Emotional responses to climate change, mental health, and climate action: How are they related?

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Keren Kaplan Mintz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4275680/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As climate change becomes a reality, people are becoming increasingly aware of the threats associated with global warming. Many people may experience climate change as an unremitting psychological stressor associated with high levels of concern, worry and anxiety, that can emerge even in the absence of short-term or direct effects. Because emotions are related both to mitigation behavior and to promoting resilience and well-being, studying people’s emotional responses to climate change is important. This study explores the links of different emotional responses to climate change with mental health and pro-environmental behavior, using an online survey of a nationwide representative sample in Israel. An online survey of a nationwide representative sample of Hebrew speakers (N=302) revealed high levels of negative emotions, along with low levels of climate anxiety and moderate levels of positive emotions and indifference. Both climate change anxiety and negative emotions were associated with impairment in mental health. Positive emotions predicted an increase in both private-sphere and collective pro-environmental behavior, whereas indifference predicted a decrease in both types of behavior. Climate change anxiety predicted an increase in collective but not in private-sphere pro-environmental behavior. The research findings extend our understanding of the role played by different emotional responses to climate change in explaining impairment in mental health and adaptive pro-environmental behavior. Emotional responses to climate change climate change anxiety pro-environmental behavior mental health resilience Introduction Climate change is expected to have a pervasive impact on human health and natural systems worldwide (IPCC, 2022). Today, climate change is no longer a distant and unimaginable threat, but rather a growing reality manifested in conditions such as rising average temperatures and growing storm intensity (Manning & Clayton, 2018; Tam et al., 2023). As climate change becomes a reality, people are becoming increasingly aware of the threats associated with global warming (Hickman et al., 2021; Tam et al., 2023). Based upon its projected and ambiguous consequences, climate change can be considered a stressful life event (Schwarzer & Luszczynska, 2012). Many people may even experience climate change as an unremitting psychological stressor associated with high levels of concern, worry and anxiety, that can emerge even in the absence of short-term or direct effects (Clayton, 2020; Clayton & Karazsia, 2020; Hickman et al., 2021). Hence, the widespread emotional and mental responses to climate change are not surprising (Bouman et al., 2020; Tam et al., 2023). Given that climate change is a source of stress, researchers have begun to examine how people cope with it and how their resilience can be enhanced (Doherty, 2018; Homburg et al., 2007). Because emotions are related both to mitigation behavior and to promoting resilience and well-being, studying people’s emotional responses to climate change is important (Brosch, 2021; Clayton & Karazsia, 2020; Doherty, 2018; Pihkala, 2022). Most research on emotional responses to climate change has focused on climate change anxiety (CCA), defined as an intense state of distress concerning climate change accompanied by impairment in cognitive and behavioral functioning (Clayton & Karazsia, 2020). One of the challenges in this line of research entails making a clear distinction between CCA and other emotional responses to climate change (Sangervo et al., 2022; Whitmarsh et al., 2022). Another challenge is to study the prevalence and structure of CCA in various societies worldwide (Tam et al., 2023). The current study aims to address these objectives. It was conducted with an Israeli sample and focuses on CCA along with three other emotional responses to climate change: positive emotions, negative emotions, and indifference. By studying how these are linked to mental health and to engagement in pro-environmental behavior (PEB), the study seeks to enhance our understanding of the nature of CCA and to clarify how it differs from other emotional responses to climate change. Literature Review Different Kinds of Emotional Responses to Climate Change Emotions are defined as changes in organic subsystems in response to an external or internal stimulus appraised as relevant to the individual (Brosch, 2021; Scherer, 2005). Emotional responses to climate change are defined as affective phenomena associated with the climate crisis (Pihkala, 2022). When faced with stressful events, individuals are expected to experience multiple and even conflicting emotions (Folkman & Lazarus, 1988). It is therefore not surprising that emotional responses to climate change are many and varied, ranging from negative feelings such as despair, anger, and shame to positive feelings such as hope and pride (Hickman et al., 2021; Pihkala, 2022; Stanley et al., 2021). The emotional responses discussed in this paper comprise four groups of emotions: positive emotions, negative emotions, indifference, and CCA. Positive emotions and negative emotions . Empirical research has consistently found that positive emotions and negative emotions are two distinct dimensions, usually described as positive affect and negative affect (Feldman, 2006; Watson et al., 1988). Positive affect is marked by a state of high energy, full concentration, and pleasurable engagement that reflects the extent to which the individual feels enthusiastic and active. Negative affect, in contrast, is a general dimension of subjective distress and unpleasant engagement that includes aversive mood states such as anger, fear, and nervousness (Watson et al., 1988). The literature on stress and coping points to several important distinctions between these two emotional dimensions that have important implications for coping processes. Prolonged negative affect may lead to clinical depression and anxiety disorders. Positive affect, in contrast, triggers an upward spiral toward emotional well-being, broadening the individual's attentional focus and behavioral repertoire and building social, intellectual, and physical resources required to facilitate adaptation (Fredrickson, 1998; Fredrickson & Joiner, 2002). Positive emotions are therefore considered to be an important aspect of coping with stressful life events and enhanced mental health (Folkman & Moskowitz, 2000). Awareness of the projected consequences of climate change can be associated with various negative feelings, such as grief associated with changes in nature, feeling threatened by the potential loss of security, or losing confidence in the natural world (Clayton & Karazsia, 2020). In measuring emotional responses to climate change, some studies focus on specific emotions, claiming that these have a differential impact on climate action and mental health (e.g., Stanley et al., 2021). Yet, based on the research on emotions described above, it is advocated to examine the structure of climate emotions and group them by meaningful measures (Pihkala, 2022; Tam et al.,2023). Initially, most research on climate change emotions focused on negative emotions (Brosch, 2021; Bamberg et al., 2018). In recent years more research attention has been directed toward positive emotions as well (Ojala, 2023; Pihkala, 2022; Schneider et al., 2022). Ojala for example, conducted a series of studies on hope in the context of climate change, stressing the ability of hope to enhance adaptive coping associated both with climate action and with well-being (Ojala, 2012a,2012b,2023). Ojala (2012a) claimed that because negative emotions are a realistic response to climate change, it is important to find effective ways of handling such feelings. This approach is in line with research on the role of positive affect in coping with stressful events described above. Similarly, Sangervo et al. (2022) contend that climate hope and efficacy should be measured since they may moderate the effect of CCA on behavior (Sangervo et al., 2022). Indifference. Feeling indifferent about climate change is tantamount to being bored with this topic and perceiving it as unimportant (Marczak et al., 2022). Indifference is considered to be the emotional component of denial: It is a defensive, self-protective strategy that serves to suppress or avoid uncomfortable emotions and distress. Indifference is sometimes defined as implicatory denial of climate change (recognition of climate change as a problem but denial of its psychological, political, and moral implications) (Wullenkord et al., 2021; Wullenkord & Reese, 2021). The assumption is that indifference is part of emotion management and is motivated by a desire to avoid unpleasant emotions such as helplessness and guilt (Nogaard, 2006). It also can be seen as an aspect of emotion-focused coping strategy, which is aimed at reducing aversive feelings emerging in the face of stressful events through processes of denial, avoidance, and distancing (Lazarus & Folkman, 1984). CCA . People’s feelings regarding climate change may vary in intensity (Clayton & Karazsia, 2020; Pihkala, 2021). CCA is characterized by an intense and cognitive-emotional response to climate change that includes anxiety, worried thoughts, and concerns about physiological changes brought on by the climate crisis (Sangervo et al., 2022). CCA is differentiated from climate worry based on its intensity and its potential to affect daily life: Whereas concerns about climate change are a common and natural response to current threatening projections, CCA is characterized by an intense emotional reaction that may interfere with daily cognitive and behavioral functioning (Clayton & Karazsia, 2020). CCA has both mild and more severe manifestations (Sangervo et al., 2022). Although CCA is associated with impairment in mental health, it is still considered to be a rational response to climate crises and not a pathological psychological condition (Clayton & Karazsia, 2020; Hickman et al., 2021; Sangervo et al., 2022). Nevertheless, due to CCA’s potential impact on mental health, it is important to investigate its prevalence, its predictors, and the ways it is associated with adaptive and maladaptive functioning (Clayton & Karazsia, 2020; Whitemarsh, et al., 2022). Until recently there was very little conceptual clarity regarding the concept of CCA that had the power to leverage rigorous research. Clayton and Karazsia (2020) recently developed a valid scale for measuring CCA known as the Climate Change Anxiety Scale (CCAS). This scale has been validated and tested among several samples in the US (Clayton & Karazsia, 2020; Tam et al., 2023), Europe (Mouguiama - Daouda et al., 2021; Whitmarsh et al., 2022; Wullenkord et al., 2021), and Asia (Simon et al., 2022; Tam et al., 2023). Yet, more research is needed to investigate the worldwide prevalence of CCA, and specifically to examine societies that are more likely to be affected by climate change (Tam et al., 2023). What is the Prevalence of Different Emotional Responses to Climate Change? Worries and concerns about climate are quite prevalent. In an international study that investigated the reported experience of 14 distinct emotions among young people, more than 50% of respondents reported negative emotions such as sadness, and anger (Hickman et al., 2021). In a UK study, over 40% of participants reported being worried about climate change (Whitmarsh et al., 2022). Yet, despite the high prevalence of negative emotional responses to climate change, reported levels of CCA are low. Most studies that used the validated CCAS instrument found that the average level of CCA was below the scale’s midpoint (e.g., Simon et al., 2022; Tam et al., 2023; Wullenkord et al., 2021). While research on the prevalence of negative emotions and CCA is relatively adequate, the prevalence of positive emotions has not received sufficient research attention. As noted above, Ojala (2012a, 2012b, 2023) examined the positive emotion of hope, though information on its prevalence is limited. The few studies reporting on the distribution of positive emotions show prevalence rates ranging from 30% to 46% (Hickman et al, 2021; Smit & Leiserowitz, 2014). Information on the prevalence of indifference is also limited. Hickman et al. (2021) found that 29% of participants reported feeling indifferent. How are Different Emotional Responses to Climate Change Associated with Mental Impairment and PEB? Positive emotions . As noted above, positive emotions are associated with mental health and are considered important in coping with stressful life events (Fredrickson, 1998; Fredrickson & Joiner, 2002; Folkman & Moskowitz, 2000). In line with the assertion that “feeling good about doing the ‘right thing’ can be an important motivator for behavior change” (Smith & Leiserowitz, 2014), positive emotions were found to be associated with several pro-environmental behaviors (refer to Schneider et al, 2021 for a review). Nevertheless, very little research has investigated the role of positive emotional responses to climate change in promoting mental health and PEB, and most studies in this area focused on one emotion: hope. Findings on the correlations between hope and climate engagement are not consistent (Ojala, 2023). This result can be partly explained by the fact that in some cases hope is unrealistic and related to denial instead of agency. The association between hope and climate engagement is therefore dependent on the sources of hope (Ojala, 2012b, 2023). Negative emotions. Negative emotions were found to be associated with both impairments in well-being and climate action (Brosch, 2021). The motivational engine of negative emotions appears to be driven by undesirable emotional states, which people seek to reduce through action (van Valkengoed, & Steg, 2019). Nevertheless, prolonged negative affect may be harmful to mental health (Gross & Muñoz, 1995). Some empirical results point to such associations in the context of climate change as well. For example, Whitmarsh et al. (2022) found a significant correlation between climate concerns and generalized anxiety, Stanley et al. (2021) found positive associations between eco-anxiety and eco-depression measures and impaired mental health, and Searl and Gow (2010) found a relationship between climate concerns and symptoms of depression, anxiety, and stress. Indifference. As indicated, indifference can serve as part of an emotion-focused coping strategy individuals use to reduce negative feelings when faced with a stressful situation (Lazarus & Folkman, 1984). Researchers have suggested that although such strategies may help mitigate anxiety in the short term, they may be associated with higher levels of anxiety in the long run (Schäfer et al., 2017; Wullenkord et al., 2021). Furthermore, research on coping strategies found that emotion-focused coping is used more by individuals with depression and is associated with high levels of distress (Leandro & Castillo, 2010; Rice et al., 2020). Regarding the link between indifference and PEB, Norgaard (2006) found that although people accept the existence of climate change, their indifferent emotional response often stops them from acting. Similarly, Ojala (2012a) found that the use of de-emphasizing strategy toward climate change is associated with low behavioral engagement. Wullenkord and Reese (2021) also found an association between various forms of denial (cognitive and emotional) and PEB. CCA . Research on CCA points to links to generalized anxiety (GA) and depression (Clayton & Karazsia, 2020; Whitemarsh et al., 2022; Wullenkord et al., 2021). Yet because CCA is measured along a continuum, only higher levels have the potential to affect mental health (Clayton et al., 2023). Based on these findings, some researchers suggested that individuals with existing mental health disorders may be vulnerable to higher levels of CCA (Clayton & Karazsia, 2020; Whitemarsh et al., 2022). Dew to the projected impacts of climate change the prevalence of climate change is likely to grow. Hence, it is important to study its predictors and consequences (Clayton & Karazsia, 2020; Tam et al., 2023). Moreover, most studies found positive statistical correlations between CCA and PEB engagement (Mouguiama – Daouda et al., 2022; Tam et al., 2023; Sangervo et al., 2022; Wullenkord et al., 2021), though other studies did not find such an association (Clayton & Karazsia, 2020). In addition, some variability exists in the extent to which CCA explains different kinds of PEB (Tam et al., 2023; Whitemarsh et al., 2022). Bamberg et al. (2018) recently suggested that due to the collective nature of the human impact on climate change, environmental psychology research should pay more attention to collective rather than private-sphere climate action (Bamberg et al., 2018). In the case of research on CCA, most studies do not distinguish between private-sphere and collective behavior. Such a distinction may lead to a better understanding of the links between CCA and PEB. One relevant study found that while CCA predicted both types of action, its prediction of collective PEB tended to be greater (Tam et al., 2023). How do Different Emotions Toward Climate Change Predict CCA? Since the introduction of the CCAS scale, an increasing number of studies have investigated the prevalence of CCA, its association with demographic variables such as age, and gender, mental health, and PEB (e.g., Clayton & Karazsia, 2020; Tam et al., 2023; Whitmarsh et al., 2022, Wullenkord et al., 2021). Some studies have investigated the association between emotional responses to climate change and CCA as distinct variables (Clayton & Karazsia, 2020; Tam et al., 2023; Whitmarsh et al., 2022), whereas other scholars have suggest coalescing these two variables and focusing only on CCA (e.g., Ogunbode et al., 2022). Moreover, research on how positive emotional responses to climate change and indifference are associated with CCA is very limited. The only study that was found that addresses such association focused on hope (Sangervo, 2022). This study found positive association between hope and CCA, which was explain by the fact that both are reactions to uncertainty. Overall, information on this topic is very limited, and more research is needed to clarify the associations between CCA and other emotional responses to climate change. The Present Study This study contributes to previous research by investigating how various emotional responses to climate change are associated with mental health and PEB, and how do negative emotions toward climate change eare distinguished from CCA. The study was conducted in October 2022 in Israel. Although Israel is a developed country, it is considered at high risk for climate change effects. The rate of global warming in Israel is almost two times greater than the global rate. Moreover, Israel is vulnerable to climate change risks such as intense heat waves and increased desertification (Israel Meteorological Service, 2021). Nevertheless, the state of Israel has yet to make the necessary perceptual shift (State Comptroller and Ombudsman of Israel, 2021), and a recent report of OECD has stated that Israel is not on track to reach its climate change targets (OECD, 2023). Furthermore, a 2016 survey found that relative to the citizens of most European nations, Israelis were rather skeptical about or unaware of climate change, exhibiting the lowest average rate of concern about climate change of all 24 countries surveyed (Poortinga et al., 2019). Considering the projected consequences of climate change in Israel, more in-depth investigation is needed to explore perceptions, emotional responses, and behavioral responses to climate change in this country. The study’s objectives are threefold: (a) to clarify similarities and differences between CCA and other emotional responses to climate change in predicting mental health impairment and PEB engagement; (b) to explore how different emotional responses to climate change are related to CCA; and (c) to explore the prevalence of CCA and other emotional responses to climate change in Israel. Based on the theoretical background, the study investigated the following hypotheses: H1. Impaired mental health will be positively related to (a) negative emotions, (b) feelings of indifference, and (c) CCA, and will be negatively related to (d) positive emotions. H2. Engagement in PEB will be positively related to (a) negative emotions, (b) positive emotions, and (c) CCA, and will be negatively related to (d) indifference. Moreover, very little data is available on the role the three types of emotions toward climate change in explaining CCA. Hence, this investigation is exploratory, and no hypotheses are posited. Methods An online survey was conducted via an online participant panel (Sekernet) among a representative sample of the Hebrew-speaking public in Israel. The survey received ethical approval from the University (Approval No. 362/22). Participants gave their informed consent before answering the survey. The survey included measures of CCA, emotions toward climate change, mental health (GA and depression), and PEB (private-sphere and collective). Because emotional responses to climate change may be complex and are related to cognitive appraisal (Chapman et al., 2017), the study also included two measures of cognitive and affective environmental responses: a climate change perceptions scale developed by van Valkengoed et al. (2021) and the NEP scale, which measures general environmental worldview (Dunlap et al., 2000). Survey measures and items were translated from English into Hebrew by two independent translators and then reviewed by the main author. Participants The sample was broadly representative of the Jewish population in terms of gender, age, and religiosity. In total, 302 respondents participated, of whom 151 (50%) were female. The mean age was 42.59 (median 42.00, SD 16.20, range: 18-86), and 43.7% of the participants held academic degrees (for more information refer to Tables S1a-S1c in the supplementary materials). Measures If not otherwise indicated, participants responded to all measures on 5-point Likert scales ranging from 1 (strongly disagree/not at all) to 5 (strongly agree/applies completely). Table 1 summarizes the items and their psychometric properties. Emotions toward climate change. Respondents were asked to indicate the extent to which they felt each of thirteen emotions associated with climate change. The items were based on previous research on emotions toward climate change (Clayton & Karazsia, 2020; Hickman et al., 2021; Marczak et al., 2022). An exploratory factor analysis was performed to explore whether individual emotions could be clustered into different interpretable subscales. The items were distributed over three factors (Eigenvalues = 1.25-5.9, 71% cumulative explained variance) in accordance with the theoretical concepts of negative emotions (nine items, α=.93), positive emotions (three items, α=.77), and indifference (one item). CCA was measured using the Climate Change Anxiety Scale (CCAS) (Clayton & Karazsia, 2020). As previous research yielded mixed results on the scale factor structure (Tam et al., 2023), principal component analysis was conducted on the 13 items. The Kaiser–Meyer–Olkin measure verified the sampling adequacy for the analysis (KMO = 0.95). Only one factor had an eigenvalue above the Kaiser criterion of 1 and explained 71.12% of the variance. As a result, it was decided to use a single score for CCA (α=.97). Mental health measures. Mental health was measured using the Hebrew version (Miller) of the HADS scale (Zigmond & Snaith, 1983). Participants were asked to indicate the extent to which they agree with 14 statements concerning their emotional and mental state on a four-point scale (3= very much; 0=not at all). The scale provides two measures of mental health, each comprising seven items: GA (α= .88), and depression (α=.77). Environmental worldview. Environmental worldview was measured using the New Ecological Paradigm scale (NEP). This scale consists of 15 items representing beliefs related to human domination over nature. Seven of the items were reversed (Dunlap et al., 2000). Cronbach's alpha of the scale was 0.82. Climate change perceptions. The climate change perceptions scale (van Valkengoed et al., 2021) was used to measure perceptions regarding climate change. The scale consists of 14 items grouped into five sub-scales: climate change is real; is caused by humans; negative consequences; spatial distance; and temporal distance. Because this is the first time this scale was used with an Israeli sample, an exploratory factor analysis was conducted to investigate its local factor structure. The analysis yielded a four-factor structure, as 'human caused', and 'negative consequences' were collapsed into a single factor. Yet because of the distinct meanings of the different subscales and to adhere to previous research, it was decided to use the original structure of five sub-scales. Cronbach's alphas for the five sub-scales were .77, .96, .94, .96, and .86, respectively. PEB. Measures of private-sphere and collective PEB were based on the scale developed by Stanley et al. (2021). The original scale included 16 items—eight in each sub-scale. In the current research two locally relevant items were added, one for each sub-scale. Participants were asked to indicate how often they had engaged in different forms of PEB during the past year, on a scale ranging from 0 (never) to 100 (at every opportunity) (Table S2, S3 in the supplementary materials). Cronbach's alpha for the scales is .88 for private-private sphere, and .87 for collective PEB. Demographic data. Demographic data included age, gender, education, level of religiosity, and income. Data Analysis Data analyses were conducted using SPSS version 27. For prevalence analysis, the means, and standard deviations of the emotional responses to climate change were collected, and the prevalence of different levels of each variable was analyzed. Correlational analysis was used to explore the correlations between the research variables. Then, a series of multivariable linear regression analyses were run to examine emotional responses to climate change as predictors of impairment in mental health and of PEB. Age, gender, climate change perceptions, and environmental worldview served as control variables. To explore the unique contribution of CCA in explaining impairment in mental health and PEB, the regressions were each run in two models, one excluding CCA and the other including it. Power Analysis Analyzing the data by multiple regression models was expected to yield a squared multiple correlation of 0.2 at least (R 2 >0.2), corresponding to the Cohen's f 2 effect size of 0.25. For significant results with a maximum of 14 predictors at a 5% significance level and 95% power, a sample size of 122 is needed. The power analysis was conducted using G*Power version 3.1.9.4 (freeware) (Faul, 2007). Results Prevalence Rates of Research Variables As shown in Table 1, the mean level of the CCA measure was relatively low: 1.46 within a 1-5 range. Within the three groups of emotions toward climate change, negative emotions exhibited the highest average (2.74 within a range between 1-5), followed by positive emotions (2.36) and indifference (2.30). In an effort to obtain further insights on the prevalence of the emotional responses to climate change and to be able to compare these results to other samples (e.g., Whitmarsh et al., 2022), the prevalence of these variables was determined by categorizing responses into ‘low’ (1.00 ≤ M ≥ 2.33), ‘moderate’ (2.34 ≤ M ≥ 3.66), and ‘high’ (3.67 ≤ M ≥ 5.00) (Table 2). The prevalence of negative emotions was moderate or high for most participants (39.7% and 25.5% respectively), whereas the level of CCA was low for most participants (88.4%), and high only for 3% of the participants. Positive emotions and indifference exhibited a similar prevalence: about 40%. <> <> Correlational Analysis Table 3 shows the correlations between the research variables. The two measures of impairment in mental health (GA and depression) correlated positively with negative emotions, indifference, and CCA. No significant correlation was found between impairment in mental health and positive emotions. Moreover, no significant correlations were found between environmental affective variables and measures of mental health, except for a negative correlation with the perception that climate change is real, which was negatively associated with both measures of impairment in mental health. In addition, age exhibited a negative correlation with GA, whereas gender showed a positive correlation, such that women are more prone to GA than men. Both types of PEB were positively associated with both negative emotions and positive emotions and negatively associated with indifference. CCA was positively associated with collective PEB, but not with private-sphere PEB. Of the control variables, all five forms of perceptions regarding climate change as well as environmental worldview exhibited positive correlations with both private-sphere and collective PEB, except for the perception that climate change is real, which was positively correlated only with private-sphere behavior. Moreover, all three kinds of climate change emotions were positively correlated with CCA, as were the two measures of impairment in mental health. CCA was also negatively correlated with the perception that climate change is real. The variables of age, gender, and environmental worldview exhibited no significant correlations with CCA. <> Regression Analyses: Predicting Impairment in Mental Health Table 4 shows the multiple regression analyses for GA and depression. The GA model that included CCA explained 53% of the variance [F (13,288) =26.7, p <.001], and the model of depression that included CCA explained 41% % of the variance [F (13,288) =17.2, p <.001]. As shown in Table 4, higher levels of negative emotions ( β=. 18, p<.01 ) and of CCA ( β=. 19, p<.001 ) predicted higher levels of GA, thus corroborating H1a and H1c. Heightened GA was also predicted by depression ( β=. 51, p<.001 ) and by reduced perception of spatial distance ( β=-. 16, p<.01 ). As indicated in the Table, the only variable that significantly predicted depression was GA ( β=.64 , p<.001 ). Positive emotions and indifference did not significantly predict GA or depression, refuting H1b and H1d. With respect to CCA’s unique contribution, inclusion of CCA in the GA regression model resulted in a significant change in the explained variance, from 51% to 53% (R2 change=.02 p.05). <> Regression Analysis: Predicting Private-Sphere and Collective PEB Table 5 depicts the multiple regression analyses for private-sphere and collective PEB. The model of private-sphere PEB that included CCA explained 24% of the variance [F (14,287) =7.59, p <.001], and the model of collective PEB that included CCA explained 28% of the variance [F (14,287) =9.19, p <.001]. Table 5 indicates that higher levels of positive emotions increase private-sphere ( β=. 16, p<.01 ) as well as collective PEB ( β=. 132, p<.05 ), corroborating H2b. Moreover, higher indifference decreased both private-sphere (β=-. 16 , p<.01 ) and collective PEB ( β=. 22, p<.001 ), corroborating H2d. In contrast, negative emotional responses to climate change did not predict private sphere, nor collective PEB, refuting H2a. Further, CCA did not predict private-sphere PEB but it did predict collective PEB ( β= 0.32, p<.001 ). Hence, H2c was corroborated only in reference to collective PEB. It is interesting to note that when CCA is excluded from the regression model, negative emotions predict collective PEB ( β= 0.24, p.05). Of the control variables, increased private-sphere PEB was predicted by age ( β =.13 , p<.05 ), perceived human caused ( β =.2 , p<.01 ), and environmental worldview ( β=. 16 , p<.05 ), and increased collective PEB was predicted by environmental worldview ( β=. 16 , p<.05 ). Examination of CCA’s unique contribution to the regression models showed that in the case of private-sphere PEB CCA does not produce any change in the model’s explained variance (R2 change=.001 p >.05). In the regression model for collective PEB, the variance exhibits a significant rise, from 22% to 28% (R2 change=.006 p< .001). <> Regression Analysis: Predicting CCA Table 6 shows the multiple regression model for CCA, which explains 43% of the variance in CCA [F (13,288) =18.537, p < .001]. Participants who reported higher negative emotions ( β=.41, p<.001 ), higher positive emotions ( β=.20, p<.001 ), and more indifference ( β=.14, p<.01 ) also reported higher CCA. With respect to the control variables, higher levels of CCA were predicted by higher GA ( β=.22, p<.001 ), lower perceptions that climate change is real ( β=-.24, p<.001 ), and gender (being a man was associated with higher CCA) ( β=-.12, p<.01 ). <> Discussion A growing body of literature has explored the nature of CCA and its relationship with mental health and environmental engagement (e.g. Clayton & Karazsia, 2020; Whitmarsh et al., 2022). Nevertheless, the similarities and differences between CCA and other emotional responses to climate change are less clear, particularly in terms of associations with mental health and environmental engagement. Emotional responses to climate are associated both with impairments in mental well-being and with adaptive engagement in PEB. Hence, research on the psychological aspects of climate change mitigation and adaptation must consider the interplay of these emotions. This study contributes to previous research by focusing on CCA along with three other emotional responses to climate change, and studying their associations with two measures of mental health and two measures of PEB. In addition, the study validates the Hebrew version of the CCAS in an Israeli sample and contributes to research on CCA prevalence and its determinants in different samples worldwide. Different emotional responses exhibit different relationships with mental well-being and behavioral engagement. Each of the four emotional responses to climate change investigated in this research exhibited a different pattern of association with mental health and PEB measures. Positive emotional responses to climate change were the most adaptive as they were among the leading predictors of both private-sphere and collective PEB. These findings are in line with previous research (Ojala, 2012a; Sangervo et al., 2022; Schneider et al., 2021; Venhoeven et al., 2020) and extend our understanding of the importance of positive emotions when coping with climate change. Because this was a correlational study, the source of this association may come from two directions: On the one hand, acting in a pro-environmental manner and engaging in climate action may lead to feelings of competence and enhance positive emotions (Ojala, 2023; Venhoeven et al., 2020). In addition, experiencing positive emotions such as hope and empowerment may serve as a motivational force for engaging in climate action (Bury et al., 2020; Ojala 2023). Contrary to expectations, positive emotions did not predict enhancement of mental health. Yet because positive emotions were found to be related to behavioral engagement, the findings are in line with the notion that positive emotions can trigger an upward spiral toward emotional well-being by broadening the individual's attentional focus and behavioral repertoire (Fredrickson, 1998). Moreover, although negative emotions regarding climate change did exhibit significant correlations with PEB, when controlled by other variables the prediction was no longer significant. With respect to mental health, an increase in negative emotions predicts an increase in GA. A large body of research has already discussed the possible impact on mental health of prolonged negative emotions when coping with stressors (Gross & Muñoz, 1995). The current results contribute to existing research by highlighting the impact of negative emotions on mental health in the specific context of coping with climate change. An interesting result of the present research is that negative emotional responses to climate change predicted GA but not depression. Another interesting result is that both negative emotions and CCA exert a distinct and independent effect on predicting GA, demonstrating the importance of measuring both when examining the mental effects of climate change. In terms of impact on PEB, indifference was the most maladaptive emotional response, with higher levels of indifference predicting a decrease in both private-sphere and collective PEB. These findings are in line with previous research (Norgaard, 2006; Ojala, 2012a) and are understandable, as those who do not care about something clearly will not act on it. Furthermore, it is interesting to note that indifference exhibited negative correlations to almost all measures of climate change perceptions and environmental worldview. In other words, renouncing emotional responses to climate change (i.e., indifference) is related to ignoring its cognitive aspects by perceiving climate change as unreal/having no impact/being distant in space or time. Compared to other emotional responses to climate change, CCA was the only one associated both with impairment in mental health and with enhanced PEB., supporting the notion that CCA may be both adaptive and maladaptive response. Higher levels of CCA predicted higher levels of GA and greater engagement in collective PEB. The fact that CCA predicted collective but not individual pro-environmental behavior is interesting and extends previous research on the associations between CCA and different forms of PEB (Tam et al., 2023; Whitmarsh et al., 2022). One explanation of this difference may stem from the fact that climate change is a collective problem that must be addressed through collective action. Hence, high anxiety regarding climate change is more likely to motivate collective than individual actions. In addition, meeting with other people and acting together for a common cause may serve as a social-based coping strategy when seeking to overcome the distracting feelings that accompany CCA. These results may also be explained by the fact that engaging in collective action regarding climate change may attract more attention to its projected threatening consequences, thus enhancing CCA. More research is needed to explore this issue. Research Contribution Differentiating between CCA and negative emotions toward climate change. Until recently, research did not use a systematic measure of CCA and focused more generally on negative emotional responses to climate change (Schwartz et al., 2022). Since the CCAS was developed, more research attention has been directed to CCA. Within this emerging research field, relatively little attention has been given to how negative emotional responses to climate change resemble and are different from CCA in terms of their distribution, association with mental health, and environmental engagement. In addition, some studies have described CCA as an example of negative emotions (Martin et al., 2022), and others have used the two concepts interchangeably (e.g., Ogunbode et al., 2022; Sangervo et al., 2022). The current study highlights the differences between these two emotional responses to climate change, both in their prevalence and in their distinct ability to predict GA. In addition to feelings of distress, CCA involves impaired cognitive and behavioral functioning. Hence, it is important to understand the prevalence and predictors of CCA and its association with mental health on the one hand and with PEB on the other. Nevertheless, as the prevalence of severe CCA is very low relative to that of negative emotional responses to climate change, and as negative emotions distinctly predict GA, the results of this study highlight the importance of specifically targeting negative emotional responses to climate change, in addition to CCA. Positive emotions and indifference as coping strategies. In the face of external stressors such as climate change, developing personal resilience is vital (Author(s), 2021). Emotional resilience is an important part of adaptation to climate change for two reasons: First, effective emotional coping with a threatening reality can help enhance psychological well-being. Second, adaptive coping also entails becoming involved in PEB and performing actions that can help in mitigating and adapting to climate change. The current research contributes to the growing body of research on psychological resilience in the context of climate change by examining how different kinds of emotional regulation influence adaptive responses. In line with research on coping strategies (Fredrickson, 1998; Folkman & Moskowitz, 2000; Lazarus & Folkman, 1984), Ojala (2012) suggested that in the face of climate change, meaning-focused coping (a form of coping that focuses on positive emotions such as hope) is an adaptive method of coping with projected changes in the climate. Other researchers have further suggested that de-emphasizing the problem is maladaptive as in the long run this may be associated with higher levels of anxiety (Schäfer et al., 2017; Wullenkord et al., 2021). The present study echoes these findings and underscores the destructive nature of emotional indifference relative to the adaptive impact of positive emotions. Based on the current findings, future research explore ways by which educational and community interventions can foster positive emotional responses to climate change and reduce indifference. Links between CCA and other emotional responses to climate change. This study is one of the first to investigate the associations between different emotional responses to climate change and CCA, thus extending our understanding of the nature of CCA and its predictors. Findings reveal that increase in each of the three kinds of emotions – positive, negative, and indifference – predicted increase in the level of CCA. The prediction of negative emotions is understood, and in line with previous research (Tam et al., 2023; Whitmarsh et al., 2022). The prediction of positive emotions is in line with research that found that in some cases hope and worries related to climate change can appear together (Ojala 2012a; Sangervo et al., 2022). Research suggests that positive emotions are often part of the way individuals cope with stressful life events (Folkman, & Moskowitz, 2000). Accordingly, some people may simultaneously experience a high level of CCA and positive emotions. The findings on indifference are less intuitive. A possible explanation is that claiming indifference may merely mask a deeper sense of anxiety regarding this issue and constitute an ineffective attempt to avoid the anxiety the individual already feels. CCA was also predicted by gender (men experience higher levels of CCA than women), lower perception that climate change is real, and GA. The possibility that those prone to mental impairment may be more vulnerable to CCA has already been discussed here and elsewhere (Clayton & Karazsia, 2020). The finding that a lowered perception that climate change is real negatively predicts CCA is less intuitive. In line with the explanation on indifference, a possible explanation is that perceiving climate change as unreal reflects cognitive denial, which under some circumstances may lead to higher levels of anxiety. Extending the geographical distribution of research on CCA. Most previous research on CCA used US and European samples. The addition of an Israeli sample is beneficial since Israel is a "hot spot" that may be more affected by desertification, droughts and extreme more than other countries. Nevertheless, Israel is a developed country and thus does not represent non-Western nations that have the highest climate risk. The results show that projected vulnerability is not translated into CCA level. Quite the contrary: The level of CCA in this sample is lower than in most other samples. These findings support the notion that CCA is related to a complex set of determinants from the local and social context (Clayton & Karazsia, 2020). In Israel climate change is low on the government’s list of priorities, and national security issues are often prioritize. This may explain the low level of CCA found among the Israeli sample. Limitations The current study has several limitations that can also serve as guidelines for future studies. First, due to the correlational nature of the research, caution should be taken in drawing causal conclusions about the relations between research variables. Therefore, experimental or longitude research is needed to investigate the direction of the association between emotional responses to climate change and behavioral engagement and the association between emotions regarding climate change and CCA. Second, the indifference measure was based on a single item. The decision to use a single item was based on the factor analysis for the emotion scale, which distinguished indifference from the other variables, and on its conceptual meaning, which differed from that of positive emotions and negative emotions. Yet single-item scales cannot be assessed for reliability (Schultz et al., 2004). Furthermore, indifference may represent a defensive, self-protective strategy. Hence, measuring it as an explicit self-report measure may be prone to social desirability bias. Implicit methods should be used to address this challenge (Wullenkord & Reese, 2021). Third, the emotions scale used in this research was based solely on quantitative methodology. This method provides valuable information on the psychometric nature of the variables and facilitates statistical analysis. Nevertheless, it does not provide in-depth understanding of the qualitative nature of these emotional responses to climate change. Such information is important mainly in the case of positive emotions, which may not be a straightforward response to climate change. Qualitative methods such as open items on a survey or semi-structured interviews can provide more comprehensive information on the source of diverse emotions regarding climate change and how these emotions are translated (or not) into behavioral engagement. Finally, because the questionnaire was distributed in Hebrew, it represents the Israeli Jewish population but not the Arab population. In the future the CCAS and other psychological scales related to climate change should be translated into Arabic and distributed among the Arab population in Israel. Conclusion Emotional responses to climate change are related both to climate change mitigation behavior and to the promotion of resilience and well-being. In the context of PEB engagement, the results of this study show that positive emotions predict an increase in both private-sphere and collective PEB, indifference predicts a decrease in both, and CCA predicts an increase only in collective PEB. With respect to mental health, both CCA and negative emotions predict an increase in GA. In general, these findings offer insights into how different emotional responses to climate change are differentially associated with mental health and environmental engagement. Declarations Declaration of interest: none Declaration on ethics approval and consent to participate: The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki. The research received ethical approval from the University (Approval No. 362/22). Participants gave their informed consent before answering the survey Consent for publication Not relevant as the corresponding author is the only author Competing Interests The authors have no competing interests to declare that are relevant to the content of this article. Author contributions Not relevant as the corresponding author is the only author Funding The authors did not receive support from any organization for the submitted work Availability of data and materials Supporting data file is stored at: https://osf.io/cy7mj/?view_only=bdff857791364dc08c3c2a6d5ec897b1 References Author(s), (2021). Bamberg S., Rees, J. H., & Schulte, M. (2018). Environmental protection through societal change: What psychology knows about collective climate action—and what it needs to find out. In S. Clayton, & C. Manning (Eds.), Psychology and climate change, human perceptions, impacts and responses (pp. 185-213). 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Mean Median SD [95% confidence interval] Positive emotions 1-5 3 1.00 5.00 2.36 2.33 .96 [2.25,2.47] Negative emotions 1-5 9 1.00 5.00 2.74 .99 [2.63,2.86] Indifference 1-5 1 1.00 5.00 2.30 2.00 1.10 [2.18,2.43] Climate change anxiety 1-5 13 1.00 4.31 1.46 1.15 .70 [1.38,1.54] Generalized Anxiety 0-3 7 .00 3.00 .88 .86 .63 [.81,.95] Depression 0-3 7 .00 2.29 .90 .86 .55 [.84,.97] Real 1-5 3 1.00 5.00 4.29 4.67 .86 [4.19,4.39] Human 1-5 3 1.00 5.00 3.75 4.00 1.01 [3.63,3.86] Impact 1-5 3 1.00 5.00 3.91 4.00 1.03 [3.80,4.03] Space 1-5 3 1.00 5.00 3.72 4.00 1.00 [3.61,3.83] time 1-5 2 1.00 5.00 3.26 3.00 1.08 [3.10,3.35] Environmental worldview 1-5 15 1.67 5.00 3.36 3.27 .59 [3.29,3.42] Private-sphere behavior 0-100 9 .00 100.00 45.17 45.56 24.24 [42.43,47.92] Collective behavior 0-100 9 .00 77.78 11.60 5.00 16.38 [9.75,13.46] Table 2 Prevalence rates of climate anxiety and emotions toward climate change (N=302) Low (Percentage) Moderate (Percentage) High (Percentage) CCA 267 (88.4%) 26 (8.6%) 9 (3%) Negative emotions 105 (34.8%) 120 (39.7%) 77 (25.5%) Positive emotions 180 (59.6%) 82 (27.2%) 40 (13.2%) Indifference 179 (59.3%) 75 (24.8%) 48 (15.9%) Table 3 Correlations between research variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 Age 1 2 Gender -.07 1 3 Indifference -.25 *** -.090 1 4 Positive emotions .042 .000 .004 1 5 Negative emotions .035 .14 * -.07 .11 * 1 6 Generalized Anxiety -.15 ** .18 *** .17 *** .06 .34 *** 1 7 Depression -.09 .05 .15 ** .01 .19 *** .64 ** 1 8 Real -.02 .14 * -.11 -.21 *** .25 *** -.17 ** -.19 ** 1 9 Human .088 .065 -.21 *** -.06 .50 *** .05 -.04 .42 *** 1 10 Impact .13 * .10 -.20 *** -.080 .50 *** .05 -.06 .47 *** .70 *** 1 11 Space .013 .150 ** -.15 ** -.09 .39 *** -.037 -.048 .44 *** .57 *** .67 *** 1 12 Time .07 -.06 -.29 *** -.11 .21 *** -.05 -.03 .27 *** .23 *** .23 *** .24 *** 1 13 Environmental worldview .14 * .07 -.28 ** -.17 ** .53 *** .03 -.006 .46 *** .57 *** .58 *** .52 *** .41 *** 1 14 Climate change anxiety -.002 -.06 .18 ** .32 *** .44 *** .44 *** .32 *** -.25 *** .10 .07 .04 -.04 .01 1 15 Private-sphere behavior .22 *** .11 -.31 *** .12 * .28 *** -.06 -.06 .24 *** .35 *** .28 *** .22 *** .21 *** .36 *** .03 1 16 Collective behavior .028 .005 -.23 *** .20 *** .38 *** .16 ** .03 .10 .22 *** .21 *** .17 ** .24 *** .30 *** .35 *** .49 *** Note. * p < .05, ** p < .01, *** p < .001. Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance Table 4 Multiple regression models testing the predictors of generalized anxiety and depression, and the main effects of climate change anxiety. Generalized anxiety Model 95.0% Confidence Interval for B B SE B β t p sr2 Lower Bound Upper Bound 1 (Constant) 0.36 0.24 1.48 0.139 -0.118 0.839 Age 0.00 0.00 -0.104 -2.43 0.016 0.010 -0.007 -0.001 Gender 0.18 0.05 0.141 3.33 0.001 0.018 0.072 0.281 Positive emotions 0.00 0.03 -0.004 -0.10 0.922 0.000 -0.059 0.053 Negative emotions 0.17 0.03 0.266 4.89 0.000 0.039 0.101 0.237 Indifference 0.04 0.03 0.074 1.62 0.105 0.004 -0.009 0.093 Real -0.10 0.04 -0.134 -2.63 0.009 0.011 -0.170 -0.025 Human 0.02 0.04 0.026 0.42 0.672 0.000 -0.058 0.090 Impact 0.07 0.04 0.117 1.72 0.087 0.005 -0.010 0.152 Space -0.09 0.04 -0.145 -2.51 0.013 0.010 -0.163 -0.020 Time 0.00 0.03 -0.007 -0.15 0.877 0.000 -0.057 0.049 Environmental worldview -0.02 0.06 -0.022 -0.37 0.714 0.000 -0.151 0.104 Depression 0.62 0.05 0.542 12.50 0.000 0.256 0.524 0.720 R2adj = 0.51 2 (Constant) 0.23 0.24 0.95 0.344 0.000 -0.246 0.703 Age 0.00 0.00 -0.108 -2.57 0.011 0.010 -0.007 -0.001 Gender 0.20 0.05 0.158 3.78 0.000 0.023 0.095 0.301 Positive emotions -0.03 0.03 -0.042 -0.95 0.340 0.001 -0.084 0.029 Negative emotions 0.11 0.04 0.178 3.03 0.003 0.014 0.040 0.187 Indifference 0.03 0.03 0.044 0.98 0.327 0.002 -0.025 0.076 Real -0.06 0.04 -0.083 -1.61 0.109 0.004 -0.135 0.014 Human 0.01 0.04 0.018 0.29 0.768 0.000 -0.062 0.084 Impact 0.07 0.04 0.114 1.71 0.088 0.005 -0.010 0.149 Space -0.10 0.04 -0.155 -2.73 0.007 0.012 -0.168 -0.027 Time -0.01 0.03 -0.009 -0.21 0.837 0.000 -0.057 0.046 Environmental worldview -0.01 0.06 -0.005 -0.08 0.933 0.000 -0.131 0.120 Depression 0.59 0.05 0.511 11.76 0.000 0.218 0.488 0.685 CCA 0.17 0.05 0.186 3.53 0.000 0.020 0.074 0.259 R2adj = 0.53; R2 change=.020 p<.001 Depression Model 95.0% Confidence Interval for B B SE B β t p sr2 Lower Bound Upper Bound 1 (Constant) 0.57 0.23 2.49 0.013 0.120 1.024 Age 0.00 0.00 0.032 0.67 0.503 0.001 -0.002 0.004 Gender -0.06 0.05 -0.051 -1.10 0.273 0.002 -0.157 0.045 Positive emotions -0.03 0.03 -0.044 -0.93 0.351 0.002 -0.078 0.028 Negative emotions 0.01 0.03 0.013 0.22 0.828 0.000 -0.060 0.075 Indifference 0.02 0.03 0.039 0.78 0.438 0.001 -0.029 0.068 Real -0.05 0.04 -0.072 -1.29 0.199 0.003 -0.116 0.024 Human -0.02 0.04 -0.044 -0.67 0.505 0.001 -0.094 0.047 Impact -0.06 0.04 -0.108 -1.45 0.149 0.004 -0.134 0.021 Space 0.05 0.04 0.085 1.34 0.181 0.004 -0.022 0.116 Time 0.01 0.03 0.022 0.44 0.657 0.000 -0.039 0.062 Environmental worldview 0.03 0.06 0.036 0.54 0.590 0.001 -0.088 0.154 Generalized Anxiety 0.56 0.05 0.647 12.50 0.000 0.305 0.475 0.653 R2adj = 0.41 2 (Constant) 0.54 0.23 2.34 0.020 0.000 0.087 1.002 Age 0.00 0.00 0.029 0.62 0.535 0.001 -0.002 0.004 Gender -0.05 0.05 -0.045 -0.96 0.340 0.002 -0.152 0.053 Positive emotions -0.03 0.03 -0.054 -1.10 0.270 0.002 -0.086 0.024 Negative emotions -0.00 0.04 -0.007 -0.10 0.921 0.000 -0.076 0.069 Indifference 0.02 0.03 0.032 0.63 0.531 0.001 -0.034 0.065 Real -0.04 0.04 -0.060 -1.04 0.300 0.002 -0.111 0.034 Human -0.03 0.04 -0.046 -0.69 0.489 0.001 -0.095 0.046 Impact -0.06 0.04 -0.107 -1.44 0.152 0.004 -0.134 0.021 Space 0.05 0.04 0.081 1.27 0.206 0.003 -0.025 0.114 Time 0.01 0.03 0.022 0.43 0.667 0.000 -0.039 0.061 Environmental worldview 0.04 0.06 0.040 0.60 0.548 0.001 -0.084 0.159 Generalized Anxiety 0.55 0.05 0.635 11.76 0.000 0.271 0.461 0.646 Climate change anxiety 0.04 0.05 0.049 0.81 0.418 0.001 -0.054 0.130 R2adj = 0.41; R2 change=.001 p>.05 Note: Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance Table 5 : Multiple regression models testing the predictors of private-sphere and collective pro-environmental behavior and the main effects of climate change anxiety. Private-sphere pro-environmental behavior Model 95.0% Confidence Interval for B B SE B β t p sr2 Lower Bound Upper Bound 1 (Constant) -16.96 11.71 -1.45 0.149 -39.998 6.084 Age 0.20 0.08 0.14 2.50 0.013 0.016 0.043 0.360 Gender 4.16 2.59 0.09 1.61 0.109 0.007 -0.938 9.266 Indifference -3.46 1.25 -0.16 -2.77 0.006 0.020 -5.911 -1.000 Positive emotions 4.20 1.36 0.17 3.08 0.002 0.024 1.516 6.882 Negative emotions 1.93 1.73 0.08 1.12 0.266 0.003 -1.473 5.327 Generalized Anxiety -3.14 2.82 -0.08 -1.11 0.267 0.003 -8.700 2.417 Depression 1.32 2.97 0.03 0.45 0.656 0.001 -4.517 7.158 Real 2.80 1.80 0.10 1.56 0.120 0.006 -0.737 6.338 Human 4.96 1.81 0.21 2.74 0.006 0.019 1.399 8.516 Impact -1.17 1.99 -0.05 -0.59 0.558 0.001 -5.091 2.753 Space -1.52 1.77 -0.06 -0.86 0.390 0.002 -5.006 1.958 Time 1.09 1.29 0.05 0.84 0.399 0.002 -1.447 3.621 Environmental worldview 6.54 3.11 0.16 2.11 0.036 0.011 0.424 12.651 R2adj = 0.24 2 (Constant) -17.72 11.84 -1.50 0.136 0.000 -41.019 5.588 Age 0.20 0.08 0.13 2.47 0.014 0.016 0.040 0.358 Gender 4.35 2.63 0.09 1.66 0.099 0.007 -0.822 9.521 Indifference -3.55 1.27 -0.16 -2.80 0.005 0.020 -6.047 -1.058 Positive emotions 4.04 1.41 0.16 2.87 0.004 0.021 1.265 6.812 Negative emotions 1.61 1.86 0.07 0.86 0.388 0.002 -2.054 5.277 Generalized Anxiety -3.41 2.89 -0.09 -1.18 0.239 0.004 -9.095 2.275 Depression 1.26 2.97 0.03 0.42 0.673 0.001 -4.597 7.108 Real 3.01 1.86 0.11 1.62 0.106 0.007 -0.646 6.671 Human 4.93 1.81 0.21 2.72 0.007 0.019 1.364 8.495 Impact -1.16 2.00 -0.05 -0.58 0.561 0.001 -5.088 2.767 Space -1.59 1.78 -0.07 -0.89 0.372 0.002 -5.087 1.909 Time 1.08 1.29 0.05 0.84 0.404 0.002 -1.460 3.615 Environmental worldview 6.65 3.12 0.16 2.13 0.034 0.012 0.509 12.792 CCA 1.08 2.36 0.03 0.46 0.648 0.001 -3.573 5.734 R2adj = 0.24; R2 change=.001 p>.05 Collective pro-environmental behavior 95.0% Confidence Interval for B Model B SE B β t p sr2 Lower Bound Upper Bound 1 (Constant) -15.98 8.008 -1.995 0.047 -31.738 -0.215 Age -0.04 0.055 -0.041 -0.758 0.449 0.002 -0.150 0.067 Gender -2.42 1.773 -0.074 -1.366 0.173 0.005 -5.912 1.068 Positive emotions 3.39 0.932 0.198 3.639 0.000 0.034 1.558 5.228 Negative emotions 4.05 1.182 0.244 3.426 0.001 0.031 1.723 6.374 Indifference -2.64 0.853 -0.178 -3.097 0.002 0.025 -4.323 -0.963 Real 0.20 1.230 0.011 0.165 0.869 0.000 -2.217 2.623 Human -0.41 1.237 -0.025 -0.329 0.742 0.000 -2.841 2.027 Impact -0.64 1.363 -0.040 -0.470 0.639 0.001 -3.323 2.043 Space 0.37 1.210 0.022 0.303 0.762 0.000 -2.016 2.748 Time 1.68 0.881 0.111 1.905 0.058 0.010 -0.055 3.411 Environmental worldview 3.76 2.125 0.136 1.770 0.078 0.008 -0.420 7.944 Generalized Anxiety 4.30 1.932 0.165 2.227 0.027 0.013 0.500 8.104 Depression -2.74 2.029 -0.092 -1.351 0.178 0.005 -6.735 1.252 R2adj = 0.22 2 (Constant) -21.32 7.784 -2.739 0.007 0.000 -36.639 -5.998 Age -0.06 0.053 -0.056 -1.069 0.286 0.003 -0.161 0.048 Gender -1.12 1.727 -0.034 -0.646 0.519 0.001 -4.515 2.284 Positive emotions 2.26 0.927 0.132 2.443 0.015 0.014 0.440 4.087 Negative emotions 1.83 1.224 0.110 1.493 0.137 0.005 -0.582 4.238 Indifference -3.33 0.833 0.244 -3.992 0.000 0.038 -4.966 -1.686 Real 1.70 1.222 0.089 1.389 0.166 0.005 -0.708 4.103 Human -0.61 1.191 -0.038 -0.510 0.610 0.001 -2.952 1.736 Impact -0.58 1.312 -0.036 -0.440 0.660 0.001 -3.160 2.004 Space -0.09 1.168 -0.005 -0.076 0.940 0.000 -2.388 2.211 Time 1.61 0.848 0.106 1.902 0.058 0.009 -0.056 3.281 Environmental worldview 4.56 2.051 0.164 2.222 0.027 0.012 0.520 8.595 Generalized Anxiety 2.41 1.899 0.093 1.270 0.205 0.004 -1.325 6.149 Depression -3.20 1.955 -0.107 -1.636 0.103 0.006 -7.046 0.649 Climate change anxiety 7.61 1.554 0.325 4.893 0.000 0.058 4.547 10.666 R2adj = 0.28; R2 change=.006 p<.001 Note: Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance Table 6 Multiple regression showing the predictors of climate change anxiety. 95.0% Confidence Interval for B B SE B β t p sr2 Lower Bound Upper Bound (Constant) 0.70 0.29 2.40 0.027 0.127 1.277 Age 0.00 0.00 0.05 0.98 0.326 0.002 -0.002 0.006 Gender -0.17 0.07 -0.12 -2.66 0.008 0.013 -0.299 -0.044 Positive emotions 0.15 0.03 0.20 4.37 0.000 0.036 0.082 0.215 Negative emotions 0.29 0.04 0.41 6.77 0.000 0.087 0.207 0.377 Indifference 0.09 0.03 0.14 2.88 0.004 0.016 0.029 0.151 Generalized Anxiety 0.25 0.07 0.22 3.53 0.000 0.024 0.110 0.387 Depression 0.06 0.07 0.05 0.81 0.418 0.001 -0.086 0.206 Real -0.20 0.05 -0.24 -4.38 0.000 0.036 -0.285 -0.108 Human 0.03 0.05 0.04 0.59 0.559 0.001 -0.062 0.115 Impact -0.01 0.05 -0.01 -0.17 0.869 0.000 -0.106 0.090 Space 0.06 0.04 0.09 1.35 0.177 0.004 -0.027 0.147 Time 0.01 0.03 0.01 0.27 0.788 0.000 -0.055 0.072 Environmental worldview -0.11 0.08 -0.09 -1.35 0.178 0.003 -0.257 0.048 R2adj = 0.43 Note: Real= climate change is real; 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Today, climate change is no longer a distant and unimaginable threat, but rather a growing reality manifested in conditions such as rising average temperatures and growing storm intensity (Manning \u0026amp; Clayton, 2018; Tam et al., 2023). As climate change becomes a reality, people are becoming increasingly aware of the threats associated with global warming\u0026nbsp;(Hickman et al., 2021; Tam et al., 2023). Based upon its projected and ambiguous consequences, climate change\u0026nbsp;can be considered a stressful life event (Schwarzer \u0026amp; Luszczynska, 2012). Many people may even experience climate change as\u0026nbsp;an unremitting psychological stressor\u0026nbsp;associated with\u0026nbsp;high levels of concern, worry and anxiety, that can emerge even in the absence of short-term or direct effects (Clayton, 2020; Clayton \u0026amp; Karazsia, 2020; Hickman et al., 2021). Hence, the widespread\u0026nbsp;emotional and mental responses to climate change are not surprising (Bouman\u0026nbsp;et al., 2020; Tam et al., 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven that climate change is a source of stress, researchers have begun to examine how people cope with it and how their resilience can be enhanced (Doherty, 2018; Homburg et al., 2007). Because emotions are related both to mitigation behavior and to promoting resilience and well-being, studying people\u0026rsquo;s emotional responses to climate change is important (Brosch, 2021; Clayton \u0026amp; Karazsia, 2020; Doherty, 2018; Pihkala, 2022). Most research on emotional responses to climate change has focused on climate change anxiety (CCA), defined as an intense state of distress concerning climate change accompanied by impairment in cognitive and behavioral functioning (Clayton \u0026amp; Karazsia, 2020). One of the challenges in this line of research entails making a clear distinction between CCA and other emotional responses to climate change (Sangervo et al., 2022; Whitmarsh et al., 2022). Another challenge is to study the prevalence and structure of CCA in various societies worldwide (Tam et al., 2023). The current study aims to address these objectives. It was conducted with an Israeli sample and focuses on CCA along with three other emotional responses to climate change: positive emotions, negative emotions, and indifference. By studying how these are linked to mental health and to engagement in pro-environmental behavior (PEB), the study seeks to enhance our understanding of the nature of CCA and to clarify how it differs from other emotional responses to climate change.\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDifferent Kinds of Emotional Responses to Climate Change\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmotions are defined as changes in organic subsystems in response to an external or internal stimulus appraised as relevant to the individual (Brosch, 2021; Scherer, 2005). Emotional responses to climate change\u0026nbsp;are defined as affective phenomena associated with the climate crisis (Pihkala, 2022). When faced with stressful events, individuals are expected to experience multiple and even conflicting emotions (Folkman \u0026amp; Lazarus, 1988). It is therefore not surprising that emotional responses to climate change are many and varied, ranging from negative feelings such as despair, anger, and shame to positive feelings such as hope and pride (Hickman et al., 2021; Pihkala, 2022;\u0026nbsp;Stanley et al., 2021). The emotional responses discussed in this paper comprise four groups of emotions: positive emotions, negative emotions, indifference, and CCA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePositive emotions and negative emotions\u003c/strong\u003e. Empirical research has consistently found that positive emotions and negative emotions are two distinct dimensions, usually described as positive affect and negative affect (Feldman, 2006; Watson et al.,\u0026nbsp;1988).\u0026nbsp;Positive affect is marked by a state of high energy, full concentration, and pleasurable engagement that reflects the extent to which the individual feels enthusiastic and active. Negative affect, in contrast, is a general dimension of subjective distress and unpleasant engagement that includes aversive mood states such as anger, fear, and nervousness (Watson et al., 1988). The literature on stress and coping points to several important distinctions between these two emotional dimensions that have important implications for coping processes. Prolonged negative affect may lead to clinical depression and anxiety disorders. Positive affect, in contrast, triggers an upward spiral toward emotional well-being, broadening the individual's attentional focus and behavioral repertoire and building social, intellectual, and physical resources required to facilitate adaptation (Fredrickson, 1998; Fredrickson \u0026amp; Joiner, 2002). Positive emotions are therefore considered to be an important aspect of coping with stressful life events and enhanced mental health (Folkman \u0026amp; Moskowitz, 2000). Awareness of the projected consequences of climate change can be associated with various negative feelings, such as grief associated with changes in nature, feeling threatened by the potential loss of security, or losing confidence in the natural world (Clayton \u0026amp; Karazsia, 2020). In measuring emotional responses to climate change, some studies focus on specific emotions, claiming that these have a differential impact on climate action and mental health (e.g., Stanley et al., 2021). Yet, based on the research on emotions described above, it is advocated to examine the structure of climate emotions and group them by meaningful measures (Pihkala, 2022; Tam et al.,2023). Initially, most research on climate change emotions focused on negative emotions (Brosch, 2021; Bamberg et al., 2018). In recent years more research attention has been directed toward positive emotions as well (Ojala, 2023; Pihkala, 2022; Schneider\u0026nbsp;et al., 2022). Ojala for example, conducted a series of studies on hope in the context of climate change, stressing the ability of hope to enhance adaptive coping associated both with climate action and with well-being (Ojala, 2012a,2012b,2023). Ojala (2012a) claimed that because negative emotions are a realistic response to climate change, it is important to find effective ways of handling such feelings. This approach is in line with research on the role of positive affect in coping with stressful events described above. Similarly, Sangervo et al. (2022) contend that climate hope and efficacy should be measured since they may moderate the effect of CCA on behavior (Sangervo et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndifference.\u003c/strong\u003e Feeling indifferent about climate change is tantamount to being bored with this topic and perceiving it as unimportant (Marczak et al., 2022). Indifference is considered to be the emotional component of denial: It is a defensive, self-protective strategy that serves to suppress or avoid uncomfortable emotions and distress. Indifference is sometimes defined as implicatory denial of climate change (recognition of climate change as a problem but denial of its psychological, political, and moral implications)\u0026nbsp;(Wullenkord et al., 2021; Wullenkord \u0026amp; Reese, 2021). The assumption is that indifference is part of emotion management and is motivated by a desire to avoid unpleasant emotions such as helplessness and guilt (Nogaard, 2006). It also can be seen as an aspect of emotion-focused coping strategy, which is aimed at reducing aversive feelings emerging in the face of stressful events through processes of denial, avoidance, and distancing (Lazarus \u0026amp; Folkman, 1984).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCCA\u003c/strong\u003e. People’s feelings regarding climate change may vary in intensity (Clayton \u0026amp; Karazsia, 2020; Pihkala, 2021). CCA is characterized by an intense and cognitive-emotional response to climate change that includes anxiety, worried thoughts, and concerns about physiological changes brought on by the climate crisis\u0026nbsp;(Sangervo\u0026nbsp;et al.,\u0026nbsp;2022). CCA is differentiated from climate worry based on its intensity and its potential to affect daily life: Whereas concerns about climate change are a common and natural response to current threatening projections, CCA is characterized by an intense emotional reaction that may interfere with daily cognitive and behavioral functioning (Clayton \u0026amp; Karazsia, 2020). CCA has both mild and more severe manifestations (Sangervo\u0026nbsp;et al.,\u0026nbsp;2022). Although CCA is associated with impairment in mental health, it is still considered to be a rational response to climate crises and not a pathological psychological condition (Clayton \u0026amp; Karazsia, 2020; Hickman et al., 2021; Sangervo et al., 2022). Nevertheless, due to CCA’s potential impact on mental health, it is important to investigate its prevalence, its predictors, and the ways it is associated with adaptive and maladaptive functioning (Clayton \u0026amp; Karazsia, 2020; Whitemarsh, et al., 2022). Until recently there was very little conceptual clarity regarding the concept of CCA that had the power to leverage rigorous research. Clayton and Karazsia (2020) recently developed a valid scale for measuring CCA known as the Climate Change Anxiety Scale (CCAS). This scale has been validated and tested among several samples in the US (Clayton \u0026amp; Karazsia, 2020; Tam et al., 2023), Europe (Mouguiama - Daouda et al., 2021; Whitmarsh et al., 2022; Wullenkord et al., 2021), and Asia (Simon et al., 2022; Tam et al., 2023). Yet, more research is needed to investigate the worldwide prevalence of CCA, and specifically to examine societies that are more likely to be affected by climate change (Tam et al., 2023).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eWhat is the Prevalence of Different Emotional Responses to Climate Change?\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWorries and concerns about climate are quite prevalent. In an international study that investigated the reported experience of 14 distinct emotions among young people, more than 50% of respondents reported\u0026nbsp;negative emotions such as sadness, and anger (Hickman et al., 2021). In a UK study, over 40% of participants reported being worried about climate change (Whitmarsh et al., 2022). Yet, despite the high prevalence of negative emotional responses to climate change, reported levels of CCA are low. Most studies that used the validated CCAS instrument found that the average level of CCA was below the scale’s midpoint (e.g., Simon et al., 2022; Tam et al., 2023; Wullenkord et al., 2021).\u003c/p\u003e\n\u003cp\u003eWhile research on the prevalence of negative emotions and CCA is relatively adequate, the prevalence of positive emotions has not received sufficient research attention. As noted above, Ojala (2012a, 2012b, 2023) examined the positive emotion of hope, though information on its prevalence is limited. The few studies reporting on the distribution of positive emotions show prevalence rates ranging from 30% to 46% (Hickman et al, 2021; Smit \u0026amp; Leiserowitz, 2014). Information on the prevalence of indifference is also limited. Hickman et al. (2021) found that 29% of participants reported feeling indifferent.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eHow are Different Emotional Responses to Climate Change Associated with Mental Impairment and PEB?\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePositive emotions\u003c/strong\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eAs noted above, positive emotions are associated with mental health and are considered important in coping with stressful life events (Fredrickson, 1998; Fredrickson \u0026amp; Joiner, 2002; Folkman \u0026amp; Moskowitz, 2000). In line with the assertion that “feeling good about doing the ‘right thing’ can be an important motivator for behavior change” (Smith \u0026amp; Leiserowitz, 2014), positive emotions were found to be associated with several pro-environmental behaviors (refer to Schneider et al, 2021 for a review). Nevertheless, very little research has investigated the role of positive emotional responses to climate change in promoting mental health and PEB, and most studies in this area focused on one emotion: hope. Findings on the correlations between hope and climate engagement are not consistent (Ojala, 2023). This result can be partly explained by the fact that in some cases hope is unrealistic and related to denial instead of agency. The association between hope and climate engagement is therefore dependent on the sources of hope (Ojala, 2012b, 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNegative emotions.\u003c/strong\u003e Negative emotions were found to be associated with both impairments in well-being and climate action\u0026nbsp;(Brosch, 2021).\u0026nbsp;The motivational engine of negative emotions appears to be driven by undesirable emotional states, which people seek to reduce through action (van Valkengoed, \u0026amp; Steg, 2019). Nevertheless, prolonged negative affect may be harmful to mental health (Gross \u0026amp; Muñoz, 1995). Some empirical results point to such associations in the context of climate change as well. For example, Whitmarsh et al. (2022) found a significant correlation between climate concerns and generalized anxiety, Stanley et al. (2021) found positive associations between eco-anxiety and eco-depression measures and impaired mental health, and Searl and Gow (2010) found a relationship between climate concerns and symptoms of depression, anxiety, and stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndifference.\u003c/strong\u003e As indicated, indifference can serve as part of an emotion-focused coping strategy individuals use to reduce negative feelings when faced with a stressful situation (Lazarus \u0026amp; Folkman, 1984). Researchers have suggested that although such strategies may help mitigate anxiety in the short term, they may be associated with higher levels of anxiety in the long run (Schäfer\u0026nbsp;et al., 2017;\u0026nbsp;Wullenkord et al., 2021).\u0026nbsp;Furthermore, research on coping strategies found that emotion-focused coping is used more by individuals with depression and is associated with high levels of distress\u0026nbsp;(Leandro \u0026amp; Castillo, 2010; Rice et al., 2020). Regarding the link between indifference and PEB, Norgaard (2006) found that although people accept the existence of climate change, their indifferent emotional response often stops them from acting. Similarly, Ojala (2012a) found that the use of de-emphasizing strategy toward climate change is associated with low behavioral engagement. Wullenkord and Reese (2021) also found an association between various forms of denial (cognitive and emotional) and PEB.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCCA\u003c/strong\u003e. Research on CCA points to links to generalized anxiety (GA) and depression (Clayton \u0026amp; Karazsia, 2020; Whitemarsh et al., 2022; Wullenkord et al., 2021). Yet because CCA is measured along a continuum, only higher levels have the potential to affect mental health (Clayton et al., 2023). Based on these findings, some researchers suggested that individuals with existing mental health disorders may be vulnerable to higher levels of CCA (Clayton \u0026amp; Karazsia, 2020; Whitemarsh et al., 2022). Dew to the projected impacts of climate change the prevalence of climate change is likely to grow. Hence, it is important to study its predictors and consequences (Clayton \u0026amp; Karazsia, 2020; Tam et al., 2023). Moreover, most studies found positive statistical correlations between CCA and PEB engagement (Mouguiama – Daouda et al., 2022; Tam et al., 2023; Sangervo et al., 2022; Wullenkord et al., 2021), though other studies did not find such an association (Clayton \u0026amp; Karazsia, 2020). In addition, some variability exists in the extent to which CCA explains different kinds of PEB (Tam et al., 2023; Whitemarsh et al., 2022). Bamberg et al. (2018) recently suggested that due to the collective nature of the human impact on climate change, environmental psychology research should pay more attention to collective rather than private-sphere climate action (Bamberg et al., 2018). In the case of research on CCA, most studies do not distinguish between private-sphere and collective behavior. Such a distinction may lead to a better understanding of the links between CCA and PEB. One relevant study found that while CCA predicted both types of action, its prediction of collective PEB tended to be greater (Tam et al., 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHow do Different Emotions Toward Climate Change Predict CCA?\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince the introduction of the CCAS scale, an increasing number of studies have investigated the prevalence of CCA, its association with demographic variables such as age, and gender, mental health, and PEB (e.g., Clayton \u0026amp; Karazsia, 2020; Tam et al., 2023; Whitmarsh et al., 2022, Wullenkord et al., 2021). Some studies have investigated the association between emotional responses to climate change and CCA as distinct variables (Clayton \u0026amp; Karazsia, 2020; Tam et al., 2023; Whitmarsh et al., 2022), whereas other scholars have suggest\u0026nbsp;coalescing these two variables and focusing only on CCA (e.g., Ogunbode et al., 2022). Moreover, research on how positive emotional responses to climate change and indifference are associated with CCA is very limited. The only study that was found that addresses such association focused on hope (Sangervo, 2022). This study found positive association between hope and CCA, which was explain by the fact that both are reactions to uncertainty. Overall, information on this topic is very limited, and more research is needed to clarify the associations between CCA and other emotional responses to climate change.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThe Present Study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study contributes to previous research by investigating how various emotional responses to climate change are associated with mental health and PEB, and how do negative emotions toward climate change eare distinguished from CCA. The study was conducted in October 2022 in Israel. Although Israel is a developed country, it is considered at high risk for climate change effects. The rate of global warming in Israel is almost two times greater than the global rate. Moreover, Israel is vulnerable to climate change risks such as intense heat waves and increased desertification (Israel Meteorological Service, 2021). Nevertheless, the state of Israel has yet to make the necessary perceptual shift (State Comptroller and Ombudsman of Israel, 2021), and a recent report of OECD has stated that Israel is not on track to reach its climate change targets (OECD, 2023). Furthermore, a 2016 survey found that relative to the citizens of most European nations, Israelis were rather skeptical about or unaware of climate change, exhibiting the lowest average rate of concern about climate change of all 24 countries surveyed (Poortinga et al., 2019).\u0026nbsp;Considering the projected consequences of climate change in Israel, more in-depth investigation is needed to explore perceptions, emotional responses, and behavioral responses to climate change in this country. The study’s objectives are threefold: (a) to clarify similarities and differences between CCA and other emotional responses to climate change in predicting mental health impairment and PEB engagement; (b) to explore how different emotional responses to climate change are related to CCA; and (c) to explore the prevalence of CCA and other emotional responses to climate change in Israel.\u003c/p\u003e\n\u003cp\u003eBased on the theoretical background, the study investigated the following hypotheses:\u003c/p\u003e\n\u003cp\u003eH1. Impaired mental health will be positively related to (a) negative emotions, (b) feelings of indifference, and (c) CCA, and will be negatively related to (d) positive emotions.\u003c/p\u003e\n\u003cp\u003eH2. Engagement in PEB will be positively related to (a) negative emotions, (b) positive emotions, and (c) CCA, and will be negatively related to (d) indifference.\u003c/p\u003e\n\u003cp\u003eMoreover, very little data is available on the role the three types of emotions toward climate change in explaining CCA. Hence, this investigation is exploratory, and no hypotheses are posited.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAn online survey was conducted via an online participant panel (Sekernet) among a representative sample of the Hebrew-speaking public in Israel. The survey received ethical approval from the University (Approval No. 362/22). Participants gave their informed consent before answering the survey. The survey included measures of CCA, emotions toward climate change, mental health (GA and depression), and PEB (private-sphere and collective). Because emotional responses to climate change may be complex and are related to cognitive appraisal (Chapman et al., 2017), the study also included two measures of cognitive and affective environmental responses: a climate change perceptions scale developed by\u0026nbsp;van Valkengoed\u0026nbsp;et al. (2021) and the NEP scale, which measures general environmental worldview (Dunlap et al., 2000).\u0026nbsp;Survey measures and items were translated from English into Hebrew by two independent translators and then reviewed by the main author.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe sample was broadly representative of the Jewish population in terms of gender, age, and religiosity. In total, 302 respondents participated, of whom 151 (50%) were female. The mean age was 42.59 (median 42.00, SD 16.20, range: 18-86), and 43.7% of the participants held academic degrees (for more information refer to Tables S1a-S1c in the supplementary materials).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eMeasures\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eIf not otherwise indicated, participants responded to all measures on 5-point Likert scales ranging from 1 (strongly disagree/not at all) to 5 (strongly agree/applies completely). Table 1 summarizes the items and their psychometric properties.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmotions toward climate change.\u0026nbsp;\u003c/strong\u003eRespondents were asked to indicate the extent to which they felt each of thirteen emotions associated with climate change. The items were based on previous research on emotions toward climate change (Clayton \u0026amp; Karazsia, 2020; Hickman et al., 2021; Marczak et al., 2022). An exploratory factor analysis was performed to explore whether individual emotions could be clustered into different interpretable subscales. The items were distributed over three factors (Eigenvalues = 1.25-5.9, 71% cumulative explained variance) in accordance with the theoretical concepts of negative emotions (nine items,\u0026nbsp;\u0026alpha;=.93), positive emotions (three items,\u0026nbsp;\u0026alpha;=.77), and indifference (one item).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCCA\u0026nbsp;\u003c/em\u003ewas measured using the Climate Change Anxiety Scale (CCAS) (Clayton \u0026amp; Karazsia, 2020). As previous research yielded mixed results on the scale factor structure (Tam et al., 2023), principal component analysis was conducted on the 13 items.\u0026nbsp;The Kaiser\u0026ndash;Meyer\u0026ndash;Olkin measure verified the sampling adequacy for the analysis (KMO = 0.95).\u0026nbsp;Only one factor had an eigenvalue above the Kaiser criterion of 1 and explained 71.12% of the variance. As a result, it was decided to use a single score for CCA (\u0026alpha;=.97).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMental health measures.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eMental health was measured using the Hebrew version (Miller) of the HADS scale (Zigmond \u0026amp; Snaith, 1983). Participants were asked to indicate the extent to which they agree with 14 statements concerning their emotional and mental state on a four-point scale (3= very much; 0=not at all). The scale provides two measures of mental health, each comprising seven items: GA (\u0026alpha;= .88), and depression (\u0026alpha;=.77).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental worldview.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eEnvironmental worldview was measured using the New Ecological Paradigm scale (NEP). This scale consists of 15 items representing beliefs related to human domination over nature. Seven of the items were reversed (Dunlap et al., 2000). Cronbach\u0026apos;s alpha of the scale was 0.82.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClimate change perceptions.\u003c/strong\u003e The climate change perceptions scale (van Valkengoed et al., 2021) was used to measure perceptions regarding climate change. The scale consists of 14 items grouped into five sub-scales: climate change is real; is caused by humans; negative consequences; spatial distance; and temporal distance. Because this is the first time this scale was used with an Israeli sample, an exploratory factor analysis was conducted to investigate its local factor structure. The analysis yielded a four-factor structure, as \u0026apos;human caused\u0026apos;, and \u0026apos;negative consequences\u0026apos; were collapsed into a single factor. Yet because of the distinct meanings of the different subscales and to adhere to previous research, it was decided to use the original structure of five sub-scales. Cronbach\u0026apos;s alphas for the five sub-scales were .77, .96, .94, .96, and .86, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePEB.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eMeasures of private-sphere and collective PEB were based on the scale developed by Stanley et al. (2021). The original scale included 16 items\u0026mdash;eight in each sub-scale. In the current research two locally relevant items were added, one for each sub-scale. Participants were asked to indicate how often\u0026nbsp;they had engaged in different forms of PEB during the past year, on a scale ranging from 0 (never) to 100 (at every opportunity)\u0026nbsp;(Table S2, S3 in the supplementary materials).\u0026nbsp;Cronbach\u0026apos;s alpha for the scales is .88 for private-private sphere, and .87 for collective PEB. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic data.\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eDemographic data included age, gender, education, level of religiosity, and income.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eData analyses were conducted using SPSS version 27. For prevalence analysis, the means, and standard deviations of the emotional responses to climate change were collected, and the prevalence of different levels of each variable was analyzed. Correlational analysis was used to explore the correlations between the research variables. Then, a series of multivariable linear regression analyses were run to examine emotional responses to climate change as predictors of impairment in mental health and of PEB. Age, gender, climate change perceptions, and environmental worldview served as control variables. To explore the unique contribution of CCA in explaining impairment in mental health and PEB, the regressions were each run in two models, one excluding CCA and the other including it.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003ePower Analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eAnalyzing the data by multiple regression models was expected to yield a squared multiple correlation of 0.2 at least (R\u003csup\u003e2\u003c/sup\u003e\u0026gt;0.2), corresponding to the Cohen\u0026apos;s \u003cem\u003ef\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e effect size of 0.25. For significant results with a maximum of 14 predictors at a 5% significance level and 95% power, a sample size of 122 is needed. The power analysis was conducted using G*Power version 3.1.9.4 (freeware) (Faul, 2007).\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cem\u003ePrevalence Rates of Research Variables\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eAs shown in Table 1, the mean level of the CCA measure was relatively low: 1.46 within a 1-5 range. Within the three groups of emotions toward climate change, negative emotions exhibited the highest average (2.74 within a range between 1-5), followed by positive emotions (2.36) and indifference (2.30). In an effort to obtain further insights on the prevalence of the emotional responses to climate change and to be able to compare these results to other samples (e.g., Whitmarsh et al., 2022), the prevalence of these variables was\u0026nbsp;determined by categorizing responses into ‘low’ (1.00 ≤ \u003cem\u003eM\u0026nbsp;\u003c/em\u003e≥ 2.33), ‘moderate’ (2.34 ≤ \u003cem\u003eM\u0026nbsp;\u003c/em\u003e≥ 3.66), and ‘high’ (3.67 ≤ \u003cem\u003eM\u0026nbsp;\u003c/em\u003e≥ 5.00) (Table 2). The prevalence of negative emotions was moderate or high for most participants (39.7% and 25.5% respectively), whereas the level of CCA was low for most participants (88.4%), and high only for 3% of the participants. Positive emotions and indifference exhibited a similar prevalence: about 40%.\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt; Table 1\u0026gt;\u0026gt;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt; Table 2\u0026gt;\u0026gt;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eCorrelational Analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 3 shows the correlations between the research variables. The two measures of impairment in mental health (GA and depression) correlated positively with negative emotions, indifference, and CCA. No significant correlation was found between impairment in mental health and positive emotions. Moreover, no significant correlations were found between environmental affective variables and measures of mental health, except for a negative correlation with the perception that climate change is real, which was negatively associated with both measures of impairment in mental health. In addition, age exhibited a negative correlation with GA, whereas gender showed a positive correlation, such that women are more prone to GA than men. Both types of PEB were positively associated with both negative emotions and positive emotions and negatively associated with indifference. CCA was positively associated with collective PEB, but not with private-sphere PEB.\u003c/p\u003e\n\u003cp\u003eOf the control variables, all five forms of perceptions regarding climate change as well as environmental worldview exhibited positive correlations with both private-sphere and collective PEB, except for the perception that climate change is real, which was positively correlated only with private-sphere behavior. Moreover, all three kinds of climate change emotions were positively correlated with CCA, as were the two measures of impairment in mental health. CCA was also negatively correlated with the perception that climate change is real. The variables of age, gender, and environmental worldview exhibited no significant correlations with CCA.\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt;Table 3\u0026gt;\u0026gt;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eRegression Analyses: Predicting Impairment in Mental Health\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 4 shows the multiple regression analyses for GA and depression. The GA model that included CCA explained 53% of the variance [F\u003csub\u003e(13,288)\u003c/sub\u003e=26.7, \u003cem\u003ep\u003c/em\u003e\u0026lt;.001], and the model of depression that included CCA explained 41% % of the variance [F\u003csub\u003e(13,288)\u003c/sub\u003e=17.2, \u003cem\u003ep\u003c/em\u003e\u0026lt;.001]. As shown in Table 4, higher levels of negative\u0026nbsp;emotions (\u003cem\u003eβ=.\u003c/em\u003e18,\u003cem\u003e\u0026nbsp;p\u0026lt;.01\u003c/em\u003e) and of CCA (\u003cem\u003eβ=.\u003c/em\u003e19,\u003cem\u003e\u0026nbsp;p\u0026lt;.001\u003c/em\u003e) predicted higher levels of GA, thus corroborating H1a and H1c. Heightened GA was also predicted by depression (\u003cem\u003eβ=.\u003c/em\u003e51,\u003cem\u003e\u0026nbsp;p\u0026lt;.001\u003c/em\u003e) and by reduced perception of\u0026nbsp;spatial distance\u0026nbsp;(\u003cem\u003eβ=-.\u003c/em\u003e16,\u003cem\u003e\u0026nbsp;p\u0026lt;.01\u003c/em\u003e). As indicated in the Table, the only variable that significantly predicted depression was GA (\u003cem\u003eβ=.64\u003c/em\u003e,\u003cem\u003e\u0026nbsp;p\u0026lt;.001\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePositive emotions and indifference did not significantly predict GA or depression, refuting H1b and H1d.\u003c/p\u003e\n\u003cp\u003eWith respect to CCA’s unique contribution, inclusion of CCA in the GA regression model resulted in a significant change in the explained variance, from 51% to 53% (R2 change=.02 p\u0026lt;.001). In the depression regression model, CCA does not yield any change in the model’s explained variance (R2 change=.001 \u003cem\u003ep\u003c/em\u003e\u0026gt;.05).\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt;Table 4\u0026gt;\u0026gt;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eRegression Analysis: Predicting Private-Sphere and Collective PEB\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 5 depicts the multiple regression analyses for private-sphere and collective PEB. The model of private-sphere PEB that included CCA explained 24% of the variance [F\u003csub\u003e(14,287)\u003c/sub\u003e=7.59, \u003cem\u003ep\u003c/em\u003e\u0026lt;.001], and the model of collective PEB that included CCA explained 28% of the variance [F \u003csub\u003e(14,287)\u003c/sub\u003e =9.19, \u003cem\u003ep\u003c/em\u003e\u0026lt;.001].\u003c/p\u003e\n\u003cp\u003eTable 5 indicates that higher levels of positive emotions increase private-sphere (\u003cem\u003eβ=.\u003c/em\u003e16,\u003cem\u003e\u0026nbsp;p\u0026lt;.01\u003c/em\u003e) as well as collective PEB (\u003cem\u003eβ=.\u003c/em\u003e132, \u003cem\u003ep\u0026lt;.05\u003c/em\u003e), corroborating H2b. Moreover, higher indifference decreased both private-sphere \u003cem\u003e(β=-.\u003c/em\u003e16\u003cem\u003e, p\u0026lt;.01\u003c/em\u003e) and collective PEB (\u003cem\u003eβ=.\u003c/em\u003e22,\u003cem\u003e\u0026nbsp;p\u0026lt;.001\u003c/em\u003e), corroborating H2d. In contrast, negative emotional responses to climate change did not predict private sphere, nor collective PEB, refuting H2a. Further, CCA did not predict private-sphere PEB but it did predict collective PEB (\u003cem\u003eβ=\u003c/em\u003e0.32, \u003cem\u003ep\u0026lt;.001\u003c/em\u003e). Hence, H2c was corroborated only in reference to collective PEB. It is interesting to note that when CCA is excluded from the regression model, negative emotions predict collective PEB (\u003cem\u003eβ=\u003c/em\u003e0.24, \u003cem\u003ep\u0026lt;.001\u003c/em\u003e), but this effect disappears when CCA is included (\u003cem\u003eβ=\u003c/em\u003e0.11. \u003cem\u003ep\u003c/em\u003e\u0026gt;.05).\u003c/p\u003e\n\u003cp\u003eOf the control variables, increased private-sphere PEB was predicted by age (\u003cem\u003eβ\u003c/em\u003e=.13\u003cem\u003e, p\u0026lt;.05\u003c/em\u003e), perceived human caused (\u003cem\u003eβ\u003c/em\u003e=.2\u003cem\u003e, p\u0026lt;.01\u003c/em\u003e), and environmental worldview (\u003cem\u003eβ=.\u003c/em\u003e16\u003cem\u003e, p\u0026lt;.05\u003c/em\u003e), and increased collective PEB was predicted by environmental worldview (\u003cem\u003eβ=.\u003c/em\u003e16\u003cem\u003e, p\u0026lt;.05\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eExamination of CCA’s unique contribution to the regression models showed that in the case of private-sphere PEB CCA does not produce any change in the model’s explained variance (R2 change=.001 \u003cem\u003ep\u003c/em\u003e\u0026gt;.05). In the regression model for collective PEB, the variance exhibits a significant rise, from 22% to 28% (R2 change=.006 \u003cem\u003ep\u0026lt;\u003c/em\u003e.001).\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt;Table 5\u0026gt;\u0026gt;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eRegression Analysis: Predicting CCA\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTable 6 shows the multiple regression model for CCA, which explains 43% of the variance in CCA [F \u003csub\u003e(13,288)\u003c/sub\u003e =18.537, \u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e.001]. Participants who reported higher negative emotions (\u003cem\u003eβ=.41, p\u0026lt;.001\u003c/em\u003e), higher positive emotions (\u003cem\u003eβ=.20, p\u0026lt;.001\u003c/em\u003e), and more indifference (\u003cem\u003eβ=.14, p\u0026lt;.01\u003c/em\u003e) also reported higher CCA.\u003c/p\u003e\n\u003cp\u003eWith respect to the control variables, higher levels of CCA were predicted by higher GA (\u003cem\u003eβ=.22, p\u0026lt;.001\u003c/em\u003e), lower perceptions that climate change is real (\u003cem\u003eβ=-.24, p\u0026lt;.001\u003c/em\u003e), and gender (being a man was associated with higher CCA) (\u003cem\u003eβ=-.12, p\u0026lt;.01\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026lt;Table 6\u0026gt;\u0026gt;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA growing body of literature has explored the nature of CCA and its relationship with mental health and environmental engagement (e.g. Clayton \u0026amp; Karazsia, 2020; Whitmarsh et al., 2022). Nevertheless, the similarities and differences between CCA and other emotional responses to climate change are less clear, particularly in terms of associations with mental health and environmental engagement. Emotional responses to climate are associated both with impairments in mental well-being and with adaptive engagement in PEB. Hence, research on the psychological aspects of climate change mitigation and adaptation must consider the interplay of these emotions.\u0026nbsp;This study contributes to previous research by focusing on CCA along with three other emotional responses to climate change, and studying their associations with two measures of mental health and two measures of PEB. In addition, the study validates the Hebrew version of the CCAS in an Israeli sample and contributes to research on CCA prevalence and its determinants in different samples worldwide.\u003c/p\u003e\n\u003cp\u003eDifferent emotional responses exhibit different relationships with mental well-being and behavioral engagement. Each of the four emotional responses to climate change investigated in this research exhibited a different pattern of association with mental health and PEB measures. Positive emotional responses to climate change were the most adaptive as they were among the leading predictors of both private-sphere and collective PEB. These findings are in line with previous research (Ojala, 2012a; Sangervo et al., 2022; Schneider et al., 2021; Venhoeven et al., 2020) and extend our understanding of the importance of positive emotions when coping with climate change. Because this was a correlational study, the source of this association may come from two directions: On the one hand, acting in a pro-environmental manner and engaging in climate action may lead to feelings of competence and enhance positive emotions (Ojala, 2023; Venhoeven et al., 2020). In addition, experiencing positive emotions such as hope and empowerment may serve as a motivational force for engaging in climate action (Bury et al., 2020; Ojala 2023). Contrary to expectations, positive emotions did not predict enhancement of mental health. Yet because positive emotions were found to be related to behavioral engagement, the findings are in line with the notion that positive emotions can trigger an upward spiral toward emotional well-being by broadening the individual\u0026apos;s attentional focus and behavioral repertoire (Fredrickson, 1998). Moreover, although negative emotions regarding climate change did exhibit significant correlations with PEB, when controlled by other variables the prediction was no longer significant. With respect to mental health, an increase in negative emotions predicts an increase in GA. A large body of research has already discussed the possible impact on mental health of prolonged negative emotions when coping with stressors (Gross \u0026amp; Mu\u0026ntilde;oz, 1995). The current results contribute to existing research by highlighting the impact of negative emotions on mental health in the specific context of coping with climate change.\u003c/p\u003e\n\u003cp\u003eAn interesting result of the present research is that negative emotional responses to climate change predicted GA but not depression. Another interesting result is that both negative emotions and CCA exert a distinct and independent effect on predicting GA, demonstrating the importance of measuring both when examining the mental effects of climate change. In terms of impact on PEB, indifference was the most maladaptive emotional response, with higher levels of indifference predicting a decrease in both private-sphere and collective PEB. These findings are in line with previous research (Norgaard, 2006; Ojala, 2012a) and are understandable, as those who do not care about something \u0026nbsp;clearly will not act on it. Furthermore, it is interesting to note that indifference\u0026nbsp;exhibited negative correlations to almost all measures of climate change perceptions and environmental worldview. In other words, renouncing emotional responses to climate change (i.e., indifference) is related to ignoring its cognitive aspects by perceiving climate change as unreal/having no impact/being distant in space or time. Compared to other emotional responses to climate change, CCA was the only one associated both with impairment in mental health and with enhanced PEB., supporting the notion that CCA may be both adaptive and maladaptive response. Higher levels of CCA predicted higher levels of GA and greater engagement in collective PEB. The fact that CCA predicted collective but not individual pro-environmental behavior is interesting and extends previous research on the associations between CCA and different forms of PEB (Tam et al., 2023; Whitmarsh et al., 2022). One explanation of this difference may stem from the fact that climate change is a collective problem that must be addressed through collective action. Hence, high anxiety regarding climate change is more likely to motivate collective than individual actions. In addition, meeting with other people and acting together for a common cause may serve as a social-based coping strategy when seeking to overcome the distracting feelings that accompany CCA. These results may also be explained by the fact that engaging in collective action regarding climate change may attract more attention to its projected threatening consequences, thus enhancing CCA. More research is needed to explore this issue.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eResearch Contribution\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eDifferentiating between CCA and negative emotions toward climate change. Until recently, research did not use a systematic measure of CCA and focused more generally on negative emotional responses to climate change (Schwartz et al., 2022). Since the CCAS was developed, more research attention has been directed to CCA. Within this emerging research field, relatively little attention has been given to how negative emotional responses to climate change resemble and are different from CCA in terms of their distribution, association with mental health, and environmental engagement. In addition, some studies have described CCA as an example of negative emotions (Martin et al., 2022), and others have used the two concepts interchangeably (e.g., Ogunbode et al., 2022; Sangervo et al., 2022). The current study highlights the differences between these two emotional responses to climate change, both in their prevalence and in their distinct ability to predict GA. In addition to feelings of distress, CCA involves impaired cognitive and behavioral functioning. Hence, it is important to understand the prevalence and predictors of CCA and its association with mental health on the one hand and with PEB on the other. Nevertheless, as the prevalence of severe CCA is very low relative to that of negative emotional responses to climate change, and as negative emotions distinctly predict GA, the results of this study highlight the importance of specifically targeting negative emotional responses to climate change, in addition to CCA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePositive emotions and indifference as coping strategies. In the face of external stressors such as climate change, developing personal resilience is vital (Author(s), 2021). Emotional resilience is an important part of adaptation to climate change for two reasons: First, effective emotional coping with a threatening reality can help enhance psychological well-being. Second, adaptive coping also entails becoming involved in PEB and performing actions that can help in mitigating and adapting to climate change. The current research contributes to the growing body of research on psychological resilience in the context of climate change by examining how different kinds of emotional regulation influence adaptive responses. In line with research on coping strategies (Fredrickson, 1998; Folkman \u0026amp; Moskowitz, 2000; Lazarus \u0026amp; Folkman, 1984), Ojala (2012) suggested that in the face of climate change, meaning-focused coping (a form of coping that focuses on positive emotions such as hope) is an adaptive method of coping with projected changes in the climate. Other researchers have further suggested that de-emphasizing the problem is maladaptive as in the long run this may be associated with higher levels of anxiety (Sch\u0026auml;fer et al., 2017; Wullenkord et al., 2021). The present study echoes these findings and underscores the destructive nature of emotional indifference relative to the adaptive impact of positive emotions. Based on the current findings, future research explore ways by which educational and community interventions can foster positive emotional responses to climate change and reduce indifference.\u003c/p\u003e\n\u003cp\u003eLinks between CCA and other emotional responses to climate change. This study is one of the first to investigate the associations between different emotional responses to climate change and CCA, thus extending our understanding of the nature of CCA and its predictors. Findings reveal that increase in each of the three kinds of emotions \u0026ndash; positive, negative, and indifference \u0026ndash; predicted increase in the level of CCA. The prediction of negative emotions is understood, and in line with previous research (Tam et al., 2023; Whitmarsh et al., 2022). The prediction of positive emotions is in line with research that found that in some cases hope and worries related to climate change can appear together (Ojala 2012a; Sangervo et al., 2022). Research suggests that positive emotions are often part of the way individuals cope with stressful life events (Folkman, \u0026amp; Moskowitz, 2000). Accordingly, some people may simultaneously experience a high level of CCA and positive emotions. The findings on indifference are less intuitive. A possible explanation is that claiming indifference may merely mask a deeper sense of anxiety regarding this issue and constitute an ineffective attempt to avoid the anxiety the individual already feels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCCA was also predicted by gender (men experience higher levels of CCA than women), lower perception that climate change is real, and GA. The possibility that those prone to mental impairment may be more vulnerable to CCA has already been discussed here and elsewhere (Clayton \u0026amp; Karazsia, 2020). The finding that a lowered perception that climate change is real negatively predicts CCA is less intuitive. In line with the explanation on indifference, a possible explanation is that perceiving climate change as \u003cem\u003eunreal\u003c/em\u003e reflects cognitive denial, which under some circumstances may lead to higher levels of anxiety.\u003c/p\u003e\n\u003cp\u003eExtending the geographical distribution of research on CCA. Most previous research on CCA used US and European samples. The addition of an Israeli sample is beneficial since Israel is a \u0026quot;hot spot\u0026quot; that may be more affected by desertification, droughts and extreme more than other countries. Nevertheless, Israel is a developed country and thus does not represent non-Western nations that have the highest climate risk. The results show that projected vulnerability is not translated into CCA level. Quite the contrary: The level of CCA in this sample is lower than in most other samples. These findings support the notion that CCA is related to a complex set of determinants from the local and social context (Clayton \u0026amp; Karazsia, 2020). In Israel climate change is low on the government\u0026rsquo;s list of priorities, and national security issues are often prioritize. This may explain the low level of CCA found among the Israeli sample.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eLimitations\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe current study has several limitations that can also serve as guidelines for future studies. First, due to the correlational nature of the research, caution should be taken in drawing causal conclusions about the relations between research variables. Therefore, experimental or longitude research is needed to investigate the direction of the association between emotional responses to climate change and behavioral engagement and the association between emotions regarding climate change and CCA. Second, the indifference measure was based on a single item. The decision to use a single item was based on the factor analysis for the emotion scale, which distinguished indifference from the other variables, and on its conceptual meaning, which differed from that of positive emotions and negative emotions. Yet single-item scales cannot be assessed for reliability (Schultz et al., 2004). Furthermore, indifference may represent a defensive, self-protective strategy. Hence, measuring it as an explicit self-report measure may be prone to social desirability bias. Implicit methods should be used to address this challenge (Wullenkord \u0026amp; Reese, 2021). Third, the emotions scale used in this research was based solely on quantitative methodology. This method provides valuable information on the psychometric nature of the variables and facilitates statistical analysis. Nevertheless, it does not provide in-depth understanding of the qualitative nature of these emotional responses to climate change. Such information is important mainly in the case of positive emotions, which may not be a straightforward response to climate change. Qualitative methods such as open items on a survey or semi-structured interviews can provide more comprehensive information on the source of diverse emotions regarding climate change and how these emotions are translated (or not) into behavioral engagement. Finally, because the questionnaire was distributed in Hebrew, it represents the Israeli Jewish population but not the Arab population. In the future the CCAS and other psychological scales related to climate change should be translated into Arabic and distributed among the Arab population in Israel.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eEmotional responses to climate change are related both to climate change mitigation behavior and to the promotion of resilience and well-being. In the context of PEB engagement, the results of this study show that positive emotions predict an increase in both private-sphere and collective PEB, indifference predicts a decrease in both, and CCA predicts an increase only in collective PEB. With respect to mental health, both CCA and negative emotions predict an increase in GA. In general, these findings offer insights into how different emotional responses to climate change are differentially associated with mental health and environmental engagement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of interest:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration on ethics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki. The research received ethical approval from the University (Approval No. 362/22). Participants gave their informed consent before answering the survey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot relevant as the corresponding author is the only author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot relevant as the corresponding author is the only author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupporting data file is stored at: https://osf.io/cy7mj/?view_only=bdff857791364dc08c3c2a6d5ec897b1\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAuthor(s), (2021).\u003c/li\u003e\n\u003cli\u003eBamberg S., Rees, J. 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Avoidance, rationalization, and denial: defensive self-protection in the face of climate change negatively predicts pro-environmental behavior. \u003cem\u003eJournal of Environmental Psychology\u003c/em\u003e, \u003cem\u003e77\u003c/em\u003e, 101683.\u0026rlm; https://doi.org/10.1016/j.jenvp.2021.101683\u003c/li\u003e\n\u003cli\u003eZigmond, A.S., \u0026amp; Snatith, R.P. (1983). The hospital anxiety depression scale. Acta Psychiatrica Scandinavia, 67,; 361-370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp dir=\"LTR\"\u003eTable 1\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eDescriptive statistics of research variables\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003eItems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003eMin.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003eMax.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[95% confidence interval]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[2.25,2.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[2.63,2.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[2.18,2.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eClimate change anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[1.38,1.54]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e0-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[.81,.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e0-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[.84,.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[4.19,4.39] \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[3.63,3.86]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[3.80,4.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[3.61,3.83]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003etime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[3.10,3.35]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[3.29,3.42]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003ePrivate-sphere behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e0-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e100.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e45.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e45.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e24.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[42.43,47.92]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.115562403697997%\"\u003e\n \u003cp dir=\"LTR\"\u003eCollective behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e0-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.782742681047766%\"\u003e\n \u003cp dir=\"LTR\"\u003e77.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.24191063174114%\"\u003e\n \u003cp dir=\"LTR\"\u003e11.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp dir=\"LTR\"\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.550077041602465%\"\u003e\n \u003cp dir=\"LTR\"\u003e16.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.02773497688752%\"\u003e\n \u003cp dir=\"LTR\"\u003e[9.75,13.46]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003eTable 2\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003ePrevalence rates of climate anxiety and emotions toward climate change (N=302)\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLow (Percentage)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eModerate (Percentage)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eHigh (Percentage)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e267\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(88.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e26\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(8.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e105\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(34.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e120\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(39.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e77\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(25.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e180\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e82\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(27.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e40\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e179\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(59.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e75\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.46938775510204%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e48\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"LTR\"\u003e(15.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003eTable 3\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eCorrelations between research variables\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"731\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.25\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.11\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.18\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.17\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp 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dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd 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\u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.27\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.14\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.28\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.17\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.53\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.46\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.57\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.58\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.52\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.41\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eClimate change anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.44\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.44\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.32\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.25\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003ePrivate-sphere behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.22\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.31\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.12\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.22\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"3.1377899045020463%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.414733969986358%\"\u003e\n \u003cp dir=\"LTR\"\u003eCollective behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e-.23\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.16\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.139154160982264%\"\u003e\n \u003cp dir=\"LTR\"\u003e.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.729877216916781%\"\u003e\n \u003cp dir=\"LTR\"\u003e.22\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.17\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.30\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.457025920873124%\"\u003e\n \u003cp dir=\"LTR\"\u003e.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eNote.\u0026nbsp;\u003c/em\u003e* \u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e.05, **\u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e.01, ***\u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e.001.\u0026nbsp;Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eTable 4\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eMultiple regression models testing the predictors of generalized anxiety and depression, and the main effects of climate change anxiety.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"666\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.97897897897898%\" colspan=\"10\" valign=\"top\" style=\"width: 14.4351%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eGeneralized anxiety\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.663663663663664%\" colspan=\"\" valign=\"top\" style=\"width: 6.841%;\"\u003e\n \u003cp dir=\"LTR\"\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.315315315315315%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.207207207207207%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.057057057057057%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.70870870870871%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.5075075075075075%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.15915915915916%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\" colspan=\"2\" valign=\"top\" style=\"width: 8.0736%;\"\u003e\n \u003cp dir=\"LTR\"\u003e95.0% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.663663663663664%\" colspan=\"\" valign=\"top\" style=\"width: 6.841%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.315315315315315%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.207207207207207%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.057057057057057%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSE\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.70870870870871%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5075075075075075%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15915915915916%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003esr2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.26126126126126%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.36036036036036%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.663663663663664%\" colspan=\"\" rowspan=\"13\" style=\"width: 6.841%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.315315315315315%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.207207207207207%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.057057057057057%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.70870870870871%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.5075075075075075%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15915915915916%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.26126126126126%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.36036036036036%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.720\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.663663663663664%\" colspan=\"\" valign=\"top\" style=\"width: 6.841%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.315315315315315%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.207207207207207%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.057057057057057%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.70870870870871%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.5075075075075075%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.15915915915916%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.26126126126126%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.36036036036036%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.663663663663664%\" colspan=\"\" rowspan=\"14\" style=\"width: 6.841%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.315315315315315%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.207207207207207%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.057057057057057%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.70870870870871%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.5075075075075075%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.15915915915916%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.26126126126126%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.36036036036036%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.73913043478261%\" colspan=\"\" valign=\"top\" style=\"width: 7.6569%;\"\u003e\n \u003cp dir=\"LTR\"\u003eCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.347826086956522%\" colspan=\"\" valign=\"top\" style=\"width: 2.7615%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.173913043478262%\" valign=\"top\" style=\"width: 2.4477%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.08695652173913%\" colspan=\"\" valign=\"top\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.695652173913043%\" colspan=\"\" valign=\"top\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.91304347826087%\" colspan=\"\" valign=\"top\" style=\"width: 3.3263%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.608695652173912%\" colspan=\"\" valign=\"top\" style=\"width: 3.954%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12%\" valign=\"top\" style=\"width: 3.4343%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.643178410794603%\" colspan=\"\" valign=\"top\" style=\"width: 6.841%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"83.35832083958022%\" colspan=\"9\" valign=\"top\" style=\"width: 32.8242%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.53; R2 change=.020\u0026nbsp;p\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.323353293413174%\" colspan=\"10\" style=\"width: 5.9623%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDepression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.323353293413174%\" style=\"width: 5.9623%;\"\u003e\n \u003cp dir=\"LTR\"\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.269461077844312%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.736526946107785%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.335329341317365%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.532934131736527%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.18562874251497%\" style=\"width: 3.0125%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.952095808383234%\" colspan=\"2\" style=\"width: 8.2845%;\"\u003e\n \u003cp dir=\"LTR\"\u003e95.0% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.323353293413174%\" style=\"width: 5.9623%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.269461077844312%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.736526946107785%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSE\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.335329341317365%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.532934131736527%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.18562874251497%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003esr2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.574850299401197%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.323353293413174%\" rowspan=\"14\" style=\"width: 5.9623%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.269461077844312%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.736526946107785%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.335329341317365%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.532934131736527%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.18562874251497%\" style=\"width: 3.0125%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.574850299401197%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" style=\"width: 35.7739%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.323353293413174%\" rowspan=\"15\" style=\"width: 5.9623%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.269461077844312%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.736526946107785%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.682634730538922%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.335329341317365%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.532934131736527%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.18562874251497%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.574850299401197%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.377245508982035%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.616580310880828%\" colspan=\"\" valign=\"top\" style=\"width: 7.8452%;\"\u003e\n \u003cp dir=\"LTR\"\u003eClimate change anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.772020725388601%\" colspan=\"\" style=\"width: 2.9498%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7657%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.01727115716753%\" colspan=\"\" style=\"width: 3.7029%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.46286701208981%\" colspan=\"\" style=\"width: 3.2636%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" colspan=\"\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.290155440414507%\" style=\"width: 3.0125%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.507772020725389%\" colspan=\"\" style=\"width: 4.2678%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.12607944732297%\" style=\"width: 4.0167%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" style=\"width: 35.7739%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.41; R2 change=.001\u0026nbsp;p\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003eNote: Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eTable 5\u003c/em\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eMultiple regression models testing the predictors of private-sphere and \u0026nbsp;collective pro-environmental\u003c/em\u003e \u003cem\u003ebehavior and the main effects of climate change anxiety.\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"703\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.00568181818182%\" colspan=\"10\" style=\"width: 25.0578%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003ePrivate-sphere pro-environmental behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.073863636363637%\" style=\"width: 5.5759%;\"\u003e\n \u003cp dir=\"LTR\"\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.3974%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 4.9041%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" style=\"width: 4.2323%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.676136363636363%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.181818181818183%\" colspan=\"2\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003e95.0% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.073863636363637%\" style=\"width: 5.5759%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.3974%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSE\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.676136363636363%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003esr2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.380681818181818%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.801136363636363%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.073863636363637%\" rowspan=\"15\" style=\"width: 5.5759%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-16.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e11.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.676136363636363%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.380681818181818%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-39.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.801136363636363%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e9.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5.327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-8.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n 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style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.338\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.621\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"92.88025889967638%\" colspan=\"9\" style=\"width: 38.0234%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003eR2adj\u0026nbsp;\u003c/em\u003e= 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.073863636363637%\" rowspan=\"16\" style=\"width: 5.5759%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-17.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e11.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.676136363636363%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.096590909090908%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.380681818181818%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-41.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.801136363636363%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5.588\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e9.521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-6.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-9.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-4.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e7.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.615\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e12.792\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.093699515347335%\" style=\"width: 8.3974%;\"\u003e\n \u003cp dir=\"LTR\"\u003eCCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.662358642972537%\" style=\"width: 4.9041%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" style=\"width: 4.2323%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.592891760904685%\" colspan=\"\" style=\"width: 3.0902%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.208400646203554%\" colspan=\"\" style=\"width: 3.762%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.531502423263328%\" colspan=\"\" style=\"width: 3.8964%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.147011308562197%\" style=\"width: 4.501%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5.734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"92.88025889967638%\" colspan=\"9\" style=\"width: 38.0234%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.24; R2 change=.001\u0026nbsp;p\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eCollective pro-environmental behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.814992025518341%\" valign=\"top\" style=\"width: 5.3088%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.862838915470494%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\" style=\"width: 7.2997%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\" valign=\"top\" style=\"width: 6.3043%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\" valign=\"top\" style=\"width: 6.4149%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\" valign=\"top\" style=\"width: 6.4149%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\" valign=\"top\" style=\"width: 6.3043%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\" valign=\"top\" style=\"width: 6.3043%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.02232854864434%\" colspan=\"2\" valign=\"top\" style=\"width: 11.5025%;\"\u003e\n \u003cp dir=\"LTR\"\u003e95.0% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.802547770700637%\" style=\"width: 5.3088%;\"\u003e\n \u003cp dir=\"LTR\"\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.8343949044586%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.509554140127388%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSE\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003esr2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.802547770700637%\" rowspan=\"14\" style=\"width: 5.3088%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.8343949044586%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.509554140127388%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-15.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-31.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e5.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.723\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.374\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-4.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.748\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.411\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e7.944\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-6.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.827476038338658%\" valign=\"top\" style=\"width: 5.3088%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"92.17252396166134%\" colspan=\"9\" style=\"width: 63.8167%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.802547770700637%\" rowspan=\"15\" style=\"width: 5.3088%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.8343949044586%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.509554140127388%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-21.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e7.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-36.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.07643312101911%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-5.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-4.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.284\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.238\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-4.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.686\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.736\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e3.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e8.595\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e6.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e-7.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.649\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.34369602763385%\" valign=\"top\" style=\"width: 12.8297%;\"\u003e\n \u003cp dir=\"LTR\"\u003eClimate change anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.398963730569948%\" style=\"width: 7.2997%;\"\u003e\n \u003cp dir=\"LTR\"\u003e7.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e1.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.4149%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.3043%;\"\u003e\n \u003cp dir=\"LTR\"\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 6.5255%;\"\u003e\n \u003cp dir=\"LTR\"\u003e4.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.844559585492227%\" style=\"width: 4.977%;\"\u003e\n \u003cp dir=\"LTR\"\u003e10.666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.827476038338658%\" valign=\"top\" style=\"width: 5.3088%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"92.17252396166134%\" colspan=\"9\" style=\"width: 63.8167%;\"\u003e\n \u003cp dir=\"LTR\"\u003eR2adj = 0.28; R2 change=.006\u0026nbsp;p\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003eNote: Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003e\u003cem\u003eTable 6\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp dir=\"LTR\"\u003eMultiple regression showing the predictors of climate change anxiety.\u003c/p\u003e\n\u003cdiv align=\"left\" dir=\"ltr\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"24.731182795698924%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e95.0% Confidence Interval for B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eSE\u003csub\u003eB\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003esr2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eLower Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eUpper Bound\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003ePositive emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e4.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eNegative emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e6.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eIndifference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eGeneralized Anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\"\u003e\n \u003cp dir=\"LTR\"\u003eReal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\"\u003e\n \u003cp dir=\"LTR\"\u003eHuman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\"\u003e\n \u003cp dir=\"LTR\"\u003eImpact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\"\u003e\n \u003cp dir=\"LTR\"\u003eSpace \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\"\u003e\n \u003cp dir=\"LTR\"\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.439324116743471%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003eEnvironmental worldview\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.138248847926267%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.674347158218126%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e-0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.056835637480798%\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cem\u003eR2adj\u0026nbsp;\u003c/em\u003e= 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp dir=\"LTR\"\u003eNote: Real= climate change is real; Human=caused by humans; Impact=negative consequences; Space=spatial distance; Time= temporal distance\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Emotional responses to climate change, climate change anxiety, pro-environmental behavior, mental health, resilience","lastPublishedDoi":"10.21203/rs.3.rs-4275680/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4275680/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As climate change becomes a reality, people are becoming increasingly aware of the threats associated with global warming. Many people may experience climate change as an unremitting psychological stressor associated with high levels of concern, worry and anxiety, that can emerge even in the absence of short-term or direct effects. Because emotions are related both to mitigation behavior and to promoting resilience and well-being, studying people’s emotional responses to climate change is important. This study explores the links of different emotional responses to climate change with mental health and pro-environmental behavior, using an online survey of a nationwide representative sample in Israel. An online survey of a nationwide representative sample of Hebrew speakers (N=302) revealed high levels of negative emotions, along with low levels of climate anxiety and moderate levels of positive emotions and indifference. Both climate change anxiety and negative emotions were associated with impairment in mental health. Positive emotions predicted an increase in both private-sphere and collective pro-environmental behavior, whereas indifference predicted a decrease in both types of behavior. Climate change anxiety predicted an increase in collective but not in private-sphere pro-environmental behavior. The research findings extend our understanding of the role played by different emotional responses to climate change in explaining impairment in mental health and adaptive pro-environmental behavior.","manuscriptTitle":"Emotional responses to climate change, mental health, and climate action: How are they related?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 15:40:42","doi":"10.21203/rs.3.rs-4275680/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aed31074-9bd9-4841-966c-dec023043597","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-30T19:31:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 15:40:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4275680","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4275680","identity":"rs-4275680","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}