"Don't Look Up! Thinking Fast About Climate Change and its Consequences"

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"Don't Look Up! Thinking Fast About Climate Change and its Consequences"

Presented by: Maartje van der Molen

Faculty of Economics and Business, University of Amsterdam MSc in Business Administration: Leadership and Management

Supervised by: Dr. Richard Ronay

EBEC Approval number: EC 20220321050348 24/06/2022

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Statement of originality

This document is written by Student Maartje van der Molen, who declares to take full responsibility for the contents of this document.

"I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it."

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

People tend to have rosy future expectations, regardless of the daunting environmental prospects humanity is going to face. Perhaps we unconsciously overlook information about these challenges and fool ourselves with the available evidence to feel better. This research focuses on information processing mechanisms and aims to determine if thinking fast causes biased information processing, which may lead to self-enhancement and eventually, rosy future expectations. An experiment was performed to find out if positive- or negative text about food scarcity influences how information is processed. Results show that participants who read the positive text report more optimistic perspectives on food scarcity than those who read the negative text. In addition, greater attitude change was observed when participants were assigned to the positive condition compared to the negative condition, suggesting people so indeed welcome and integrate favourable information more readily than negative information.

Nevertheless, no evidence was found for other effects in the research model. Future research must focus on other factors such as political influence and social groups and norms to find out why people hold on to such positive outlooks, while facing a major ecological crisis.

Keywords: Rosy Future Expectations, Self-enhancement, Thinking Fast, Motivated Cognition, Biased Information Processing

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List of Figures

Figure 1. Conceptual model ... 9 Figure 2. Pre- and post-measures of attitude towards food scarcity, by condition ... 22 Figure 3. Results for the proposed model ... 25

List of tables

Table 1: Means Standard Deviations and Correlations ... 23

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Introduction

The world is facing severe challenges due to the alarming effects of global warming (Masson-Delmotte et al., 2021). According to the latest Intergovernmental Panel on Climate Change (IPCC) report (Masson-Delmotte et al., 2021), emissions of human influence drive the observed warming. These emissions have unequivocally warmed the atmosphere, ocean, and land; the consequences are already observable in every region across the globe. The consequences manifest themselves in extremes such as heatwaves, heavy precipitation, droughts, and tropical cyclones. These are daunting prospects for humanity (Clayton et al., 2016), and the global surface temperature rise will continue until at least mid-century under all emissions scenarios considered (Masson-Delmotte et al., 2021). Heavy interventions are needed to save the planet. Surprisingly, people tend to stay optimistic despite these alarming future expectations and do not seem to be addressing them (Masson-Delmotte et al., 2021). But where do these rosy future expectations come from?

According to Clayton (2015), human capacities are fundamental to overcoming the environmental challenges described. Firstly, because all individuals need to deal with these challenges in the future. Secondly, because individuals' lives will be dramatically affected.

Lastly, remarkably, because human responses often do not exploit and sometimes even hinder opportunities for successful reduction and adaptation of intimidating challenges. Cognitive limitations and biases distort our interpretations of evidence, and emotional defences encourage the denial of challenging information (Clayton et al., 2016). This suggests that the way people process information persuades their attitudes and behaviours (Petty & Briñol, 2010) and may be why we do not effectively address the world's massive challenges. But how do people process information?

Petty and Cacioppo (1981) proposed the Elaboration Likelihood Model (ELM) of persuasion, which involves two information processing routes. The first route involves high-

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level processing, whereby information is considered carefully and thoughtfully. A condition is that an individual needs to be motivated and able to follow this route. The second route is the peripheral route, which involves low-level and less thorough information processing. It basically involves less 'thinking'. People often use the peripheral route because we are 'cognitive misers' who seek to avoid unnecessary effort (Petty & Briñol, 2010; Petty & Cacioppo, 1986).

Drawing on existing models of dual information processing (Petty & Cacioppo, 1986;

Wason & Evans, 1974), Kahneman (2017) similarly describes two systems of thinking. System 1 involves little or no effort, has no sense of voluntary control, and works automatically and fast. The capabilities of System 1 include innate skills that do not need practice because we are born with them. Whereas System 1 requires no attention because an 'automatic pilot runs it', System 2 demands attention and effortful mental engagement and concentration. However, attention is limited and the cognitive fluency of System 1 alluring. It might be that this instigates people to overlook critical information. Yet, how is it possible that this system systematically overlooks the depressing information about the future?

According to Petty and Briñol (2010), cognitive mechanisms are subject to our motivations, which ultimately influence our behaviours. Balcetis (2008) states that motivations influence the information-gathering process by setting up barricades and filters before information comes in.

Motivations also infiltrate cognition at later processing points by biasing how information is processed after receiving it. So, it is to be expected that when using System 1, information acquisition and processing are biased by our personal motivations (Balcetis, 2008; Petty &

Briñol, 2010).

The benefits of positive prospects, such as individual fitness and positive mental and physical health are likely to be motivational factors that shape information processing (Lopez

& Fuxjager, 2012; Petty & Briñol, 2010). Therefore, people are perhaps happier and more receptive towards familiar, comforting, and easily understandable situations or information as

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such information makes them feel safer, more confident, and at ease. Likely, the natural tendency to look for information that makes one feel more confident leads people to unconsciously deceive themselves towards a more positive appraisal of one's situation and self- image (Kahneman, 2011).

The motivated behaviour described above, namely "the tendency for people to exaggerate their virtues and to minimize their shortcomings, as well as to construe or remember events in a way that places their attributes in the most favourable light that is credible to oneself and others" (p.2) is referred to as self-enhancement (Alicke & Sedikides, 2009). It is likely that when negative information is avoided because of the uncomfortable feelings it creates (Kahneman, 2011), more confidence is created than is warranted by one's situation, thereby defending the self from negative views (Alicke & Sedikides, 2009). Thus, it appears that people can often avoid telling themselves the whole truth by searching out those bits of truth they want to hear (von Hippel & Trivers, 2011). Therefore, self-enhancing individuals are expected to see the world more positively than it is because they mislead themselves while searching for satisfying truths. So, this research examines the following question: "Is the relationship between 'Thinking Fast' and rosy future expectations sequentially mediated by biased information processing and self-enhancement?"

Figure 1. Conceptual model

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Theoretical framework

Rosy Future Expectations

Research from many prominent scientists across the world strongly suggests that the impact of the climate problems is enormous (Masson-Delmotte et al., 2021). For instance, Masson- Delmotte et al. (2021) considered all possible emissions scenarios and concluded that it is inevitable that the global surface temperature continues to rise until mid-century. Current estimates of temperature rise between 1.5°C and 2°C will be exceeded this century unless effective reduction strategies in CO2 and other greenhouse gas emissions are successfully implemented. The consequences of this temperature rise include increases in the amount and strength of extreme temperatures, heavy rainfall, periods of extreme drought, marine heatwaves, tropical cyclones, melted Arctic Sea ice, snow cover, and permafrost. While these natural disasters are a severe threat to humanity, even more terrifying is that humans have not managed to reverse the numerous changes described above (Masson-Delmotte et al., 2021).

Despite the dire news, many people deny climate change and the severe challenges that come along with it. According to Haltinner and Sarathchandra (2018), research stated different percentages of climate sceptics, varying between 18% and 29% of the population in 2017. When asked for a reason for their denial of climate change, 22% of these people did not want to share a reason, 18% held on to the belief that climate change is not happening at all, 12% stated that temperature varies naturally and changes are only temporary, 5% reported that news on climate change is fake, and the remaining people had various other reasons why they denied climate change (Haltinner & Sarathchandra, 2018). Haltinner and Sarathchandra (2018) stated different causes for the denial, like political influences that result in polarization. In addition, demographic factors such as race, age, gender, and belief in conspiracy theories were named as causes for denial. In the current research, I argue that this denial of the problem occurs partly because we find ways to convince ourselves that things are not so serious after all.

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According to Crompton (2009), the environmental movement faced, and presumably continues to face, many challenges such as scarce funding and mighty countervailing forces.

Shellenberger and Nordhaus (2009) stated that hundreds of millions are invested in fighting global warming. Still, the results remain disappointing, and efforts to lower carbon emissions via international agreements have largely failed (Shellenberger & Nordhaus, 2009). An example of denying the problem comes from the Norwegian Minister of Environment (Norgaard, 2006). The minister stressed the special responsibility of the country regarding climate change because of the amount of fossil fuels they possess. Instead of taking responsibility, gas and oil production tripled over the next ten years, and the already wealthy country built a fortune with it. Consequently, they broke their promise to limit greenhouse gas emissions, captured in the Kyoto Protocol. Denying that they knew about the consequences is a convenient way to stave off guilt because it suggests they would have acted if they knew. In this way, "turning a blind eye" or "don't look up", implying that one has access to the truth, appeared more convenient.

Another recent example of a countervailing force is the former president of the United States, Donald Trump, also called the "denier-in-chief". When asked if he believed in climate change, his answers appeared mostly based on personal feelings rather than scientific knowledge. Moreover, economic viability seemed to shape his opinion (de Pryck & Gemenne, 2017). All in all, his opinion led to the withdrawal from the Paris agreement in 2020 (McGrath, 2020). To be sure, these rosy future expectations and countervailing forces limit the efficacy of current strategies, as can be concluded by the IPCC report by Masson-Delmotte et al. (2021).

As demonstrated by the examples above, human responses hinder opportunities for successful reduction and adaptation of intimidating challenges (Clayton et al., 2016). The question arises why we behave like this, and it might be that the way we process information has something to do with this.

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Biased Information processing

Petty and Cacioppo (1986) developed the Elaboration Likelihood Model (ELM), which describes two routes to persuasion. Elaboration is considered the 'amount of effort' one can put in processing presented information. The model describes how attitudes and behaviours are formed and changed, and it is based on a continuum that ranges from low to high motivation.

The ELM was initially based on their speculations of contrasting central and peripheral processing routes.

Thoughts follow the central route when an individual is highly motivated to contemplate arguments. When this condition is fulfilled, relevant arguments develop. Consequently, information processed via this central route can cause a positive or negative attitude change that is relatively long-lasting, resistant, and predictive of behaviour. This central route requires a high motivation and concentration level because distractions must be ignored while processing the convincing elements of the available information. When there is low motivation or ability to process the information, people apply less scrutiny, and information processing follows the peripheral route. This route relies more on general impressions, the context's positive and negative signs, and one's mood. Thoughts processed via the peripheral route cause a relatively short temporal shift in attitude that is less stable and predictive of behaviour compared to attitude change that follows from the central route. Thus, it depends on the ability and motivation to process the information, which route is followed, and how one's attitude is changed.

Thinking Fast and Slow

Kahneman (2017) built on this dual processing theory by further interpreting the two different routes, which he labelled System 1 and System 2. System 1 can be compared with the peripheral route, as it facilitates intuitive processing that works via automatic operations and produces fast thinking. It is quick, effortless, gullible, and difficult to change. People are usually

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unaware they use their associative memory to process information because it happens unconsciously. System 1 enables individuals to interpret information rapidly to form a judgment or decide on the spot. Expert intuition derived from extensive practice and skills development is one basis for these intuitive judgments and choices. However, many intuitive thoughts are also caused by heuristics, defined as "principles which reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations." (Tversky and Kahneman, 1974, p.1124).

System 2 can be compared with the central route, facilitating reasoned processing or deliberate thought, and so producing slower thinking. In contrast to System 1, System 2 is often associated with a sense of voluntary control and is responsible for one's attitude towards a situation. For example, when dealing with anger, counting from 1 to 10 can move people past their "gut" reaction—slowing down the initial response. This delay results in considering the situation more carefully, and it helps individuals rationalize their behaviour via System 2.

Consequently, they can stay polite or prevent the self from making an error (Kahneman, 2011;

Osgood & Muraven, 2016). This process requires self-control, mental effort, and attention, and is therefore time-consuming. However, people only have limited capacity to pay attention.

Therefore, Systems 1 and 2 work together efficiently to minimize effort and optimize performance (Kahneman, 2011).

So it might be that when using System 1, the heuristics make us overlook crucial information, leading us to dismiss the daily sobering information we are confronted with.

Therefore, I hypothesize the following:

Hypothesis 1: Thinking Fast will be positively related to rosy future expectations.

Yet, how is it possible that System 1 systematically misses the daunting information about the future? The biased operations of System 1 might explain this. Biases are systematic errors that emerge in specific circumstances. Petty and Briñol (2010) argue that cognitive mechanisms

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tend to be easily biased by our motivations. In turn, these motivations also influence our attitudes – “what one likes and dislikes, favors or disfavors, supports or opposes, and views positively or negatively” (Petty & Briñol, 2010, p.335).

When assessing factors that can change or persuade our initial attitude, different variables influence this process: source, message, recipient, and context. According to the ELM, these variables change attitudes by affecting the process of persuasion. According to Petty and Briñol (2010), they can do this by: "(1) serving as simple cues and heuristics; (2) biasing the thoughts that are generated, (3) affecting one's confidence in those thoughts; (4) serving as persuasive arguments or evidence; and/or (5) affecting the amount of information processing that occurs."

(p.337).

This is consistent with research from Balcetis (2008), who describes how motivated cognition influences cognition already in two ways before cognitive processing mechanisms are engaged (Balcetis, 2008). Firstly, blockades defend the self from threatening information, as people often skip the opportunity to take stock of potentially undesirable information.

Secondly, filters constrain the unlimited stream of information we encounter, and our motivations shape these filters. People's self-schema also influences their attention to and processing of information, as people tend toward favourable self-assessments. Together with motivational barricades and filters, people attend to versus avoid specific informational inputs (Balcetis, 2008; Meng & Tong, 2004).

One consequence of this motivated cognition is that cognitive barricades and filters stimulate people to more readily accept and integrate information that supports their current idea(s), holding information that is consistent with a favoured conclusion to lower scrutiny than they would countervailing information (Lord et al., 1979). This phenomenon is called confirmation bias, which is people's tendency to search for, interpret, favor, and recall information in a way that confirms or supports their view or opinion. When looking to the past,

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motivations constrain the retrieved information via hindsight bias (Kahneman, 2011), with memory searches more likely to find information consistent with one's existing beliefs (Woike and Polo, 2001). And when information is ambiguous, limited, or inconclusive, it becomes easier for the self-deceiver to deploy motivated information processing (Balcetis, 2008).

Perhaps the psychological discomfort of negative messages interferes with the motivation to evaluate a situation accurately because people wish to protect themselves from these "mood killers" (Norgaard, 2006; Webb et al., 2013). Accordingly, we tend to search for information that supports our beliefs to overcome insecurities and become confident (von Hippel & Trivers, 2011). In this way, people neglect negative information and rather gravitate towards the bright side and satisfying information that supports their value orientation. For this research, the focus is to find out if Thinking Fast leads to biased information processing in a way that people resist information in messages they do not want to hear, like daunting environmental prospects.

Self-enhancement

The irrationally acquired positive views can lead to self-deceptive self-enhancement.

According to Kovačić (2021), self-enhancement is "an unconscious tendency to see oneself in a positive light that is manifested in overly positive self-descriptions that an individual truly believes in" (p.2). This tendency is already seen as problematic since 65 b.c.–8 b.c, when the Roman Poet Horace advised his fellow citizens to remember not only what they are capable of but also what exceeds their grasp (Dufner et al., 2019).

Nonetheless, self-enhancement is ubiquitous (Dufner et al., 2019). People perceive themselves as better than their peers, exaggerating their strengths while downscaling their weaknesses. For example, we long for and chase feedback that emphasizes our positive characteristics (Gaertner et al., 2012; Sedikides, 1993). In addition, we hold more optimistic views about our own futures than we do about the futures of our peers. We disparage the validity

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of negative feedback (Shepperd, 1993) and forget negative feedback on characteristics we consider important (Sedikides et al., 2016).

These manifestations of self-enhancement are likely to be caused by biased information processing since it accepts or disregards information based on personal values, feelings, and experience, rather than the deliberate and effortful processing of System 2, where judgments and conclusions are based on rational thinking (Kahneman, 2017). This irrational way of processing information may lead to unconscious overestimations of oneself. As a result, we may see ourselves, and even the world's future, in a more positive light than justifiable.

When considering why people hold rosy future expectations, it might be that the insecurity about the future, or global warming, results in biased information processing because people tend to search for reassuring information. Individuals' fine-tuned, yet unconscious practices of not noticing unwelcome information, also called "turning a blind eye", probably lead to overestimations of the self, and less concerns about the future (Norgaard, 2006). Research from Schultz and Zelezny (1999) already demonstrated this last effect. They found a negative correlation between self-enhancement and biospheric environmental concern, which was measured by the New Ecological Paradigm (NEP) (r = -0-28; p < 0.001). Hence, I hypothesize that:

Hypothesis 2: The relationship between thinking fast and rosy future expectations will be sequentially mediated by self-enhancement and biased information processing.

Method

Participants

An a priori power analysis was conducted using G*Power version 3.1. (Mayr et al., 2007) for sample size estimation. With a significance criterion of α = .05 and power = .80, the

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minimum sample size needed with this effect size is N = 199 for the ANCOVA: fixed effects, main effects, and interactions. Since nationality and age are not expected to influence this research, non-probability sampling was used. Participants were recruited through convenience sampling because of the lack of other resources and time to ensure true randomization. This might result in some sampling bias after all.

Data was collected by Kees Gruwèl, Davide Campoli and Maartje van der Molen. Family, friends, colleagues, and connections on the network platform LinkedIn were reached via a post on LinkedIn, Facebook, a message on Whatsapp, or a phone call and asked to participate in the research. Testing was conducted between April 19, 2022, and April 25, 2022. As a result, a total of 279 persons participated in the experiment administered via Qualtrics. The obtained sample size (N = 279) was more than adequate to test the study hypothesis, even after excluding the individuals who did not successfully finish the survey. In the end, 224 participants were included in the analysis (age M = 34.49, SD = 15.67, range = 16–72). Of these participants, 100 were randomly assigned to the negative condition (age M = 35.62, SD = 15.32) and 124 were randomly assigned to the positive text condition (age M = 33.60, SD = 15.94).

Data collection procedure

The data was collected by a group of three Master's students who write their theses on similar topics. Therefore, the experiment also included measures for two other research projects. The survey measured six constructs (Thinking Fast, Self-enhancement, Overconfidence, Locus of control, Biased information processing, and Rosy Future Expectations). Only four constructs (Thinking Fast, Self-enhancement, Biased information processing, and Rosy Future Expectations) were analysed in this research. The survey can be found in Appendix 1.

In the survey's introduction, participants were informed that the survey aims to understand better how people think about societal issues. After that, participants were assured of

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anonymity, that the research is completely voluntary, and that they can stop at any time. In the last part of the introduction, they were given the option to agree to participate in this research.

After the introduction, the participants were asked for their age, gender, and the highest level of education completed. Participants then completed measures of overconfidence, self- enhancement, the locus of control, a cognitive reflection test (CRT), and the Anticipated Food Scarcity Scale (AFSS). Thereafter, participants were randomly assigned to read a positive or negative text about food scarcity. Then, the AFSS was presented again, and the survey ended with the NEP. Before completion, participants were asked if they had any feedback and if they wished to receive our findings.

Measures Thinking Fast

Thinking Fast was measured by the cognitive reflection test from Toplak et al. (2014), based on Frederick's original CRT (2005). Toplak et al. (2014) extended the original three-item version with four items because participants might know the original CRT. An example question from the CRT+4 is: "A bat and a ball cost $1.10. The bat costs $1.00 more than the ball. How much does the ball cost?". Participants were asked to fill in their answers in a blank text box. Responses were coded as reflective (correct answer), intuitive (incorrect intuitive answer), and proportion incorrect (PI). Thinking Fast was computed by taking the mean of the intuitive responses across the seven questions (α = .617).

Self-enhancement

Participants completed a shortened version of the How I See Myself Questionnaire (HSM;

(Taylor et al., 1995), a measure of self-enhancement. The scale consists of 11 positive qualities or skills (e.g., academic ability, cheerful) and 11 negative traits and characteristics (e.g., selfish, manipulative) (α = .775). Participants rated themselves in comparison with their peers, on a 7- point Likert scale, on how much each positive and negative characteristic described them. The

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values on the scale were anchored from 1 (less than the average person of my age and gender) to 7 (more than the average person of my age and gender). Hence, all negatively keyed items were reverse coded, meaning that for those items, the response "much more" was assigned a value of 7 and "much less" a value of 1.

Biased information Processing

To measure Biased Information Processing, I used a repeated-measures between-subject design. Participants first completed a shortened version of the AFSS (Folwarczny et al., 2021) to measure their baseline attitude toward food scarcity (T0) (α = .892). After reading either positive or negative information about food scarcity in the future (randomly assigned), they again completed the AFSS (T1) (α = .904). An example item from the scale is, "There may not be enough food for everyone." Responses were collected via a 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Biased information processing is expected to manifest in greater (positive) attitude change following the reading of the positive account of future food scarcity and less (negative) attitude change following the reading of the negative account. This variable was operationalized as T1 food scarcity attitudes after controlling for T0 food scarcity attitudes and condition. The standardized residuals were then saved as Biased information processing.

The variable Rosy Future Expectations was measured by the revised New Ecological Paradigm (NEP) (Lundmark, 2007). The revised NEP consisted of 15 statements, which were brought back by the researchers to 7 statements that solely focused on general environmental concern (α = .719). An example of a statement is: "The balance of nature is strong enough to cope with the impacts of modern industrial nations.". Participants rated statements on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

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Results

This chapter presents the results of the performed data analysis. First, this section describes the data preparation for the analysis. After that, Table 1 gives an overview of the data, including means, standard deviations, and bivariate correlations between all measured variables. Then, the manipulation was checked by a paired sample t-test. This is followed by testing the direct and indirect effects of the proposed model by using model 6 from the PROCESS macro of Hayes (Hayes, 2013).

Data preparation

A total of 279 responses were recorded in Qualtrics. However, only 224 respondents fully completed the survey. Since the sample was large enough to be effective, listwise deletion was applied to responses with missing values. As the variable "age" was recorded as date and year of birth, this was converted into years. Moreover, because participants were randomly exposed to two mutually exclusive conditions, dummy coding was performed for the assigned positive- and negative-text conditions, and a new variable called 'condition' was created. After reading the comments of the remaining participants, data was deleted for one participant who forgot to read the text that was part of the manipulation. I expected a positive or negative attitude change after reading the text, and when the participant did not read the text, I could not measure attitude change correctly. Therefore, answers were considered invaluable and unusable for the research.

Lastly, outliers were considered. Only for the biased information processing variable, there were some outliers > 3 Standard Deviations. It was decided not to remove outliers because of the relatively big sample size. Therefore, normalisations are often unnecessary because they could potentially bias the estimates. (Schmidt & Finan, 2018). Moreover, regarding further analysis, regression is generally robust to non-normalities (Knief & Forstmeier, 2021).

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Descriptive statistics

Table 1 presents the means, standard deviations, and bivariate correlations between all measured variables. No significant bivariate relationships were found between the variables of the research model. However, the positive relationship between gender and thinking fast indicates that within this sample, men (M = .20, SD = .18) and women (M = .32, SD = .24) significantly differed on thinking fast, F(3, 221) = 6.72, p < .001, η2 = .08. Men (M = 2.64, SD

= .69) and women (M = 2.34, SD = .65) also differed with respect to their optimism about the environmental future – rosy future expectations, F(3, 220) = 4.50, p = .004, η2 = .06 . Age and self-enhancement were also significantly correlated, r(224) = .22, p = .001, suggesting that when people become older, they become more self-enhancing.

Lastly, as expected, a significant effect of condition on biased information processing was found (Figure 2). The change score in Figure 2 shows the difference in attitude towards food scarcity before and after reading the positive- or negative text. Participants who read the negative text showed significantly worse perspectives on the future in the second measure (Mchange = 0.21, SDchange = 0.73), t(99) = -2.91, p = .005, and participants who read the positive text report significantly better perspectives on the future in the second measure (Mchange = -0.58, SDchange = 0.98), t(123) = 6.55, p < .001. The results also show that for participants who read the positive text, the change score is significantly greater than when the participant is confronted with the negative text. This suggests that participants who read the positive text are more susceptible to changing their attitude drastically compared to participants who read the negative text.

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Figure 2. Pre- and post-measures of attitude towards food scarcity, by condition

Note that higher scores on the mean show more concerns about the future of food scarcity. * p .005, ** p < .001

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Correlations

Variable N M SD 1 2 3 4 5 6 7 8 9 10

1. Thinking Fast 225 0.26 0.22 1

2. Thinking Slow 225 0.55 0.30 -0.82** 1

3. Proportion Incorrect 225 0.19 0.17 0.14* -0.69** 1

4. Self-enhancement 225 4.56 0.59 -0.03 0.04 -0.32 1

5. Rosy Future Expectations 224 2.51 0.69 -0.00 0.01 -0.02 0.12 1

6. Biased information processing 224 0.00 1.00 -0.08 0.05 0.01 0.00 -0.05 1

7. Age 224 34.49 15.67 0.13 -0.11 0.02 0.22** 0.05 -0.09 1

8. Highest level of education completed

225 3.19 0.88 0.06 -0.02 -0.03 0.05 -0.07 -0.01 0.24** 1

9. Gender 225 1.48 0.54 0.26** -0.25** 0.11 -0.03 -0.17** 0.00 -0.04 0.09 1

10. Condition 225 0.56 .50 -0.03 0.10 -0.14* -0.03 0.07 0.00 -0.07 -0.00 -0.11 1

Note. Gender was coded as (1) = male, (2) = female. Age was measured in years. No schooling completed was coded as (1), High school as (2), Bachelor's degree as (3), Master's degree as (4), PhD as (5), and Other answers were coded as (6). Condition was dummy coded as (0) negative text and (1) positive text. * p < .05, ** p < .01

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In the following part of the data analysis, hypothesis testing will take place. PROCESS model 6 from Hayes (2013) was used to test for a serial mediation effect (Appendix 2). For further analysis, standardized scores were used for easier data interpretation. Figure 3 shows an overview of the effects that were found.

To test Hypothesis 1, the variable rosy future expectations was regressed onto thinking fast, revealing a non-significant direct effect, B = -.01, 95%CI[-.15,.12], t(223) = -0.82, p = .87.

Therefore, H1 is rejected. As indirect effects can still emerge in the absence of a direct effect (Hayes, 2013), I proceeded to test my hypothesized indirect pathway from thinking fast to rosy future expectations, via biased information processing and self-enhancement. To test the first indirect step in the model, biased information processing was regressed onto thinking fast. I observed a non-significant relationship between thinking fast and biased information processing, B = -.10, 95%CI[-.23,.04], t(223) = -1.44, p = .15.

No other hypothesized steps in the sequential model returned significant coefficients.

Self-enhancement was unrelated to biased information processing, B = -.01, 95%CI[-14,.13], t(223) = -0.11, p = .91. Rosy future expectations was also unrelated to biased information processing, B = -.06, 95%CI[-19,.08], t(223) = -.85, p = .39 and self-enhancement, B = .12, 95%CI[-.02,.25], t(223) = 1.72, p = .09. Moreover, self-enhancement was not significantly related to thinking fast, b = -.04, 95%CI[-.18,.09], t(223) = -.65, p = .52. Therefore, H2 is also rejected.

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Figure 3. Results for the proposed model

Discussion

This research examined the role of information processing mechanisms on people's perception of the environmental future, intending to contribute to psychological studies on human-environmental relationships that might help solve environmental issues (Clayton, 2015).

According to Clayton (2015): "Effective responses to today's environmental problems require coordinated actions among diverse environmental actors, such as users, experts, and decision- makers. These responses must be sensitive to how people think, interact, and behave." (p.5).

Individuals' risk perceptions are shaped by many factors, separate from direct threats such as floodings or periods of extreme heat. Other influences that shape this are, for example, political ideology and social groups. On an individual level, attitude towards and acceptance of the environmental policy and how values and worldviews shape this play a key role in their expectations and perceived risk (Clayton, 2015). This research aimed to find out if thinking fast was sequentially mediated by biased information processing and self-enhancement, potentially leading to rosy future expectations.

Results indicate that the proposed research model did not explain rosy future expectations on its own. It might be that thinking fast contributes to people's optimistic beliefs,

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but as Clayton (2015) described, many other factors also influence risk perceptions.

Surprisingly, the data did not reveal the expected relationship between thinking fast and biased information processing (Kahneman, 2017; Petty & Briñol, 2010; Petty & Cacioppo, 1986;

Wason & Evans, 1974). Whereas the manipulation showed to be robust, thinking fast did not account for a significant effect on biased information processing. As the participants who read the positive text showed significantly higher scores on attitude change than those who read the negative text, I expected that this would be explained by the natural tendency of people to look for confirming information that aligns with their motivations – a characteristic of thinking fast.

However, no evidence was found that 'fast-thinkers' are prone to a higher attitude change when confronted with positive information.

In addition, the effect of biased information processing on self-enhancement was also not significant. Perhaps placing oneself in a positive light is not related to biased information processing but relies more on other factors that make one have an overly positive view of the self. Moreover, self-enhancement did not significantly relate to rosy future expectations, which I did not expect because earlier work from Schultz and Zelezny (1999) did find a significant relation. Possibly, an enhanced view of the self and the future does not indicate that one sees the future of the collective as rosy. Moreover, viewing the future as positive depends on direct threats that might not be experienced yet. This might have been the reason that I found a different effect. Lastly, political influence and social groups also impact these views significantly, so the context and zeitgeist were expected to differ in this study (Norgaard, 2006).

Theoretical implementations

This research adds to the studies investigating human-environmental relationships and information processing mechanisms. First, it showed that the performed manipulation is robust, extending the existing literature on information processing mechanisms by showing that there is a difference in attitude change when being confronted with a positive- or a negative message

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(Kahneman, 2011; Petty & Briñol, 2010; Petty & Cacioppo, 1986; Wason & Evans, 1974). This is in line with Petty and Briñol's research (2010), which states that the source, message, recipient, and context can change or persuade the initial attitude in various ways, as described earlier.

Secondly, the study showed that thinking fast did not significantly impact rosy future expectations, suggesting that thinking fast does not play a significant role in how people perceive the future. Kahneman (2011) stated that thoughts produced by thinking fast could cause a short temporal shift in attitude, which relies on general impressions, context, and mood.

Results from this study show that the context's negative or positive signs do significantly impact one's attitude about the future of food scarcity, but not the future in general. Perhaps one’s attitude towards the future in general is not so ‘temporal’, and less likely to be shifted by only reading a text. It might be that recent news and direct threats regarding food scarcity, that may be experienced because of the Ukraine-Russia war, have caused more concern and as a result, a greater attitude change. The studies on human-environmental relationships did not yet test for this specific effect, so these findings expand the existing literature, and questions arise for future research directions.

Thirdly, this study suggests that thinking fast does not significantly impact biased information processing. Therefore, it contradicts the existing body of literature on information processing mechanisms that show that individuals are inclined to believe positive information and resist negative information (Kahneman, 2011; Petty & Briñol, 2010; Petty & Cacioppo, 1986; Wason & Evans, 1974). Nonetheless, the results add to the existing literature by showing that the test used in this research might not be suitable to measure thinking fast anymore, or that the cognitive mechanisms are more complex than we think.

Lastly, our results conflict with research from Schultz and Zelezny (1999) that shows opposite results for the relationship between self-enhancement and rosy future expectations. I

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argue that this may be caused by a change in attitude towards the future, since 1999. Perhaps the direct effects of climate change are more tangible now, resulting in more worries about the future on an individual level, even for the ‘self-enhancer’. Therefore, it adds a new perspective to the existing theories.

Practical implications

Considering the non-significant effects of this research model, organisations, institutions and/or governments should reconsider other elements such as context, mood, social groups, and political influence when trying to change people's attitudes towards the future.

While the results suggest that people are inclined to a bigger attitude change when reading a positive text, it does not significantly impact future perceptions. Organisations can learn from this, as the tone of voice is not the primary solution to addressing the climate change denial or inaction. As Crompton (2009) stated that effective responses must be sensitive to how people think, interact, and behave, organisations might shift towards a focus on the impact of the interaction between and in social groups, and political influences, to respond accurately.

In addition, organisations must note that individuals' self-enhanced views do not appear to result in rosy future expectations. The approach to convince people to behave pro- environmentally is therefore susceptible to more effects than only the overly positive view of themselves. So, it also has to do with the light in which they see others—indicating that engagement with social environments deserves attention too.

The data from this study speaks to the complex nature of why people hold rosy future expectations. The non-significant relationships showed that more factors impact the level of concern than only thinking fast. Thus, these findings suggest that the field of human- environmental relationship studies needs more attention to find a solution to addressing climate change.

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Limitations

The current research has several limitations. Firstly, the research was conducted among a non-representative convenience sample, so external validity cannot be guaranteed. It is unknown to what extent the results are generalizable, yet it remains to be examined in the number of surveys distributed among students during this semester may have led to 'survey fatigue'. This could account for lower reliability because participants might have been bored or uninterested, resulting in less attention to the survey. Secondly, multiple participants commented that the survey was distributed in English, which increased the difficulty of the questions. This might have biased the research, as questions can have been misunderstood.

Thirdly, the NEP scale that Schultz & Zelezny (1999) used in their research was adjusted because of its length. A possible consequence of this adjustment might result in different results for this research. A recommendation for future research would be to use the original NEP.

Lastly, several participants reported that they were familiar with the questions used in the CRT.

This might have affected the variable thinking fast

A major limitation of this research is the recent impact of the Russia-Ukraine war on the attitude towards food scarcity and rosy future expectations. This conflict adds to the pre-existing challenges, such as the COVID-19 pandemic, the energy crisis shipping constraints, and recent climate-induced extreme events. The disruption of the export of wheat, corn, and barley has largely impacted food security since Russia and Ukraine produce nearly 30% of the world's traded wheat and 12% of its calories (Behnassi & el Haiba, 2022). Nations, households, and individuals experience difficulties in protecting their food needs. A specific and relatable example is the shortage of sunflower oil produced in Ukraine, which is now hard to get in all supermarkets across Europe (Hauser, 2022). Altogether, this may have led to more insecurity about the future of food scarcity and perhaps also less rosy future expectations.

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Suggestions for further research

Future research could focus on other influences contributing to rosy future expectations, like political influence, social groups, and cultural values. The results from this study showed that gender impacted rosy future expectations significantly. An interesting vein of research would be to find out why men have more optimistic expectations of the future and how the policies they make impact the attitude of the collective. Since men possess more powerful positions in influential organisations, an interesting research direction would be to find if climate change would be addressed more accurately when women hold more influential positions. This would add interesting insights to existing literature that showed that more women on the board increase firm-level commitment to corporate social responsibility (Cook

& Glass, 2017).

Also, it can be interesting to re-test the effect of self-enhancement on rosy future expectations and then test rosy future expectations concerning the self, versus others since the results of this study conflicted with the existing literature. Perhaps, people have experienced climate change in the vicinity, making them more concerned about the future. For communication purposes, it might be interesting to find out if tailored messages increase people’s receptiveness and ultimately, attitude change.

Concluding remarks

According to Steg and Vlek (2009), "individuals can contribute significantly to achieving long-term environmental sustainability by adopting pro-environmental behaviour patterns." (p.315). The challenge that comes along with this is to figure out what the role of cognitive, motivational, and structural factors and processes is that threaten environmental sustainability. This research showed that the cognitive processes of thinking fast do not account for why people hold rosy future expectations. However, biased information

processing does show to be dependent on the tone of the message, perhaps accounting for a

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negligible effect on how attitude can be shaped in the right direction. Therefore, it needs more attention, and to find out what accounts for this, further research must be done so that pro- environmental behaviours can be facilitated and emerge worldwide.

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Appendices

Survey

General knowledge questionnaire (GKQ)

Below you will be presented with some general knowledge questions.

Imagine that you are taking part in a game, like "Trivial pursuit" or "Who wants" to be a Millionaire?", and you have to choose the correct answer from the three given alternatives.

1) Please select ONLY ONE of the three given answers. Only one of them is correct.

2) When you have made your choice and have selected your answer, we would like to know how sure/confident you are that your answer is correct.

Since there are three alternative answers and only one of them is correct you have a 33% chance of giving a correct answer. Therefore 33% means that you are guessing and do not know the correct answer, and 100% corresponds to absolute certainty.

You can choose any number between 33% and 100% to indicate your confidence that your answer is correct. Enter your confidence for every answer after every test item.

1. Which of the following is known for being an instant camera?

Canon Camera   Polaroid Camera   Minolta Camera 

How confident are you that your answer is correct?

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

2. Where do flounders mostly live?

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in coral reefs   dug into the ground  in reeds 

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

3. What do roll mops mostly consist of?

herring fillet    pork   salmon fillet 

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

4. Which country does the Nobel Prize winner in Literature Gabriel García Márquez come from?

Colombia    Spain   Venezuela 

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

5. Which style movement does Anacreontics belong to?

Rococo    Romanticism   Realism 

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33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

6. What is meant by horripilation?

itch    goose bumps   muscle pain 

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

7. How many letters does the Russian alphabet consist of?

40    33   26 

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

8. "Tosca" i" an o"era from?

G. Puccini    G. Verdi   A. Vivaldi

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33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

9. What is the name of the Greek Goddess of wisdom?

Pallas Athena   Nike   Penelope

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

10. What is the most abundant metal on Earth?

Iron   aluminum   copper

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

11. What is the word for a person who lacks knowledge?

ignatius   ignorant   ideologue

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33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

12. Who was the first to fly in an airship around the Eiffel tower?

Santos-Dumont  Count Zeppelin   Saint-Exupery

33% ––––––––––––––––––––––––––––––––––––––––––––––––––––––– 100%

Locus of control scale (LoCs)

Below are a number of statements about how various topics affect your personal beliefs. There are no right or wrong answers. For every item there are a large number of people who agree or disagree. Please read each item and fill in the appropriate space the choice you believe to be true.

1. I have usually found that what is going to happen will happen, regardless of my actions 2. Many times I feel that we might just as well make many of our decisions by flipping a coin.

3. Getting a good job seems to be largely a matter of being lucky enough to be in the right place at the right time.

4. It is difficult for ordinary people to have much control over what politicians do in office 5. It isn't wisisn'tplan too far ahead because most thing turn out to be a matter of good or bad fortune anyhow

6. When things are going well for me, I consider it due to a run of good luck 7. Success is mostly a matter of getting good breaks

8. I think that life is mostly a gamble

9. There's nThere's use in worrying about things… what will be will be

10. Many times I feel that I have little influence over the things that happen to me

11. Success in dealing with people seems to be more a matter of the other person's person'sd feelings at the time rather than one's ownone'sons.

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Cognitive Reflection Test (CRT)

The following section contains seven questions that test basic reasoning skills. Please fill in the blank in numbers.

(1) A bat and a ball cost $1.10 in total. The bat costs a dollar more than the ball. How much does the ball cost? ____ cents [Correct answer = 5 cents; intuitive answer = 10 cents]

(2) If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets? ____ minutes [Correct answer = 5 minutes; intuitive answer = 100 minutes]

(3) In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake? ____ days [Correct answer = 47 days; intuitive answer = 24 days]

(4) If John can drink one barrel of water in 6 days, and Mary can drink one barrel of water in 12 days, how long would it take them to drink one barrel of water together? _____ days [correct answer = 4 days; intuitive answer = 9]

(5) Jerry received both the 15th highest and the 15th lowest mark in the class. How many students are in the class? ______ students [correct answer = 29 students; intuitive answer = 30]

(6) A man buys a pig for $60, sells it for $70, buys it back for $80, and sells it finally for $90.

How much has he made? _____ dollars [correct answer = $20; intuitive answer = $10]

(7) Simon decided to invest $8,000 in the stock market one day early in 2008. Six months after he invested, on July 17, the stocks he had purchased were down 50%. Fortunately for Simon, from July 17 to October 17, the stocks he had purchased went up 75%. At this point, Simon has: a. broken even in the stock market, b. is ahead of where he began, c. has lost money [correct answer = c, because the value at this point is $7,000; intuitive response = b].

How I see myself scale (HISM)

For each of the qualities or skills below, we would like you to compare yourself to your peers.

Specifically, we want you to think about how the average person of your age and gender scores on each of these qualities or skills, and then rate yourself in comparison.

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Food scarcity scale (AFSS)

Next we would like to know your thoughts on a sustainability issue that has recently been in the news. Below are a number of statements about food scarcity. There are no right or wrong answers. Please read each item and fill in the appropriate space the choice you believe to be true.

"Don't Look Up! Thinking Fast About Climate Change and its Consequences"