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Article

Predictors of Climate Change Activism Communication in Social Networks

by
Carl A. Latkin
1,2,*,
Lauren Dayton
1,
Kelsie Parker
1 and
Rajiv Rimal
1
1
Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
2
Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
*
Author to whom correspondence should be addressed.
Climate 2024, 12(12), 195; https://doi.org/10.3390/cli12120195
Submission received: 13 September 2024 / Revised: 9 November 2024 / Accepted: 18 November 2024 / Published: 22 November 2024
(This article belongs to the Section Policy, Governance, and Social Equity)
Versions Notes

Abstract

It is critical to understand the determinants of climate change activism (CCA) and CCA communications (CCAC). Such information can help organizations that are committed to addressing climate understand and predict who will engage in CCA, identify barriers to CCA, and develop programs to address these barriers to diffuse climate change activism messages and behaviors through social networks and to mobilize action. This study longitudinally investigates psychosocial predictors of CCAC. Study participants were drawn from a randomized clinical trial of US adults (N = 622). Participants completed baseline and follow-up surveys between August to September 2022. Logistic regression models assessed psychosocial factors and implementation intention factors that predicted CCAC at follow-up. The multivariate logistic regression model baseline factors of positive social network norms related to CCAC (aOR: 1.25, 95% CI: 1.10–1.43), comfort encouraging others to engage in CCAC (aOR: 1.74, 95% CI: 1.01–2.88), and following a climate change social media account (aOR: 2.65, 95% CI: 1.74–4.02) were significantly associated with CCAC at follow-up. In a sub-analysis, plans on talking within a week and having in-person conversations versus texting/email were positively associated with CCAC. These findings suggest that strategies to improve comfort talking about CCA and implementation intentions may increase interpersonal CCAC.

1. Introduction

Robust scientific evidence supports the effectiveness of climate mitigation policies, yet the passing of legislation to limit greenhouse gas emissions is often stymied by the fossil fuel industry and their allied political and economic organizations. Moreover, addressing climate change competes with other social and political priorities that require policymakers’ attention. In this social environment of competing political priorities and opposition, individuals and organizations concerned about climate change must effectively mobilize to engage in climate change activism (CCA). CCA includes activities such as voting, protesting, letter writing, volunteering with, and donating to organizations working to curb climate change. Increasing discussions about CCA within social networks is a critical strategy to mobilize networks to advocate for climate change mitigation policies [1]. The current study longitudinally examines the predictors of the behavior of speaking with network members about engaging in activities to help address climate change, also known as climate change activism communication (CCAC). It is critical to understand the determinants of CCAC within social networks. Such information can help organizations addressing climate change to understand and predict who is likely to engage in CCAC, identify potential barriers to CCAC, and develop programs to address these barriers in order to diffuse CCA messages and behaviors through social networks and to mobilize action. Social networks have a significant effect on engagement in pro-environmental behaviors. For example, social networks have been found to influence farmers’ adaptation strategies to climate change in Ethiopia [2]. A recent meta-analysis, which screened 556 studies and identified 125 that provided sufficient information to calculate effect sizes, concluded that social network factors were strongly related to pro-environmental behaviors with a standardized coefficient of 0.34, and that social influence is essential for the emergence of pro-environmental behaviors [3]. Another meta-analysis on resource conservation found that social influence approaches were effective, albeit effectiveness differed by approaches and target group [4]. Social networks also have a demonstrated influence on political activism behaviors. For instance, a study utilizing a nationally representative sample of US adults found that those who are more socially isolated are less likely to participate in political activities such as making donations, attending political meetings or rallies, and persuading others to vote [5]. An analysis of the Chinese General Social Survey found that social capital, measured through social networks, and level of trust were significantly associated with environmental concerns and willingness to make sacrifices to enhance the environment [6]. One way that social networks operate to shape behaviors is through communication. Communication about CCA can keep the issue alive in the public agenda, diffuse information and opinions through social networks, and, in turn, influence the behavior of network members [7,8,9]. A systematic review of research on effective climate change education strategies documented the importance of discussions to shape knowledge about climate change and increase self-efficacy to take action [10]. Numerous studies suggest climate change discussions can influence public opinion [11,12,13]. Discussions about climate change, especially with family, have been linked to climate change policy preferences and climate change mitigation behaviors [14,15]. Moreover, in areas with low access to media or low literacy, interpersonal discussions can be essential for climate change education [16]. However, in a study of the content of conversations about climate change among US adults, it was identified that most conversations about climate change focused on discussions of extreme weather events rather than on adaptation and mitigation policies and actions necessary to address climate change [17]. In the current study, we focused specifically on climate change discussions that include actions to address climate change.
Emotions may be a barrier or facilitator to discussions of climate change action [18,19,20]. Feelings of awkwardness in discussion can reduce CCAC [21]. Fear communication has not been found to be effective in climate change messaging [22]. However, the concern or fear of upsetting others may lead to a “spiral of silence” and impede climate change discussions [23]. Pluralist ignorance has also been found to influence CCAC and perpetuate a spiral of silence [24]. Pluralist ignorance is a shared misperception of a norm and can lead to the perception that others are less concerned about climate change and lead to self silencing [24]. A representative survey in 125 countries highlighted the widespread pluralistic ignorance with the belief that others are less likely than the respondents to support climate change action [25]. Furthermore, a study of US legislative staff members indicated they underestimated their constituent’s support for carbon restriction legislation [26,27]. To break the spiral of silence around CCA, it is critical to identify factors supporting engagement in CCAC as discussions among family and friends improve understanding of the causes of climate change [28].
Another factor that may influence CCAC is behavioral intentions. Intention is a construct that has been extensively applied to environmental behaviors as it is a key construct of the Theory of Planned Behavior (TPB) [29,30]. Over 150 studies on environmental behaviors utilized the TPB [29]. In the TPB, behavioral intentions are the key mediator between attitudes, norms, perceived control, and the behavior [31,32,33]. Studies of climate change behaviors have found that intention is a significant correlate of behavior [33]. However, studies that have specifically examined intentions predicting pro-environmental consumer behaviors have found mixed results [34,35]. In the study of ethical consumer behaviors, numerous studies have identified the gap between behavioral intentions and actual behaviors [34,36,37,38,39,40,41,42]. Further, few studies of pro-environmental behaviors measure the link between intentions and subsequent behaviors. To address this research gap on the ability of intention to predict CCAC, we examined whether the reported intention of CCAC at baseline was a meaningful predictor of this behavior at the follow-up assessment. We were also interested in whether negative intentions of not planning to engage in CCAC were as strong of a predictor as planning to engage in CCAC.
Intentions may have a weak relationship to behaviors due to the influence of contextual factors [43]. The cognitive bias of the fundamental attribution error suggests that people frequently overemphasize personal agency and under-emphasize social and environmental factors in understanding and predicting behaviors [44]. A construct that incorporates contextual factors related to behavioral intentions is implementation intentions, which can be conceptualized as a plan for when, where, and how the intentions will be actualized [45]. In the current study, implementation intentions were determined by information provided on the mode of the intended CCAC (how and where) and the timing of the CCAC (when). We also added the domain of who and how many people they would communicate with.
Self-efficacy may also impact CCAC. In numerous studies, self-efficacy has been linked to pro-environmental behaviors [46,47]. However, there have been critiques of self-efficacy as confounding the affective impact of attempting to perform the behavior and perceived capabilities to perform [48]. In the current study, we hypothesized that perceived discomfort in discussing CCA may be a greater barrier than perceived difficulty in engaging in these conversations. In this prospective study of predictors of CCAC, we assessed if baseline factors predicted whether people would talk with their social network members about CCA in a subsequent assessment.

2. Materials and Methods

Participants were recruited from 18 August to 1 September 2022 through Prolific, an online platform frequently used for recruiting individuals for social science research [49]. Prolific is known for its high reliability and diverse participant pool, making it a valuable resource for researchers [49]. The study protocols received IRB approval from the Johns Hopkins Bloomberg School of Public Health.
Participants were from a randomized clinical trial. Individuals were randomly assigned in equal numbers to either a CCAC training group or an equal attention control group, which received training on becoming a COVID-19 vaccine peer educator. The study was grounded in Diffusion of Innovation, Cognitive Dissonance, and Social Cognitive Theories [50]. After providing informed consent, participants were administered the online survey and randomly assigned to the experimental CCAC intervention or equal attention comparison condition. The CCAC intervention training included 5 short videos, which were from one to three minutes long, on ways to communicate about climate change actions in-person and online, who you can talk to about climate change action, how you can use social media for climate change, why talk about climate change to family and friends, and, using social media to promote climate change actions (See Supplementary Materials). Each module included questions to check comprehension and graphics/messages that could be shared with peers about CCA. As the final part of the training session, participants completed a planning exercise to prepare for their upcoming conversations about climate change activism.
A total of 622 participants completed the training, passed the attention checks, and completed the follow-up survey one month after the intervention, resulting in an 86% retention rate from the original sample of 720 participants. To ensure racial diversity, Black participants were oversampled. There were no significant differences in income, climate change concern, randomization status, or race between participants who completed the follow-up survey and those who did not. However, those who completed the follow-up were significantly more likely to be older and male compared to those who did not remain in the study (p < 0.05). The key follow-up outcome was talking to others about climate change activism in the past month. A prior analysis found that there were no differences between the two conditions on this outcome [51].
To ensure that participants had similar understandings of climate change activism, they were informed that climate change activism included activities such as voting, letter writing, volunteering with, and donating to organizations working to curb climate change. To reinforce the definition of climate change activism in the two surveys, they were asked, “When, if ever, have you done these things related to climate change in the past”: personally written letters, emailed, or phoned government officials to urge them to take action to reduce climate change; voted for candidates who support measures to reduce climate change; signed an online petition or provided their name and email address to an environmental organization to curb climate change; provided their name and email address to an environmental organization to send an email to a policy maker about climate change; volunteered with organizations working to curb climate change; donated money to organizations working to reduce climate change; or attended protests or rallies to reduce climate change.
The primary dependent variable assessed at follow-up was talking to others about addressing climate change as measured by the variable, “In the past month, how many people did you speak with about engaging in activities to help address climate change?” Response options were 0, 1–2, 3–4, 5–6, and 7 or more. Based on the distribution, responses were dichotomized into zero and one or greater to assess whether participants engaged in any CCAC in the prior month.
Based on Lee and colleagues’ measures [52], three items assessed the level of concern about climate change: “How important is the issue of climate change to you personally” (extremely important, very important, somewhat important, slightly important, not at all important); “how worried are you about climate change” (extremely worried, very worried, somewhat worried, not at all worried); “how bad do you think climate change is currently” (mild, moderate, severe). These items were combined into a scale (alpha = 0.86), which was then transformed into z-scores in the inferential statistical analyses for ease of interpretation.
One descriptive and one injunctive social norm question were included: “How many friends/family would encourage you to take action to reduce climate change?” and “Of your friends/family, how many do you think are involved in climate change actions?” The response options for each of these questions were none (0%), some (25%), half (50%), most (75%), and all (100%). These two items were added together to form a brief social norms measure.
The CCAC intention question asked of all participants was, “Do you plan to have conversations about climate change actions in the future?” (Yes/no). Comfort and difficulty in starting such conversations were assessed by the items “How comfortable do you feel talking to family/friends to encourage them to take action on climate change?” (Very comfortable, somewhat comfortable, neither comfortable nor uncomfortable, somewhat uncomfortable, very uncomfortable) and “how difficult is it to start conversations with family/friends about what actions they can take to encourage climate change action?” (Very difficult, somewhat difficult, neither difficult nor easy, somewhat easy, very easy). Based on the distribution, these later two variables were recoded and dichotomized with a median split with a higher score representing greater comfort and lower difficulty.
There were three CCAC intention questions only asked of the subsample of participants (N = 261) randomly assigned to the CCAC condition, which trained participants to talk to others about CCA. These questions included: “How do you plan on starting the conversation about climate change with this person?” The response options were “talking to them in person, talking to them on the phone, sending them an email, sharing information from social media, and other things”. This question was dichotomized to phone/in-person versus email/social media. This latter included one “other” response that reported “texting”. The second question was, “When do you plan on talking to this person?” The response options were “within the next few days, within a week, within a few weeks, within a month”. These responses were dichotomized to within a week versus more than a week. The third intention question assessed the target of their communication with the question, “Who are you planning to talk to about preventing climate change? (select all that apply)”: (1) friend, (2) family member, (3) colleague, (4) child, (5) neighbor, and (6) someone else in the community. Another question assessed engagement in climate change information online: “On social media, do you follow an account, page, organization, or person who focuses on climate change?”
Gender was assessed as gender assigned at birth. Age was assessed as a continuous variable. Political ideology was measured with the question, “Where would you place yourself on a 7-point scale running from ‘very liberal’ to ‘very conservative’?” There were 11 who reported “Not applicable” and, based on the results from multiple imputations, were recoded as 3.0. Urbanicity was measured by the question, “What size community do you live in?” Large urban area (>250,000 residents), medium urban area (100,000–250,000), town (2500–under 100,000), rural (under 2500), and dichotomized as urban versus town/rural. Race/ethnicity options included the categories of Non-Hispanic White, Non-Hispanic Black, Hispanic, Asian, and mixed/other. The level of education was assessed by asking “What is the highest level of education that you’ve completed?” This was dichotomized with a median split at bachelor’s degree and above.
The primary outcome was talking to others about addressing climate change in the prior month. Bivariate and multivariable logistic regression models were run. The first set of models included the full sample at follow-up. The second model focused on the subset of participants in the CCA training condition as this group received two additional variables that assessed how and when participants planned to talk to others about CCA. The initial analysis also included a variable indicating whether the participant was randomized to the CCAC or the COVID-19 vaccine condition. However, this variable was not significantly associated with the outcome, so it was removed from the subsequent analyses. In the multivariable model, we first treated each category to the question “Who are you planning to talk to about preventing climate change?” This was an independent dichotomous variable (friend, family member, colleague, child, neighbor, and someone else in the community). We also added these 6 items together. The tables present the results of the independent dichotomous analyses. However, the findings were similar.

3. Results

In the full sample (N = 622), on average, participants were 34.5 years old (SD = 11.2), and 44% reported their gender at birth was female (Table 1). About half (46%) had a household income greater than USD 60,000 and a bachelor’s degree or higher (52%), and about two-thirds (66%) lived in an urban metropolitan area. A total of 38% of respondents reported their race as white, 39% as Black, 12% as Hispanic, and 11% as other. The majority of participants (59%) identified as liberal on a political scale, and 19% and 20% identified as conservative and moderate, respectively.
At follow-up, less than half (41%) of the sample reported having CCA conversations in the prior month, whereas at baseline, 70% reported planning on having a conversation about CCA. The most common planned recipients of CCA conversations were family (35.4%) and friends (37.5%). One-third of participants reported following on social media an account, page, organization, or person who focuses on climate change.
In the subsample (N = 261), participants had a median age of 33 years, and approximately 56% reported their gender at birth was male (Table 2). Approximately 41% reported their race/ethnicity as Black, 36% White, 12% Hispanic, 3% Asian, and 8% other. Approximately half of the participants had a bachelor’s degree or higher (51%), and a majority reported residing in an urban metropolitan area (65%). Approximately 57% reported a household income under $60,000. The majority of participants (65%) identified as liberal on a political scale, 20% as moderate, and 13% as conservative.
Within this subsample, most planned to have a CCA conversation within a week (76%), with an average of three different types of individuals, and in-person or by phone (89%), with only 11% planning to start a conversation by email or social media.
In the first model with the full sample, in the bivariate models, a higher level of concern about climate change (OR = 2.25, CI = 1.85–2.74); lower perceived difficulty starting discussions with others about CCA (OR = 1.95, CI = 1.41–2.70); greater comfort in encouraging others to engage in CCA (OR = 4.62, CI = 3.13–6.82); greater social network norms about engaging in CCA (OR = 1.61, CI = 1.45–1.79); following climate change social media account (OR = 5.66, CI = 3.94–8.14); and intentions to have a to have CCA conversation (OR = 7.26, CI = 4.57–11.51) were significantly associated with CCAC (Table 3). Although they were attenuated in the multivariable model, all of the aforementioned variables, with the exception of perceived difficulty starting discussions with others about CCA, remained statistically significant. In the multivariable model, a higher level of education was positively associated with past month CCAC, whereas the racial category of “other” was negatively associated compared to non-Hispanic white participants.
In the model that assessed CCAC intentions using the subsample, the bivariate analysis examined baseline factors predicting the reporting at follow-up having a CCA conversation in the prior month. Reports of four of the role types as targets of conversation were associated with having a CCA conversation (Table 4). The strongest associations were with a colleague (OR = 4.56, CI = 2.70–7.73), a neighbor (OR = 4.07, CI = 2.26–7.34), and someone else in the community (OR = 5.24, CI = 2.83–9.70). Planning to have a CCA conversation with a family member was also significant (OR = 3.72, CI = 1.74–7.96).
Planning to have a CCA conversation within a week, compared to longer, was associated with having a CCA conversation within the past month (OR = 3.15, CI = 1.70–5.83), as was planning to have the conversation in-person or by phone compared to an electronic medium (OR = 2.42, CI = 1.06–5.54). Intentions to have a CCA conversation at baseline, as in the full model, also predicted the CCA conversation with the past month at follow-up (OR = 2.34, CI = 1.15–4.76). In the multivariable model, six of the seven CCAC intention variables continued to be statistically significant. The one variable that dropped out was the general question of intention to have a CCA conversation in the future.

4. Discussion

This longitudinal study identified several factors that predicted communication about climate change activism. Interestingly, participants who identified types of individuals to talk with who they were not as close with (colleagues and others in the community) vs closer to (friends and family members) were more likely to talk to someone about CCA in the prior month. It may be that those who plan to talk to less close individuals cognitively process the content, setting, and/or timing of the proposed conversion more than those who plan to talk to family or friends, and this processing leads to a greater likelihood of the intention leading to a behavior. It may also be that conversations with socially distal others loom larger in people’s minds, as compared to conversations with closer others (with whom such discussions may be less salient). This finding has important implications, particularly when viewed in light of social network theory, where strengths of weak ties are found to be more consequential for certain topics; whether it is also applicable in CCA, as suggested by our findings, is worthy of future research [53].
Perceived comfort and difficulty engaging in CCAC at baseline were found to have varied effects on engaging in CCAC at follow-up. In the bivariate models, both the comfort and difficulty variables predicted the outcome of CCA conversations. However, in the multivariable model, only comfort remained statistically significant. This continued association may be due in part to the fact that comfort had a strong association. The finding also suggests that when training people to engage in CCA conversations, these programs may need to address and assess the level of comfort. Certainly, role-plays and positive feedback can enhance comfort [54,55,56,57]. Additionally, preparing people for how to address anticipated skepticism from others may serve to increase comfort.
In line with prior research on social norms and climate change behaviors, perceptions of social network members’ support of and engagement in climate change activism predicted CCA conversations [57,58]. However, we do not know if the conversations reported were with those network members who they perceived to be more supportive of climate change conversations. Future research should examine the recipients of these conversations. Additionally, in line with prior research, in the full sample, a greater level of education was positively associated with CCA conversations.
Interestingly, across all models, this study found that individuals who, on social media, follow an account, page, organization, or person who focuses on climate change were more than twice as likely to report one or more CCA conversations at follow-up. Future research is needed to understand this dynamic better. It may be that they are more engaged in CCA and/or they have acquired more materials for conversations about CCA. Social media posts may also cue the behavior of CCA discussions. Finally, the same factors that drive people to follow a climate-related social media account (e.g., concern about climate change) may also be driving their intentions to engage in CCA.
The relationship between conversational intentions and engaging in CCAC was nuanced, and some consistent findings were identified across the two models. In the full sample, conversation intentions were significantly predictive (p < 0.001). However, on further examination, it was most predictive for those who reported that they did not intend to have a conversation by follow-up, with only 13% of those who said that they did not plan to have a conversation about CCA in the future reporting such a conversation at follow-up. Of those who reported that they intended to have a CCA conversation, only approximately half (53%) actually did so within the next month. These findings suggest that to promote CCA conversations, it may be useful to focus on individuals who report that they plan to engage in this behavior. However, even among those who reported a general intention, the likelihood of a CCA conversation was similar to obtaining a “heads” in a coin toss. In the analyses of the subsample, although significant in the bivariate analyses, in the multivariable analyses, intentions did not remain statistically significant after the inclusion of implementation intention questions of when they planned to have a conversation and the mode of communication. Those who planned to have a conversation within a week had 2.8 odds of being more likely to have a conversation in the month prior to follow-up compared to those who planned to have a conversation in more than a week, suggesting that to reduce forgetting or other time-dependent barriers, individuals should be encouraged to have such conversations in a relatively short time. Based on the data, they should also be encouraged to have a face-to-face or phone conversation as well.
Several study limitations should be noted, including not being a random sample, which limits generalizability, a relatively short follow-up of one month, potential social desirability bias, self-reports were not verified, and we do not know the content or the recipients of the reported conversations. Moreover, we do not know if these CCA conversations have led to collective actions on climate change. Study strengths should also be noted, including the racial diversity of the sample and the high quality of the Prolific research platform. Moreover, since the survey assessed COVID-19 attitudes and behaviors as well as those on climate change, there may have been some masking of the study focus.
Many prior interventions focused on educating people on the scientific factors of climate change. Fortunately, most of the population in the US and many other countries are concerned about climate change. These findings and the findings from the current study indicate that people who do not plan to have conversations with others about CCA are much less likely to do so, suggesting that to mobilize collective climate change activism, it is much more efficient to target individuals who are willing to engage in conversation about CCA. The findings suggest that helping people develop implementation intentions and comfort in talking about CCA may lead to increased CCA conversations. Providing opportunities and options for following and interacting with people and organizations on social media may also help to facilitate CCA conversations. Communication strategies that feature the existence of everyday people (friends, coworkers, family, etc.) engaging in CCA and increased conversations on CCA may help change social norms about the acceptability of such conversations and break spirals of silence, and also lead to changes in injunctive and descriptive norms regarding CCA which may facilitate more CCA conversations and behaviors.
To increase CCAC, a strategy that climate change organizations can use to help individuals turn their intentions into actual behaviors is to encourage participants to make concrete plans for their actions, including encouraging them to engage in CCAC within a week. They can also help to increase comfort in having climate change action conversations through role-plays, which have been found to be effective in increasing comfort in having difficult conversations [50]. Moreover, climate change organizations can provide information on social media to follow. Following social media accounts that focus on climate change can cue CCAC behaviors and provide social support. Climate change organizations can also provide online materials that viewers can share and are easy to remember and discuss with others. The study’s findings also suggest that it may be beneficial to encourage people to have in-person conversations rather than emailing or texting. Planning for an in-person conversation may lead to more cognitive rehearsal of the materials and hence increase the likelihood of the conversation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cli12120195/s1.

Author Contributions

Conceptualization, L.D. and C.A.L.; methodology, L.D. and C.A.L.; validation, L.D. and C.A.L.; formal analysis, C.A.L. and K.P.; investigation, L.D. and C.A.L.; resources, L.D. and C.A.L.; data curation, L.D. and C.A.L.; writing—original draft preparation, and C.A.L.; writing—review and editing, L.D., K.P., C.A.L. and R.R.; supervision, LD; project administration, L.D. and C.A.L.; funding acquisition, L.D. and C.A.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Bloomberg America Health Initiative, Johns Hopkins Bloomberg School of Public Health.

Data Availability Statement

The data set is available from the first author.

Conflicts of Interest

The authors declare no conflicts of interest. The funder had no role in the design of the study, in the collection, analysis, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

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Table 1. Sociodemographic characteristics of the study sample (N = 622).
Table 1. Sociodemographic characteristics of the study sample (N = 622).
CharacteristicsTotal (N = 622)Did Not Communicate About Climate Change Activism in the Past Month (n = 366)Communicated About Climate Change Activism in the Past Month (n = 256)
Age (mean, SD) 34.5 (11.2)35 (11.6)33.8 (10.7)
Gender at
birth		Male349 (56.1)196 (53.5)153 (59.8)
Female273 (43.9)170 (46.4)103 (40.2)
Race/EthnicityNon-Hispanic White234 (37.6)150 (41.0)84 (32.8)
Non-Hispanic Black244 (39.2)132 (36.1)112 (43.7)
Hispanic77 (12.4)46 (12.6)31 (12.1)
Asian23 (3.7)17 (4.6)6 (2.3)
Other44 (7.1)21 (5.7)23 (9.0)
Level of
education		Grade 12, GED, or less101 (16.2)67 (18.3)34 (13.3)
Some college or associates196 (31.5)138 (37.7)58 (22.7)
Bachelor’s degree239 (38.4)120 (32.8)119 (46.5)
Graduate degree86 (13.8)41 (11.2)45 (17.6)
Household
income		Less than $15k70 (11.2)40 (10.9)30 (11.7)
$15k–$35k126 (20.3)79 (21.6)47 (18.4)
$35k–$60k142 (22.8)91 (24.9)51 (19.9)
$60k–$90k140 (22.5)82 (22.4)58 (22.7)
$90k and over144 (23.1)74 (20.2)70 (27.3)
Size of
community		Large urban area218 (35.0)115 (31.4)103 (40.2)
Medium urban area190 (30.5)114 (31.1)76 (29.7)
Town173 (27.8)110 (30.0)63 (24.6)
Rural41 (6.6)27 (7.4)14 (5.5)
Political scale
identity		Liberal367 (59.0)192 (52.5)175 (68.4)
Moderate123 (19.8)82 (22.4)41 (16.0)
Conservative121 (19.4)87 (23.8)34 (13.3)
N/A11 (1.8)5 (1.4)6 (2.3)
Table 2. Sociodemographic characteristics of the study subsample (N = 261).
Table 2. Sociodemographic characteristics of the study subsample (N = 261).
CharacteristicsTotal (N = 261)Did Not Communicate About Climate Change Activism in the Past Month (n = 131)Communicated About Climate Change Activism in the Past Month (n = 130)
Age (mean, SD) 35.0 (11.7)35.4 (11.8)34.9 (11.6)
Gender at
birth		Male147 (56.3)71 (54.2)76 (58.5)
Female114 (43.7)60 (45.8)54 (41.5)
Race/EthnicityNon-Hispanic White95 (36.4)53 (40.5)42 (32.3)
Non-Hispanic Black106 (40.6)47 (35.9)59 (45.4)
Hispanic30 (11.5)16 (12.2)14 (10.8)
Asian9 (3.4)6 (4.6)3 (2.3)
Other21 (8.0)9 (6.9)12 (9.2)
Level of
education		Grade 12, GED, or less39 (15.0)24 (18.3)15 (11.5)
Some college or associates89 (34.1)53 (40.5)36 (27.7)
Bachelor’s degree94 (36.0)39 (29.8)55 (42.3)
Graduate degree39 (15.0)15 (11.4)24 (18.5)
Household
income		Less than $15k25 (9.6)11 (8.4)14 (10.8)
$15k–$35k59 (22.6)30 (22.9)29 (22.3)
$35k–$60k66 (25.3)37 (28.2)29 (22.3)
$60k–$90k45 (17.2)21 (16.0)24 (18.5)
$90k and over66 (25.3)32 (24.4)34 (26.1)
Size of
community		Large urban area98 (37.5)42 (32.1)56 (43.1)
Medium urban area73 (28.0)38 (29.0)35 (26.9)
Town75 (28.7)45 (34.3)30 (23.1)
Rural15 (5.7)6 (4.6)9 (6.9)
Political scale
identity		Liberal170 (65.1)82 (62.6)88 (67.7)
Moderate52 (19.9)32 (24.4)20 (15.4)
Conservative34 (13.0)15 (11.4)19 (14.6)
N/A5 (2.0)2 (1.5)3 (2.3)
Table 3. Unadjusted and adjusted logistic regression models for communication about climate change activism in the past month with full sample, N = 622.
Table 3. Unadjusted and adjusted logistic regression models for communication about climate change activism in the past month with full sample, N = 622.
PredictorOR (95% CI)aOR (95% CI)
Age (continuous)0.99 (0.98–1.01)1.00 (0.98–1.02)
Gender assigned at birth (ref: male vs.
female)		0.78 (0.56–1.07)0.86 (0.58–1.28)
Race/ethnicity (ref: Non-Hispanic White)
      Non-Hispanic Black0.51 (0.27–0.98) *0.54 (0.25–1.17)
      Hispanic0.77 (0.41–1.47)0.75 (0.35–1.60)
      Asian0.61 (0.29–1.30)0.69 (0.29–1.64)
      Other0.32 (0.11–0.97) *0.28 (0.08–0.99) *
Level of education (ref: less than
Bachelor’s)		2.27 (1.64–3.15) *1.73 (1.14–2.64) *
Income (ref: less than $60,000)1.35 (0.98–1.86)0.94 (0.62–1.43)
Size of community (ref: town/rural vs.
urban)		1.39 (0.99–1.96)0.86 (0.56–1.31)
Political ideology (continuous: “very
liberal” to “very conservative”)		0.81 (0.74–0.90) *1.03 (0.90–1.18)
Level of concern about climate
change		2.25 (1.85–2.74) *1.32 (1.01–1.73) *
Difficulty starting discussions with others about CCA1.95 (1.41–2.70) *0.79 (0.51–1.22)
Comfort with encouraging others
to engage in CCA		4.62 (3.13–6.82) *1.74 (1.01–2.88) *
Social network norms about engaging
in CCA 		1.61 (1.45–1.79) *1.25 (1.10–1.43) *
Follow climate change social media
account		5.66 (3.94–8.14) *2.65 (1.74–4.02) *
Plan to have CCA conversation7.26 (4.57–11.51) *2.85 (1.63–4.98) *
* Indicates a p-value less than 0.05.
Table 4. Unadjusted and adjusted logistic regression models for communication about climate change activism in the past month with subsample, N = 261.
Table 4. Unadjusted and adjusted logistic regression models for communication about climate change activism in the past month with subsample, N = 261.
PredictorOR (95% CI)aOR (95% CI)
Age (continuous)1.00 (0.97–1.02)0.99 (0.97–1.02)
Gender assigned at birth (ref: male vs.
female)		0.84 (0.52–1.37)1.06 (0.58–1.94)
Race/ethnicity (ref: Non-Hispanic White)
      Non-Hispanic Black1.58 (0.91–2.77)0.71 (0.22–2.33)
      Hispanic1.10 (0.49–2.52)1.06 (0.32–3.47)
      Asian0.63 (0.15–2.67)0.80 (0.20–3.18)
      Other1.68 (0.65–4.37)0.61 (0.09–4.24)
Level of education (ref: less than
Bachelor’s)		2.21 (1.35–3.62) *1.88 (0.97–3.66)
Income (ref: less than $60,000)1.19 (0.73–1.94)0.82 (0.42–1.57)
Size of community (ref: town/rural vs.
urban)		1.48 (0.89–2.49)0.86 (0.45–1.65)
Political ideology (continuous: “very
liberal” to “very conservative”)		0.99 (0.86–1.15)0.94 (0.77–1.15)
Plan on talking to someone within a week (ref: more than a week)3.15 (1.70–5.83) *2.89 (1.37–6.08) *
Planned CCA conversation contact
      Friend2.28 (0.99–5.25)1.58 (0.60–4.12)
      Family member3.72 (1.74–7.96) *2.86 (1.16–7.03) *
      Colleague4.56 (2.70–7.73) *2.85 (1.45–5.61) *
      Child1.18 (0.68–2.03)0.47 (0.22–1.00)
      Neighbor4.07 (2.26–7.34) *1.36 (0.56–3.33) *
      Someone else5.24 (2.83–9.70) *3.36 (1.35–8.40) *
Planned communication mode:
(ref: email/social media vs. in-person
or by phone)		2.42 (1.06–5.54) *2.96 (1.06–8.25) *
Plan to have CCA conversation2.34 (1.15–4.76) *1.17 (0.49–2.77)
* Indicates a p-value less than 0.05.
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Latkin, C.A.; Dayton, L.; Parker, K.; Rimal, R. Predictors of Climate Change Activism Communication in Social Networks. Climate 2024, 12, 195. https://doi.org/10.3390/cli12120195

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Latkin CA, Dayton L, Parker K, Rimal R. Predictors of Climate Change Activism Communication in Social Networks. Climate. 2024; 12(12):195. https://doi.org/10.3390/cli12120195

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Latkin, Carl A., Lauren Dayton, Kelsie Parker, and Rajiv Rimal. 2024. "Predictors of Climate Change Activism Communication in Social Networks" Climate 12, no. 12: 195. https://doi.org/10.3390/cli12120195

APA Style

Latkin, C. A., Dayton, L., Parker, K., & Rimal, R. (2024). Predictors of Climate Change Activism Communication in Social Networks. Climate, 12(12), 195. https://doi.org/10.3390/cli12120195

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