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Eco-Anxiety and Trust in Science in Spain: Two Paths to Connect Climate Change Perceptions and the General Willingness for Environmental Behavior

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22 March 2024

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25 March 2024

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Abstract
Abstract: This article aims to better understand the mechanisms that connect climate change perceptions and general willingness to engage in pro-environmental behavior using Spanish cross-sectional data (N = 403). To do this, we first developed and validated the General Willingness for Environmental Behavior Scale (GWEBS), which includes the classical approach of voluntarily doing new actions but also actions implying not doing things (degrowth) and actions forced by social constraints. The exploratory and confirmatory factor analysis showed a good fit for the one-factor structure, which had adequate validity based on their relationship with other variables. Additionally, the GWEBS distinguished between women and men, left- and right-oriented people, and people who belonged to pro-environmental groups and people who did not. In the second place, we tested the parallel mediator role of eco-anxiety and trust in science in the relationship between climate change perceptions and the GWEBS. The results showed that eco-anxiety, fully, and trust in science partially mediated such a relationship, making them crucial to mobilize the intention to act following the perception. This study contributes to our understanding of the psychological mechanisms that eventually drive pro-environmental behaviors and provides a clear direction for future research.
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Subject: Social Sciences  -   Psychology

Introduction

The global environmental crisis is one of the most pressing issues of the 21st Century [1]. It includes various ecological crises happening in the world today, including climate change. The scientific evidence for anthropogenic climate change is overwhelming, and 97% of peer-reviewed papers accept that global climate change results from human activities [2,3]. Before this situation, feeling eco-anxiety should be a common human reaction but it is not the case, and most people keep buying, consuming, and acting as if nothing is happening. The current mission of science, also of Psychology, is to promote social change and with it the pro-environmental behaviors that can reverse or at least stabilize the situation [4]. This is not always easy because when it comes to acting pro-environmentally, there is not one behavior but many of very different scopes. Only Stern [5] proposed up to four major categories with their consequent subcategories of types of pro-environmental behaviors more than two decades ago.
Our study contributes to this general goal by, first, developing an emotional measure of willingness for environmental behavior which is not reducible to any particular pro-environmental behavior but open to all, and second by analyzing whether eco-anxiety and trust in science reinforce the connection between the perception of the climate situation and the willingness to act pro-environmentally. This is especially important in the Spanish context in which according to the Transatlantic Trends 2023 report by the German Marshall Fund, climate change is the top global challenge concern for Spaniards, ahead of other major political, economic and social issues, including the war over Russia's invasion of Ukraine. It is surprising that given the perceived seriousness of the problem, most studies carried out with Spanish samples have been only a part of eminently descriptive studies that do not address why people do not act as they think (e.g. [6,7]).

1.1. Perception and Behavior: An Essential Path but not Sufficient

It is assumed that perceptions about climate change play a role in whether people take actions to mitigate their environmental impacts and whether they support government climate policies [8-13]. In this respect, reliable perceptions about climate change can be considered a success of many disciplines in the last decades to make us aware of the incredible variety of climate change consequences. Such perceptions can be regarded as indisputably necessary, and there are good current models to explain what variables depend on [14-16].
However, it is also well known that good perceptions of reality do not necessarily connect with coherent behaviors [9,17]. Many other variables may also explain why good perceptions about the situation are necessary but not enough to change behaviors and make significant impacts. One of them is the behavioral intention, long ago proposed by the Theory of Planned Action, that above all insisted on the need to use variables at the same level of abstraction [18,19]. This means that in order to predict any pro-environmental behavior, for example, recycling, the best predictor won’t be the pro-environmental attitude (too general) but the behavioral intention to recycle in a specific period.
An additional difficulty in the context of the climate crisis is that the pro-environmental behaviors and their corresponding specific behavioral intentions are innumerable, of very different scopes, and even of a different nature [5,20-22]. The possible universe of pro-environmental behaviors is so extensive that it can be considered pure arbitrariness to choose some to the detriment of others. Why are recycling, cycling, and saving energy better indicators than composting, cooking with a lid, and sticking to museum paintings? Furthermore, it must be taken into account that people not only do what they want, they do what they can, given their social conditions [23]. Trying to predict specific sets of pro-environmental behaviors subjectively grouped that, in addition, may depend not only on psychological factors, can be a problem for researchers. In this respect, researchers need something more complex than one specific behavioral intention item to study the psychological mechanisms that promote the multiple behaviors in line with what improves or at least does not worsen the environmental crisis. So, our first objective was to develop a new measure of general willingness to act pro-environmentally to which psychological variables such as eco-anxiety can be connected, and which in turn are connected to very different sets of pro-environmental behaviors.

1.2. Eco-Anxiety: An Unpleasant Consequence that Precedes Willingness for Environmental Behavior

Nowadays, feeling anxious about the state of the planet appears to be universal [24], with evidence currently emerging from Europe [25,26], America [27], Canada [28], Pacific Islands [29], and China [30]. In Spain, the levels of eco-anxiety seem to be among the highest in Europe (only behind Germany), with 55.2% of the population experiencing such unpleasant emotion [6]. Despite this, there is much to study about its role and optimal level in promoting consistent behaviors that should resolve the causes that originate it.
Technically, eco-anxiety is described as any anxiety related to the global ecological crisis, including climate anxiety [31-33]. This broader perspective that examines anxiety in relation to a multitude of environmental issues places eco-anxiety at a high level of abstraction. That is why most authors define it as an emotional reaction of concern, worry, and fear, given global climate change threats and concurrent environmental degradation [34].
Such a general perspective does not prevent eco-anxiety from being understood as a multi-faceted concept [35]. At least four dimensions have been studied: affective symptoms, behavioral symptoms, negative emotionality, and rumination [36]. Because these underlying dimensions seem to be distinct from stress and depression, there is some consensus when considering eco-anxiety as a rational reaction to the enormity of the ecological threat humanity and the planet is facing [36]. In this respect, it would be considered a “practical anxiety” [37], leading to problem-solving attitudes [33,38] and pro-environmental actions [39].
Although experiences of anxiety relating to environmental crises include negative emotions and feelings of unpredictability, and uncontrollability, all of which are classic ingredients in anxiety disorders [33], most forms of eco-anxiety can be considered non-pathological. This non-pathological eco-version of anxiety is currently being associated with pro-ecological worldviews, green self-identity, and specific pro-environmental behaviors such as saving energy in the household, trying to influence family and friends to act pro-environmentally, taking public transportation instead of the car, or avoid food waste [22,40]. These initial results suggest that eco-anxiety would not always be a state to be resolved or avoided but rather a desirable state that, together with other variables, such as trust in science that provides cognitive security to the unpleasant atmosphere created by eco-anxiety, can play an active and positive role in promoting a wide range of pro-environmental behaviors.

1.3. Trust in Science as a Metacognition of Confidence in One’s Own Beliefs about the Climate Crisis

Science is the most trusted source of information about climate change [41,42]. It is estimated that there is 98% agreement amongst climate scientists that it is real and human-caused [43,44]. Although skepticism about climate change seems to be a prevalent answer that also tries to find support for scientific arguments [42,45], it is estimated that climate change denial or skepticism is less widespread than often assumed [46,47]. So, trust in science mostly means confidence about one’s own climate change beliefs, that is, the existence and danger of climate change.
Additionally, when people’s ability and motivation to carefully process scientific information is limited, which is the case for most people most of the time [48,49], it is expected people to use message source as a heuristic cue in evaluating the message, with more congruent change in response to scientist sources [50,51]. This seems to be the case of the Spanish population where more than 60% consider that scientists are contributing "a lot" or "quite a lot" to face this global severe challenge [52].
Since trusting in science can exempt us from thinking carefully, it is possible to suggest that it can work as a metacognition that provides cognitive confidence and security in one’s perceptions about climate change. This heuristic security in the information source could play a relevant role in motivating pro-environmental behavior in any of its multiple formats.
Generally, trust in science has been associated with greater concerns about environmental issues [42,53]. It has also been associated with political ideology, where Liberals are more likely than Conservatives to trust in science as a source of information about climate change [54]. These connections are promising, but much remains to be done to outline the role of trust in science concerning other variables. In this respect, we anticipated that trust in science could be the perfect partner for eco-anxiety, adding cognitive security to the emotional discomfort provided by eco-anxiety.

1.4. Objectives and Hypothesis

With the general objective of contributing to the understanding of the many psychological mechanisms that promote the huge number of pro-environmental behaviors on which stopping the climate emergency currently depends, we set two specific objectives: 1) developing a measure of general willingness for environmental behavior that makes it possible to connect at a high level of abstraction psychological variables; and 2) testing two indirect paths that, through the unpleasant emotion of eco-anxiety and the metacognition of trust in science, allow to connect climate change perceptions with the general willingness for environmental behavior. These two related objectives can be useful in the research field and in designing policies and communication strategies to join increasingly individual efforts against climate change.
Regarding objective 1, we started from the idea that using a single item to evaluate the intention to act in favor of the environment can be simple and very common [55,56] but perhaps also insufficient to capture its true meaning, especially if we take into account the great diversity of pro-environmental behaviors. They may imply doing (using public transport, planting trees) and the opposite, not doing (do not consume, do not waste), and also accepting doing and accepting not doing at the request of governments that begin to legislate in this way, forcing and prohibiting the entire population from doing and not doing. In this regard, from July 3, 2021, the Directive EU 2019/904 on single-use plastics (single-use plastic plates, cutlery, straws, balloon sticks, and cotton buds) is in force, so they cannot be placed on the markets of EU Member States. Evaluating the degree of acceptance or rejection of social impositions that affect the freedom of all individuals in a society will not only serve to have more reliable and precise intentional measures but will also allow the design of restrictive policies that are necessary but that governments are afraid to undertake [57].
Upon reviewing existing literature and drawing from our conceptualization of general willingness toward environmental behavior, we developed four novel items aimed at assessing four distinct content areas: emotional inclination to contribute, readiness to abstain from activities harmful to the environment (primarily degrowth and reduced consumption), perceived likelihood of engaging in additional pro-environmental actions, and openness to societal restrictions. These items collectively capture our conception of general willingness toward environmental behavior, characterized by its emotional essence and expansiveness across various behaviors. Initially drafted in Spanish, the items were translated into English, as presented in Table 1. We hypothesized a one-factor structure, suggesting a latent construct comprised of four observed variables (H1).
Regarding objective 2, we hypothesized that perceptions about climate change [47] would be related to the previously developed General Willingness for Environmental Behavior Scale (GWEBS) through eco-anxiety [36] and trust in science (H2). In this regard, we started from the empirical evidence that each variable has shown some connection with specific pro-environmental behaviors or intentions but not in relationship models of several variables and not with Spanish samples. Because being female and holding liberal political views are generally associated with higher climate change risk perceptions and willingness to take action to mitigate climate change [15,54,58,59], we controlled gender and political orientation in our mediation model. Additionally, we controlled different levels of environmental sensitivity operationalized in this study as belonging to a group in defense of the environment.

2. Materials and Methods

2.1. Participants and Procedure

Participants were recruited between March and June 2023 by sending a questionnaire launched with the snowball mechanism through mail and social networks. We aimed to ensure diversity in the sample composition by considering factors such as age, gender, educational level, residency (within or outside Spain), political orientation, and environmental activism status (registered with an ecological association). To ensure that our sample included activist individuals, we contacted four national environmental associations, who sent the questionnaire to their members through their internal channels. Participants were required to fulfill the following eligibility criteria to participate in the study: (a) be at least 18 years old, and (b) be Spanish citizenship. All participants were given an informed consent form outlining the study's objectives, the investigation procedure, the estimated duration, and the principles of confidentiality and anonymity. Participants willingly volunteered for the research and could withdraw at any time. Furthermore, participants were given the email address of one of the researchers in case they required assistance with any issues arising from their participation. After completing an informed consent form, participants were asked to complete the questionnaire individually and in a quiet place with the fewest possible distractions. Given the online nature of the study, data collection was facilitated through the use of Google Forms, utilizing a non-probabilistic sampling method. The university ethics committee approved the study’s procedures (Ref. 0407202327123), and it was carried out in compliance with the ethical standards of the Declaration of Helsinki.
Given the variables involved in this study, the target sample size was predetermined accordingly through an a priori statistical power analysis using G*Power 3.1 [60]. Assuming a small effect size of f2 = .02, with a = .05 and power = .80, the needed sample size was N = 395. The sample was finally composed of 403 participants of Spanish nationality, with an age range between 18 and 81 years (M = 42.74, SD = 14.91). See complete sociodemographics in Table 1.
Table 1. Sociodemographic information of participants.
Table 1. Sociodemographic information of participants.
Variable n %
Gender
Women 257 64.1
Men 142 35.4
Educational attainment
Primary school 7 1.7
Secondary education / vocational training 60 14.4
University education 327 80.9
Place of residence
Spain 403 100
Other 0 0
Environmental activism
Yes 102 25.5
No 301 74.5
Political orientation
Left 271 67.6
Right 130 32.2
Note. N total = 403

2.2. Instruments

Climate Change Perceptions Scale (CCP) [47] measures five dimensions of climate change: the perceived reality, human causes, negative consequences, spatial proximity, and temporal distance of consequences. We used the short version of five items (1 = completely disagree; 5 = completely agree). The items were the following: ‘I believe that climate change is real’ (reality), ‘The main causes of climate change are human activities’ (causes), ‘Climate change will bring about serious negative consequences’ (valence of consequences), ‘My local area will be influenced by climate change’ (spatial distance of consequences),’ It will be a long time before the consequences of climate change are felt’ (temporal distance of consequences. R).” The Cronbach’s alpha was .82.
The Hogg Eco-Anxiety Scale (HEAS-13) [36] measures anxiety in response to the global environmental crisis through four underlying factors: affective symptoms, behavioral symptoms, negative emotionality, and rumination. It focuses on enduring and non-pathological forms of anxiety. A 6-month time frame was used in the instructions to ensure the stability of the measure, saying the following: “Over the last six months, how often have you been bothered by the following problems when thinking about climate change and other global environmental conditions (e.g., global warming, ecological degradation, resource depletion, species extinction, ozone hole, pollution of the oceans, deforestation)? Some item examples are the following: “Worrying too much” (affective symptom), “Unable to stop thinking about past events related to climate change” (rumination), “Difficulty working and/or studying” (behavioral symptom), “Feeling anxious about the impact of your behaviors on the earth” (negative emotionality). The range of responses on the scale was the following: 0 = not at all, 1 = several of the days, 2 = over half the days, 3 = nearly every day”. The Cronbach’s alpha was .91.
Credibility of science. We used a single item asking participants their level of agreement with the following sentence: “I trust the veracity of the information on the climate crisis offered by science”. Responses ranged from 1 = strongly disagree to 4 = strongly agree.

2.3. Data Analyses

First, to develop a global measure of willingness to behave in favor of the environment, following a cross-validation approach, the total sample was divided randomly into two equal-sized subsamples using the SPSS program. The M age of the first group is 41.83, with an SD of 15.16. The second subsample has an M age of 44.07 years and an SD of 14.91. We used the first subsample to obtain descriptive statistics for the items and to observe whether they fit the normal distribution. We tested the multivariate normal distribution assumption using the Mardia test in the R software (version 3.6.3 [61]). Subsequently, after checking the matrix data with the Kaiser–Meyer–Olkin coefficient (KMO) and Bartlett’s test—whether there was an adequate intercorrelation between items—we also performed an exploratory factor analysis (EFA). This allowed examining the items’ distribution patterns and the underlying dimensions using principal axis estimation and direct oblique rotation [62]. We retained the dimension numbers based on a parallel analysis and the Goodness of model fit [63].
Secondly, we conducted a confirmatory factor analysis (CFA) using the first subsample in R software [61]. The CFA utilized robust maximum likelihood estimation, and model fit was assessed through various indices, including the chi-square (χ2) test, comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation (RMSEA) with a 90% confidence interval, and standardized root mean square residual (SRMR). For RMSEA, values less than or equal to 0.08 indicated excellent fit, and values less than or equal to 0.06 indicated good fit. TLI values above 0.95 and between 0.90 and 0.95 indicated excellent and acceptable fit, respectively. SRMR values less than or equal to 0.08 indicated excellent fit [64]. Once the model fit was confirmed, the second sample was utilized for cross-validation. Subsequently, factor coefficients were obtained using a CFA analysis with the total sample. The R program was used in these procedures. Later, with the total sample, to evaluate the reliability, convergence, and discriminant validity of the model, we utilized Cronbach and Omega’s alpha coefficients, composite reliability (CR, with 0.70 or higher indicating good model reliability), average variance extracted (AVE, with 0.50 or higher indicating proper convergence), and the square root of the AVE (which should be higher than the highest correlation with any other latent variable) [65].
Third, to assess the validity of the evidence-based on its relationships with other variables, we computed the Pearson correlations of the GWEBS with climate change perceptions, eco-anxiety, and trust in science. Correlations ranging from 0 to 0.3 are considered weak, from 0.3 to 0.5 are moderate, from 0.5 to 0.7 are strong, and from 0.7 to 1 are very strong, whether positive or negative [66].
Fourth, we assessed various levels of measurement invariance across gender, environmental activism, and political orientation using multigroup confirmatory factor analyses (CFAs). The less restrictive, or configural, model aimed to determine whether men and women, activists and non-activists, and individuals with left and right political orientations conceptualized general willingness for environmental behavior similarly. This model estimated the same structural model for both groups without imposing any constraints on parameters such as loadings, thresholds, and item variances. The metric invariance model introduced constraints by setting factor loadings equal across groups, assessing whether men and women, activists and non-activists, and individuals with left and right political orientations interpreted the items on the GWEBS similarly. A scalar model further imposed constraints by fixing thresholds equal across groups, examining whether latent factors exhibited identical item scores for different subgroups. Subsequently, we applied a strict invariance model, which set loadings, thresholds, and item variances to the same values across groups, allowing for an assessment of whether measurement error was consistent between men and women, activists and non-activists, and individuals with left and right political orientations. The cutoff values proposed by Cheung and Rensvold [67] to support a more restrictive invariance measurement model were changes in Comparative Fit Index (CFI) of less than or equal to 0.010 and changes in Root Mean Square Error of Approximation (RMSEA) of less than or equal to 0.015. Subsequently, to compare means, we employed the independent samples t-test (for two groups). Cohen’s d effect sizes were also calculated accordingly for the tests utilized.
Finally, a parallel mediation analysis was run with the total sample using PROCESS (Version 2; Model 4 [68]) to examine the indirect effect of climate change perceptions (X) on willingness for environmental behavior (Y) based on rates of eco-anxiety (M1) and trust in science (M2) and controlling for the influence of sociodemographic and ideological characteristics (i.e., gender, environmental activism, and political orientation). Following Hayes’ [68] procedures for testing indirect effects with serial mediators, bias-corrected confidence intervals for indirect associations were estimated based on 5,000 bootstrap samples. A CI that does not include 0 in these models indicates a statistically meaningful association.

3. Results

3.1. The General Willingness for Environmental Behavior Scale

We initiated our analysis with preliminary and exploratory examinations. The skewness and kurtosis values for the observed variables (i.e., items) were found to be within acceptable ranges in subsample 1. However, significant results were obtained for the Kolmogorov–Smirnov test (univariate normality) for all items (ps < 0.001), as well as for the Mardia test (multivariate normality) (MS = 242.25, p < 0.001; MK = 10.48, p < 0.001), indicating that the samples deviated from a strictly normal distribution (see Table 2).
Bartlett’s test (χ2 = 638.81, df = 6, p < 0.001) and the KMO coefficient (0.78) in subsample 1 indicated satisfactory intercorrelation among the items, supporting the interpretation of the factorial solution. Specifically, the exploratory factor analysis (EFA) yielded a one-factor solution with an eigenvalue of 2.66, accounting for 66.5% of the total variance. This solution was supported by acceptable goodness-of-fit indices (χ2[6] = 638.81, p < 0.001, TLI = 0.95, RMSEA = 0.062, SMRS = 0.03). Additionally, as shown in Table 2, the items exhibited appropriate factor loadings and discrimination indices (> 0.50).

3.2. Evidence Based on Internal Structure Relationships with Other Variables, and measurement invariance.

The first subsample was first used to check the one-factor structure. The fit indices obtained were χ2[6] = 291.91, p < 0.001, TLI = 0.98, CFI = 0.99, RMSEA = 0.059 90%CI [0.00, 0.20], SMRS = 0.01. With the second subsample, the fit was checked with the following fit indices: χ2[6] = 364.43, p < 0.001, TLI = 0.98, CFI = 0.99, RMSEA = 0.069 90%CI [0.00, 0.20], SMRS = 0.01. In both subsamples, all indices indicated a good model fit [69], confirming the H1. Finally, to verify the adequacy of the one-factor structure, the analysis was repeated with the entire sample to obtain the estimates (see Figure 1). The final fit was excellent: χ2[6] = 643.86, p < 0.001, TLI = 0.98, CFI = 0.99, RMSEA = 0.061 90%CI [0.00, 0.16], SMRS = 0.01. Likewise, the factor showed an excellent internal consistency. Specifically, Table 3 presents the reliability indices for the GWEBS. There were no disparities between Cronbach’s alpha (α) and McDonald’s omega (ω) observed. Additionally, composite reliability, average variance extracted (AVE), square root of AVE, mean, and standard deviation were computed (Table 3), and all these metrics fell within the reference range.
In seeking evidence of validity relative to other variables, as expected, the score for the GWEBS was correlated with the total scores obtained by the participants in all the studied variables. As Table 3 shows, the GWEBS was positively related to climate change perceptions, eco-anxiety, and trust in science.
Next, we examined the invariance of the GWEBS across gender, environmental activism, and political orientation. As indicated in Table 4, we found support for configural, metric, and scalar invariances across all of them. This suggests that men and women, activists and non-activists, and individuals with left and right orientations conceived the GWEBS construct and interpreted its items in a similar manner. Additionally, the latent factors exhibited equivalent item scores across these groups. While strict invariance was not fully achieved across gender due to a discrepancy in the indexes between the scalar and error invariance models exceeding reference values, scalar invariances were confirmed for activism and political orientation. Consequently, we can add that both the means and variances of the GWEBS can be compared between activists and non-activists, as well as between individuals with left and right orientations.
Finally and from an inter-subjects perspective, the GWEBS differentiated between 1) participants who were part of an environmental group or association and those who were not (t (402) = -8.23, p < .001, d = 0.35, M Non-activists = 3.74, SD = 0.93 vs. M Activists = 4.42, SD = 0.65), 2) women and men (t (402) = -2.53, p = .006, d = 0.26, M Men = 3.75, SD = 1.00 vs. M Women = 3.99, SD = 0.55), and 3) left- and right-oriented participants (t (402) = 4.78, p < .001, d = 0.52, M Left = 4.08, SD = 0.82 vs. M Center-right = 3.60, SD = 0.99). The differences indicated that women, left-oriented people, and members of ecologist associations had a higher general willingness for environmental behavior than men, right-oriented people, and participants who did not belong to any pro-environmental association.
3.3 Connecting climate Change Perceptions and willingness for environmental behavior through eco-anxiety and trust in science.
A parallel mediation analysis was conducted to examine whether the perceptions of climate change might affect the GWEBS through eco-anxiety and trust in science, controlling for gender, environmental activism, and political orientation. As Figure 2 shows, climate change perceptions were indirectly linked to higher general willingness for environmental behavior via increased eco-anxiety [b = 0.02, SE = 0.01, 95% CI (0.01, 0.05)] and trust in science [b = 0.24, SE = 0.05, 95% CI (0.14, 0.35)]. In other words, eco-anxiety and trust in science work in the model as mediating variables that connect climate change perceptions with a general intention to behave in favor of the environment, as measured with the GWEBS.
These patterns of relationships confirmed the H2, suggesting that perceiving climate change as real, human-caused, with serious negative consequences, and occurring closely in time and space may be necessary but not sufficient to induce willingness for environmental behavior. In this respect, feeling eco-anxiety was fully necessary, whereas trusting the veracity of the information on the climate crisis offered by science was partially required. The significance of these relationships prevailed even when we controlled for gender, political orientation, and environmental activism.

4. Discussion

We agree that there are many reasons to feel eco-anxiety nowadays [6,33], especially if you trust science’s information about the climate crisis [41,42]. However, there are no known data that, in general or in the particular context of Spain, analyze how eco-anxiety and trust in science can be jointly channeled into adaptive responses, or what is the same into the large number of pro-environmental behaviors and actions needed to reduce the worst consequences associated with climate change. This is a serious problem which can only be understood if we consider the practical difficulty of connecting psychological constructs of a high level of abstraction with very specific behaviors. Following Fishbein and Azjen [19], many researchers are using the intention to act pro-environmentally as a variable to predict or as an explanatory variable of specific pro-environmental behaviors [13,15,70]. This is not sufficient since the set of pro-environmental behaviors to ultimately be predicted is very broad, has different associated costs and impacts, which not only depend on the will of the people but also on the social conditions in which they live [5,23]. So, our first objective to face this problem was to develop a new measure of general willingness for environmental behavior that helps better connect psychological constructs with whatever selection of specific pro-environmental behaviors.
In this respect, we can concluded that the GWEBS, which was not limited to any particular pro-environmental action but rather the general willingness to do, not to do (degrow), accept social restrictions, and ultimately “do your bit” for the environment, showed a reliable one-factor structure well related to climate change perceptions, eco-anxiety, and trust in science. Additionally, the GWEBS distinguished between women and men, left- and right-oriented people, and people who belonged to pro-environmental groups and people who did not. In line with what the literature shows (e.g. 15,59,71-73), women, left-oriented people, and environmental activists showed higher general willingness for environmental behavior than men, right-oriented people, and people who did not belong to any pro-environmental group or association, respectively.
From now on and as part of the validation process, the GWEBS can be used as a dependent variable, which is how it was used in this study subsequently and serve to investigate psychological mechanisms that promote it. But the GWEBS can also be used as an independent or mediating variable regarding the great diversity of behaviors that people can perform in their particular situations. Although this is a straightforward way for future research, we can anticipate that the GWEBS should be able to explain very different subsets of pro-environmental behaviors.
In any case, the GWEBS includes aspects until now little studied, such as the willingness of individuals to accept the loss of freedom that would entail making truly restrictive social policies in line with what the climate emergency situation demands. It is not only what each person can do individually but also what each one is willing to accept via social imposition. We anticipate that the more people are willing to accept restrictions, the more likely governments will be able to articulate them into regulations that can stop and reverse the cascade of changes that has already begun.
Regarding our second objective, we sought to investigate mechanisms explaining why climate change perceptions do not seem to be associated as frequently as would be desirable with actions [15], so we tested the mediating role of both eco-anxiety and trust in science. In this respect, we can conclude that eco-anxiety, completely, and trust in science, partially, contributed to strengthening the desired relationship between the perception of climate change, understood as real, negative, proximate, and caused by human beings, and the general willingness to take action, measured with the GWEBS.
Considering eco-anxiety as a non-pathological emotional response of discomfort regarding the global environmental crisis and trust in science as a metacognition that provide security to the beliefs that people have about climate change, we can conclude that both variables play a significant role in mobilizing the intention to act according to the perception. The first one may be activating a necessary emotional discomfort and the second one a cognitive security that legitimizes it.
This piece of knowledge must be taken into account if confirmed in new studies. It may serve to address practical issues such as climate change communications and public policies [16]. In this regard, we can anticipate that changing the people’s behaviors that do not work for the planet may require hope and optimism regarding the solutions. However, according to our results, it also requires distressing discourses that mobilize the necessary doses of non-pathological anxiety that drive action. Parallel trust in science could be reinforced since it works for most people as a confidence heuristic in their perceptions about climate change. Feeling anxious but certain of the causes can serve to activate a general desire to act pro-environmentally which can then manifest itself in different sets of pro-environmental behaviors.
This article also has some limitations. First, we acknowledge that willingness for environmental behavior differs from actual enacted behavior. It is an urgently important objective to investigate the connection of the GWEBS with the great diversity of possible pro-environmental behaviors, grouped into very different sets according to the conditions in which each person lives. Nonetheless, studying and promoting the general willingness for environmental behavior is important in itself because communication campaigns can be carried out on the desire to act pro-environmentally regardless of the specific set of behaviors. In this respect, activating general willingness to act could be considered the first step in a chain that ends in specific behaviors. It may not seem like much, but it is important because activating people’s desire to act in a pro-environmental direction can involve many behaviors. Perhaps not all of them can be done, but different combinations can. Studying the variables that can predispose people in this direction is necessary and is part of the change.
Secondly, we used a convenience sample and a cross-sectional design, which do not allow us to test for the cause-and-effect relationships hypothesized. Therefore, future lines of research should employ longitudinal designs to overcome these limitations and test the practical implications of our model. Additionally, employing various sampling procedures would help mitigate potential self-selection bias.
Thirdly, it is crucial to recognize that although the GWEBS has been tailored for the cultural and linguistic context of Spain, variations in the Spanish language exist among different Spanish-speaking Latin American and Caribbean countries. Consequently, researchers utilizing this measure should thoroughly evaluate the items using an adaptation approach and provide valid evidence to ensure that the conclusions drawn are as pertinent as those derived from the Spanish version. It would also be beneficial to validate the GWEBS across different age groups, cultural contexts, and languages to investigate potential cultural differences in the presented findings.
Finally, we know that individuals are not the only actors in the play. Governments and companies also have an important role to play [74]. However, changes at the individual level are crucial and urgent [75] because, ultimately, individuals consume, protest, vote, and have the strength to induce important changes when they are a clear majority fully aware of the crisis. The results of this study tell us that there is still work to do so that people perceive and feel the magnitude of scientific data. Despite that, some valuable pieces of information can be extracted. In this respect, eco-anxiety is an unpleasant but necessary emotion that should be activated. So is trust in science that provides heuristically security in the existing information on climate change. Both variables seem to help connect climate change perceptions and willingness to behave accordingly, even when gender, political orientation, and ecological sensitivity are controlled.

5. Conclusions

We can conclude that the General Willingness for Environmental Behavior Scale (GWEBS) seems to have a reliable one-factor structure, strongly related with climate change perceptions, eco-anxiety, and trust in science. Its four items measure aspects that until now the intentional variables did not include together. Specifically, it measures the willingness to do, but also the willingness not to do (degrow), the willingness to accept social restrictions, and ultimately, the willingness to “do your bit” for the environment. Promoting increases in the GWEBS may be an intervention target as we anticipate this measure will be related to very different sets of specific pro-environmental behaviors. It can also be a specific indicator of environmental sensitivity that helps implement restrictive social measures. In the field of research, we believe that the GWEBS can be an appropriate dependent variable to connect with psychological variables of a high level of abstraction, such as eco-anxiety, trust in science, resilience, hope, etc. In this regard, we can specifically conclude that in our sample of 403 Spanish participants that included members of environmental organizations, eco-anxiety and trust in science reinforced the desired relationship between the perception of climate change, understood as real, negative, proximate, and caused by human beings, and the general willingness for environmental behavior.

Author Contributions

Conceptualization, M.L.V. and C.D.S.; methodology, M.L.V. and C.D.S.; software, M.L.V. and M.A.F.; validation, M.L.V. and M.A.F.; formal analysis, M.L.V. and M.A.F.; investigation, M.L.V., C.D.S. and L.L.G.; resources, C.D.S. and L.L.G.; data curation, M.L.V. and M.A.F.; writing—original draft preparation, M.L.V.; writing—review and editing, C.D.S.; visualization, C.D.S. and L.L.G.; supervision, M.L.V. and C.D.S.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Universidad Rey Juan Carlos (protocol code 0407202327123, September 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Acknowledgments

The authors would like to thank Greenpeace-Spain, Ecologistas en Acción [Ecologists in Action], FUHEM, and Altekio as organizations in the field of ecology and social justice that have provided us with access to people with ecological activism.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations list

AVE = average variance extracted
CFA: Confirmatory Factor Analysis
CFI: Comparative Fit Index
CI: Confidence Interval
CCP: Climate Change Perceptions Scale
CR = composite reliability
EFA: Exploratory Factor Analysis
GWEBS: General Willingness for Environmental Behavior Scale
HEAS: Hogg Eco-Anxiety Scale
KMO: Kaiser–Meyer–Olkin Coefficient
M: Mean
RMSEA: Root Mean Square Error of Approximation
SD: Standard Deviation
SE: Standard Error
SRMR: Standardized Root Mean Square Residual
TLI: Tucker-Lewis Index
α = Cronbach’s alpha
ω = McDonald’s omega

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Figure 1. Factor structure of the GWEBS.
Figure 1. Factor structure of the GWEBS.
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Figure 2. The mediation model depicts the indirect effect of climate change perceptions (CCP) on willingness to behave in favor of the environment (GWEBS) through eco-anxiety and credibility in science. Note. All reported values are unstandardized estimates (b values), with their SE reported in parentheses. The total effect of climate change perceptions on willingness to behave in favor of the environment appears in brackets [ ]. ns = no significant; *p < .05; **p < .01; ***p < .001
Figure 2. The mediation model depicts the indirect effect of climate change perceptions (CCP) on willingness to behave in favor of the environment (GWEBS) through eco-anxiety and credibility in science. Note. All reported values are unstandardized estimates (b values), with their SE reported in parentheses. The total effect of climate change perceptions on willingness to behave in favor of the environment appears in brackets [ ]. ns = no significant; *p < .05; **p < .01; ***p < .001
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Table 2. Descriptive statistics and EFA loadings of the 4 items of the GWEBS.
Table 2. Descriptive statistics and EFA loadings of the 4 items of the GWEBS.
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Table 3. Bivariate correlations, means, standard deviations, Cronbach’s alpha, McDonald’s omega, composite reliability, average variance extracted (AVE), and square roots of AVE for study variables.
Table 3. Bivariate correlations, means, standard deviations, Cronbach’s alpha, McDonald’s omega, composite reliability, average variance extracted (AVE), and square roots of AVE for study variables.
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Table 4. Fit Indices and Comparison of Invariance Models
Table 4. Fit Indices and Comparison of Invariance Models
Models χ2[df] CFI TLI RMSEA [90% IC] ΔCFI ΔRMSEA
Gender
Configural Invariance 4.17[2]*** .997 .997 .061 [.000, .170] - -
Metric Invariance 7.55[5]*** .996 .990 .051 [.000, .0119] -.001 -.010
Scalar Invariance 12.75[8]*** .992 .989 .055 [.000, .0108] -.004 .004
Strict Invariance 41.33[12]*** .953 .953 .111 [.075, .149] -.039 .056
Environmental activism
Configural Invariance 5.95[2]*** .993 .993 .061 [.000, .165] - -
Metric Invariance 8.94[5]*** .993 .983 .062 [.000, .195] .000 .001
Scalar Invariance 18.02[8]*** .983 .973 .077 [.029, .128] -.010 .015
Strict Invariance 28.74[12]*** .974 .972 .089 [.050, .130] -.009 .012
Political orientation
Configural Invariance 3.55[2]*** .997 .984 .062 [.000, .166] - -
Metric Invariance 6.88[5]*** .997 .992 .048 [.000, .114] .000 -.014
Scalar Invariance 9.80[8]*** .997 .995 .034 [.000, .093] .000 -.014
Strict Invariance 17.23[12]*** .991 .991 .047 [.000, .092] -.006 .013
Note. N total = 403. ***p <.001
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