Exploring Impacts of Environmentally Focused Imagery on Pro-Environment Behaviours and Climate Anxiety

Abstract

Climate change poses a significant threat to sustainability and may result in psychological distress, such as climate anxiety, which may play a critical role in influencing pro-environment behaviours. This study aimed to investigate how indirect exposure to environmentally focused imagery may impact pro-environment behaviours and climate anxiety. A total of 283 participants completed our task, with findings indicating that participants who viewed negative environmental imagery had a significant reduction in preference for eco-friendly transportation options compared to participants in other conditions; we saw no significant difference in preference for these participants. When examining the effects of environmental imagery on climate anxiety, we found no significant differences in the level of climate anxiety based on priming condition, indicating that climate anxiety may be more robust to situational events than associated behaviours. This study identifies the potential maladaptive effects of negative climate imagery on pro-environment behaviours and highlights the trait-like nature of climate anxiety. These findings identify the potential for disengagement with behaviour due to negative messaging and imagery associated with climate change and extreme weather events. Future research should explore the long-term stability of climate anxiety and how different forms of exposure to climate change may influence climate anxiety and pro-environment behaviours.

1. Introduction

Climate change has had a somewhat recent media and political focus, with a substantial amount of research being conducted in the last 15 years. This has highlighted climate change as a key issue and part of everyday life for many people, often affecting people’s attitudes towards peers based on their opinions of the future effects of climate change [1,2]. These judgements have seen the media heavily involved in public perceptions of climate change, with a constant focus on governmental climate policies and extreme climate disasters [3,4]. This often negative focus on policy and disaster rather than personal behaviour change can leave people feeling hopeless when thinking of climate change and actions they may take [5,6]. This makes it difficult to understand the reasons and motivations behind many choices people may make, especially regarding pro-environment behaviours [7]. Pro-environment behaviours refer to behaviours that may reduce harm to the environment or, in some cases, benefit the environment, for example, avoiding single-use plastics or minimising food waste [8].

Negative feelings such as fear and hopelessness about the health of our environment have led to a need for a deeper understanding of the psychological impacts of climate change [9,10]. These feelings may be due to being directly impacted by climate change through environmental disaster. However, in many cases, indirect exposure, such as through peers or media coverage, may also have adverse psychological impacts [10,11,12,13,14]. Recently, researchers have termed the emotional experience of climate change and ecological disaster, both from direct and indirect exposure, as “eco-emotions”. Eco-emotions are often described as encompassing a combination of thoughts, feelings and behaviours, better referred to as a mental state than an emotion; this confusing classification can often make comparison difficult [15,16]. They are often described as including feelings such as hopelessness, anger, frustration, and sadness [17].

Feelings of hopelessness and despair regarding climate change have been associated with the term eco-anxiety and are related to a “chronic fear of environmental doom” due to the long-term impacts of climate change [9,10,16]. Eco-anxiety has been identified as one of three key eco-emotions, along with eco-anger, which relates to feelings of anger regarding climate change, and eco-sadness, which relates to feelings of sadness due to the impacts of climate change [18,19]. The term eco-anxiety is often used interchangeably with “climate-anxiety” as both climate change and broader ecological disaster share many common factors [20]. These feelings have been identified as, in some cases, debilitating in nature and negatively related to wellbeing [21]. Earlier research examining climate anxiety identified no link between climate anxiety and a relevant behavioural response, e.g., an increase in pro-environmental behaviours [18,22]. However, recent research has identified that perhaps this is potentially a more complex relationship, with a range of findings, some indicating a positive relationship [10,23,24]. Whereas others have indicated that there may be an optimal level of anxiety, with people with moderate levels of climate anxiety having higher levels of pro-environment behaviours than people with low or high levels of pro-environment behaviours [12,25,26]. These findings may provide support for claims of the debilitating nature of climate anxiety in terms of behavioural outcomes.

Although a personal understanding of links between increasing rates of extreme weather events and climate change may be important in stimulating immediate action from people, disengagement with behaviours due to indirect negative exposure to climate disasters may cause further frustrations or feelings of hopelessness, leading to higher rates of scepticism [22,27,28,29,30]. This dichotomy of ideas coupled with an ever-increasing intensity of coverage of extreme weather events leads to a need for better understanding of how people may respond to indirect exposure to climate disasters [31]. Due to the nature of this coverage, it is often considered just part of everyday life, resulting in an unconscious influence on everyday behaviours. These behaviours may be positive, such as avoidance of single-use plastics due to images of pollution in oceans, or negative, disengagement with behaviours due to overwhelming distressing imagery, resulting in feeling hopeless after repeated coverage of bushfires or other extreme weather events. An example of disengagement in this sense may exist as what has been described as moral disengagement. Moral disengagement may include shifting responsibility for action to others using biassed reasoning, often ignoring or minimising personal contribution to climate change to avoid making lifestyle changes that may reduce greenhouse emissions, without feeling personally accountable [32].

To gain a better understanding of the influences that indirect exposure to climate change and extreme weather events may have on climate anxiety and pro-environment behaviours, implicit priming tasks can be useful. Implicit priming involves subtly triggering unconscious associations in participants to influence their behaviours [33,34,35]. Typically, implicit priming tasks involve participants being presented a series of images or words that are either related or unrelated to a particular topic, in this case the environment, before engaging in a related behavioural task. Previously, similar tasks have been used to examine differences in food appraisals between women with and without anorexia nervosa using food cues [36,37,38]. Another example of how implicit priming may be used to influence behaviours without awareness of the participants may be Bargh et al.’s [35] study examining stereotype activation, where participants were primed with words related to elderly stereotypes, such as “old”, “retired”, and “slow”. After completing the task participants’ walking speed leaving the experiment was measured, and it was found that participants primed with elderly-related words walked slower than participants in the control group, demonstrating an unconscious influence of behaviours.

In the context of the present study, this method may be utilised to show participants differently valanced (such as negative) environmentally focused images to influence their preference of pro-environment behaviours and level of climate anxiety. One key advantage of using an implicit priming approach is that it will allow us to influence the behaviour of participants at a subconscious level. As the participants will be unaware of the purpose of the study, it is unlikely that they will be able to consciously adjust their behaviours. Behavioural adjustments may be for the purpose of socially desirable responding or due to other prompts associated with the study, which may be particularly valuable when examining impacts on participants’ pro-environment behaviours.

Understanding how individuals make pro-environmental choices can be complex. Pro-environmental choices refer to choices that aim to protect or preserve the natural environment, such as choosing energy-efficient appliances or cycling instead of driving [39]. Previous studies have often relied on Likert-based surveys to assess people’s intentions, but these do not always accurately capture their actual behaviour [40]. In this study, we employed a Discrete Choice Experiment (DCE) design to delve deeper into these choices and simulate real-world decision-making scenarios. DCE tasks require participants to make multiple choices between two options which have differing levels of each attribute. For example, one choice may have a higher cost and be less eco-friendly but be faster; this option may appeal to someone who is time conscious, whereas someone who is more eco- or financially conscious may choose the alternate option (Figure 1). DCEs enable an analysis of the various factors influencing participants’ decision-making processes, offering insights into which elements may be crucial in pro-environmental decisions or behaviours [41].

DCEs are an efficient and cost-effective approach to understanding the choices people make. They have been successfully applied in various domains to measure consumer preferences in transport, health, and food choices [42,43,44,45,46,47]. For instance, DCEs have been used to explore the costs, whether monetary or time-related, that individuals are willing to incur for desired benefits, such as an effective treatment or a highly rated product [45,48]. These studies have shown that DCEs often produce externally valid results, with a systematic review finding that they yield reasonable predictions of health-related behaviours [44]. Consequently, DCEs can be a valuable tool not only for examining the frequency of choices but also for investigating the trade-offs people make between different factors when making decisions.

The aims of the proposed study are to further examine the impacts of imagery related to climate change on climate anxiety and pro-environment behavioural response. It is hypothesised that participants within the negative priming group will have significantly lower pro-environment behaviours than participants in all other groups, with participants in the random and neutral groups having moderate levels of pro-environment behaviours and participants in the positive priming group having significantly higher pro-environment behaviours. It is also hypothesised that there will be significant differences in climate anxiety based on priming condition; we expect that participants who are negatively primed will have significantly higher climate anxiety than random and neutral primed participants, with positively primed participants having the lowest climate anxiety. Finally, it is hypothesised that there will be an inverted-U relationship between climate anxiety and pro-environment behaviours, with participants with moderate levels of climate anxiety exhibiting the highest preference for eco-friendly choices.

2. Materials and Methods

2.1. Participants

A total of 298 participants completed the study. Participants were recruited through the University’s undergraduate student research participant pool and via Prolific Academic. Student volunteers participated and were compensated with course credit, while the participants recruited through Prolific Academic received a general pay rate of $6.63 AUD for completion. Student participants could also achieve course credit through summarising previous research articles as an alternate option to participating in research projects, ensuring participation is voluntary. All participants were also informed that they could choose to opt out at any point, with incomplete data removed from analysis, as this was treated as consent being revoked. Informed consent was obtained from all participants. The study was approved by the University ethics committee (approval number: H-2023-0104). The sample size requirement of 220 was calculated using methods described in “Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide” [49]. Data collection took place from March to August 2024.

2.2. Measures

QuestionPro online survey software (Interface Version V1) and the JATOS (Version 3.5.8) online study tool were used [50,51]. Prior to starting the survey, participants were required to read the study information statement and provide informed consent.

2.2.1. Discrete Choice Experiment (DCE)

Our DCE was developed to determine the importance of different factors (attributes) when considering transport options. Levels for the task were chosen based on factors that may be relevant for a typical trip through Sydney, Australia, during moderate traffic with various transport methods, e.g., train/car/bike. This decision includes both positive and negative factors for each attribute; for example, a participant may have to choose a more expensive option if they are more time conscious.

DCE Task Design

We constructed a 3 (attributes; time, cost, eco-friendliness) × 3 (levels; 23/34/45 min, Free/$5/$10, 1 Star/2 Star/3 Star) DCE (Figure 1). Options were presented as “Choice 1” and “Choice 2” to avoid implicit bias which may be associated with differing modes of transport; this is referred to as an unlabelled DCE design. Each DCE task required participants to complete 20 choice tasks, randomly drawn from a larger matrix of possible discrete choice scenarios. This number was chosen to avoid decision fatigue in the task and was used when calculating sample size requirements. Two dominant trials were additionally included at the same point for each participant as attention checks; these trials were not included in the analysis of participants’ utility scores.

2.2.2. Climate Change Anxiety Scale (CCAS)

The single-factor CCAS is derived from Clayton & Karazsia’s four factor 22 item measure [18]. The single factor CCAS aggregates factors one and four of the original four-factor measure as a single score. This single factor measure includes 13 items, with eight items examining cognitive-emotional impairment and five examining functional impairment associated with climate change [52]. Frequency ratings were made by participants on a series of 5-point Likert scales (0 = Never, 1 = Rarely, 2 = Sometimes, 3 = Often, 4 = Almost Always) [18]. The unidimensional CCAS has high internal reliability and good structural, convergent and discriminant validity [52]. For this task the CCAS was only delivered post-priming to ensure implicit effects of the priming task, as until this measure there was no indication to participants that environmental attitudes and behaviour were the target of the study.

2.2.3. Implicit Priming Task

Our implicit priming task was developed to simulate indirect awareness of ecological disasters, which may be experienced through actions such as watching the news. The task included 4 separate conditions, where one condition would be randomly allocated to a participant. Within each condition the unrelated images would not change; however, for each condition participants would view different related images. These conditions were as follows:

• Positive, where participants would view only positively valanced images;
• Negative, where participants would view only negatively valanced images;
• Neutral, where participants would view only neutral images;
• Random, where participants would view related images which had a random assortment of positive, negative and neutral images.

Within each condition, the task had participants view four blocks of 40 images, with 16 of these images being environmentally focused (related). These environmentally focused images were retrieved from copyright-free image databases and piloted for valence and arousal ratings. The other 24 of these images of each block were neutrally valanced OASIS images (unrelated). Images were presented in one of two orders, with the second order being a reverse-ordered image set so as to ensure there were no order effects. The initial order was randomly generated.

In order to ensure participants maintained their level of attention throughout the task, they were instructed to record whether the following image is on the left or right of the screen and respond with either “f” or “j”, respectively. Each trial consisted of an image shown for 2500 ms; participants were prompted with a reminder of the instructions if they did not respond within this time, followed by a 500 ms fixation cross (Figure 2).

2.2.4. Experimental Procedure

Following providing informed consent, participants completed our task, which took approximately 25 min. Firstly, participants were asked to answer demographic questions, age, gender and highest level of education. Participants then completed a DCE task prior to priming; participants then completed the implicit priming task, followed by a post-priming DCE, then the CCAS and then finally, one question asking participants if they had been directly impacted by climate change and a second which asked if they had been indirectly impacted by climate change (yes/no).

2.2.5. Data Preparation and Statistical Analysis

All self-report scales were scored and prepared for analysis using R. 15 participants were removed due to having below 75% accuracy in our priming task; this was decided pre-testing, as the task was designed to be easy. This was supposed, as the mean accuracy of the task was 93.24% with an IQR of 3.75. This indicates that participants below 75% accuracy, which is significantly below the mean, were not adequately engaging with the task. Attribute utility scores were calculated using a random-parameters logit (RPL) model; this involved participants’ choices being regressed against characteristics of the alternative transport options presented. The regression used a cumulative logit link function. This is psychologically equivalent to assuming that preferences are internal random variables and that people make decisions by comparing these preferences against fixed thresholds. The regression analysis estimates how much the average preference changes with changes in the attribute levels, allowing the generation of utility scores for each attribute. These “utility” coefficients were estimated separately for each person and for each attribute, and they indicate the impact of changes in these attribute levels on transport choices. Cost utility is reverse scored, rather representing value, with higher cost utility indicating cheaper options. For example, a participant may have utility scores of 0.5 for cost, 0.2 for time and 2 for eco-rating; this would indicate that a participant was primarily focused on ensuring their choices had a high eco-rating, with minimal consideration of the cost or time taken. However, if a participant had a utility score of zero, this would indicate that a participant had no preference for this attribute, whereas if this utility score was negative, this would show a preference for “unfavourable” options within an attribute. For example, if a participant had utility scores of −1 for cost, the participant showed a higher preference for more expensive options rather than cheaper options; this type of preference may be seen in luxury consumer goods. Estimation of utility parameters from choice data was carried out using the R language and its ’ordinal’ package [53,54]. Participants’ RT and accuracy of response during the implicit priming task were also recorded. Analysis was conducted on R 4.3.0 [53].

When examining differences in eco-utility scores between priming conditions, we utilised a one-way ANOVA. Initially we examined differences in eco-utility scores between pre-priming groups to ensure there were no group differences prior to priming to ensure any differences examined are due to our implicit priming task. We then utilised a one-way ANOVA with planned post hoc analysis to examine the effects of priming. This analysis allows us to explore the effects of priming. Similarly, we examined the effects of priming on climate anxiety utilising a one-way ANOVA. However, as discussed in methods, for this analysis we did not record pre-priming climate anxiety. Therefore, we were unable to ensure that there were no group differences pre-priming. We then examined the relationship between climate anxiety and pro-environment behaviours. To do this, we used correlation analysis to examine any simple effects and quadratic regression to examine a potentially non-linear relationship which has previously been examined. We then used a 2 × 2 ANOVA to examine the effect of exposure to climate change. Finally, we used two repeated measures ANOVAs to examine differences in attribute utility scores pre- and post-priming.

3. Results

3.1. Descriptive Data

The final sample included 283 participants aged between 18 and 63 years old (M = 24.85, SD = 7.67). This included 186 female participants, 89 male participants, 7 non-binary participants and 1 participant who responded other/prefer not to say. Due to the low number of participants in the non-binary and other/prefer not to say categories, these were excluded from any further gender analysis; however, they were still included in all main analyses. A total of 146 participants were recruited from the University of Newcastle, and 137 were recruited through Prolific Academic.

3.2. Analysis

A correlation matrix including all variables may be viewed in Appendix A. Through this analysis we can see a weak significant negative relationship between age and time utility scores both pre- and post-priming, indicating that time was a more important attribute for younger people. We also found a weak, significant positive relationship between pre-priming eco-utility and age. However, this relationship is not significant post-priming.

3.2.1. The Effects of Environmentally Focused Imagery on Pro-Environmental Behaviours

We first examined the differences in eco-utility scores pre-priming intervention; this was performed to ensure that any differences examined post-priming were due to priming. Utilising a one-way ANOVA, we found no significant differences in eco-utility scores prior to the priming task, F(3,278) = 0.634, p = 0.594. We then examined participants’ post-priming eco-utility scores with another one-way ANOVA and planned post hoc tests to further explore any differences. Through this analysis we found a significant main effect of priming on eco-utility scores, indicating that priming had impacted participants’ decisions on the post-decision-making task, F(3,278) = 5.004, p = 0.002. Post hoc analysis revealed that participants in the negative priming group had significantly lower eco-utility scores (preference towards eco-friendly options) than the three other priming groups, whereas we found no significant differences between the positive, neutral or random priming groups (

Table 1. Post hoc comparisons—priming.

		Mean Difference	SE	t	ptukey
Negative	Neutral	−0.525	0.189	−2.782	0.029 *
	Positive	−0.643	0.197	−3.271	0.007 *
	Random	−0.661	0.202	−3.275	0.006 *
Neutral	Positive	−0.118	0.191	−0.616	0.927
	Random	−0.136	0.197	−0.692	0.900
Positive	Random	−0.018	0.205	−0.090	1.000

Note. p-value adjusted for comparing a family of 4. * indicates p-value less than 0.05.

and Figure 3).

3.2.2. The Effects of Environmentally Focused Imagery on Climate Change Anxiety

We then examined whether the priming condition had an effect on climate change anxiety. Utilising a one-way ANOVA, we examined differences in our four implicit priming groups’ level of climate anxiety. We found no significant effect of priming on participants’ post-priming climate change anxiety scores, F(3,278) = 0.59, p = 0.62 (Figure 4). These findings may indicate that climate anxiety is somewhat robust; however, as we did not collect pre-priming climate change anxiety levels, we are unable to fully explore these effects.

3.2.3. Relationship Between Climate Change Anxiety and Pro-Environment Behaviours

We then examined the relationship between participants’ post-priming eco-utility scores and climate change anxiety levels. Using correlation analysis, we found a significant positive relationship between participants self-reported climate anxiety score and their post-priming eco-utility (r = 0.262, p < 0.001) (Figure 5). Indicating that participants with higher climate anxiety also had higher preferences towards eco-friendly choices. We then further examined this relationship utilising a quadratic linear regression; however, we did not find a significant relationship here, indicating that there was no evidence that moderate levels had the highest preference towards eco-friendly choices.

3.2.4. Differences in Climate Anxiety Based on Direct and Indirect Impacts of Climate Anxiety

We then examined whether levels of climate anxiety differed if a participant self-reported that they were directly or indirectly impacted by climate change. We utilised a 2 (Direct Impact—Yes/No) × 2 (Indirect Impact—Yes/No) ANOVA for this analysis and found a significant main effect of directly impacted by climate change (F(1,279) = 14.01, p < 0.001) and a significant main effect of indirectly impacted by climate change (F(1,279) = 18.23, p < 0.001), this showed that participants reporting yes direct/yes indirect had the highest level of climate anxiety (M = 12.07, SD = 8.21), followed by no direct/yes indirect (M = 8.49, SD = 7.21), than yes direct/no indirect (M = 7.85, SD = 7.62), and participants self-reporting no direct/no indirect impacts of climate change had the lowest level of climate anxiety (M = 4.98, SD = 6.60) (Figure 6).

3.2.5. Importance of Different Factors When Considering Travel Options

We then utilised two repeated measures ANOVAs to examine what factors were most important for participants when making these travel decisions. We found a significant main effect in both pre- (F(2,564) = 84.06, p < 0.001) and post-priming (F(2,564) = 99.82, p < 0.001) utility scores, indicating that not all factors were equally as desirable. Through further post hoc analysis we found that cost was the most desirable factor with significantly higher cost utility scores than time in both pre- (p < 0.001) and post-priming (p < 0.001) decisions. Cost was also significantly more desirable than eco-friendliness in both pre- (p < 0.001) and post-priming (p < 0.001) decisions (Figure 7). When examining differences in utility pre- and post-using paired samples t-tests, we can see that participants made more deterministic decisions post-priming, as illustrated in Figure 7, as we see significantly higher cost (t(282) = 6.91, p < 0.01), time (t(282) = 6.40, p < 0.01) and eco- (t(282) = 3.69, p < 0.01) utilities post-priming. This finding indicates an expected level of learning within the task; this may be participants learning which attributes are most important to them and what different levels are available. This is important to note when considering any pre–post comparisons between these utility scores.

4. Discussion

This study investigated how environmentally focused imagery, such as media coverage of extreme weather events, impacts pro-environment behaviours and climate anxiety. Using an implicit priming task, the research simulated unintentional engagement with environmental news and incorporated self-report measures of climate change anxiety alongside a Discrete Choice Experiment (DCE) to model daily transport decisions. These methods allowed for an analysis of behavioural differences after exposure to various environmental images.

The findings reveal that such imagery can influence pro-environment behaviours and acceptance of climate change, with insights highlighting key factors in decision-making with environmental implications. This understanding may allow for more appealing advertisements for eco-friendly options; for example, it may be more important to highlight eco-friendly options as cheaper rather than or as well as eco-friendly.

4.1. The Effects of Environmentally Focused Imagery on Pro-Environmental Behaviours

In the present study we found that participants who were negatively primed had significantly lower preference for pro-environmental choices than participants in the three other priming groups (positive, neutral and random), with there being no significant difference within the other priming groups. These findings partially support our hypothesis, as although we found negative groups to have significantly lower preference for pro-environment behaviours, we did not find positive priming to have any significant effect when compared to neutral or random. These findings may be due to a range of factors, such as the arousal level of our positively valanced images being far lower than the arousal level of our negative imagery. Previous research has found negative images to be more effective at exhibiting a response than positive images, as they may trigger feelings, such as anger [55,56]. Although effective at exhibiting a response, the response to negative environmental imagery was maladaptive, thus resulting in a reduction in pro-environment behaviours. Findings examining a reduction in behaviour due to negative priming are in line with previous research. This research has examined how negative framing in the media can trigger psychological defences, including moral disengagement, threat fatigue or psychological reactance, thus reducing pro-environmental response [57,58,59]. These theories identify that individuals may resist or be unresponsive to messaging if it is threatening to them, their lifestyle or their autonomy. These findings provide further evidence that although presentations of natural disasters or other extreme weather events may be effective at garnering an emotional response and high levels of engagement with this content, this may be counterproductive, resulting in reduced levels of pro-environment behaviours due to feelings of helplessness [60].

4.2. The Effects of Environmentally Focused Imagery on Climate Anxiety

Previous research has examined links between climate anxiety and pro-environment behaviours. Therefore, we hypothesised that priming may be used to manipulate levels of climate anxiety. Contrary to our hypothesis, we found no significant differences in climate anxiety based on priming. Although unexpected, this may indicate that climate anxiety is somewhat robust to situational events, with some consistency over time, similar to trait anxiety [61]. Therefore, levels of climate anxiety may not be as easily manipulated by our implicit priming task, as these feelings may be due to long-term concerns about climate change and feelings of hopelessness or despair. Previous research has discussed that climate anxiety is associated with long-term cognitive patterns, such as rumination and worry, which are common in trait anxiety [17,62,63]. These findings support previous findings examining a significant association between climate anxiety and trait anxiety [20]. However, this evidence is contrary to claims that even high levels of eco- or climate-anxiety are an adaptive and constructive response to current environmental challenges, as this absence of change through priming may suggest limited response to motivational framing [64,65].

4.3. The Relationship Between Climate Anxiety and Pro-Environment Behaviours

Previous literature which has examined the relationship between climate anxiety and pro-environment behaviours has found conflicting evidence. Early studies demonstrated no relationship between pro-environment behaviours and climate anxiety [18]. Whereas, more recently there is some indication of a positive relationship where high levels of climate anxiety were found to be related to increased behavioural response [66,67]. However, we have examined, using an experimental design to measure behaviour, that moderate levels may be optimal for increased levels of pro-environment behaviours [25]. In the present study, contrary to our hypothesis, we found a positive relationship between climate anxiety and pro-environment behaviours. Though this finding is supported by previous literature, this was contrary to our expected inverted-U relationship. This may indicate that these unexpected findings may be due to factors introduced during the task, as within the task we had aimed to manipulate both behaviour and climate anxiety, which in turn, may have impacted the relationship between these factors due to the above-noted stability of climate anxiety between priming groups.

4.4. Future Directions, Strengths, Limitations and Practical Implications

Future research should explore the stability of climate anxiety, aiming to understand its relationship to current events or whether it is more robust feelings of worry, similar to trait anxiety. Future research may also further explore imagery related to climate change on pro-environment behaviours; this may be using an explicit memory priming task, such as using media from news television coverage, to understand how more direct engagement with familiar stimuli may impact behaviours. Future research may also continue to use DCE; however, it should focus on other avenues of behaviour, such as other consumer choices or financial decisions people may make, to examine whether there is a similar relationship between climate anxiety and these behaviours.

The use of an implicit memory task for priming has allowed us to better understand how indirect engagement in extreme weather events or negative media on climate change may be impacting pro-environment behaviours. Furthering understanding within this topic is important for discussing ways to encourage eco-friendly choices and reduce potentially negative psychological and physical responses to climate change. This study aimed to highlight the negative impacts of overtly negative demonstrations surrounding climate change may have for an overall shift to more pro-environmental choices.

This study was limited by issues with repetitive measures, although we do not believe this impacted results in our current study design. We were limited as we were unable to make comparisons on pre- and post-priming levels of climate anxiety. Our current study design, not including a pre-priming measure of climate anxiety, was due to the belief that mention of climate change prior to behavioural or priming tasks may have influenced participants’ decisions or impacted the intended implicit nature of our priming task. Although we felt that a pre-priming measure of climate anxiety would potentially impact participants’ results, we believe, due to the unlabelled nature of our DCE, this would not have a similar effect, and thus we would only see participant learning effects when making comparisons between pre- and post-priming utility scores. We initially chose to include this pre-testing measure of behaviour to ensure an equal level of utility between groups. Pre-testing, these findings of no significant differences in behaviour pre-testing may indicate that there may also have been no significant differences in climate anxiety pre-testing. However, to ensure this, future tasks which aim to examine changes in level of climate anxiety may wish to have participants complete a multiple-time-stage task and examine shifts in beliefs over time.

This study has practical implications for the understanding and communication of climate change. As identified, climate anxiety may be stable and trait-like, which highlights the importance of long-term supportive messaging rather than episodic messaging focused on natural disasters. Public communication campaigns may benefit from adopting messaging that emphasises actionable, positive, and hopeful narratives to mitigate anxiety-related disengagement [68,69]. On that note, environmental campaigns may need to reconsider the frequent use of negative or fear-based imagery focused on climate change, as this may be reducing the efficacy of these campaigns. Feldman & Hart [70] identified that messages that emphasise response efficacy of political actions increased hope and participation in climate-related political action.

4.5. Conclusions

Indirect exposure to the topic of climate change, whether through media or peer interactions, may be having measurable impacts on climate anxiety and engagement in pro-environment behaviours. Through this study we aimed to examine how priming participants through an implicit memory task may have impacted their levels of pro-environment behaviours and climate anxiety. This study found that negative priming significantly reduced levels of pro-environment behaviours on our transport decision-making task. This study found no significant differences in the level of climate anxiety based on priming condition; this may indicate that climate anxiety may be robust to short-term situational events; however, this area should be further explored. These findings are relevant as they provide insight into the impacts of negative coverage of climate disasters and how this may result in increased feelings of hopelessness.