Evaluating the usefulness of Protection Motivation Theory for predicting climate change mitigation behavioral intentions among a US sample of climate change deniers and acknowledgers
Creators: name: Frantz, Cynthia
name: Bushkin, L
name: O'Keefe, Devlin
Publisher: name: Zenodo
Year: 2024
Subjects: protection motivation theory
climate change messaging
threat
efficacy
collective efficacy
climate change denial
behavioral intentions

description: Background: This paper summarizes data from 7 studies that used Protection Motivation Theory (PMT) to guide climate messaging with the goal of increasing climate-mitigating behavioral intentions.  Together, these studies address 5 research questions. 1) Does PMT predict behavioral intentions in the context of climate change mitigation?  2) Does PMT work similarly for climate change deniers vs believers? 3) Are the effects of threat and efficacy additive or multiplicative?  4) Does adding measures of collective threat and efficacy improve the model accuracy for a collective problem like climate change? 5) Can threat and coping appraisals – and ultimately behavioral intentions – be shifted through climate messaging?  

Methods: Seven online experiments were conducted on US adults (N = 3,761) between 2020 and 2022.  Participants were randomly assigned to a control condition or to one of several experimental conditions designed to influence threat, efficacy, or both.  Participants indicated their belief in climate change, ethnicity, gender, and political orientation.  They completed measures of personal threat and efficacy, collective threat and efficacy, and behavioral intentions. 

Results: Multiple regressions, ANCOVAs, and effect sizes were used to evaluate our research questions. Consistent with PMT, threat and efficacy appraisals predicted climate mitigation behavioral intentions, even among those who deny climate change. Different interactions emerged for climate deniers and acknowledgers, suggesting that in this context threat and efficacy are not just additive in their effects (but these effects were small). Including measures of collective threat and efficacy only modestly improved the model. Finally, evidence that threat and efficacy appraisals can be shifted was weak and inconsistent; mitigation behavioral intentions were not reliably influenced by the messages tested. 

Conclusions: PMT effectively predicts climate change mitigation behavioral intentions among US adults, whether they deny climate change or acknowledge it. Threat appraisals may be more impactful for deniers, while efficacy appraisals may be more impactful for acknowledgers.  Including collective-level measures of threat and efficacy modestly improves model fit. Contrary to PMT research in other domains, threat and efficacy appraisals were not easily shifted under the conditions tested here, and increases did not reliably lead to increases in behavioral intentions.
description: Funding provided by: Oberlin CollegeCrossref Funder Registry ID: http://dx.doi.org/10.13039/100019859Award Number:
description: The data file is an aggregate of 7 studies conducted between the summer of 2020 and spring 2022.  Studies are numbered chronologically from earliest to latest.  The studies used different manipulations and tested different hypotheses (described below). All used Protection Motivation Theory to inform messaging designed to influence threat appraisals, efficacy appraisals, and climate change mitigation behavioral intentions.  All studies used identical measures of PMT constructs (with the exception of Study 1, which used the same items but a different response scale for measures of threat).  The items used to measure severity, vulnerability, performance efficacy, and response efficacy appraisals were taken from previous research (Bostrom, Hayes, & Crosman, 2019).  Each study also included measures of collective severity, vulnerability, performance efficacy, and response efficacy. 

In all studies, participants provided informed consent and were randomly assigned to experience a manipulation of some kind (described below).  Participants then completed questions that measured our main dependent variables, and provided demographic information.  In all studies, participants also responded to an attention check question (a factual question about the condition they were assigned to).  Participants who failed the attention check question were removed from the data set (N = 181, or 4.5%). This resulted in a final sample size of 3761.

Manipulations

Study 1:  India. This study evaluated whether reading about the swift recovery of natural systems during the COVID lock-down would increase both personal and collective response efficacy for climate change mitigation behaviors. We reasoned that reading about natural systems' recovery would increase participants' sense that reducing carbon-emitting behavior would make a difference, and also that large numbers of people could and would change their behavior.  Participants were randomly assigned to read an article about dramatic air quality improvements in two Indian cities (with before and after lockdown pictures), or a travel blog about the same cities (with after pictures only).

Study 2: Prospection 1.  This study evaluated whether imagining a positive or negative future impacted threat and efficacy evaluations. We hypothesized that imagining a positive future would increase response efficacy, as things that we imagine seem more likely (cite simulation heuristic). We hypothesized that imagining a negative future would increase vulnerability and severity assessments, for the same reason. We did not have distinct hypotheses for personal vs collective levels of the variables.  After reading a brief description outlining current environmental challenges, participants were randomly assigned to one of four conditions.  The positive prospection condition was asked to imagine that we had successfully addressed our environmental challenges, and asked to describe their neighborhood 30 years in the future.  The negative prospection condition was asked to imagine that environmental challenges had continued to worsen, and were also asked to describe their neighborhood 30 years in the future. Two control conditions either wrote about current events in their neighborhood, or did no writing task. (These two groups were identical and ultimately were combined.)

Study 3: Racial Disparity 1.  This study examined whether reading about the racial disparities in climate change impacts had different impacts on White people versus People of Color (POC). We hypothesized that White people who read that communities of color are disproportionately impacted by climate change might have lower estimates of vulnerability and severity, relative to a control condition. We predicted the opposite for POC:  reading that their communities are more impacted by climate change would increase vulnerability and severity ratings. We did not have distinct hypotheses for personal vs collective levels of the variables. We recruited roughly equal numbers of White-identifying and POC-identifying participants, who were randomly assigned to read an article about climate change's disproportionate impacts on communities of color or a control article about climate change's disproportionate impacts on coastal communities.

Study 4: Scientist 1. We examined whether reading about scientists making accurate predictions would affect participants' vulnerability and severity perceptions. We contrasted reading about scientists' COVID-19 predictions to reading about climate predictions.  COVID-19 provided a recent, vivid, and tangible example of a highly disruptive threat that everyone had been undeniably affected by. It also provided a recent, vivid, and tangible example of scientists making accurate predictions, as well as showing the value of science-informed public policy and science-based solutions (vaccines). We hypothesized that the COVID article would increase climate threat and efficacy assessments more than an article focused on climate change among climate deniers, as climate change is so politically polarized in the US.  We hypothesized that both articles would increase threat and efficacy assessments among those acknowledging the reality of climate change.  Participants in our study were assigned to one of three conditions — reading an article about accurate epidemiologist predictions, reading an article about accurate climatologist predictions, or reading no article at all.

Study 5: Scientist 2.  This follow-up to Study 4 was identical, except that it included pre-measures of belief in climate change as well as the PMT variables.  This created a within-subjects design to boost statistical power.  Data included in the merged data set came from the measures collected after reading the articles, to make this data as similar as possible to the other studies.

Study 6: Racial Disparity 2.  Study 6 was a straight replication of Study 3 with a larger sample size.

Study 7: Prospection 2.  As in Study 5, this study used a prescreen survey of PMT variables to create a within-subjects design. We again hypothesized that imagining a positive future would increase efficacy, while imagining a negative future would increase threat assessments. Participants read a brief paragraph outlining the challenge of climate change and our potential to respond to it. They were then randomly assigned to see either a positive image (e.g. solar panels; positive prospection), a negative image (e.g. drought-stricken field; negative prospection), or both (order counterbalanced; positive + negative prospection). Participants were asked to imagine the future depicted and write about what it would be like to live in it. A control condition skipped this task.