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Gain-Loss Message Framing Analysis×Elaboration Likelihood Analysis×
DziedzinaCommunicationCommunication
RodzinaProcess / pipelineProcess / pipeline
Rok powstania19971986
TwórcaRothman & Salovey (health framing synthesis); roots in Kahneman & TverskyRichard Petty & John Cacioppo
TypExperiment comparing gain- versus loss-framed persuasive messagesDual-process experimental analysis of attitude change
Źródło pierwotneRothman, A. J., & Salovey, P. (1997). Shaping perceptions to motivate healthy behavior: The role of message framing. Psychological Bulletin, 121(1), 3–19. DOI ↗Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication and Persuasion (pp. 1–24). New York: Springer. DOI ↗
Inne nazwyMessage framing analysis, Gain-loss framing study, Valence framing experiment, Kazanç-Kayıp Mesaj Çerçeveleme AnaliziELM analysis, Dual-process persuasion experiment, Central and peripheral route analysis, Ayrıntılandırma Olasılığı Modeli Analizi
Pokrewne44
PodsumowanieGain-loss message framing analysis is an experimental method for testing whether a persuasive appeal works better when it stresses the benefits of acting (gain frame) or the costs of not acting (loss frame). Grounded in prospect theory and synthesized for health communication by Rothman and Salovey, it predicts that loss frames are more persuasive for risky detection behaviors while gain frames win for safe prevention behaviors.Elaboration likelihood analysis applies Petty and Cacioppo's 1986 Elaboration Likelihood Model (ELM) to study persuasion through experiments that cross message argument quality with peripheral cues under varying levels of audience motivation and ability to think. It identifies whether attitude change travels the central route — effortful scrutiny of arguments — or the peripheral route, reliance on simple cues like source attractiveness or message length.
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ScholarGatePorównaj metody: Gain-Loss Message Framing Analysis · Elaboration Likelihood Analysis. Pobrano 2026-06-24 z https://scholargate.app/pl/compare