectiveness'. Together they form a unique fingerprint.

Cite this