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Behav Res Methods
Behav Res Methods
Behavior Research Methods
1554-351X
1554-3528
Springer US New York

38637442
2408
10.3758/s13428-024-02408-1
Original Manuscript
Development and validation of the Emotional Climate Change Stories (ECCS) stimuli set
Zaremba Dominika d.zaremba@nencki.edu.pl

1
Michałowski Jarosław M. 2
Klöckner Christian A. 3
Marchewka Artur a.marchewka@nencki.edu.pl

1
http://orcid.org/0000-0003-0820-2662
Wierzba Małgorzata m.wierzba@nencki.edu.pl

1
1 grid.419305.a 0000 0001 1943 2944 Laboratory of Brain Imaging, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
2 grid.433893.6 0000 0001 2184 0541 Poznan Laboratory of Affective Neuroscience, SWPS University, Poznań, Poland
3 https://ror.org/05xg72x27 grid.5947.f 0000 0001 1516 2393 Department of Psychology, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
18 4 2024
18 4 2024
2024
56 4 33303345
18 3 2024
© The Author(s) 2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Climate change is widely recognised as an urgent issue, and the number of people concerned about it is increasing. While emotions are among the strongest predictors of behaviour change in the face of climate change, researchers have only recently begun to investigate this topic experimentally. This may be due to the lack of standardised, validated stimuli that would make studying such a topic in experimental settings possible. Here, we introduce a novel Emotional Climate Change Stories (ECCS) stimuli set. ECCS consists of 180 realistic short stories about climate change, designed to evoke five distinct emotions—anger, anxiety, compassion, guilt and hope—in addition to neutral stories. The stories were created based on qualitative data collected in two independent studies: one conducted among individuals highly concerned about climate change, and another one conducted in the general population. The stories were rated on the scales of valence, arousal, anger, anxiety, compassion, guilt and hope in the course of three independent studies. First, we explored the underlying structure of ratings (Study 1; n = 601). Then we investigated the replicability (Study 2; n = 307) and cross-cultural validity (Study 3; n = 346) of ECCS. The collected ratings were highly consistent across the studies. Furthermore, we found that the level of climate change concern explained the intensity of elicited emotions. The ECCS dataset is available in Polish, Norwegian and English and can be employed for experimental research on climate communication, environmental attitudes, climate action-taking, or mental health and wellbeing.

Supplementary Information

The online version contains supplementary material available at 10.3758/s13428-024-02408-1.

Keywords

Climate change
Pro-environmental behaviour
Emotion
Climate emotions
Valence
Arousal
http://dx.doi.org/10.13039/501100007047 Norway Grants 2019/34/H/HS6/00677 issue-copyright-statement© The Psychonomic Society, Inc. 2024
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pmcIntroduction

The climate crisis is recognised as the greatest threat that humanity has ever faced. The Intergovernmental Panel on Climate Change’s 2021 report clearly states that ‘it is unequivocal that human influence has warmed the atmosphere, ocean and land’. Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred (IPCC, 2021). With the growing awareness of climate change and the associated risks, people start to experience intense emotions (Leiserowitz et al., 2021; Marczak et al., 2023; Marks et al., 2021; Zaremba et al., 2023). In turn, emotions shape one's attitudes and behaviour in the face of climate change, including climate change attitudes (Rode et al., 2021), climate change risk perception (van der Linden, 2015) and willingness to engage in climate change mitigation (Xie et al., 2019), as well as endorsement of climate policies (Bouman et al., 2020; Rees et al., 2015; Wang et al., 2018). According to the literature, factors such as gender, political views, understanding of climate change causes and impacts, social norms, value orientations and personal experiences with extreme weather events are all recognised as meaningful predictors of climate action (van der Linden, 2015). Affect and emotions stand out as one of the major determinants (Brosch, 2021). Negative affect toward climate change was found to be the single largest predictor of all examined cognitive, experiential and socio-cultural factors (van der Linden, 2015). In another meta-analysis, negative affect was identified as one of the largest predictors of climate action, along with descriptive norms, perceived self-efficacy and outcome efficacy (van Valkengoed & Steg, 2019). Interestingly, most of these findings come from qualitative and questionnaire studies. The results of experimental studies, however, often yielded inconclusive results (Brosch, 2021; Reser & Bradley, 2017; Schneider et al., 2021). The underlying cause can be attributed to differences in operational definitions and measurement of climate emotions (Chapman et al., 2017).

In the field of environmental psychology, researchers often investigate a wide variety of emotions related to climate change (henceforth: climate emotions), such as guilt, anger (Bissing-Olson et al., 2016; Harth et al., 2013), compassion (Swim & Bloodhart, 2015), anxiety (Whitmarsh et al., 2022) or hope (Bury et al., 2020). Each of these emotions is associated with a specific appraisal pattern and a specific context in which it is experienced (Lazarus, 1991). In fact, failure to provide consistent, replicable findings in this domain of research was mainly attributed to the lack of focus on specific appraisals that accompany the emotional experience of climate change (Brosch, 2021). Therefore, attempts were made to identify distinct climate emotions (Marczak et al., 2023; Pihkala, 2022; Zaremba et al., 2023) and corresponding appraisals, as well as to understand how they motivate behaviour (Harth et al., 2013; Landmann, 2021; Marczak et al., 2023; Zaremba et al., 2023). In the following paragraphs, we will briefly define emotions commonly identified as important motivators of climate action (Brosch, 2021; Reser & Bradley, 2017; Schneider et al., 2021; Shipley & van Riper, 2022). We also specify how the experience of each of these emotions translates to a certain behavioural tendency. In Table 1, we propose the formulation of cognitive appraisals related to the investigated climate emotions.Table 1 Example of cognitive appraisals behind selected climate emotions

Emotion	Cognitive appraisal	
Anger	‘Climate change is a result of harmful actions of individuals or institutions that I don’t identify with.’	
Anxiety	‘Climate change is a real, urgent and severe threat to myself and to valued people and places.’	
Compassion	‘Climate change results in undeserved and omittable suffering and harm to innocent beings.’	
Guilt	‘Climate change is a result of my harmful actions or actions of groups that I identify with.’	
Hope	‘Climate change can be limited with collective, coordinated, proactive efforts.’	

In the context of climate change, anger can be understood as a moral outrage directed at individuals, people in power and institutions that deliberately and carelessly contribute to climate change (Marczak et al., 2023; Zaremba et al., 2023). In particular, it is experienced upon the realisation that climate change affects especially those who contribute the least to global emissions and those who will be most vulnerable to its consequences (Landmann & Hess, 2017). It increases arousal and activates behavioural tendencies to punish those blamed for causing climate change (Harth et al., 2013). The content of climate anger is relevant for the type of pro-environmental behaviours it promotes—anger at politicians and institutions predicts public sphere activism, while anger directed at general human qualities and actions predicts individual mitigation behaviours (Gregersen et al., 2023; Kleres & Wettergren, 2017; Stanley et al., 2021).

Climate anxiety is perhaps the most studied climate emotion and, as such, it has been operationalised in different ways. Some scholars frame it as disproportionate, debilitating, intense anxiety (Coffey et al., 2021) that results in active avoidance of the problem of climate change (Stanley et al., 2021). However, anxiety can also be defined as an adaptive reaction, in which climate change is perceived as a real, urgent and severe threat that needs to be addressed (Marczak et al., 2023; Zaremba et al., 2023). This type of anxiety is related to the action tendency to look for solutions and mitigate climate change (Pihkala, 2020). Thus, such anxiety can predict pro-environmental behaviours (e.g. Clayton & Karazsia, 2020; Helm et al., 2018; Hogg et al., 2021; Whitmarsh et al., 2022).

Compassion is experienced as one witnesses the suffering or undeserved harm of another being and results in the tendency to approach, help and support (Goetz et al., 2010; Landmann & Hess, 2017). The mobilising effect of compassion can be explained by the reduced psychological distance to climate change and its impact on all living things and beings (McDonald et al., 2015). It increases endorsement of climate mitigation efforts (Lu & Schuldt, 2016) and climate change activism (Swim & Bloodhart, 2015).

Guilt arises when one perceives their behaviour as incongruent with their moral standards (Tracy & Robins, 2007), or when one’s in-group is recognised as collectively responsible for causing harm (Wohl et al., 2006). It triggers action tendencies such as reparation and compensatory efforts (Harth et al., 2013; Parkinson et al., 2005; Smith & Ellsworth, 1985). In general, guilt predicts pro-environmental intentions and behaviours (Hurst & Sintov, 2022; Shipley & van Riper, 2022) and is an important moderator between climate change belief and mitigation behaviours (Ferguson & Branscombe, 2010).

In the case of hope, there is still considerable controversy, and researchers currently distinguish between the ‘false hope’ or denial-based hope, related to misguided beliefs about climate change, and the ‘constructive hope’, related to trust that climate change can still be halted with collective, coordinated efforts (Brosch, 2021). The latter type of hope was positively related to self-reported pro-environmental behaviour, support of specific policies and political engagement (Feldman & Hart, 2016, 2018; Ojala, 2015), and was shown to motivate climate action (Chadwick, 2015).

To date, the field of environmental psychology lacks ways to reliably elicit distinct climate emotions in experimental settings. Most previous studies used ad hoc stimuli, such as news reports (Chu & Yang, 2019; Nabi et al., 2018; O’Neill et al., 2013), photos (Gehlbach et al., 2022) or fictitious radio reports (Gustafson et al., 2020). While such stimuli are ecologically valid, they are difficult to use in experimental studies, in which strictly controlled conditions are required to establish a cause-and-effect relationship between variables. Therefore, there is a growing need for the development of validated emotional stimuli databases. To the best of our knowledge, there are only three available stimuli sets suitable for studying climate emotions. The first one, the Affective Climate Images Database (Lehman et al., 2019) comprises 320 pictures relevant to climate change. The second one, the Extreme Climate Event Database (EXCEED; Magalhães et al., 2018), consists of 150 pictures depicting natural disasters related to climate change. Finally, Climate Visuals (climatevisuals.org; Chapman et al., 2016) is a collection of pictures relevant to climate change selected based on both qualitative and quantitative criteria. Importantly, stimuli in the abovementioned datasets have been characterised only in terms of their dimensional properties, such as valence and arousal (Bradley & Lang, 1994; Stevenson et al., 2007), while in the context of climate change, there is a clear need to study discrete emotions (Barrett, 2006; Brosch & Steg, 2021). Empirical evidence demonstrates that it is important to control both dimensional and discrete properties of emotional stimuli (Briesemeister et al., 2014; Harmon-Jones et al., 2017).

Furthermore, despite the long tradition of using images in emotion research (Lang & Bradley, 2007; Marchewka et al., 2014; Michałowski et al., 2017), images may not always be well suited for the task of studying climate emotions. First and foremost, climate change is a multifaceted phenomenon that cannot be easily captured in a single frame. Images tend to be ambiguous, and it is therefore difficult to use them in emotion research while controlling for the associated appraisal pattern (Brosch, 2021). Finally, ecologically valid natural scenes are unsuitable for experimental designs that require strict control of physical properties (e.g. resolution, contrast, luminance). In contrast, textual stimuli (e.g. news reports, personal stories) have been used to convincingly describe the complex realities of climate change (e.g. Lu & Schuldt, 2015). Recent research suggests that naturalistic stimuli such as narratives are especially promising, as they provide all the relevant context and can be inspiring and deeply touching, thus inducing strong emotions (Goldberg et al., 2014; Saarimäki, 2021; Weber, 2006). Such naturalistic stimuli are frequently used in research, as they enable the study of many psychological processes, such as emotion (Jääskeläinen et al., 2021; Saarimäki, 2021), social perception (Mar, 2011; Redcay & Moraczewski, 2020) and language (Hamilton & Huth, 2020), in ecologically valid conditions. Despite their complexity, textual naturalistic stimuli can be easily edited (e.g. change of characters, change of cultural context) to meet the requirements of a particular study.

On the other hand, naturalistic stimuli pose many methodological challenges. Processing of complex textual stimuli demands active construction and simulation of the situation described in the story and involves many processes, such as linguistic processing, perspective taking, empathy, moral reasoning and autobiographical memory (Hsu et al., 2015). Thus, experiments using naturalistic stimuli are challenging to design and their results more difficult to interpret.

Current study

In this article, we describe the development and validation of the Emotional Climate Change Stories (ECCS) stimuli set. ECCS consists of short naturalistic stories in which climate change is placed in the context of personal experience, rather than framed as an abstract scientific phenomenon (Harris, 2017; Morris et al., 2019; van der Linden et al., 2015). The stories were designed to elicit five distinct climate emotions—anger, anxiety, compassion, guilt and hope—all of which were indicated as motivating climate action. The ECCS set was developed in a series of studies conducted in Poland and Norway, two countries heavily dependent on fossil fuels, but with different policies towards achieving climate neutrality (Marczak et al., 2023; Zaremba et al., 2023). The validation procedure was conducted in line with previous studies (Bradley & Lang, 1994, 1999; Lang & Bradley, 2007; Marchewka et al., 2014; Wierzba et al., 2015). First, the ratings were collected in Poland from a large opportunity sample (Study 1, n = 601), as well as from an independent purposive sample with a demographic profile reflecting the population of Poland (Study 2, n = 307). This step was crucial to ensuring the high quality of ECCS ratings and investigating the replicability of the findings. Next, the ratings were collected in Norway from a purposive sample with a demographic profile reflecting the population of Norway (Study 3, n = 346) for the purpose of validating the ECCS ratings in a different culture.

Method

Materials

The stories in ECCS were inspired by the material collected in two qualitative studies conducted in Poland. In each case, we identified excerpts in which participants reported having experienced five emotion categories of interest: anger, anxiety, compassion, guilt and hope. In the first qualitative study (n = 40), we conducted semi-structured in-depth interviews with people strongly concerned about climate change (Zaremba et al. 2023). In this study, participants freely described a wide array of emotions experienced in the face of climate change and the context in which these emotions emerged. The collected material was analysed in a multi-step thematic analysis: the content of the interviews was carefully tagged by several researchers independently, and then used to identify recurring themes (e.g. drought, storm, heatwave, news in social media, politicians, talking to family). All the details can be found in the original work by Zaremba et al. (2023). In the second qualitative study (n = 523), we conducted a short online survey on a large opportunity sample. In this study, participants briefly described situations in which they specifically experienced anger, anxiety, compassion, guilt and hope in the context of climate change. The survey material was reviewed and tagged according to the thematic structure developed during the interview analysis (Zaremba et al. 2023). Based on the collected material (the qualitative interviews and the survey data), we generated several hundred short stories, representing the most commonly recurring themes. Finally, we selected 30 coherent and diverse stories representing each emotion category (150 stories in total). Furthermore, 30 neutral stories were developed on the basis of a standardised list of affect-related life events (Cohen et al., 2018).

The stories were professionally translated into Norwegian and English. Furthermore, the stories underwent proofreading to ensure they were adjusted to the cultural context, avoiding content that might be specific to a particular culture and could potentially be unfamiliar or less relevant in other cultural settings. Importantly, the ECCS stories are of similar length (Polish: M = 307.2, SD = 44.49; Norwegian: M = 295.2, SD = 49.35; English: M = 304.0, SD = 51.65). The full list of stimuli included in ECCS can be found in the Supplementary Materials. The most representative stories in each emotion category are presented in Table 2, and the mean story length (number of characters) for each language version of ECCS is summarised in Table S1.Table 2 Stories that were found to best represent each emotion category

Type	Example story	
Anger	Lisha is very rich and likes to change her wardrobe frequently. Ever since she has discovered a website with very cheap clothes, she orders 20–30 items a week. Some turn out to be a poor fit, so she throws them straight into the garbage bin. Still, Lisha does not consider this wasteful, because the clothes were ridiculously cheap.	
Anxiety	Ada studies the oceans. Recently she had to double check her calculations, which indicated that melting Arctic ice may submerge areas inhabited by tens of millions of people. Unfortunately, her calculations turned out to be correct.	
Compassion	It was a hot day when Emilie was on a bus with her seriously ill rabbit, taking it to the vet. The rabbit had trouble breathing, and the poor air conditioning was not able to cool the bus sufficiently. Before she could get to the vet, the rabbit died in its cage. Emilie got out, sat down at an empty bus stop and began to cry.	
Guilt	By using plastic, we contribute to the growing environmental catastrophe every day. Even if we segregate waste carefully, there is no guarantee that plastic will be recycled. Patches of plastic garbage float on the surface of the oceans, the largest of which is three times the size of France.	
Hope	Yoshida has discovered a new species of bacteria. The bacteria are able to break down plastic that would otherwise be deposited in landfills. Yoshida's discovery gained so much publicity that he was awarded another research grant. There are reasons to hope that his solution can be implemented on a large scale.	
Neutral	Monica entered the room, opened the wardrobe and bent down to reach into one of the lower shelves. She took out her brown pants and put them on. Then she opened a drawer in her dresser and took out a belt. She passed it through the belt loops on her pants and fastened the buckle.	

Participants

Participants eligible to join the studies were native speakers of Polish (Study 1, 2) and Norwegian (Study 3). This criterion ensured that the participants had a solid understanding of their respective languages and minimised the possibility of inaccuracies or inconsistencies in the data obtained. Furthermore, we collected demographic data about participants’ gender, age, place of residence, education, parenthood status, occupation, climate activism and socio-economic status, as well as information about their belief in and concern about climate change (details provided in Table S2 of the Supplementary Materials).

Study 1

A total of 749 Polish residents were recruited via advertisements on social media and through the SWPS University mailing list. After a data quality check, data from 601 individuals (504 women, 92 men and five non-binary persons) were retained. Depending on the recruitment platform, participants received no remuneration or were remunerated with student credit points.

Study 2

A total of 349 Polish residents were recruited by a professional company. Purposive sampling was used in order to reach a diverse group of participants, with a demographic profile broadly reflecting the population of Poland. After a data quality check, data from 307 individuals (164 women, 142 men and one non-binary person) were retained. Participants received remuneration equivalent to €2.

Study 3

A total of 450 Norwegian residents were recruited by a professional company. Purposive sampling was used in order to reach a diverse group of participants, with a demographic profile broadly reflecting the population of Norway. After a data quality check, data from 346 individuals (181 women and 165 men) were retained. Participants received remuneration equivalent to €0.50.

Procedure

The procedures used in Studies 1–3 were as closely matched as possible. Participants completed the procedure remotely, working on their own devices (e.g. desktops, tablets, mobile phones). A purpose-built, secure web application was used to collect the ratings. The participants first read the description of the aims of the study, and provided their informed consent and demographic data. Then, participants were informed that they would be asked to read stories describing different situations and rate each of the stories on several scales. Participants provided their ratings using a slider from 0 to 99, with the bounds of the scales explicitly defined in the following way: valence (from negative emotions, through no emotions, to positive emotions); arousal (from no arousal to strong arousal); emotion categories: anger, anxiety, compassion, guilt, hope (from not at all, to to a large extent). The participants were able to return to the instruction screen at any time during the task. The stories to be rated in a given session were randomly selected from the initial pool of stories. However, stories with the smallest number of ratings collected so far had a greater chance of being selected. During the assessment task, each trial began with a display of a story in full-screen mode. Next, on the following screen, the participants were still able to see the story in the upper part of the screen, but this time, they were asked to rate the story in terms of valence, arousal, as well as the extent to which the story elicited anger, anxiety, compassion, guilt and hope. As soon as all the responses were submitted, the next trial would begin. There was no time limit to complete the task, but the time spent on reading the story and the time spent providing the ratings was recorded. After completing the ratings for 10 stories, participants could choose to continue rating additional stories or finish the task.

Data preprocessing

To ensure data quality, we defined the following criteria: (1) only adult, native Polish speakers (in the case of Study 1 and Study 2) /native Norwegian speakers (in the case of Study 3) were permitted to join the study; (2) their responses regarding gender, age and the level of climate change concern had to be consistent with their responses to the same questions in the screening survey (applicable to Study 2 and Study 3 only); (3) participants had to complete ratings for at least 10 stories.

Results

Here, we will use the following abbreviations to denote story types: ANG, anger; ANX, anxiety; COM, compassion; GUI, guilt; HOP, hope; NEU, neutral. Otherwise, we will use full terms to denote rating scales: valence, arousal, anger, anxiety, compassion, guilt and hope.

General information about the collected ratings

A complete list of stories in all available language versions (Polish, Norwegian and English), together with their mean ratings, can be found in the Supplementary Materials. On average, each story was rated by 147.6 people (min = 141, max = 155), and depending on the study, a participant rated on average 19.93–23.41 stories. Depending on the study, the mean story presentation time was 6.8–11.5 seconds, and the mean story evaluation time was 16.4–19.5 seconds. A detailed report on the total number of ratings and the number of stories rated per participant in each study can be found in Table S3 in the Supplementary Materials.

Dimensional characteristics

First, we investigated the distribution of valence and arousal ratings, which are commonly used to characterise emotional stimuli (e.g. Lang & Bradley, 2007; Lehman et al., 2019; Magalhães et al., 2018; Marchewka et al., 2014; Wierzba et al., 2015, 2022). Figure 1 presents the pattern of results obtained in Studies 1–3. In agreement with previous research, we observed a non-linear relationship between valence and arousal ratings. Furthermore, three characteristic clusters emerged: stories evoking negative emotions (ANG, ANX, COM and GUI stories, characterised by high arousal and low valence), neutral stories (NEU stories characterised by low arousal and moderate valence) and stories evoking positive emotions (HOP stories, characterised by high arousal and high valence). Thus, stimuli rated more extreme in terms of valence (either more negative or more positive) were also rated high in terms of arousal. Although the dispersion of ratings in the dimensions of valence and arousal was greater in Study 1 than in Studies 2 and 3, the general pattern of results seems consistent across the studies. Comparisons of ratings of each story between studies can be found in Figures S1 and S2 in the Supplementary Materials.Fig. 1 Mean valence and arousal ratings for each story. Note: Individual stories are represented by dots. Colours denote different story types: ANG - anger, ANX - anxiety, COM - compassion, GUI - guilt, HOP - hope, NEU - neutral

Climate emotions

Next, we explored the distribution of ratings in terms of distinct climate emotions: anger, anxiety, compassion, guilt and hope. The general distribution of mean ratings for each rating scale and each study is presented separately in Fig. 2.Fig. 2 Distribution of mean anger, anxiety, compassion, guilt and hope ratings for each story type. Note: The results are presented separately for each rating scale (rows) and each study (columns). Colours denote different story types: ANG - anger, ANX - anxiety, COM - compassion, GUI - guilt, HOP - hope, NEU - neutral

Furthermore, we statistically examined the effects of story type and study on the mean ratings of anger, anxiety, compassion, guilt and hope. In particular, we were interested in determining whether stories belonging to a specific story type were rated similarly on the scale relevant for that story type (e.g. anger ratings for ANG stories, anxiety ratings for ANX stories). As the initial step, we performed a MANOVA with story type and study as factors. We found significant main effects for story type, F(5, 35,050) = 331.05, p < .001, Pillai’s trace = .955, and study, F(2, 14,014) = 144.26, p < .001, Pillai’s trace = .187, revealing that both factors had a significant overall impact on the collected ratings. Furthermore, a significant interaction effect was observed, F(10, 35,050) = 36.61, p < .001, Pillai’s trace = .248). To further investigate this interaction, ANOVA analyses were performed for each rating scale separately and corrected for multiple comparisons. In each case, the ANOVAs were followed by post hoc comparisons to further investigate whether the ratings collected in the compared studies differed. For simplicity, we focused on comparing ratings on story-type relevant scales.

First, we compared samples with different motivations to participate in the study (Study 1: opportunity sample, Study 2: purposive sample). The ANOVAs (with a correction for multiple comparisons) revealed a significant interaction effect between story type and study for all of the rating scales (anger: F(5, 5084) = 18.44, p < .0001, partial η2 = .02; anxiety: F(5, 5084) = 17.14, p < .0001, partial η2 = .02; compassion: F(5, 5084) = 30.012 p < .0001, partial η2 = .03; guilt: F(5, 5084) = 7.32, p < .0001, partial η2 =.01; hope F(5, 5084) = 35.87 p < .0001, partial η2 = .03). Post hoc comparisons showed that none of the interactions between story type and study were significant for the relevant scales (ANG stories on anger scale: p = .64; ANX stories on anxiety scale: p = .93; COM stories on compassion scale: p = .16; GUI stories on guilt scale: p = .07; HOP stories on hope scale: p > .99), indicating no significant differences in how participants from the opportunity and purposive samples rated stories of each type on the relevant scales (see Table S4 in the Supplementary Materials).

Next, we compared story ratings between samples from different countries, where different language versions of ECCS were used (Study 2: Polish sample, Study 3: Norwegian sample). The ANOVAs (with a correction for multiple comparisons) revealed a significant interaction effect between story type and study for almost all rating scales (anger: F(5, 3611) = 8.99, p < .0001, partial η2 = .01; anxiety: F(5, 3611) = 4.09, p = .015, partial η2 = .01; compassion: F(5, 3611) = 16.28, p < .0001, partial η2 = .02; guilt: F(5, 3611) = 2.15, p = .84, partial η2 < .01; hope F(5, 3611) = 5.97, p < .0001, partial η2 = .01). Similarly, post hoc comparisons showed that none of the interactions between story type and study were significant for the relevant scales (ANG stories on anger scale: p > .99, ANX stories on anxiety scale: p > .99, COM stories on compassion scale: p = .86, GUI stories on guilt scale: p = .33, HOP stories on hope scale: p = .19), indicating no significant differences in how participants from Poland and Norway rated stories of each type on relevant scales (see Table S5 in the Supplementary Materials).

Impact of climate change concern on story ratings

Finally, we investigated whether the level of concern about climate change predicts the intensity of emotions experienced when reading the ECCS stories. To start, we divided our sample into three groups (of approximately equal size), representing three levels of concern about climate change: low (n = 395; score of 1–3 on a five-point scale), medium (n = 500; score of 4 on a five-point scale) and high (n = 343; score of 5 on a five-point scale). Next, for each participant, we calculated their summary emotion score, representing the intensity of experienced emotions. The participant’s summary score was calculated for each story type separately, using the following formula:score=rvalence-50∗rarousal,

where r denotes the mean ratings for a given story type. The summary score was then rescaled to take values between 0 and 1.

The relationship between the summary emotion score and the level of climate change concern for each story type is shown in Fig. 3. To test this relationship statistically, we performed a linear regression analysis. The model was statistically significant, F(2, 6933) = 329.85, p < .001, suggesting that the collected ratings could be predicted based on participants’ climate change concern. However, the model accounted for a rather weak proportion of variance (R2 = 0.09, adj. R2 = 0.09). Results showed that participants with medium climate concern had significantly higher scores than those with low concern (β = 0.10, 95% CI [0.09, 0.12], t(6933) = 15.37, p < .001), as did participants with high climate concern (β = 0.19, 95% CI [0.17, 0.20], t(6933) = 25.54, p < .001).Fig. 3 The impact of climate concern on story ratings. Note: For simplicity, we recoded the climate change concern from a five-point to a three-point scale (low, medium, high). Colours denote different story types: ANG - anger, ANX - anxiety, COM - compassion, GUI - guilt, HOP - hope, NEU - neutral

Classification of stories into emotion classes

Previous research has demonstrated that the emotional response to climate change is complex and multifaceted. Similarly, we expected that realistic personal stories about climate change would evoke a range of different emotions simultaneously. For instance, a story about trees damaged by municipal workers could elicit feelings of compassion towards the victims (the trees) and anger towards those responsible for causing the harm (the people in power who issued a permit to cut the trees). Each individual ECCS story was rated according to the intensity of five emotions: anger, anxiety, compassion, guilt and hope. In other words, some stories could be associated mostly with one dominant emotion (e.g. hope), while others could be related to several emotions (e.g. anxiety and compassion) or none.

We used the collected data to identify stories that best represented each emotion category. To achieve this, we adopted a method introduced in our previous work (Wierzba et al., 2015, 2022). Here, we consider a five-dimensional hypercube, with each axis corresponding to one of the emotions. The ratings of a given story determine its position in the hypercube. Five of the hypercube's corners represent the emotion classes: [99 0 0 0 0] anger, [0 99 0 0 0] anxiety, [0 0 99 0 0] compassion, [0 0 0 99 0] guilt and [0 0 0 0 99] hope. The origin, namely [0 0 0 0 0], represents the neutral class. The distance of each story from each of the corners can be calculated using the standard formula:d(p,q)=(p1-q1)2+(p2-q2)2+...+(pk-qk)2

The distances are first calculated for each participant separately, based on the individual ratings contributed by each person. Next, the distances are averaged over all participants to yield a summary measure of the distance of each story from each of the corners:d¯=1n∑i=1ndi=d1+d1+...+dnn

The following conditions must be fulfilled for a story to be assigned to one of the classes: (1) the story’s distance to the respective class must be smaller than a chosen threshold; (2) the story must meet the first condition for one class only; (3) if the story falls within an area of intersection of two (or more) classes, it remains unclassified; (4) if the story does not meet the first condition for any of the classes, it remains unclassified; (5) the assigned class must match the initial category label (i.e. the emotion the story was constructed for).

Importantly, this method can be tailored to one's needs. One approach is to set a threshold value for each class, which will determine the size of each class (i.e. the number of stories it contains). Alternatively, one could set a desired class size for each class, which would require a particular combination of threshold values to achieve.

First, we tested different values of thresholds by simultaneously increasing the threshold for each of the classes. Figure S3 in the Supplementary Materials illustrates how class sizes change as we gradually increase the thresholds from 0 to 140 (the minimum and maximum possible distance between the hypercube's corners, respectively). We observed that it was especially easy to classify stories into the neutral class, followed by the hope, anger and compassion classes. Almost no stories were classified into the anxiety class, and none were assigned to the guilt class.

Based on these findings, we attempted to create NEU, HOP, ANG and COM classes of equal size. The threshold values were determined with the help of a simple genetic algorithm (the exact implementation of the algorithm is available in the Supplementary Materials). Figure 4 presents the resulting distribution of classes, each containing nine stories. The list of classified stories can be found in the Supplementary Materials.Fig. 4 Distribution of the ratings of stories from ANG, COM, HOP and NEU classes identified with the classification algorithm. Note: Here, rows and columns represent different rating scales: valence, arousal, anger, anxiety, compassion, guilt, and hope. Each subplot shows the distribution of the ECCS stories in the domain of two rating scales. For instance, the top-left corner shows the distribution of the stories in the domain of valence (horizontal axis) and arousal (vertical axis). Each dot represents one of 180 stories, with colours denoting different classes identified with the classification algorithm: ANG - anger, COM - compassion, HOP - hope, NEU - neutral. Unclassified stories are marked in light grey for visualisation purposes

Discussion

Recent findings indicate that emotions play a crucial role in shaping people's perception of climate change. While most of these findings come from qualitative and questionnaire studies, experimental studies are of particular importance as they allow us to establish causal relationships between the studied variables. Thus, there is a growing need for the development of validated emotional stimuli databases, suitable for reliably and effectively eliciting distinct emotions related to climate change in experimental settings. The employment of such validated stimuli sets, in contrast to ad hoc stimuli, enables researchers to exert greater control over their experiments, thereby promoting a higher level of objectivity in research inferences.

In this article, we describe the development and validation of the Emotional Climate Change Stories (ECCS) database. ECCS is a collection of naturalistic, relatable stories that place climate change in the context of personal experience, thus avoiding the framing of this phenomenon solely as a distant and abstract scientific fact (Morris et al., 2019; Weber, 2006). For instance, some of the stories describe people who learn about the consequences of climate change and make personal choices that prioritise the environment (Ockwell et al., 2009). This format has been confirmed as an effective means of eliciting engagement in climate communication research (Gustafson et al., 2020; Jones & Song, 2014; Moezzi et al., 2017). Importantly, the stories were created based on qualitative in-depth interviews (Zaremba et al., 2023), in which individuals freely described a wide array of emotions experienced in the face of climate change and the context in which these emotions emerged.

The data-driven, narrative origins of ECCS stories allow for their analysis through the lens of empirical ecocriticism (Schneider-Mayerson et al., 2020). Even though ECCS are shorter than most texts investigated by ecocritics (novels, poetry, children's literature, film, etc.), they definitely reflect contemporary discourse on climate change. Future research could use this approach to provide additional insights.

The ECCS stories are characterised in terms of their dimensional properties, such as valence and arousal (Bradley & Lang, 1994; Stevenson et al., 2007), as well as in terms of discrete emotions (Barrett, 2006; Ekman, 1992). Moreover, we demonstrate that the story ratings can be predicted by the self-reported level of concern about climate change. This relationship was consistently observed for all story types except the neutral stories, providing evidence for the validity of the collected ratings. In particular, our findings are in line with the notion that individuals strongly concerned about the environment should—through their personal, lived experiences of climate change—find the stories more relatable and thus report higher intensity of emotions (Morris et al., 2019). Interestingly, although investigated, this relationship was not observed for other existing datasets of stimuli related to climate change. Specifically, Lehman and colleagues (Lehman et al., 2019) examined whether the valence and arousal ratings of climate change images depended on participants’ environmental attitudes, but found no evidence for that.

As for the dimensional properties of ECCS, we observed a non-linear relationship between valence and arousal. Specifically, stories that were rated more extreme in terms of valence (either more negative or more positive) were also rated as more arousing. This finding is in agreement with many previous studies (Lang & Bradley, 2007; Magalhães et al., 2018; Marchewka et al., 2014; Riegel et al., 2015; Wierzba et al., 2015). Furthermore, negative stories were rated more arousing than positive stories. Similarly, previous studies demonstrated that negative, disturbing pictures of climate change were found most salient (Lehman et al., 2019; Leiserowitz, 2006).

As for the discrete properties of ECCS, we were able to identify stories that predominantly represent one emotion category, such as anger, compassion or hope. ECCS contains stories representing some of the most studied climate emotions: guilt, anger (Bissing-Olson et al., 2016; Harth et al., 2013), compassion (Swim & Bloodhart, 2015), anxiety (Whitmarsh et al., 2022) or hope (Bury et al., 2020). Each of these emotions is associated with a specific appraisal pattern and a specific context in which it is experienced (Brosch, 2021), and in turn can lead to different behavioural tendencies (Böhm, 2003; Landmann, 2021; Marczak et al., 2023; Zaremba et al., 2023). Individuals from different populations did not differ in terms of how they rated stories on relevant scales (e.g. ANG stories on the anger scale). However, they did differ in terms of how they evaluated stories on the remaining scales (e.g. ANG stories on the compassion scale). In particular, we observed significant differences between Studies 1 and 2 (same country, different motivation to participate) in this regard. In Study 1, both the range and the variance of responses was greater than in Study 2. This suggests that populations with different demographic profiles (e.g. young, mostly student sample with non-financial motivation to participate vs general population with financial motivation to participate) might show a slightly different response pattern. Interestingly, ratings collected in Studies 2 and 3 (same motivation to participate, different country) were much more similar, suggesting that the collected ratings may be universal across the context of the Global North. Overall, our results—replicated across different populations and different cultures—suggest that by framing climate change in a specific context, one can reliably elicit distinct climate emotions.

At the same time, our results clearly indicate that ECCS stories differ in their potential to represent the emotion category they were intended to evoke. In other words, some stories convey a single, pure emotion, while others elicit a blend of emotions. With the use of the classification method described in the manuscript, we were able to identify stories related strongly and specifically to anger, compassion and hope, but we failed to identify stories related to anxiety and guilt. ANX stories received comparably high anxiety and compassion ratings, while also scoring relatively high on anger and guilt scales. These results are in line with previous findings, which suggest that these emotions often co-occur (Hatfield et al., 2009; Marczak et al., 2023). Evoking strong and specific guilt turned out to be especially challenging. Cognitive appraisals related to the guilt category revolve around the locus of responsibility for taking part in causing and solving climate change (Wang et al., 2018; Zaremba et al., 2023). GUI stories were designed to evoke guilt by promoting identification with the character or the group that contributes to climate change. They were, however, associated with the least specific emotional response and the lowest overall intensity of emotion compared to other stories. On average, elicited feelings of guilt were not intense. Perhaps the fact that most of the ECCS stories were third-person narratives makes it a less suitable means of eliciting guilt, for example in comparison to the Ecological Footprint Task (Mallett et al., 2013). Furthermore, people demonstrate resistance in response to attempts to evoke climate emotions that threaten self-esteem or sense of security (Ma & Hmielowski, 2022). The low intensity of reported guilt might have also resulted from the fact that the participants tried to preserve a positive self-image (Caillaud et al., 2016) and therefore used a variety of coping strategies (such as disidentifying with the protagonist or minimising the negative consequences of climate-unfriendly actions). Similarly, climate anxiety may also activate maladaptive emotion-focused coping strategies, such as denial or de-emphasising the threat (Haltinner & Sarathchandra, 2018; Ojala, 2012). Masking climate emotions as a form of defensive reaction to cognitive dissonance or a threat to self-concept has been identified in previous studies (Bercht, 2021). We advise taking these factors into consideration when using ECCS for research purposes.

The ECCS dataset was created based on the data collected in Poland and Norway, two European countries that belong to the Global North and are highly reliant on fossil fuels (Brauers & Oei, 2020; EIA, 2019). While we created ECCS with the aim that the stories would be as culturally universal as possible, we acknowledge that the stories are more representative of the experiences of people living in the Global North countries. Because the relatability of such stories may depend on the geopolitical context, we encourage researchers who plan further ECCS adaptations to take these limitations into account. Moreover, in-depth interviews and survey studies that inspired the stories were conducted between 2020 and 2021. Thus, ECCS narratives describe contemporary discourse on climate change (e.g. technological solutions to climate change that are presently being developed; political and social issues that are currently prevalent in traditional and social media). Over time, as the perception of climate change and its impacts evolves, the stories may become less relevant or relatable.

Future directions

The ECCS database holds the potential for facilitating research across various disciplines of scientific study. In particular, it can be used to explore the role of emotions in motivating pro-environmental behaviour, policy support and consumer decisions, as well as psychological well-being and mental health. The collected ratings turned out to be highly consistent across different populations and different cultural contexts, which suggests that ECCS can be successfully used in various cultural contexts (Henrich et al., 2010). Importantly, the ratings are available both as summary scores and as individual scores to enable research on specific groups, such as different generations (Gray et al., 2019), parents (Schneider-Mayerson & Leong, 2020) or climate activists (Eide & Kunelius, 2021). Consequently, researchers can flexibly choose stimuli with desired parameters that best suit their needs. The choice of emotion categories in ECCS was based on our focus on the role of emotions in motivating pro-environmental behaviour. For this reason, our research was not concerned with many other climate emotions, which are currently widely recognized by the research community. In future, it may be useful to extend the ECCS dataset, by including stories representing other climate emotions. Because the ECCS stories have only been investigated with self-report measures, it would also be beneficial to investigate their properties using more objective measures (e.g. physiological reactions, brain activity). The ECCS stories, together with the accompanying data and code used for the analysis, are publicly available for scientific, non-commercial use and can be found at: https://osf.io/v8hts/.’

Supplementary Information

Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 658 KB)

Authors' contributions

D. Zaremba: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualisation, Writing—original draft; Writing—Review and editing;

J. M. Michałowski: Funding acquisition, Project administration, Writing—Review and editing;

C. A. Klöckner: Conceptualization, Funding acquisition, Project administration, Supervision, Writing—Review and editing;

A. Marchewka: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing—Review and editing;

M. Wierzba: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Project administration, Software, Supervision, Validation, Visualization, Writing—Review and editing.

Funding

This research was conducted under the project ‘Understanding patterns of emotional responses to climate change and their relation to mental health and climate action taking’ funded by Norway Grants No. 2019/34/H/HS6/00677.

Availability of data and materials

Data and materials can be accessed at: https://osf.io/v8hts/

Code availability

Code used for the analyses can be accessed at: https://github.com/nencki-lobi/ECCS

Declarations

Conflicts of interest

The authors declare no conflicts of interest.

Ethics approval

The research was carried out in compliance with the principles of the Declaration of Helsinki. The study protocol was approved by the SWPS University of Social Sciences and Humanities Research Ethics committee in Poland (approval no. 2021–52-12).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open practices statement

None of the work described in this paper was preregistered. All data and code are openly shared at: https://osf.io/v8hts/

Artur Marchewka and Małgorzata Wierzba share equal senior contribution.
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References

Barrett LF Are emotions natural kinds? Perspectives on Psychological Science: A Journal of the Association for Psychological Science 2006 1 1 28 58 10.1111/j.1745-6916.2006.00003.x 26151184
Bercht AL How qualitative approaches matter in climate and ocean change research: Uncovering contradictions about climate concern Global Environmental Change: Human and Policy Dimensions 2021 70 102326 10.1016/j.gloenvcha.2021.102326
Bissing-Olson MJ Fielding KS Iyer A Experiences of pride, not guilt, predict pro-environmental behavior when pro-environmental descriptive norms are more positive Journal of Environmental Psychology 2016 45 145 153 10.1016/j.jenvp.2016.01.001
Böhm G Emotional reactions to environmental risks: Consequentialist versus ethical evaluation Journal of Environmental Psychology 2003 23 2 199 212 10.1016/S0272-4944(02)00114-7
Bouman T Verschoor M Albers CJ Böhm G Fisher SD Poortinga W Whitmarsh L Steg L When worry about climate change leads to climate action: How values, worry and personal responsibility relate to various climate actions Global Environmental Change: Human and Policy Dimensions 2020 62 102061 10.1016/j.gloenvcha.2020.102061
Bradley MM Lang PJ Measuring emotion: the Self-Assessment Manikin and the Semantic Differential Journal of Behavior Therapy and Experimental Psychiatry 1994 25 1 49 59 10.1016/0005-7916(94)90063-9 7962581
Bradley, M. M., & Lang, P. J. (1999). Affective norms for English words (ANEW): Instruction manual and affective ratings. Technical report C-1, The Center for Research in Psychophysiology, University of Florida. https://pdodds.w3.uvm.edu/teaching/courses/2009-08UVM-300/docs/others/everything/bradley1999a.pdf
Brauers H Oei P-Y The political economy of coal in Poland: Drivers and barriers for a shift away from fossil fuels Energy Policy 2020 144 111621 10.1016/j.enpol.2020.111621
Briesemeister BB Kuchinke L Jacobs AM Emotion word recognition: Discrete information effects first, continuous later? Brain Research 2014 1564 62 71 10.1016/j.brainres.2014.03.045 24713350
Brosch T Affect and emotions as drivers of climate change perception and action: A review Current Opinion in Behavioral Sciences 2021 42 15 21 10.1016/j.cobeha.2021.02.001
Brosch T Steg L Leveraging emotion for sustainable action One Earth 2021 4 12 1693 1703 10.1016/j.oneear.2021.11.006
Bury SM Wenzel M Woodyatt L Against the odds: Hope as an antecedent of support for climate change action The British Journal of Social Psychology/the British Psychological Society 2020 59 2 289 310 10.1111/bjso.12343
Caillaud S Bonnot V Ratiu E Krauth-Gruber S How groups cope with collective responsibility for ecological problems: Symbolic coping and collective emotions The British Journal of Social Psychology/ the British Psychological Society 2016 55 2 297 317 10.1111/bjso.12126
Chadwick AE Toward a theory of persuasive hope: effects of cognitive appraisals, hope appeals, and hope in the context of climate change Health Communication 2015 30 6 598 611 10.1080/10410236.2014.916777 25297455
Chapman DA Corner A Webster R Markowitz EM Climate visuals: A mixed methods investigation of public perceptions of climate images in three countries Global Environmental Change: Human and Policy Dimensions 2016 41 172 182 10.1016/j.gloenvcha.2016.10.003
Chapman DA Lickel B Markowitz EM Reassessing emotion in climate change communication Nature Climate Change 2017 7 12 850 852 10.1038/s41558-017-0021-9
Chu, H., & Yang, J. Z. (2019). Emotion and the Psychological Distance of Climate Change. In Science Communication (Vol. 41, Issue 6, pp. 761–789). 10.1177/1075547019889637
Clayton S Karazsia BT Development and validation of a measure of climate change anxiety Journal of Environmental Psychology 2020 69 101434 10.1016/j.jenvp.2020.101434
Coffey Y Bhullar N Durkin J Islam MS Usher K Understanding Eco-anxiety: A Systematic Scoping Review of Current Literature and Identified Knowledge Gaps The Journal of Climate Change and Health 2021 3 100047 10.1016/j.joclim.2021.100047
Cohen DJ Barker KA White MR A standardized list of affect-related life events Behavior Research Methods 2018 50 5 1806 1815 10.3758/s13428-017-0948-9 28779458
EIA. (2019). Internationa l - U.S. Energy Information Administration (EIA). https://www.eia.gov/international/rankings/country/NOR?pa=12&u=0&f=A&v=none&y=01%2F01%2F2019. Accessed 18 March 2024.
Eide E Kunelius R Voices of a generation the communicative power of youth activism Climatic Change 2021 169 1–2 6 10.1007/s10584-021-03211-z 34744220
Ekman P Are there basic emotions? Psychological Review 1992 99 3 550 553 10.1037/0033-295X.99.3.550 1344638
Feldman L Hart PS Using political efficacy messages to increase climate activism: The mediating role of emotions Science Communication 2016 38 1 99 127 10.1177/1075547015617941
Feldman L Hart PS Is there any hope? how climate change news imagery and text influence audience emotions and support for climate mitigation policies Risk Analysis: An Official Publication of the Society for Risk Analysis 2018 38 3 585 602 10.1111/risa.12868 28767136
Ferguson MA Branscombe NR Collective guilt mediates the effect of beliefs about global warming on willingness to engage in mitigation behavior Journal of Environmental Psychology 2010 30 2 135 142 10.1016/j.jenvp.2009.11.010
Gehlbach H Robinson CD Vriesema CC Bernal E Heise UK Worth more than 1000 words: How photographs can bolster viewers’ valuing of biodiversity Environmental Conservation 2022 49 2 99 104 10.1017/S0376892922000042
Goetz JL Keltner D Simon-Thomas E Compassion: An evolutionary analysis and empirical review Psychological Bulletin 2010 136 3 351 374 10.1037/a0018807 20438142
Goldberg H Preminger S Malach R The emotion-action link? Naturalistic emotional stimuli preferentially activate the human dorsal visual stream NeuroImage 2014 84 254 264 10.1016/j.neuroimage.2013.08.032 23994457
Gray SG Raimi KT Wilson R Árvai J Will Millennials save the world? The effect of age and generational differences on environmental concern Journal of Environmental Management 2019 242 394 402 10.1016/j.jenvman.2019.04.071 31059952
Gregersen T Andersen G Tvinnereim E The strength and content of climate anger Global Environmental Change: Human and Policy Dimensions 2023 82 102738 10.1016/j.gloenvcha.2023.102738
Gustafson A Ballew MT Goldberg MH Cutler MJ Rosenthal SA Leiserowitz A Personal stories can shift climate change beliefs and risk perceptions: The mediating role of emotion Communication Reports 2020 33 3 121 135 10.1080/08934215.2020.1799049
Haltinner K Sarathchandra D Climate change skepticism as a psychological coping strategy Sociology Compass 2018 12 6 e12586 10.1111/soc4.12586
Hamilton LS Huth AG The revolution will not be controlled: Natural stimuli in speech neuroscience Language, Cognition and Neuroscience 2020 35 5 573 582 10.1080/23273798.2018.1499946 32656294
Harmon-Jones, E., Harmon-Jones, C., & Summerell, E. (2017). On the Importance of Both Dimensional and Discrete Models of Emotion. Behavioral Sciences, 7(4). 10.3390/bs7040066
Harris DM Telling the story of climate change: Geologic imagination, praxis, and policy Energy Research & Social Science 2017 31 179 183 10.1016/j.erss.2017.05.027
Harth NS Leach CW Kessler T Guilt, anger, and pride about in-group environmental behaviour: Different emotions predict distinct intentions Journal of Environmental Psychology 2013 34 18 26 10.1016/j.jenvp.2012.12.005
Hatfield E Rapson RL Le Y-CL Emotional contagion and empathy The Social Neuroscience of Empathy. 2009 255 19 30 10.7551/mitpress/9780262012973.003.0003
Helm SV Pollitt A Barnett MA Curran MA Craig ZR Differentiating environmental concern in the context of psychological adaption to climate change Global Environmental Change: Human and Policy Dimensions 2018 48 158 167 10.1016/j.gloenvcha.2017.11.012
Henrich J Heine SJ Norenzayan A The weirdest people in the world? The Behavioral and Brain Sciences 2010 33 2–3 61 83 10.1017/S0140525X0999152X 20550733
Hogg, T., Stanley, S., O’Brien, L., Wilson, M., & Watsford, C. (2021). The Hogg Eco-Anxiety Scale: Development and Validation of a Multidimensional Scale. 10.31219/osf.io/rxudb
Hsu C-T Jacobs AM Citron FMM Conrad M The emotion potential of words and passages in reading Harry Potter–an fMRI study Brain and Language 2015 142 96 114 10.1016/j.bandl.2015.01.011 25681681
Hurst KF Sintov ND Guilt consistently motivates pro-environmental outcomes while pride depends on context Journal of Environmental Psychology 2022 80 101776 10.1016/j.jenvp.2022.101776
IPCC. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. In Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (Eds.). Cambridge University Press. In press.
Jääskeläinen IP Sams M Glerean E Ahveninen J Movies and narratives as naturalistic stimuli in neuroimaging NeuroImage 2021 224 117445 10.1016/j.neuroimage.2020.117445 33059053
Jones MD Song G Making sense of climate change: How story frames shape cognition Political Psychology 2014 35 4 447 476 10.1111/pops.12057
Kleres, J., & Wettergren, Å. (2017). Fear, hope, anger, and guilt in climate activism. Social Movement Studies, 1–13. 10.1080/14742837.2017.1344546
Landmann H Hess U What elicits third-party anger? The effects of moral violation and others’ outcome on anger and compassion Cognition and Emotion 2017 31 6 1097 1111 10.1080/02699931.2016.1194258 27347663
Landmann, H. (2021). Emotions in the context of environmental protection: Theoretical considerations concerning emotion types, eliciting processes, and affect generalization. 10.31234/osf.io/yb2a7
Lang P Bradley MM The International Affective Picture System (IAPS) in the study of emotion and attention Handbook of Emotion Elicitation and Assessment 2007 29 70 73
Lazarus RS Progress on a cognitive-motivational-relational theory of emotion The American Psychologist 1991 46 8 819 834 10.1037//0003-066x.46.8.819 1928936
Lehman B Thompson J Davis S Carlson JM Affective Images of Climate Change Frontiers in Psychology 2019 10 960 10.3389/fpsyg.2019.00960 31156493
Leiserowitz A Climate change risk perception and policy preferences: The role of affect, imagery, and values Climatic Change 2006 77 1 45 72 10.1007/s10584-006-9059-9
Leiserowitz A Roser-Renouf C Marlon J Maibach E Global warming’s six americas: A review and recommendations for climate change communication Current Opinion in Behavioral Sciences 2021 42 97 103 10.1016/j.cobeha.2021.04.007
Lu H Schuldt JP Exploring the role of incidental emotions in support for climate change policy Climatic Change 2015 131 4 719 726 10.1007/s10584-015-1443-x
Lu H Schuldt JP Compassion for climate change victims and support for mitigation policy Journal of Environmental Psychology 2016 45 192 200 10.1016/j.jenvp.2016.01.007
Ma Y Hmielowski JD Are You Threatening Me? Identity Threat, Resistance to Persuasion, and Boomerang Effects in Environmental Communication Environmental Communication 2022 16 2 225 242 10.1080/17524032.2021.1994442
Magalhães de Sousa S Miranda DK de Miranda DM Malloy-Diniz LF Romano-Silva MA The Extreme Climate Event Database (EXCEED): Development of a picture database composed of drought and flood stimuli PloS One 2018 13 9 e0204093 10.1371/journal.pone.0204093 30235273
Mallett RK Melchiori KJ Strickroth T self-confrontation via a carbon footprint calculator increases guilt and support for a proenvironmental group Ecopsychology 2013 5 1 9 16 10.1089/eco.2012.0067
Mar RA The neural bases of social cognition and story comprehension Annual Review of Psychology 2011 62 103 134 10.1146/annurev-psych-120709-145406 21126178
Marchewka A Żurawski Ł Jednoróg K Grabowska A The Nencki Affective Picture System (NAPS): Introduction to a novel, standardized, wide-range, high-quality, realistic picture database Behavior Research Methods 2014 46 2 596 610 10.3758/s13428-013-0379-1 23996831
Marczak M Winkowska M Chaton-Østlie K Morote Rios R Klöckner CA “When I say I’m depressed, it's like anger. An exploration of the emotional landscape of climate change concern in Norway and its psychological, social and political implications Emotion, Space and Society 2023 46 100939 10.1016/j.emospa.2023.100939
Marks, E., Hickman, C., Pihkala, P., Clayton, S., Lewandowski, E. R., Mayall, E. E., Wray, B., Mellor, C., & van Susteren, L. (2021). Young People’s Voices on Climate Anxiety, Government Betrayal and Moral Injury: A Global Phenomenon. 10.2139/ssrn.3918955
McDonald RI Chai HY Newell BR Personal experience and the “psychological distance” of climate change: An integrative review Journal of Environmental Psychology 2015 44 109 118 10.1016/j.jenvp.2015.10.003
Michałowski JM Droździel D Matuszewski J Koziejowski W Jednoróg K Marchewka A The Set of Fear Inducing Pictures (SFIP): Development and validation in fearful and nonfearful individuals Behavior Research Methods 2017 49 4 1407 1419 10.3758/s13428-016-0797-y 27613018
Moezzi M Janda KB Rotmann S Using stories, narratives, and storytelling in energy and climate change research Energy Research & Social Science 2017 31 1 10 10.1016/j.erss.2017.06.034
Morris BS Chrysochou P Christensen JD Orquin JL Barraza J Zak PJ Mitkidis P Stories vs facts: triggering emotion and action-taking on climate change Climatic Change 2019 154 1 19 36 10.1007/s10584-019-02425-6
Nabi RL Gustafson A Jensen R Framing Climate Change: Exploring the Role of Emotion in Generating Advocacy Behavior Science Communication 2018 40 4 442 468 10.1177/1075547018776019
O’Neill SJ Boykoff M Niemeyer S Day SA On the use of imagery for climate change engagement Global Environmental Change: Human and Policy Dimensions 2013 23 2 413 421 10.1016/j.gloenvcha.2012.11.006
Ockwell D Whitmarsh L O’Neill S Reorienting climate change communication for effective mitigation: Forcing people to be green or fostering grass-roots engagement? Science Communication 2009 30 3 305 327 10.1177/1075547008328969
Ojala M How do children cope with global climate change? Coping strategies, engagement, and well-being Journal of Environmental Psychology 2012 32 3 225 233 10.1016/j.jenvp.2012.02.004
Ojala M Hope in the face of climate change: Associations with environmental engagement and student perceptions of teachers’ emotion communication style and future orientation The Journal of Environmental Education 2015 46 3 133 148 10.1080/00958964.2015.1021662
Parkinson B Fischer AH Manstead ASR Emotion in social relations: Cultural, group, and interpersonal processes 2005 Psychology Press
Pihkala Anxiety and the ecological crisis: An analysis of eco-anxiety and climate anxiety Sustainability: Science Practice and Policy 2020 12 19 7836 10.3390/su12197836
Pihkala, P. (2022). Toward a Taxonomy of Climate Emotions. Frontiers in Climate, 3. 10.3389/fclim.2021.738154
Redcay E Moraczewski D Social cognition in context: A naturalistic imaging approach NeuroImage 2020 216 116392 10.1016/j.neuroimage.2019.116392 31770637
Rees JH Klug S Bamberg S Guilty conscience: motivating pro-environmental behavior by inducing negative moral emotions Climatic Change 2015 130 3 439 452 10.1007/s10584-014-1278-x
Reser, J. P., & Bradley, G. L. (2017). Fear appeals in climate change communication. In Oxford research encyclopedia of climate science. 10.1093/acrefore/9780190228620.013.386
Riegel M Wierzba M Wypych M Żurawski Ł Jednoróg K Grabowska A Marchewka A Nencki affective word list (NAWL): The cultural adaptation of the Berlin Affective Word List-Reloaded (BAWL-R) for Polish Behavior Research Methods 2015 47 4 1222 1236 10.3758/s13428-014-0552-1 25588892
Rode JB Dent AL Benedict CN Brosnahan DB Martinez RL Ditto PH Influencing climate change attitudes in the United States: A systematic review and meta-analysis Journal of Environmental Psychology 2021 76 101623 10.1016/j.jenvp.2021.101623
Saarimäki H Naturalistic stimuli in affective neuroimaging: A review Frontiers in Human Neuroscience 2021 15 675068 10.3389/fnhum.2021.675068 34220474
Schneider CR Zaval L Markowitz EM Positive emotions and climate change Current Opinion in Behavioral Sciences 2021 42 114 120 10.1016/j.cobeha.2021.04.009
Schneider-Mayerson M Leong KL Eco-reproductive concerns in the age of climate change Climatic Change 2020 163 2 1007 1023 10.1007/s10584-020-02923-y
Schneider-Mayerson M Weik von Mossner A Małecki WP Empirical Ecocriticism: Environmental Texts and Empirical Methods ISLE: Interdisciplinary Studies in Literature and Environment 2020 27 2 327 336 10.1093/isle/isaa022
Shipley NJ van Riper CJ Pride and guilt predict pro-environmental behavior: A meta-analysis of correlational and experimental evidence Journal of Environmental Psychology 2022 79 101753 10.1016/j.jenvp.2021.101753
Smith CA Ellsworth PC Attitudes and social cognition Journal of Personality and Social Psychology 1985 48 4 813 838 10.1037/0022-3514.48.4.813 3886875
Stanley SK Hogg TL Leviston Z Walker I From anger to action: Differential impacts of eco-anxiety, eco-depression, and eco-anger on climate action and wellbeing The Journal of Climate Change and Health 2021 1 100003 10.1016/j.joclim.2021.100003
Stevenson RA Mikels JA James TW Characterization of the affective norms for English words by discrete emotional categories Behavior Research Methods 2007 39 4 1020 1024 10.3758/bf03192999 18183921
Swim JK Bloodhart B Portraying the Perils to Polar Bears: The role of empathic and objective perspective-taking toward animals in climate change communication Environmental Communication 2015 9 4 446 468 10.1080/17524032.2014.987304
Tracy JL Robins RW Self-conscious emotions: Where self and emotion meet Self 2007 364 187 209
van der Linden S The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model Journal of Environmental Psychology 2015 41 112 124 10.1016/j.jenvp.2014.11.012
van der Linden S Maibach E Leiserowitz A Improving Public Engagement With Climate Change: Five “Best Practice” Insights From Psychological Science Perspectives on Psychological Science: A Journal of the Association for Psychological Science 2015 10 6 758 763 10.1177/1745691615598516 26581732
van Valkengoed AM Steg L Meta-analyses of factors motivating climate change adaptation behaviour Nature Climate Change 2019 9 2 158 163 10.1038/s41558-018-0371-y
Wang S Leviston Z Hurlstone M Lawrence C Walker I Emotions predict policy support: Why it matters how people feel about climate change Global Environmental Change: Human and Policy Dimensions 2018 50 25 40 10.1016/j.gloenvcha.2018.03.002
Weber EU Experience-Based and Description-Based Perceptions of Long-Term Risk: Why Global Warming does not Scare us (Yet) Climatic Change 2006 77 1 103 120 10.1007/s10584-006-9060-3
Whitmarsh L Player L Jiongco A James M Williams M Marks E Kennedy-Williams P Climate anxiety: What predicts it and how is it related to climate action? Journal of Environmental Psychology 2022 83 101866 10.1016/j.jenvp.2022.101866
Wierzba, M., Riegel, M., Wypych, M., Jednoróg, K., Turnau, P., Grabowska, A., & Marchewka, A. (2015). Basic emotions in the Nencki Affective Word List (NAWL BE): New method of classifying emotional stimuli. PloS One, 10(7), e0132305. 10.1371/journal.pone.0132305
Wierzba M Riegel M Kocoń J Miłkowski P Janz A Klessa K Juszczyk K Konat B Grimling D Piasecki M Marchewka A Emotion norms for 6000 Polish word meanings with a direct mapping to the Polish wordnet Behavior Research Methods 2022 54 5 2146 2161 10.3758/s13428-021-01697-0 34893969
Wohl MJA Branscombe NR Klar Y Collective guilt: Emotional reactions when one’s group has done wrong or been wronged European Review of Social Psychology 2006 17 1 1 37 10.1080/10463280600574815
Xie B Brewer MB Hayes BK McDonald RI Newell BR Predicting climate change risk perception and willingness to act Journal of Environmental Psychology 2019 65 101331 10.1016/j.jenvp.2019.101331
Zaremba, D., Kulesza, M., Herman, A. M., Marczak, M., Kossowski, B., Budziszewska, M., Michałowski, J. M., Klöckner, C. A., Marchewka, A., & Wierzba, M. (2023). A wise person plants a tree a day before the end of the world: coping with the emotional experience of climate change in Poland. Current Psychology, 42, 27167–27185. 10.1007/s12144-022-03807-3
