Abstract
As it becomes increasingly urgent to address climate change, scholars have begun to explore how attitudes toward climate change are shaped, including the influence of messages people hear in the context of the ongoing climate change debate. What has not yet been addressed, however, is how these arguments might be affecting not only climate change attitudes (direct attitude change), but other environmental attitudes as well (lateral attitude change). To explore this possibility, two experimental studies were conducted in which participants read a message either supporting or opposing climate change action. Attitudes toward climate change, the closely related issues of recycling and alternative energy, and the distantly related issues of mandatory vaccination and gun control were assessed before and after message exposure. Results indicated that lateral attitude change (specifically, generalization) occurred for recycling and alternative energy, but not vaccination or gun control. Several possible moderators of these effects were explored, but were found to have only a limited impact. General implications for public opinion are discussed.
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Notes
Subjects were undergraduates at a large Midwestern university. The sample was predominantly female (62.2%), White (77.3%), economically (M = 4.49, SD = 1.40) and socially liberal (M = 5.22, SD = 1.30), and split between Republicans (37.8%), Democrats (31.1%), and Independents (28.9%).
Confirmatory factor analysis (Hunter and Gerbing 1982) was conducted to examine fit of the attitude data to the proposed 11-factor structure. The initial test of the model indicated unsatisfactory fit, but acceptable fit (given the small sample size, N = 45) was obtained by removing several items (RMSE = .09). Remaining items were averaged into a composite for each attitude.
Before the study, both arguments were assessed by an expert in social influence, revised until judged to be strong, then pilot tested. On average, participants (N = 179) rated both arguments as high in quality (M = 4.83, SD = 1.23) and legitimacy (M = 4.64, SD = 0.73).
Reported demographics pertain to this final group (N = 710). Attrition analyses revealed that age was the only variable significantly associated with attrition (r = .18). Given the number of tests performed and modest size of the correlation, however, this may simply be a chance finding.
CFAs were used to test the fit of the attitude data to a three-factor model. At the pretest, the initial test of the model indicated good fit (CFI = .97, RMSE = .05), but there were numerous residuals larger than would be expected by chance. Fit was improved by removing one recycling and two mandatory vaccination items (CFI = .99, RMSE = .02). This same factor structure exhibited excellent fit at both the post-test (CFI = .99, RMSE = .03) and delayed post-test (CFI = .99, RMSE = .03).
However, this effect may have resulted from a general trend for anti-action participants to develop more favorable attitudes over time. Even among those receiving an anti-action messsage, there was a tendency to develop more positive attitudes toward climate change between the pretest and delayed post-test, t (37) = 3.69, p < .001, r = .52.
A reverse mediation model in which recycling attitudes mediated the effect of the message on climate change attitudes was also checked. It exhibited poor fit to the data, χ2 (3, n = 563) = 11.70, p < .001, RMSE = .11.
Attrition analyses revealed that only age was a significant predictor of attrition (r = .21). Given that age was not expected to be relevant to study outcomes and the large number of tests performed, however, this finding was not particularly concerning.
CFAs were conducted to test fit of the data to the proposed factor structures for each measure. Initially, good fit was observed for all measures, but a few items across scales were associated with larger errors than would be expected to occur due to chance. Removing these problematic items produced excellent fit to the models of the pretest (CFI = .98, RMSE = .02) and post-test (CFI = .98, RMSE = .03) attitudes scales, pre-test ideology and preference for consistency scales (CFI = .98, RMSE = .03), and post-test author and message scales (CFI = .98, RMSE = .05). Remaining items were averaged within each factor to produce a composite score.
Reverse mediation models in which recycling or alternative energy attitudes mediated the effect of the message on climate change attitudes were also checked. For both, the message effect was nonexistent (β ≤ .01), indicating poor fit to the data. Global fit of the alternative energy model was also poor, χ2 (3, n = 283) = 8.55, p = .036, RMSE = .07; and global fit of the recycling model was substantially worse than for the generalization model, χ2 (3, n = 283) = 2.94, p = .401, RMSE = .07.
References
Alvaro EM, Crano WD (1997) Indirect minority influence: evidence for leniency in source evaluation and counterargumentation. J Pers Soc Psychol 72:949–964. https://doi.org/10.1037//0022-3514.72.5.949
Amazon Mechanical Turk. (n.d.). Retrieved from https://www.mturk.com/mturk/welcome
Boykoff M (2008) Lost in translation? United States television news coverage of anthropogenic climate change, 1995-2004. Clim Chang 86:1–11. https://doi.org/10.1007/s10584-007-9299-3
Cialdini RB, Trost MR, Newsom JT (1995) Preference for consistency: the development of a valid measure and the discovery of surprising behavioral implications. J Pers Soc Psychol 69:318–328. https://doi.org/10.1037/0022-3514.69.2.318
Core Writing Team, Pachauri, R. K., & Meyer, L. (Eds.). (2015). IPCC, 2014: Climate change 2014: synthesis report. Contribution of working groups I, II, and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Geneva, CH: IPCC
Crano WD, Chen X (1998) The leniency contract and persistence of majority and minority influence. J Pers Soc Psychol 74:1437–1450. https://doi.org/10.1037//0022-3514.74.6.1437
Dunlap RE, McCright AM, Yarosh JH (2016) The political divide on climate change: partisan polarization widens in the U.S. Environ Sci Policy Sustain Dev 58:4–23. https://doi.org/10.1080/00139157.2016.1208995
Feldman L, Maibach EW, Roser-Renoug C, Leiserowitz A (2012) Climate on cable: the nature and impact of global warming coverage on Fox News, CNN, and MSNBC. Int J Press/Polit 17:3–31. https://doi.org/10.1177/1940161211425410
Glaser T, Dickel N, Liersch B, Rees J, Süssenbach P, Bohner G (2015) Lateral attitude change. Personal Soc Psychol Rev 19:257–276. https://doi.org/10.1177/1088868314546489
Glum, J. (2015). At democratic debate, Bernie Sanders says climate change helps terrorism spread. Int Bus Times Retrieved from http://www.ibtimes.com/democratic-debate-bernie-sanders-says-climate-change-helps-terrorism-spread-2183773
Google News. (2017). Retrieved from news.google.com
Guber DL (2013) A cooling climate for change? Party polarization and the politics of global warming. Am Behav Sci 57:93–115. https://doi.org/10.1177/000276421246336
Hart SP, Feldman L (2014) Threat without efficacy? Climate change on U.S. network news. Sci Commun 36:325–351. https://doi.org/10.1177/1075547013520239
Hout MC, Papesh MH, Goldinger SD (2013) Multidimensional scaling. Wiley Interdiscip Rev Cogn Sci 4:93–103. https://doi.org/10.1002/wcs.1203
Hovland CI, Lumsdaine AA, Sheffield FD (1949) Experiments on mass communication. Princeton University Press, Princeton
Hunter JE, Gerbing DW (1982) Unidimensional measurement, second order factor analysis, and causal models. Res Organ Behav 4:267–320
Hunter JE, Hamilton MA (1987) PATH: a least squares static PATH analysis program [revised version]. Michigan State University, East Lansing
Iyengar S, Hahn KS (2009) Red media, blue media: evidence of ideological selectivity in media use. J Commun 59:19–39. https://doi.org/10.1111/j.1460-2466.2008.01402.x
Iyengar S, Hahn KS, Krosnick JA, Walker J (2008) Selective exposure to campaign communication: the role of anticipated agreement and issue public membership. J Polit 70:186–200. https://doi.org/10.1017/s0022381607080139
Jang SM, Hart SP (2015) Polarized frames on “climate change” and “global warming” across countries and states: evidence from twitter big data. Glob Environ Chang 32:11–17. https://doi.org/10.1016/j.gloenvcha.2015.02.010
Lord CG, Ross L, Lepper MR (1979) Biased assimilation and attitude polarization: the effects of prior theories on subsequently considered evidence. J Pers Soc Psychol 37:2098–2109. https://doi.org/10.1037//0022-3514.37.11.2098
Mackie DM (1987) Systematic and nonsystematic processing of majority and minority persuasive communications. J Pers Soc Psychol 53:41–52. https://doi.org/10.1037/0022-3514.53.1.41
Manata, B., Boster, F. J., Wittenbaum, G. M., & Bergan, D. E. (2018). Assessing the effects of partisan bias at the group level of analysis: a hidden profile experiment. Am Politics Res (Advance online publication). https://doi.org/10.1177/1532673X18788052
Mason L (2014) “I disrespectfully agree”: the differential effects of partisan sorting on social and issue polarization. Am J Polit Sci 59:128–145. https://doi.org/10.1111/ajps.12089
McCright AM, Dunlap RE (2011) The politicization of climate change and polarization in the American public’s views of global warming, 2001-2010. Sociol Q 52:155–194. https://doi.org/10.1111/j.1533-8525.2011.01198.x
Moscovici S (1980) Toward a theory of conversion behavior. Adv Exp Soc Psychol 13:209–239
Nilsson A, Bergquist M, Schultz WP (2017) Spillover effects in environmental behaviors, across time and context: a review and research agenda. Environ Educ Res 23:573–589. https://doi.org/10.1080/13504622.2016.1250148
Nisbet EC, Cooper KE, Ellithorpe M (2015) Ignorance or bias? Evaluating the ideological and informational drivers of communication gaps about climate change. Public Underst Sci 24:285–301. https://doi.org/10.1177/0963662514545909
Pettigrew TF (2009) Secondary transfer effect of contact: do intergroup contact effects spread to noncontacted outgroups? Soc Psychol 40(2):45–65. https://doi.org/10.1027/1864-9335.40.2.55
Petty RE, Cacioppo JT (1979) Effects of forewarning of persuasive intent and involvement on cognitive responses and persuasion. Personal Soc Psychol Bull 5:173–176. https://doi.org/10.1177/014616727900500209
Schuldt JP, Konrath SH, Schwarz N (2011) “Global warming” or “climate change”? Whether the planet is warming depends on question wording. Public Opin Quart 75:115–124. https://doi.org/10.1093/poq/nfq073
Schuldt JP, Roh S (2014) Of accessibility and applicability: how heat-related cues affect belief in “global warming” versus “climate change”. Soc Cogn 32:217–238. https://doi.org/10.1037/e578192014-269
Schulman, J. (2015). One thing missing from tonight’s GOP debate: Science Newsweek Retrieved from http://www.newsweek.com/one-thing-missing-tonights-gop-debate-serious-discussion-about-climate-change-392654
Stroud NJ (2010) Polarization and partisan selective exposure. J Commun 60:556–576. https://doi.org/10.1111/j.1460-2466.2010.01497.x
van der Linden SL, Leiserowitz AA, Feinberg GD, Maibach EW (2014) How to communicate the scientific consensus on climate change: plain facts, pie charts or metaphors? Clim Chang 126:255–262. https://doi.org/10.1007/s10584-014-1190-4
Wood W, Lundgren S, Ouellette JA, Busceme S, Blackstone T (1994) Minority influence: a meta-analytic review of social influence processes. Psychol Bull 115:323–345. https://doi.org/10.1037/0033-2909.115.3.323
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Cruz, S.M. Lateral attitude change on environmental issues: implications for the climate change debate. Climatic Change 156, 151–169 (2019). https://doi.org/10.1007/s10584-019-02474-x
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DOI: https://doi.org/10.1007/s10584-019-02474-x