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The persuasive effects of narrative entertainment: a meta-analysis of recent experiments

Published online by Cambridge University Press:  07 October 2025

Bardia Rahmani
Affiliation:
Harvard Academy for International and Area Studies, Harvard University, Cambridge, MA, USA
Beatrice Montano
Affiliation:
Department of Political Science, Columbia University, New York, NY, USA
Dylan W. Groves
Affiliation:
Department of Political Science, Lafayette College, Easton, PA, USA
Donald P. Green*
Affiliation:
Department of Political Science, Columbia University, New York, NY, USA
*
Corresponding author: Donald P. Green; Email: donald.p.green@gmail.com
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Abstract

Is narrative entertainment simply a form of recreation, or does it have meaningful effects on public opinion? Building on prior reviews, we present a meta-analysis of 377 findings from 77 experiments evaluating the persuasive effects of narrative radio, television and film, including a growing body of work from low- and middle-income countries. Our sample includes both entertainment-first narratives – popular media created primarily to entertain but which may incidentally shape audiences’ attitudes, beliefs and behaviors – and education-first narratives designed by policymakers to inform, persuade or motivate public action. Using a hierarchical-effects model, we assess narrative media’s influence across a wide range of settings and issue domains. The results suggest that narrative entertainment is quite influential, with sizable persuasive effects that remain apparent weeks after initial exposure. A smaller literature reports head-to-head tests of the relative effectiveness of narrative vs non-narrative messages; although inconclusive, the evidence suggests that narratives may be only slightly more persuasive than non-narrative messages. If true, this finding would imply that the main advantage of narratives may be their ability to attract and engage large and diverse audiences. We conclude by calling attention to gaps in the literature and proposing avenues for further research.

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Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial licence (http://creativecommons.org/licenses/by/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.
Copyright
© The Author(s), 2025. Published by Cambridge University Press.
Figure 0

Table 1. Outcome types

Figure 1

Figure 1. Location of included RCTs.

Figure 2

Figure 2. Distribution of study designs across settings and over time.

Figure 3

Figure 3. Diagnostic test for publication bias.

Figure 4

Figure 4. Summary of main results: narrative message vs no message/placebo message.

Note.N reports the total number of observations used in the analysis, where each observation is a finding within each of the K studies or experimental comparisons.
Figure 5

Figure 5. Summary of heterogeneous effects: narrative message vs no message/placebo message, all outcome types combined.

Note.N reports the total number of observations used in the analysis, where each observation is a finding within each of the Kstudies or experimental comparisons. The p-value reported refers to the estimate provided by the hierarchical model of the difference between the meta-estimates of the subgroup considered compared to the baseline group (the ‘Field’ group in the Settings analysis, the ‘Other’ group in the Topics analysis and the single other available group in all other cases).
Figure 6

Figure 6. Summary of relative results: narrative message vs non-narrative message.

Note.N reports the total number of observations used in the analysis, where each observation is a finding within each of the Kstudies or experimental comparisons.
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