The authors have declared that no competing interests exist.
To make informed choices about how to address climate change, members of the public must develop ways to consider established facts of climate science and the uncertainties about its future trajectories, in addition to the risks attendant to various responses, including non-response, to climate change. One method suggested for educating the public about these issues is the use of simple mental models, or analogies comparing climate change to familiar domains such as medical decision making, disaster preparedness, or courtroom trials. Two studies were conducted using online participants in the U.S.A. to test the use of analogies to highlight seven key decision-relevant elements of climate change, including uncertainties about when and where serious damage may occur, its unprecedented and progressive nature, and tradeoffs in limiting climate change. An internal meta-analysis was then conducted to estimate overall effect sizes across the two studies. Analogies were not found to inform knowledge about climate literacy facts. However, results suggested that people found the medical analogy helpful and that it led people—especially political conservatives—to better recognize several decision-relevant attributes of climate change. These effects were weak, perhaps reflecting a well-documented and overwhelming effect of political ideology on climate change communication and education efforts in the U.S.A. The potential of analogies and similar education tools to improve understanding and communication in a polarized political environment are discussed.
Efforts to educate citizens about climate change have predominantly treated the topic as one of standard science education. The main goal has been to improve “climate literacy” by conveying established facts about the nature of climatic phenomena. Understanding of climate change is typically assessed by comparing people’s beliefs about climate change facts—including its human causes—to the scientific consensus [
We have argued elsewhere [
If the goal of climate change education is to create a public that is appropriately informed for decision making, then one key aspect that must be conveyed is that risk and uncertainty are both inherent in climate change. Treating the topic as one in which decisions can be based on established facts alone creates a mistaken impression of climate change risks. It also allows any attack on ideas portrayed as established fact to support the view that climate science is fundamentally in doubt, justifying inaction. People need to understand the progressive nature of climate change as well as the uncertainties to have informed debates about how to address the risks, costs, and benefits of possible actions and inaction.
The public is familiar with uncertain risks in many other domains, such as public health, terrorism, and earthquakes, which create possibility (but not the guarantee) that bad things may happen. People are also familiar with the idea that the exact timing and location of such events cannot be predicted with certainty. Experts in these arenas are often quite blunt with the public about these uncertainties [
Conveying uncertainty should be part of climate change education if its primary goal is to bring the public’s beliefs and understandings into line with scientific consensus. For informing climate-related decisions, education has the slightly different goal of helping citizens develop informed opinions about how to address climate risks. Informed choice requires understanding both of climate facts and of uncertainties: both what is known about climate change and what is potentially important, but uncertain. Many of the outcomes that motivate preemptive action on climate change most strongly (and are subject to the most intense debates) involve uncertain possibilities in the climate future.
Informing decisions does not imply bringing the beliefs of the public into line with any particular policy agenda. Differences of opinion are to be expected in dealing with any kind of risk. The goal is to support better-informed discussions and debates. This goal has been elusive in the U.S.A., where climate change is a highly polarized issue [
We propose that to enable well-informed choices about responses to the risks of climate change, citizens should develop understanding not only of key climate facts, but also of key uncertainties and decision-relevant attributes of climate change. We recognize that some attributes will be more important for some people than others [
Climate change is
Climate change is
Climate change is
Climate change can take the climate outside historical experience, such that
There are
The things people do that cause climate change also benefit people, so there can be
The potential negative effects of climate change are linked, such that actions to slow or stop climate change
Although acceptance of some of these elements of the climate science consensus may support policy preferences that favor actions to mitigate climate change (elements 2, 4, and 7), acceptance of others may support preferences against mitigation (elements 5 and 6).
Simple mental models in the form of analogies may help convey these difficult ideas about climate change. Cognitive psychology research suggests that a good simple model should (1) be factual and not misleading, (2) use a familiar domain to explain the unfamiliar, (3) be novel enough to capture interest, and (4) allow for correct extrapolations based on understanding of the known domain [
This paper examines the potential of simple models for supporting not only climate literacy, but also the citizenship objectives of characterizing climate risks and uncertainties, and informing decisions given these uncertainties. For simple models to achieve all this, we have proposed that they should also (5) help users take into account uncertainty in climate projections, (6) recognize the need to consider options in the face of uncertainty, and (7) highlight unresolved issues in ways that provide space and conceptual guidance for public discourse among people who may initially disagree [
Although climate “facts” have been successfully conveyed through the use of simple mental models such as the bathtub and greenhouse analogies mentioned above, other research has been less promising. Likening climate change to a medical decision or to an engineering problem has not been more helpful than simple direct messages in increasing understanding of climate facts or the proportion of scientists who agree about anthropogenic climate change [
A multitude of mental models could be used to explain climate change. We focus on three that capture some key attributes of the challenges of decision-making under uncertainty that climate change presents.
We expected a medical analogy to be most relevant to climate decision-making based on our own writing and the research of others [
Others have used analogies to disaster preparedness or insurance against disasters [
Finally, we have included the analogy to a courtroom trial in which lawyers on competing sides argue about facts to influence a decision. This analogy is invoked implicitly by some opponents of climate change mitigation, who justify their position on the ground that there remains some scientific doubt. We believe this analogy is less helpful than the others, as it puts people in the mindset of judging the existence of climate change rather than considering options for action. However, it does embody several decision elements. A courtroom trial implies a human cause to a problem (or crime) (Element 1) and an event that has already occurred and is thus difficult to reverse (Element 3). It may also imply some sense of progression, analogous to a defendant’s likelihood of recidivism (Element 2). But given that trials usually deal with past rather than future harm, the analogy does not evoke issues of unprecedented future harm (Element 4), uncertainties of future harm (Element 5), tradeoffs in preventing those harms (Element 6), or treating the underlying issues rather than deciding the fate of the current defendant (Element 7).
This research tests whether analogies can help educate people on uncertainty management, as well increase climate literacy as examined in previous research [
Given the intense political polarization surrounding climate change in the U.S.A. [
Participants were 400 U.S. adults recruited via Amazon’s Mechanical Turk (MTurk) [
All materials were administered using Qualtrics software. All study materials and procedures were approved by the Vanderbilt University Institutional Review Board.
After providing written consent, participants read one of four passages describing climate change (see
Reading comprehension was tested by asking, “In the passage you just read, was climate change described as being like any of the following?” with response options of (1 =
After reading a passage, participants were asked how much it helped them think about climate change (1 =
Climate science literacy was assessed by having participants indicate which of several causes of climate change are true and which are false, using the measure from Guy et al. [
Participants reported their level of agreement (1 =
Two statements related to anthropogenic climate change formed a composite (Element 1): “The climate is changing” and “Climate change is caused in large part by human activities” (α = .77). The idea that climate change is progressive (Element 2) was assessed with the item “Climate change will get worse if we don’t do something about it.” Element 3 was measured with the statement, “Climate change is hard to reverse.” The statement, “Climate change may cause catastrophes, such as storms, floods, and wildfires greater than ever seen before” captured the idea that climate change will cause extreme unprecedented events (Element 4). The uncertainty of climate change’s exact effects (Element 5) was measured with the item, “It is difficult to predict when and where serious damage from climate change will occur.” Beliefs about tradeoffs (Element 6) were assessed with two items: “The things that people do that cause climate change also promote human comfort and convenience” and “Stopping climate change would be very disruptive to society.” A composite of these two items was considered, but they did not form a reliable scale (α = .26), and thus were analyzed separately. Finally, Element 7—the importance of mitigation (rather than just adaptation)—was assessed with the item “It is important to reduce the causes of climate change because that reduces all the negative effects—other actions only deal with one effect at a time.”
Participants reported demographic characteristics including age, gender, and race. They also indicated their political affiliation (1 = Republican, 2 = Republican-leaning independent, 3 = Independent, 4 = Democratic-leaning independent, 5 = Democrat) and overall political ideology ranging from 1 =
Participants who failed the reading comprehension check were removed from the dataset (
Study 1 | ||||||
Climate literacy | Scientific consensus | |||||
Predictor | ||||||
MA | 0.47 |
0.27 | .01 | 5.25 | 2.89 | .01 |
DA | -0.20 | 0.28 | .00 | 2.71 | 2.95 | .00 |
TA | 0.10 | 0.29 | .00 | 6.29 |
3.07 | .01 |
2.16 |
1.75 | |||||
0.02 | .02 | |||||
Ideology | 0.59 |
0.10 | 5.69 |
1.02 | .08 | |
38.56 |
30.82 |
|||||
.10 | .08 | |||||
MA x Ideo. | 0.05 | 0.27 | -5.28 |
2.87 | .01 | |
DA x Ideo. | 0.33 | 0.27 | -4.32 | 2.90 | .01 | |
TA x Ideo. | 0.10 | 0.27 | -2.19 | 2.93 | .00 | |
0.61 | 1.33 | |||||
.01 | .01 | |||||
3.80 | 78.59 | |||||
1.85 | 19.87 | |||||
Study 2 | ||||||
Climate literacy | Scientific consensus | |||||
Predictor | ||||||
MA | -0.12 | 0.30 | -0.54 | 3.35 | ||
0.16 | 0.03 | |||||
.01 | .00 | |||||
Ideology | 0.67 |
0.13 | 5.92 |
1.46 | ||
28.93 |
16.57 |
|||||
.13 | .08 | |||||
MA x Ideo. | -0.07 | 0.25 | -1.35 | 2.93 | ||
0.08 | 0.21 | |||||
.00 | .00 | |||||
3.83 | 76.65 | |||||
2.03 | 22.83 |
†
*
***
df for Study 1: Step 1 (3,349), Step 2 (1, 348), Step 3 (3, 345)
df for Study 2: Step 1 (1,188), Step 2 (1, 187), Step 3 (1,186)
MA = Medical Analogy condition, DA = Disaster Preparedness Condition, TA = Trial Analogy
Condition, Ideo. = political ideology
Multicollineary tests (VIF and Tolerance) were with acceptable ranges (< 10 and > .10, respectively).
Predictor | Element 1: ACC |
Element 2: Progressive |
Element 3: Hard to reverse |
Element 4: Unprecedented |
||||||||
MA | 0.21 | 0.12 | .01 | 0.19 | 0.14 | .00 | 0.23 |
0.13 | .01 | 0.29 |
0.13 | .01 |
DA | 0.03 | 0.12 | .00 | -0.07 | 0.15 | .00 | 0.06 | 0.13 | .00 | 0.09 | 0.13 | .00 |
TA | 0.10 | 0.13 | .00 | 0.05 | 0.15 | .00 | 0.14 | 0.13 | .00 | 0.29 |
0.14 | .01 |
1.21 | 1.19 | 1.27 | 2.33 |
|||||||||
.01 | .01 | .01 | .02 | |||||||||
Ideology | 0.38 |
0.04 | 0.21 | 0.42 |
0.05 | .18 | 0.12 |
0.05 | .02 | 0.34 |
0.05 | .14 |
96.28 |
77.06 |
7.31 |
58.42 |
|||||||||
.21 | .18 | .02 | .14 | |||||||||
MA x Ideo. | -0.28 |
0.11 | .01 | -0.31 |
0.13 | .01 | -0.04 | 0.13 | .00 | -0.32 |
0.13 | .02 |
DA x Ideo. | -0.05 | 0.11 | .00 | 0.05 | 0.14 | .00 | 0.06 | 0.13 | .00 | -0.04 | 0.13 | .00 |
TA x Ideo. | -0.10 | 0.11 | .00 | -0.15 | 0.14 | .00 | 0.23 | 0.13 | .01 | -0.30 |
0.13 | .01 |
0.02 |
2.92 |
1.70 | 3.47 |
|||||||||
.02 | .02 | .01 | .03 | |||||||||
4.17 | 4.19 | 4.10 | 4.15 | |||||||||
0.81 | 0.98 | 0.86 | 0.91 | |||||||||
Predictor | Element 5: Uncertainties |
Element 6a: Comfort |
Element 6b: Disruptive |
Element 7: Mitigation |
||||||||
MA | 0.00 | 0.13 | .00 | 0.17 | 0.12 | .01 | -0.17 | 0.15 | .00 | 0.31 |
0.13 | |
DA | 0.04 | 0.13 | .00 | 0.22 |
0.12 | .01 | -0.01 | 0.16 | .00 | 0.31 |
0.13 | |
TA | -0.33 |
0.14 | .02 | 0.24 |
0.13 | .01 | -0.30 |
0.16 | .01 | 0.50 |
0.14 | |
3.12 |
1.53 | 1.52 | 4.69 |
|||||||||
.03 | .01 | .01 | .04 | |||||||||
Ideology | 0.02 | 0.05 | .00 | 0.13 |
0.04 | .02 | -0.25 |
0.06 | .06 | 0.30 |
0.05 | |
0.16 | 8.20 |
20.43 |
43.90 |
|||||||||
.00 | .02 | .06 | .11 | |||||||||
MA x Ideo. | 0.09 | 0.13 | .00 | -0.35 |
0.12 | .02 | -0.12 | 0.16 | .00 | -0.27 |
0.12 | .01 |
DA x Ideo. | 0.10 | 0.13 | .00 | -0.16 | 0.12 | .00 | -0.13 | 0.16 | .00 | -0.05 | 0.13 | .00 |
TA x Ideo. | 0.32 |
0.14 | .02 | -0.24 |
0.12 | .01 | -0.01 | 0.16 | .00 | -0.33 |
0.13 | .02 |
2.05 | 2.98 |
0.39 | 3.28 |
|||||||||
.02 | .02 | .00 | .02 | |||||||||
3.89 | 3.91 | 2.90 | 3.89 | |||||||||
0.89 | 0.82 | 1.06 | 0.90 |
†
*
**
***
1df: Step 1 (1,349), Step 2 (3, 348), Step 3 (3, 345)
2df: Step 1 (1,346), Step 2 (3, 345), Step 3 (3, 342)
3df: Step 1 (1,348), Step 2 (3, 347), Step 3 (3, 444)
MA = Medical Analogy condition, DA = Disaster Preparedness Condition, TA = Trial Analogy Condition, Ideo. = political ideology
Multicollineary tests (VIF and Tolerance) were with acceptable ranges (< 10 and > .10, respectively).
The means for each dependent measure by condition are shown in
However, due to the importance of political ideology in climate change messaging, our focal analyses used hierarchical linear regressions (HLRs) to test the effects of condition, ideology, and their interactions on each of the dependent measures. Conditions were dummy-coded using the control as the referent. Political ideology was not mean-centered, but rather recoded so that the midpoint of the scale (moderate) was zero to create a meaningful intercept. All analyses included conditions in Step 1, political ideology in Step 2, and the interactions between ideology and each condition in Step 3.
Participants in all three analogy conditions rated their passages as more helpful than control participants; this effect was particularly strong for the medical analogy (MA:
Climate literacy descriptive statistics and regression estimates are shown in
Participant estimates of the scientific consensus on climate change were also examined. Only 6.2% participants reported the exact 97% number used elsewhere [
Condition, ideology, and their interaction were used to predict decision-relevant beliefs about climate change (
A number of condition effects emerged, but most were qualified by interactions. The exception was assignment to the DA condition, which was associated with greater belief in the importance of mitigation (Element 7), but not affected by ideology. Ideology was also a significant predictor of most decision-relevant outcomes. For example, liberal ideology positively predicted the belief that climate change is difficult to reverse (Element 3) and negatively predicted belief that mitigation would be disruptive (Element 6b). All other main effects were qualified by interactions, as outlined below.
A consistent pattern emerged in which ideology interacted with MA condition when predicting decision-relevant beliefs (see
Despite the predominant findings that the MA condition x ideology interaction was most predictive of decision-relevant attributes, the interaction between ideology and assignment to the TA condition also predicted a few outcomes. Simple slope tests revealed that these interactions were also driven by conservatives and moderates. Conservatives in the TA condition reported greater belief in unprecedented consequences of climate change (Element 4:
Replicating past research, political ideology emerged as a strong predictor of reactions to climate messaging. Yet the current study extended beyond this finding to reveal the medical analogy as a promising way to achieve understanding of key decision-relevant elements of climate change processes, especially among non-liberals.
Our results were consistent with previous research on the use of analogies for climate change [
The medical analogy had clear and consistent effects on understandings relevant to climate change decisions. For five out of the eight elements tested, conservatives (and to a lesser degree, moderates) who read the medical analogy reported greater agreement with these considerations than did those in the control group. Therefore, at least for the decision-relevant elements identified in previous research [
Study 1 demonstrated that using analogies for climate change, particularly a medical analogy, could encourage people to think about some of the decision-relevant attributes of climate change that are less commonly discussed in studies of climate literacy. Political liberals tended to recognize many of these elements irrespective of the framing of climate change, but using an analogy to a familiar context for decision-making under uncertainty increased recognition of these elements among conservatives. However, Study 1 did not test whether recognition of these decision-relevant elements translated into change in preferences about climate change action. For example, if conservatives who read about a medical analogy to climate change became more convinced of the need for mitigation (rather than simply adaptation), would this analogy also provoke support for mitigation policies? Study 2 set out to answer these questions.
Two hundred American participants were recruited via MTurk in exchange for $1.00 in December of 2015. Sample demographics are shown in
Given the lack of promising results for the disaster-preparedness and trial analogies in Study 1, only the medical analogy was tested in Study 2. Participants were randomly assigned to either the medical analogy (MA) or the control condition. A set of questions was added to assess participants’ policy preferences. Otherwise, all procedures and measures were identical to Study 1. This study was approved by the Institutional Review Board of the University of Michigan.
Participants reported their preferences for various policy approaches to climate change. Participants first read a statement that “People have suggested different approaches to deal with the threats that we hear come from climate change.” They then used a 7-point bipolar scale to indicate which of two approaches was closest to their own view: “Wait to take action to reduce climate risks until we know that there are real dangers” or “Take action quickly to reduce the use of fossil fuels and other activities that contribute to climate change.”
Participants were also asked how much they supported each of nine policies that have been proposed to mitigate climate change (1 =
Ten participants were removed from the dataset for failing in reading comprehension, leaving a total
Dependent measures were assessed with the same analytic strategy as in Study 1. Means are shown in
As in Study 1, both assignment to the medical analogy condition and liberal ideology were associated with perceived helpfulness of the passage in thinking about climate change (MA:
All climate literacy results are shown in
Responses regarding the seven decision-relevant attributes of climate change are summarized in
Predictor | Element 1: ACC | Element 2: Progressive | Element 3: Hard to reverse | Element 4: Unprecedented | ||||
MA | -0.08 | 0.12 | 0.10 | 0.15 | -0.01 | 0.13 | 0.01 | 0.15 |
0.43 | 0.41 | 0.01 | 0.00 | |||||
.00 | .00 | .00 | .00 | |||||
Ideology | 0.28 |
0.05 | 0.34 | 0.06 | 0.15 |
0.06 | 0.33 | 0.06 |
32.89 |
28.06 |
7.62 |
28.33 |
|||||
.15 | .13 | .04 | .13 | |||||
MA x Ideo. | -0.09 | 0.10 | -0.09 | 0.13 | 0.01 | 0.11 | -0.07 | 0.12 |
0.90 | 0.48 | 0.00 | 0.36 | |||||
.00 | .00 | .00 | .00 | |||||
4.14 | 4.13 | 4.03 | 4.08 | |||||
0.80 | 1.04 | 0.85 | 0.99 | |||||
Predictor | Element 5: Uncertainties | Element 6a: Comfort | Element 6b: Disruptive | Element 7: Mitigation | ||||
MA | 0.12 | 0.13 | 0.01 | 0.13 | 0.18 | 0.15 | 0.05 | 0.14 |
0.84 | 0.01 | 1.45 | 0.12 | |||||
.00 | .00 | .01 | .00 | |||||
Ideology | 0.00 | 0.06 | 0.14 | 0.06 | -0.27 |
0.06 | 0.32 |
0.06 |
.00 | 5.84 |
17.49 |
28.27 |
|||||
.00 | .03 | .08 | .13 | |||||
MA x Ideo. | 0.23 |
0.12 | -0.12 | 0.12 | 0.23 |
0.13 | 0.01 | 0.12 |
3.94 |
1.14 | 3.25 |
.01 | |||||
.02 | .01 | .02 | .00 | |||||
4.04 | 3.80 | 2.95 | 3.82 | |||||
0.88 | 0.88 | 1.02 | 0.96 |
†
*
**
***
df for all regressions: Step 1 (1, 188), Step 2 (1, 187), Step 3 (1, 186)
MA = Medical Analogy condition, Ideo. = political ideology
Multicollineary tests (VIF and Tolerance) were with acceptable ranges (< 10 and > .10, respectively).
Only liberal ideology predicted the beliefs in anthropogenic climate change (composite α = .75: Element 1), that climate change is progressive (Element 2), that it is difficult to reverse (Element 3) that climate change events are unprecedented (Element 4), that the causes of climate change also have benefits (Element 6a), and that mitigation (rather than adaptation) is important for reducing the full set of climate change risks (Element 7). Furthermore, the more liberal a participant’s ideology, the less they thought climate change action would be disruptive (Element 6b).
The HLR on uncertainties about the precise effects of climate change revealed no main effects for ideology or MA condition, in keeping with Study 1. However, there was a significant interaction between ideology and assignment to the MA condition. Specifically, liberals were more likely to agree that there are uncertainties about the precise effects of climate change if they had read the medical analogy,
Only ideology predicted participant preference for taking a wait-and-see approach to climate change (vs. immediate action), with liberals preferring more immediate action,
Contrary to Study 1, Study 2 found almost no effect of a medical analogy on recognition of the decision-relevant elements of climate change. It also found no effect of the analogy on policy preferences. The only major replications in Study 2 were the findings that political ideology strongly predicted all climate change beliefs and that the medical analogy was considered helpful to understanding, regardless of political ideology. Study 2 also replicated Study 1 in showing that the medical analogy did not affect understanding of climate literacy facts.
Only one decision-relevant aspect of climate change was affected by the medical analogy in Study 2: uncertainty about climate change’s precise effects. Liberals (but not moderates or conservatives) were more convinced of these uncertainties after learning about climate change via a medical analogy. This effect did not appear in Study 1, suggesting that this finding is also less than robust.
The failure to replicate the effects of the medical analogy on beliefs was unexpected, given that the materials and procedure in Study 2 were identical to Study 1 except for additional measures added to the end of the questionnaire. Although we did not have a priori hypotheses for these disparate findings, one possible explanation is the months in which these data were collected (June, 2015 for Study 1 and December, 2015 for Study 2). Ambient temperature and weather have been shown to affect climate change beliefs [
Whatever the reason for the differences in statistical significance, the results for the two studies were often trending in the same direction. Therefore, we tested the overall effect of the medical analogy by combining the results of the two studies in an internal meta-analysis.
Meta-analysis is useful for synthesizing results from multiple studies, particularly when focusing less on statistical significance and more on the overall strength of effects [
To facilitate comparisons between studies, only participants from Study 1 assigned to the medical analogy or control conditions were included in these analyses.
Meta-analysis was conducted with the STATA 14 [
Main effects of reading about climate change in terms of a medical analogy on decision-relevant beliefs were small (all
Main effects of medical analogy (vs control) predicting decision-relevant beliefs, interactions of medical analogy and political ideology, and simple slopes for conservatives and liberals of assignment to the medical analogy condition.
Element | Main effects of MA condition | Interactions of MA and ideology | ||||
Study 1 |
Study 2 |
Combined |
Study 1 |
Study 2 |
Combined |
|
Element 1 | .25 | -.10 | .08 (-.26, .42) | -.37 | -.14 | -.25 (-.48, -.03) |
Element 2 | .20 | .09 | .15 (-.06, .35) | -.34 | -.10 | -.22 (-.46, .02) |
Element 3 | .27 | -.02 | .13 (-.15, .40) | -.29 | .01 | -.14 (-.43, .15) |
Element 4 | .34 | .01 | .17 (-.15, .50) | -.39 | -.09 | -.24 (-.54, .06) |
Element 5 | .00 | .13 | .07 (-.13, .27) | .11 | .29 | .20 (-.01, .40) |
Element 6a | .20 | .01 | .11 (-.09, .31) | -.43 | -.16 | -.29 (-.57, -.02) |
Element 6b | -.16 | .18 | .01 (-.32, .34) | -.11 | .26 | .07 (-.30, .44) |
Element 7 | .33 | .05 | .19 (-.08, .47) | -.30 | .02 | -.14 (-.45, .17) |
Element | Simple slopes for conservatives | Simple slopes for liberals | ||||
Study 1 |
Study 2 |
Combined |
Study 1 |
Study 2 |
Combined |
|
Element 1 | .42 | .06 | .24 (-.12, .59) | -0.03 | -.15 | -.09 (-.29, .11) |
Element 2 | .36 | .15 | .25 (.05, .46) | -.01 | .03 | .01 (-.20, .21) |
Element 3 | .18 | -.01 | .08 (-.12, .29) | .19 | .00 | .10 (-.11, .30) |
Element 4 | .50 | .08 | .29 (-.11, .69) | .04 | -.03 | .00 (-.20, .21) |
Element 5 | -.08 | -.15 | -.12 (-.32, .09) | .07 | .28 | .18 (-.03, .38) |
Element 6a | .46 | .14 | .30 (-.02, .62) | -.08 | -.08 | -.08 (-.28, .12) |
Element 6b | .02 | -.10 | -.04 (-.24, .16) | -.14 | .30 | .08 (-.35, .51) |
Element 7 | .41 | .03 | .22 (-.16, .60) | .09 | .06 | .08 (-.13, .28) |
The interaction of MA condition with political ideology mainly produced small effects. The largest effect sizes were observed for Elements 1, 2, 4, 5, and 6a.
Because the interaction effects in Study 1 were driven by changes among conservatives, the effect sizes for these simple slopes were computed again using meta-analysis. Small but positive effects emerged for Elements 1, 2, 4, 6a, and 7: Conservatives in the MA condition (as compared to the control) indicated stronger belief in anthropogenic climate change, stronger beliefs that climate change is progressive and unprecedented, greater belief that the causes of climate change also have benefits, and stronger belief that mitigation reduces the full set of risks. Thus, as suggested by
Although fewer significant effects emerged for liberals, we used a meta-analysis to test the overall effect sizes for these simple slopes as well. The only effect that approached significance was Element 5, suggesting that liberals became more aware of uncertainties in climate science after reading the medical analogy.
We identified seven decision-relevant attributes of climate change on the basis of a priori analysis [
The medical analogy resulted in the majority of significant effects and changed the responses of conservatives consistently with respect to most of the key decision-relevant elements of climate change. The other analogies had weaker and less consistent effects. Respondents who read the trial analogy, particularly conservatives and moderates, were more likely to believe climate change will lead to unprecedented consequences and requires mitigation, but also that carbon-emitting behaviors provide comfort and convenience and that the timing and location of future damage from climate change are difficult to predict. The disaster-preparedness analogy had no effect on beliefs, except to produce an increase in the belief that mitigation is a vital form of response—a finding also observed with the trial and medical analogies. Unlike the other two analogies, the disaster preparedness analogy did not lessen the differences between conservatives and liberals in support for mitigation.
We found that although the mental models we used had no effect on climate literacy or beliefs about the degree of scientific consensus, the medical analogy stood out as being seen as helpful and as affecting multiple climate-related beliefs. The most typical pattern of these effects was to shift the beliefs of conservatives (and to a lesser degree, moderates) toward the scientific consensus regarding several key decision-relevant characteristics of the climate change phenomenon, while leaving the beliefs of liberals largely unchanged. This pattern was observed with most of the beliefs examined, but not all. Effect sizes across the two studies suggested that non-liberal respondents became more convinced of the human causes of climate change, the progressive and unprecedented nature of climate change, and the need for mitigation to reduce the full set of risks. The medical analogy also led liberals to be slightly more aware of the uncertainties of climate projections. However, there were no effects on beliefs about the reversibility of climate change or the disruptive effects of mitigation.
Although promising, the effects of the medical analogy were generally weak. With issues as complicated and politically polarized as climate change, it may be too much to expect that any way of framing the issue in 350 words will lead to major shifts in understanding. Our studies replicated the well-established finding that political conservatives in the U.S.A. are more skeptical than liberals regarding many attributes of climate change that are consensually recognized in the scientific community [
We do not read our findings as suggesting that the medical analogy is a useful way to persuade conservatives to think more like climate activists. In line with our objective of improving nuanced thinking about climate decisions, we found changes that reduced polarization in other ways. For example, the medical analogy affected liberals by increasing their belief that many uncertainties still exist in climate change predictions. Furthermore, although the medical analogy helped respondents, especially conservatives, appreciate aspects of climate change that they would not otherwise endorse, it did not affect knowledge of climate “facts” or beliefs about the degree of scientific consensus. We also found in Study 2 that it did not change certain key policy preferences, particularly willingness to take a wait-and-see approach to policy in response to climate change or support for specific policies. We hesitate to draw conclusions from this non-finding because in Study 2 the medical analogy had such miniscule effects on the understandings that might be required to change policy preferences.
We conclude that the use of a medical analogy has promise for increasing people’s sense of ease in thinking about climate change as a phenomenon calling for decision making under uncertainty, for calling the attention of citizens to important decision-relevant aspects of the climate change phenomenon, and perhaps also for reducing the polarization of views in the U.S.A. along lines of political ideology. As already noted, this polarization has been highly resistant to past efforts to reduce it by educational means [
As noted earlier, the overall effect sizes we observed were fairly small according to traditional guidelines [
Another limitation of the current study was our use of an online convenience sample. Some of our findings were in line with those of nationally representative samples [
Although our findings suggest that a brief encounter with the medical analogy is unlikely to change fundamentally the public’s basic understanding of climate mechanisms, they offer some cause for hope for this educational approach. By introducing novel ways of educating the public about climate change, such as decision-relevant analogies, climate communicators may be able to edge the public a bit closer to a deeper understanding of how to address such a wicked problem and an increased ability to engage in productive discussions despite ideological differences.
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