Appealing to fear: A meta-analysis of fear appeal effectiveness and theories

Melanie B Tannenbaum, Justin Hepler, Rick S Zimmerman, Lindsey Saul, Samantha Jacobs, Kristina Wilson, Dolores Albarracín, Melanie B Tannenbaum, Justin Hepler, Rick S Zimmerman, Lindsey Saul, Samantha Jacobs, Kristina Wilson, Dolores Albarracín

Abstract

Fear appeals are a polarizing issue, with proponents confident in their efficacy and opponents confident that they backfire. We present the results of a comprehensive meta-analysis investigating fear appeals' effectiveness for influencing attitudes, intentions, and behaviors. We tested predictions from a large number of theories, the majority of which have never been tested meta-analytically until now. Studies were included if they contained a treatment group exposed to a fear appeal, a valid comparison group, a manipulation of depicted fear, a measure of attitudes, intentions, or behaviors concerning the targeted risk or recommended solution, and adequate statistics to calculate effect sizes. The meta-analysis included 127 articles (9% unpublished) yielding 248 independent samples (NTotal = 27,372) collected from diverse populations. Results showed a positive effect of fear appeals on attitudes, intentions, and behaviors, with the average effect on a composite index being random-effects d = 0.29. Moderation analyses based on prominent fear appeal theories showed that the effectiveness of fear appeals increased when the message included efficacy statements, depicted high susceptibility and severity, recommended one-time only (vs. repeated) behaviors, and targeted audiences that included a larger percentage of female message recipients. Overall, we conclude that (a) fear appeals are effective at positively influencing attitude, intentions, and behaviors; (b) there are very few circumstances under which they are not effective; and (c) there are no identified circumstances under which they backfire and lead to undesirable outcomes.

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Figures

Figure 1
Figure 1
Forest plot of the effect sizes. Note: This forest plot includes point estimates and confidence intervals for all studies in the manuscript. The solid vertical line represents the combined effect size (d = .29).
Figure 2
Figure 2
Funnel plot of effect sizes. Note: Effect size (d) is plotted on the x-axis and standard error on the y-axis. The solid vertical line represents the combined effect size (d = .29). The dotted line represents the x-intercept (x = 0) for a reference line. The white region represents the inside of the 95% pseudo confidence interval, whereas the shaded region represents the outside (i.e., the area of statistical significance).
Figure 3
Figure 3
Normal quantile plot. Note: The dashed lines represents a 95% confidence band. The line on the diagonal indicates normality.

Source: PubMed

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