Next Article in Journal
Studies on Heavy Precipitation in Portugal: A Systematic Review
Previous Article in Journal
Crop Coefficients and Irrigation Demand in Response to Climate-Change-Induced Alterations in Phenology and Growing Season of Vegetable Crops
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Climate
Volume 12
Issue 10
10.3390/cli12100162
climate-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Does Climate Change Worry Decrease during Armed Conflicts?

by
Yaira Hamama-Raz
1,* and
Shiri Shinan-Altman
2
1
School of Social Work, Ariel University, Ariel 407000, Israel
2
The Louis and Gabi Weisfeld School of Social Work, Bar-Ilan University, Ramat Gan 5290002, Israel
*
Author to whom correspondence should be addressed.
Climate 2024, 12(10), 162; https://doi.org/10.3390/cli12100162
Submission received: 23 August 2024 / Revised: 8 October 2024 / Accepted: 10 October 2024 / Published: 14 October 2024
Browse Figures
Versions Notes

Abstract

:
Climate change stands out as an especially pressing global concern. The aim of the present study was to explore whether climate change worry decreases during armed conflicts, using two time-points: before and during an armed conflict. Guided by the Transactional Theory of Stress and Coping (TTSC), we examined the interplay between risk appraisal, pro-environmental behaviors (PEBs), and climate change worry. A sample of 202 Israeli adults participated in two waves of data collection, completing self-report measures addressing climate change worry, risk appraisal, and PEBs. Results revealed a significant decline in climate change worry and risk appraisal during the armed conflict, whereas PEBs remained unchanged. Contrary to expectations, the associations between risk appraisal, PEBs, and climate change worry did not weaken during the conflict. Mediation analyses indicated that the decline in risk appraisal led to a decline in PEBs, which subsequently contributed to a decline in climate change worry. However, this mediation effect was partial, with most of the association remaining direct. These findings imply that the psychological impact of armed conflict may temporarily overshadow environmental concerns, emphasizing the need for strategies to maintain environmental awareness and behavior even during an armed conflict.

1. Introduction

Climate change has increasingly strong and long-lasting impacts on people’s lives [1]. Both direct exposure to climate change, whether acute (e.g., extreme weather, wildfire) or chronic (e.g., heat, drought, decreased air quality), as well as indirect exposure (i.e., the idea or social representation of climate change) have been found to be associated with decreased well-being and negative physical and mental health outcomes [2,3,4].
Worry about climate change includes both micro-climate worry, which entails worrying about negative consequences for oneself or one’s family/friends, and macro-climate worry, which entails worrying about negative consequences for animals and plants, people in poorer countries, or future generations [4]. Indeed, according to the Office for National Statistics in Great Britain [5] around three in four adults (74%) reported feeling (very or somewhat) worried about climate change in Great Britain. Similarly, Hickman and colleagues [6] revealed in their study across 10 countries (Australia, Brazil, Finland, France, India, Nigeria, Philippines, Portugal, the UK, and the US; 1000 participants per country) that 59% were very or extremely worried, and 84% were at least moderately worried about climate change.
Worry about climate change is a complex environmental emotion that can have contrasting effects—negatively impacting mental health while simultaneously encouraging behavioral engagement. Specifically, worry about climate change has been found to be associated with greater depression, anxiety, and stress, impacting the mental health of young Italian adults [7]. Similarly, these researchers reported a positive effect of climate change worry on future anxiety, suggesting that concerns about the climate crisis reinforce a negative and anxious outlook toward the future in young Italian adults [7]. The negative association between worry about climate change and mental well-being was also found in data collected from multiple European countries and Israel [8] and in a study of Norwegian adolescents, which demonstrated a significant association between climate change worry and depressive symptoms, lower subjective well-being, and reduced expectations of experiencing happiness in the future [9]. Nevertheless, a previous study revealed that the more individuals worried about climate change, the stronger their feelings of personal responsibility to reduce it, which, in turn, was linked to support for climate policies and personal climate mitigation behaviors [10]. Likewise, in a study which used data from 23 countries that participated in the European Social Survey Round 8 (N = 44,387), worry about climate change was an important predictor of individuals engaging in both energy curtailment and energy efficiency behaviors [11]. In line with this, worries about climate change appear to play a pivotal role in one’s subjective well-being and behavioral engagement [12].
Such feelings of worry might change during armed conflicts, as armed conflicts compound immediate feelings of fear and uncertainty [13,14], whereas climate change is perceived as a future and psychologically distant threat [15]. Nevertheless, there is a reciprocal relationship between climate change and armed conflicts. Specifically, armed conflicts contribute significantly to environmental degradation and climate change, as military activities and conflicts lead to deforestation, soil degradation, and increased greenhouse gas emissions, further accelerating climate change [16]. Moreover, destroying infrastructure and displacing populations during conflicts can result in significant environmental damage, disrupting ecosystems and increasing vulnerability to climate impacts [17]. Conversely, climate change can contribute to armed conflict by intensifying resource scarcity and sociopolitical tensions, particularly in regions with high population densities and low adaptive capacities [18,19]. Thus, we hypothesized that during an armed conflict, participants would report lower levels of climate change worry.
Given the aforementioned vicious cycle that poses significant challenges to global security and environmental sustainability, the focus of the current study was on climate change worry during an armed conflict in Israel. On 7 October 2023, Hamas terrorists in Gaza fired thousands of rockets toward Israel [20], and since then Hezbollah (a terrorist group situated on Israel’s northern border) has continuously sparked daily bushfires in northern Israel (a result of their own rocket attacks on Israel), with swathes of forest reserve destroyed and people hospitalized for smoke inhalation [21]. In this context, we aimed to explore whether climate change worry might have decreased and whether climate change-related factors might explain this worry differently as a result of the armed conflict.
The theoretical framework that guided the present study was the Transactional Theory of Stress and Coping (TTSC) [22], which focuses on the interaction between individuals and their environment. According to the TTSC, individual appraisal processes are composed of evaluating the stressors’ relevance (primary appraisal) and the individuals’ resources to overcome these stressors (secondary appraisal), with both appraisals highly influencing stress responses. Primary and secondary appraisals are believed to impact the coping strategies chosen by individuals. These processes are dynamic and interrelated, as individuals continually appraise changes in the situation and their ability to cope [22]. Thus, in the present study, we also examined the interplay of risk appraisal related to climate change, pro-environmental behaviors (PEBs), and climate change worry before and during an armed conflict in Israel.
Risk appraisal related to climate change (hereafter, risk appraisal) involves evaluating the likelihood and severity of climate change impacts [23]. A previous study revealed that higher risk appraisal was associated with increased stress, as individuals perceived greater threats to their well-being [24]. In addition, risk appraisal has been found to be positively associated with climate change worry among adult participants [25]. In line with this notion, we hypothesized that during an armed conflict, participants will report lower levels of risk appraisal, and that the association between risk appraisal and climate change worry will be weaker during the armed conflict than during a period of peace.
Pro-environmental behaviors are defined as purposeful actions that can reduce negative environmental impacts via three major behaviors: waste reduction, reuse, and recycling [26]. According to Helm and colleagues [27], “PEBs can best be described as a mixture of self-interest (e.g., changing behavior to minimize one’s own health risk), and of concern for other people, future generations, other species, or whole ecosystems (e.g., preventing air pollution that may cause climate change)” (p. 161). Scholars have revealed a consistent positive association between PEBs and well-being or life satisfaction [28,29]. Additionally, engagement in PEBs has been found to be positively associated with climate change worry [30]. Based on these previous findings, we hypothesized that during an armed conflict, participants will report lower levels of engagement in PEBs, and that the association between PEBs and climate change worry will be weaker during the armed conflict than during a period of peace.
In reference to the association between risk appraisal and PEBs, it was found that risk appraisal promoted mitigation and adaptation behaviors and significantly impacted stress levels [27]. Thus, in the present study, the mediating role of PEBs was assessed within the direct link between risk appraisal and climate change worry. We hypothesized that a greater decline in risk appraisal will be associated with a greater decline in PEBs, which will subsequently be associated with a greater decline in climate change worry.
Taken together, in the present study, we examined the following: (a) differences in climate change worry (outcome variable), risk appraisal, and PEBs before and during an armed conflict; (b) differences in the direct associations between the independent variables (i.e., risk appraisal and PEBs) and climate change worry before and during an armed conflict; and (c) the indirect effect of PEBs (mediation effect) in the association between risk appraisal and climate change worry before and during an armed conflict (See Figure 1).

2. Materials and Methods

2.1. Participants and Procedure

Participants were recruited at Time 1 (before the armed conflict) from an internet panel (iPanel), consisting of about 100,000 Israelis, that adheres to the Israel Bureau of Statistics in key demographic factors including age, gender, marital status, and education that represent the general population [31]. At Time 2, we returned to the same participants for a re-assessment, six months after the 7 October 2023 Hamas-led attack on Israel. Inclusion criteria were being 18 years of age or older and being fluent in Hebrew.
Sample size was calculated using G*Power software [32,33], and Kenny’s calculator for a mediation analysis (https://davidakenny.shinyapps.io/MedPower/). For a repeated-measures analysis of variance with two time-points, with a moderate-low effect size, f = 0.15, α = 0.05, a low correlation between the repeated measures—r = 0.20, and power = 0.80, the required minimum sample size is N = 142. For a mediation analysis with a minimum β of the paths X to M and M to Y of 0.22, and a minimum direct effect X to Y of β = 0.30, with α = 0.05, and power = 0.80, the required minimum sample size is N = 200 participants.
The study was approved by the second author’s university’s institutional review board (IRB; for Time 1, approval No.052202; for Time 2, approval No. 032403). Data collection was conducted at two times: during the first two weeks of June 2022 (Time 1) and during the last two weeks of March 2024 (six months after the 7 October attack). Participants were required to sign an electronic informed consent form before accessing the questionnaire at both times.
Data were obtained from 402 participants at Time 1, of whom 202 participants responded at Time 2 (response rate 50.2%). Time 2 respondents consisted of about half men and half women, with a mean age of about 45 years (SD = 13.94), and most were married and had children (Table 1). About 43% of them had a higher education, whereas most of the remainder had a high school education. Over half were secular, and the remainder were somewhat religious. Most participants were urban, employed, had a good-to-excellent health status, and reported varying income levels.
Those who responded at Time 2 were older (mean = 44.87, SD = 13.94) than those who did not respond (mean = 38.37, SD = 15.13) (t(100) = 4.48, p < 0.001), and a higher percentage of them had children (75.2% vs. 59.0%, Z = 3.47, p < 0.001). A somewhat higher percentage of those who responded at Time 2 were men (54.0% vs. 43.0%, Z = 2.20, p = 0.028). No other demographic differences were found.

2.2. Measures

The following battery of self-report questionnaires was administered at the two time-points.
Sociodemographic characteristics: gender; age (years); area of residence (urban/rural); marital status (married, divorced, widowed, single); number of children; highest education completed (elementary or secondary school; high school; vocational education; BA or higher); employment status (full-time, part-time, self-employed, unemployed, pensioner, stay-at-home parent), and religiosity (secular, traditional but not very religious, traditional and religious/Orthodox). Self-rated health was assessed with one question, “In general, how do you rate your health?” (ranging from 1 = bad to 4 = excellent) [34].
Climate change worry was measured using Stewart’s climate change scale [35], which comprises ten items (e.g., “I worry that I might not be able to cope with climate change”) on a 5-point Likert scale ranging from 1 (never) to 5 (often). The scale was translated from English to Hebrew using a back-and-forth translation method performed by a professional English translator. This Hebrew version of the scale was previously used in a study conducted in Israel [25]. An average score was calculated, with higher scores indicating greater worry about climate change (Cronbach’s α = 0.94 at Time 1 and α = 0.94 at Time 2).
Risk appraisal was measured using six items related to harm and threat perceptions of climate change [36]. Participants rated their agreement with each statement (e.g., “I have lost hope because pollution has just gotten worse and worse”) on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). An average score was computed, with higher scores indicating higher levels of risk appraisal (Cronbach’s α = 0.77 at Time 1 and α = 0.72 at Time 2).
Pro-environmental behaviors (PEBs) were assessed using a modified version of the Homburg and Stolberg [36] questionnaire. Five items were used: (1) “I take part in events run by environmental organizations such as setting up nest boxes or toad fences, taking part in litter clean-ups, etc.”; (2) “I participate in protest campaigns or demonstrations for environmental protection”; (3) “When possible I use public transport instead of going by car”; (4) “For short distances (up to 2 km) I leave the car at home and walk or go by bike”; (5) “When cooking I use a lid to cover the pot or pan, to avoid wasting energy.” These items were rated on a 5-point Likert scale from 1 (strongly agree) to 5 (strongly disagree). The items were translated from English to Hebrew using a back-and-forth translation method performed by a professional English translator. This Hebrew version of the scale was previously used in a study conducted in Israel [37]. An average score was calculated, with higher scores indicating greater levels of PEBs (Cronbach’s α = 0.69 at Time 1 and α = 0.69 at Time 2).
Notably, a factor analysis was conducted for the 21 items of the study questionnaires over time, using Principal Axis Factoring with oblique rotation. Three factors emerged, consistent with the study variables. The first factor (Eigenvalue = 7.07) included the ten items measuring “climate change worry,” with loadings ranging from 0.52 to 0.83 (Pattern matrix). The second factor (Eigenvalue = 4.43) included the six items measuring “risk appraisal,” with loadings ranging from 0.37 to 0.72. The third factor (Eigenvalue = 2.28) included the five items measuring “pro-environmental behaviors,” with loadings ranging from 0.32 to 0.70.
Besides the aforementioned measures, participants were asked at Time 2 to fill out a questionnaire assessing their level of exposure to the armed conflict, with four dichotomous items: loss of a family member, acquaintance, or close friend; injury of a family member, acquaintance, or close friend; being close to a Hamas-abducted hostage; and being evacuated from their homes.

2.3. Data Analysis

Data were analyzed with SPSS ver. 29. Descriptive statistics were used for the participants’ characteristics, and t-tests and z-ratios for the significance of the difference between two independent proportions were calculated for differences between participants who took part at Time 2 and those who did not. Cronbach’s alpha was used for the internal consistencies of the measures, and Pearson correlations and t-tests were used between the demographic characteristics and the study variables, to identify any potential covariates. As the five-point income variable had zero skewness (skewness = −0.02, SE = 0.17) it was used as a continuous variable. A multivariate repeated measures analysis of covariance was calculated for time differences in the study variables, controlling for age, gender, and income level. Pearson correlations were calculated between the study variables at each time-point, and mixed linear hierarchical models were used to assess the time differences in the extent of the associations between the study variables. Climate change worry was the dependent variable in these mixed models; time was the within-subject repeated variable; and the interaction between each independent variable and time was defined as a covariate, denoting the difference between each pair of associations. Relevant demographic characteristics were controlled for. Next, change scores in the study variables were defined as residual gain scores, controlling for the values of the first measurement. The study model was assessed for Time 1, and for the change scores, using Hayes’ PROCESS procedure [38], model no. 4 was used, with 5000 bootstrap samples and 95% confidence intervals.
It should be noted that data were not analyzed using SEM (Structural Equation Modeling) due to the sample size. For a model with three latent variables and 21 indicators (the total number of items for worry, risk appraisal, and PEBs), with a medium effect size of 0.30, α = 0.05, and power of 0.80, the minimum required sample size was 400 participants [39]. Additionally, data were not analyzed using PLS-SEM (Partial Least Squares Structural Equation Modeling) due to several statistical critiques of this technique, e.g., as in [40,41,42]. Rönkkö and colleagues [41,42] argue that the PLS technique is essentially a form of regression using scale scores rather than a true Structural Equation Modeling (SEM) approach. They demonstrate that using indicator weights offers no advantage over unweighted summed scales. Similarly, Goodhue and colleagues [40], through a simulation study, conclude that PLS, multiple regression, and LISREL produce similar results. Based on these considerations, we opted to use unweighted scales rather than PLS weights.

3. Results

About a third of the participants (n = 66, 32.7%) reported at least one experience related to the armed conflict: loss of a family member, acquaintance, or close friend (n = 39, 19.3%); injury of a family member, acquaintance, or close friend (n = 39, 19.3%); being close to a hostage (n = 19, 9.4%); or being evacuated from home (n = 10, 5.0%). The experience of the armed conflict was not related to the study variables at Time 2 (p = 0.056 to p = 0.590). The participants’ ages were associated with PEBs at both times (Time 1: r = 0.15, p = 0.028, Time 2: r = 0.16, p = 0.027), and income level was associated with climate change worry at Time 2 (r = 0.20, p = 0.004). Men reported higher PEBs at Time 2 than did women (mean = 2.70, SD = 0.75, vs. mean = 2.47, SD = 0.80; t (200) = 2.04, p = 0.021). Thus, age, gender, and income level were controlled for in further analyses.
A comparison of the study variables by time (Table 2) showed a significant decline in both climate change worry and risk appraisal. No change was found for PEBs. Thus, the hypotheses that the levels of climate change worry and risk appraisal would decline during an armed conflict were supported but not the hypothesis for PEBs.
The direct associations between risk appraisal, PEBs, and climate change worry were examined with Pearson correlations (Table 3). All associations were positive and significant, revealing that a higher risk appraisal was associated with higher PEBs, and both were associated with higher climate change worry, at both times. No differences were found in the extent of the associations between the two times (risk appraisal and worry: t (213.28) = 0.07, p = 0.948; PEBs and worry: t (212.58) = 0.06, p = 0.948; risk appraisal and PEBs: t (222.93) = −0.85, p = 0.396). Thus, the hypotheses related to the associations between risk appraisal and climate change worry, and between PEBs and climate change worry, were not supported.
The study model was examined with the PROCESS procedure, model 4 for mediation [38]. The model was first examined for the first measurement, and then for the change scores. Before conducting the PROCESS analysis, Variance Inflation Factor (VIF) values were calculated for each variable to assess potential multicollinearity (multicollinearity defined as VIF > 10) [43]. The highest VIF value for the Time 1 model was 1.13, and for the change scores model, it was 1.11. The Durbin–Watson test yielded a value of 2.07 for the Time 1 model and 1.89 for the change scores model. In both cases, the scatterplot showed widespread points, indicating that the data were homoscedastic.
The indirect effect for Time 1 was significant (effect = 0.08, SE = 0.03, 95% CI = 0.03, 0.13), revealing that a higher risk appraisal was associated with higher PEBs, which in turn was associated with higher climate change worry (Figure 2).
However, as both the indirect and the total effects were significant, the association was partly direct and partly mediated. The mediated proportion was found to be 13.5%, and thus most of the association was direct.
Finally, the study model was examined for the change scores. The indirect effect for the change scores was significant (effect = 0.07, SE = 0.03, 95% CI = 0.02, 0.13), revealing that a greater decline in risk appraisal was associated with a greater decline in PEBs, which in turn was associated with a greater decline in climate change worry (Figure 3).
As before, the association between change in risk appraisal and change in climate change worry was partly direct and partly mediated. The mediated proportion was found to be 19%, and thus most of the association was direct. The hypothesis related to the mediation effect was thus supported, although the indirect effect was partial.

4. Discussion

In the current study, we investigated how climate change worry, PEBs, and risk appraisal were affected post-October 7th, during the 2023 Swords of Iron War in Israel. Drawing on the TTSC [22], we aimed to understand whether immediate threats such as an armed conflict would diminish concerns about long-term stressors such as climate change. Previous research has highlighted how conflicts can dominate psychological resources and influence environmental concerns [16]. The current study provides insights into the shifts in climate-related worries and behaviors during times of crisis. Our findings are consistent with previous research, which has shown that immediate threats, such as the physical and emotional dangers associated with armed conflicts, can overshadow future-oriented worries such as those about climate change [13,14]. This finding aligns with the TTSC [22], which posits that immediate stressors tend to take priority in individuals’ cognitive processes. Armed conflicts present an urgent and tangible risk that may prompt individuals to shift their mental resources toward more immediate concerns, relegating long-term threats, such as climate change, to a lower level of awareness. Additionally, the literature suggests that climate change is often viewed as a psychologically distant phenomenon [15], a notion that might further explain why individuals in the current study focused less on climate change during the conflict.
According to the findings, there was no significant change in PEBs before vs. during the armed conflict, which runs counter to the expectation that engagement in these behaviors would decrease due to the overshadowing effects of the conflict. The lack of significant change in PEBs suggests that once established, PEBs may persist, even during crises. This resilience in behavior might reflect a habituated response, where individuals continue to act pro-environmentally even when their cognitive focus shifts away from long-term environmental risks. These findings align with prior research showing that PEBs are often driven by a mixture of self-interest and concern for others [27]. It may be that PEBs are not solely linked to an individual’s worry about climate change but also to a more stable ethical or personal commitment to environmentalism [26]. The persistence of PEBs highlights the need to support and encourage these behaviors as habitual practices, which are resilient even in the face of external stressors such as armed conflicts.
The decline in risk appraisal during the armed conflict reveals that participants perceived climate change as a less immediate threat when being confronted with more direct, pressing concerns. This decrease indicates that individuals may psychologically distance themselves from longer-term threats, such as climate change, when more immediate risks, such as those posed by war, are present [24]. From the perspective of TTSC [22], the focus of the primary appraisal during a war would be on survival and immediate safety, shifting attention away from secondary stressors such as environmental concerns. This notion is supported by research on the effects of armed conflicts, which has shown that mental health and cognitive resources are often strained under conditions of acute stress [13]. However, this reduced risk appraisal has long-term consequences for environmental policy, as it underscores the challenge of maintaining environmental risk awareness during crises.
The mediation analysis revealed that PEBs partially mediated the relationship between risk appraisal and climate change worry. A significant indirect effect was found, meaning that the decline in risk appraisal led to a decline in PEBs, which in turn contributed to a decline in climate change worry. However, the mediation effect was partial, indicating that most of the association between risk appraisal and climate change worry remained direct. This finding supports the idea that engagement in PEBs can influence emotional responses to environmental threats [27]. Prior studies have shown that individuals who engage in PEBs tend to report lower levels of environmental stress, possibly because they feel more empowered and in control of their contribution to mitigating climate change [28]. However, as the mediation effect was partial, it seems that risk appraisal played a strong direct role in shaping climate change worry.

4.1. Limitations

Several limitations should be noted. First, the study sample was drawn from an online panel, which may not fully represent the broader Israeli population. Participants who engage in online surveys might have different levels of environmental concern or conflict exposure compared to those who do not participate in such panels. Thus, generalizing the findings should be conducted cautiously. Second, all data were collected through self-reported measures, which can introduce biases such as social desirability bias or recall bias. Third, related to the previous points, a larger sample size would have allowed the use of Structural Equation Modeling (SEM), enabling the inclusion of latent variables and multigroup analysis based on time (Time 1, Time 2). Fourth, the study’s two time-points, although strategically chosen, may not have captured the full temporal dynamics of how climate change worry fluctuates during and after armed conflicts. Future studies might benefit from additional time-points to allow for a better understanding of the long-term effects of armed conflicts on environmental concerns. Fourth, the study was conducted in Israel during a specific armed conflict, thus potentially limiting the generalizability of the findings to other regions or conflicts. Different cultural, political, and environmental contexts may yield different results, suggesting that other scholars replicate the present study model. Fifth, the study did not account for all possible confounding variables, such as participants’ previous experiences with climate change or their political views, which may have influenced both their climate change worry and their responses to armed conflict. Finally, a specific set of PEBs was measured, which may not have encompassed all types of environmental actions relevant to different individuals. This aspect may limit the generalizability of the findings to broader environmental engagement.

4.2. Implications

The findings of this study offer practical implications for maintaining environmental engagement during times of crisis. The decline in climate change worry and risk appraisal during an armed conflict suggests that immediate threats overshadow long-term concerns. Policymakers and environmental organizations should develop strategies to keep climate change awareness front and center, even amidst conflict, ensuring that public awareness does not wane. Doing so could involve targeted communication campaigns that acknowledge immediate stressors while emphasizing the continued importance of environmental sustainability. Furthermore, the resilience of PEBs observed in the study highlights the value of fostering habitual behaviors that can persist despite external stress. Programs that encourage these behaviors as routine actions could help ensure that individuals remain engaged in environmentally positive practices, even during crises. Mental health professionals might also play a role in integrating environmental concerns into broader well-being interventions during periods of conflict, addressing both immediate and long-term challenges.
Authors should discuss the results and how they can be interpreted from the perspective of previous studies and of the working hypotheses. The findings and their implications should be discussed in the broadest context possible. Future research directions may also be highlighted.

5. Conclusions

Overall, the study offers significant insights into the interplay between climate change worry, risk appraisal, and PEBs in the context of an armed conflict. The findings suggest that immediate threats such as war can overshadow environmental concerns, leading to a temporary decline in climate change worry and risk appraisal. However, the persistence of PEBs during such crises is encouraging and suggests that environmental behaviors can become habitual and resistant to external stressors. These results have important implications for environmental policy, particularly in conflict-prone regions, where maintaining environmental awareness is crucial despite the distraction of more immediate threats.

Author Contributions

Conceptualization, Y.H.-R. and S.S.-A.; methodology, Y.H.-R. and S.S.-A.; writing—original draft preparation, Y.H.-R. and S.S.-A.; writing—review and editing, Y.H.-R. and S.S.-A.; supervision, Y.H.-R. and S.S.-A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. World Health Organization. Mental Health and Climate Change: Policy Brief. 2022, p. 16. Available online: https://www.who.int/publications/i/item/9789240045125 (accessed on 10 August 2024).
  2. Clayton, S. Climate change and mental health. Curr. Environ. Health Rep. 2021, 8, 1–6. [Google Scholar] [CrossRef] [PubMed]
  3. Environmental Protection Agency/EPA. Climate Change and Human Health 2023. Available online: https://www.epa.gov/climateimpacts/climate-change-and-human-health (accessed on 10 August 2024).
  4. Wullenkord, M.C.; Ojala, M. Climate-change worry among two cohorts of late adolescents: Exploring macro and micro worries, coping, and relations to climate engagement, pessimism, and well-being. J. Environ. Psychol. 2023, 90, 102093. [Google Scholar] [CrossRef]
  5. Office for National Statistics (ONS). Worries about Climate Change, Great Britain: September to October 2022. Available online: https://www.ons.gov.uk/peoplepopulationandcommunity/wellbeing/articles/worriesaboutclimatechangegreatbritain/septembertooctober2022 (accessed on 10 August 2024).
  6. Hickman, C.; Marks, E.; Pihkala, P.; Clayton, S.; Lewandowski, R.E.; Mayall, E.E.; Wray, B.; Mellor, C.; van Susteren, L. Climate anxiety in children and young people and their beliefs about government responses to climate change: A global survey. Lancet Planet Health 2021, 5, e863–e873. [Google Scholar] [CrossRef] [PubMed]
  7. Regnoli, G.M.; Tiano, G.; De Rosa, B. Is Climate Change Worry Fostering Young Italian Adults’ Psychological Distress? An Italian Exploratory Study on the Mediation Role of Intolerance of Uncertainty and Future Anxiety. Climate 2024, 12, 118. [Google Scholar] [CrossRef]
  8. Martin, G.; Roswell, T.; Cosma, A. Exploring the relationships between worry about climate change, belief about personal responsibility, and mental wellbeing among adolescents and young adults. Wellbeing Space Soc. 2024, 6, 100198. [Google Scholar] [CrossRef]
  9. Leonhardt, M.; Granrud, M.D.; Bonsaksen, T.; Lien, L. Associations between Mental Health, Lifestyle Factors and Worries about Climate Change in Norwegian Adolescents. Int. J. Environ. Res. Public Health 2022, 19, 12826. [Google Scholar] [CrossRef] [PubMed]
  10. Bouman, T.; Verschoor, M.; Albers, C.; Böhm, G.; Fisher, S.D.; Poortinga, W.; Whitmarsh, L.; Steg, L. When worry about climate change leads to climate action: How values, worry and personal responsibility relate to various climate actions. Glob. Environ. Chang. 2020, 62, 102061. [Google Scholar] [CrossRef]
  11. Gregersen, T.; Doran, R.; Böhm, G.; Poortinga, W. Outcome expectancies moderate the association between worry about climate change and personal energy-saving behaviors. PLoS ONE 2021, 16, e0252105. [Google Scholar] [CrossRef]
  12. Van Weezel, S. Local warming and violent armed conflict in Africa. World Dev. 2020, 126, 104708. [Google Scholar] [CrossRef]
  13. Carpiniello, B. Psychopathological consequences of war and armed conflicts. Eur. Psychiatry 2023, 66 (Suppl. S1), S49. [Google Scholar] [CrossRef]
  14. Moreno-Chaparro, J.; Piñeros-Ortiz, S.; Rodríguez-Ramírez, L.; Urrego-Mendoza, Z.; Garzón-Orjuela, N.; Eslava-Schmalbach, J. Mental health consequences of armed conflicts in adults: An overview. Actas Esp. Psiquiatr. 2022, 50, 68–91. [Google Scholar] [PubMed]
  15. Guenther, L.; Brüggemann, M. Not here, not now, not me: How distant are climate futures represented in journalistic reporting across four countries? J. Sci. Commun. 2023, 22, A01. [Google Scholar] [CrossRef]
  16. Landholm, D.; Pradhan, P.; Kropp, J. Diverging forest land use dynamics induced by armed conflict across the tropics. Glob. Environ. Chang. 2019, 56, 86–94. [Google Scholar] [CrossRef]
  17. Berhe, A. On the relationship of armed conflicts with climate change. PLoS Clim. 2022, 1, e0000038. [Google Scholar] [CrossRef]
  18. International Committee of the Red Cross (ICRC). ICRC Position on Climate Change, Armed Conflict, and other Situations of Violence. 2024. Available online: https://www.icrc.org/sites/default/files/topic/file_plus_list/icrc_position_on_climate_change.pdf (accessed on 22 August 2024).
  19. Levy, B. Increasing risks for armed conflict: Climate change, food and water insecurity, and forced displacement. Int. J. Health Serv. 2019, 49, 682–691. [Google Scholar] [CrossRef]
  20. Reuters Explainer: What You Need to Know about Hezbollah, the Group Backing Hamas against Israel. 2023. Available online: https://www.reuters.com/world/middle-east/what-is-hezbollah-lebanese-group-backing-hamas-its-war-with-israel-2023-10-16/ (accessed on 10 July 2024).
  21. BBC. Fires in Northern Israel Fuel Demands to Tackle Escalation with Hezbollah. 2024. Available online: https://www.bbc.com/news/articles/cpdd8z0zjdzo) (accessed on 10 July 2024).
  22. Lazarus, R.S.; Folkman, S. Transactional theory and research on emotions and coping. Eur. J. Pers. 1987, 1, 141–169. [Google Scholar] [CrossRef]
  23. Weaver, C.P.; Moss, R.; Ebi, K.; Gleick, P.; Stern, P.; Tebaldi, C.; Wilson, R.; Arvai, J. Reframing climate change assessments around risk: Recommendations for the US National Climate Assessment. Environ. Res. Lett. 2017, 12, 080201. [Google Scholar] [CrossRef] [PubMed]
  24. Clayton, S.; Manning, C.M.; Speiser, M.; Hill, A.N. Mental Health and Our Changing Climate: Impacts, Inequities, Responses; American Psychological Association and ecoAmerica: Washington, DC, USA, 2021.
  25. Shinan-Altman, S.; Hamama-Raz, Y. The association between climate change exposure and climate change worry among Israeli Adults: The Interplay of risk appraisal, collective efficacy, age, and gender. Sustainability 2023, 15, 13689. [Google Scholar] [CrossRef]
  26. Li, D.; Zhao, L.; Ma, S.; Shao, S.; Zhang, L. What influences an individual’s pro-environmental behavior? A literature review. Resour. Conserv. Recycl. 2019, 146, 28–34. [Google Scholar] [CrossRef]
  27. Helm, S.V.; Pollitt, A.; Barnett, M.A.; Curran, M.A.; Craig, Z.R. Differentiating environmental concern in the context of psychological adaption to climate change. Glob. Environ. Chang. 2018, 48, 158–167. [Google Scholar] [CrossRef]
  28. Netuveli, G.; Watts, P. Pro-environmental behaviours and attitudes are associated with health, wellbeing and life satisfaction in multiple occupancy households in the UK Household Longitudinal Study. Popul. Environ. 2020, 41, 347–371. [Google Scholar] [CrossRef]
  29. Schmitt, M.T.; Aknin, L.B.; Axsen, J.; Shwom, R.L. Unpacking the relationships between pro-environmental behavior, life satisfaction, and perceived ecological threat. Ecol. Econ. 2018, 143, 130–140. [Google Scholar] [CrossRef]
  30. Larionow, P.; Gawrych, M.; Mackiewicz, J.; Michalak, M.; Mudło-Głagolska, K.; Preece, D.A.; Stewart, A.E. The Climate Change Worry Scale (CCWS) and its links with demographics and mental health outcomes in a Polish sample. Healthcare 2024, 12, 1128. [Google Scholar] [CrossRef] [PubMed]
  31. Bodas, M.; Siman-Tov, M.; Kreitler, S.; Peleg, K. Psychological correlates of civilian preparedness for conflicts. Disaster Med. Public Health Prep. 2017, 11, 451–459. [Google Scholar] [CrossRef] [PubMed]
  32. Faul, F.; Erdfelder, E.; Lang, A.-G.; Buchner, A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 2007, 39, 175–191. [Google Scholar] [CrossRef] [PubMed]
  33. Faul, F.; Erdfelder, E.; Buchner, A.; Lang, A.G. Statistical power analysis using G*Power 3.1: Tests for correlation and regression analyses. Behav. Res. Methods 2009, 41, 1149–1160. [Google Scholar] [CrossRef] [PubMed]
  34. Benyamini, Y.; Blumstein, T.; Lusky, A.; Modan, B. Gender differences in the self-rated health–mortality association: Is it poor self-rated health that predicts mortality or excellent self-rated health that predicts survival? Gerontologist 2003, 43, 396–405. [Google Scholar] [CrossRef] [PubMed]
  35. Stewart, A.E. Psychometric properties of the climate change worry scale. Int. J. Environ. Res. Public Health 2021, 18, 494. [Google Scholar] [CrossRef]
  36. Homburg, A.; Stolberg, A. Explaining pro-environmental behavior with a cognitive theory of stress. J. Environ. Psychol. 2006, 26, 1–14. [Google Scholar] [CrossRef]
  37. Shinan-Altman, S.; Hamama-Raz, Y. Factors associated with pro-environmental behaviors in Israel: A comparison between participants with and without a chronic disease. Int. J. Environ. Res. Public Health 2022, 19, 13123. [Google Scholar] [CrossRef]
  38. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis, 3rd ed.; The Guilford Press: New York, NY, USA, 2022. [Google Scholar]
  39. Soper, D.S. A-Priori Sample Size Calculator for Structural Equation Models [Software]; Pearson Education Limited: Harlow, UK, 2024; Available online: https://www.danielsoper.com/statcalc (accessed on 10 August 2024).
  40. Goodhue, D.L.; Lewis, W.; Thompson, R. Does PLS have advantages for small sample sizes or non-moral data? MIS Q. 2012, 36, 981–1001. [Google Scholar] [CrossRef]
  41. Rönkkö, M.; McIntosh, C.N.; Antonakis, J.; Edwards, J.R. Partial least squares path modeling: Time for some serious second thoughts. Oper. Manag. Res. 2016, 47, 9–27. [Google Scholar] [CrossRef]
  42. Rönkkö, M.; Lee, N.; Evermann, J.; McIntosh, C.; Antonakis, J. Arketing or methodology? Exposing the fallacies of PLS with simple demonstrations. Eur. J. Mark. 2023, 57, 1597–1617. [Google Scholar] [CrossRef]
  43. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 7th ed.; Pearson new international edition; Pearson Education Limited: London, UK, 2014. [Google Scholar]
Climate 12 00162 g001
Figure 1. The study model.
Figure 1. The study model.
Climate 12 00162 g001
Climate 12 00162 g002
Figure 2. The mediating role of PEBs in the association between risk appraisal and climate change worry, Time 1. Note: values on arrows: B(SE), values within rectangles: R2, C = total effect, C’ = direct effect. *** p < 0.001.
Figure 2. The mediating role of PEBs in the association between risk appraisal and climate change worry, Time 1. Note: values on arrows: B(SE), values within rectangles: R2, C = total effect, C’ = direct effect. *** p < 0.001.
Climate 12 00162 g002
Climate 12 00162 g003
Figure 3. The mediating role of change in PEBs in the association between change in risk appraisal and change in climate change worry. Note: values on arrows: B(SE), values within rectangles: R2, C = total effect, C’ = direct effect. *** p < 0.001.
Figure 3. The mediating role of change in PEBs in the association between change in risk appraisal and change in climate change worry. Note: values on arrows: B(SE), values within rectangles: R2, C = total effect, C’ = direct effect. *** p < 0.001.
Climate 12 00162 g003
Table 1. Demographic characteristics (N = 202).
Table 1. Demographic characteristics (N = 202).
VariableCategoriesValues
Age, mean (SD), range 44.87 (13.94), 18–68
Gender, n (%)Male109 (54.0)
Female93 (46.0)
Marital status, n (%)Single59 (29.2)
Married, in a relationship115 (56.9)
Divorced, widowed, other28 (13.9)
Children, n (%)Yes152 (75.2)
Level of education, n (%)Up to high school, high school77 (38.1)
Vocational education39 (19.3)
College/university education 86 (42.6)
Religiosity, n (%)Secular114 (56.4)
Traditional60 (29.7)
Religious28 (13.9)
Employed, n (%)Yes157 (77.7)
No45 (22.3)
Income, n (%)Below average76 (37.6)
Average53 (26.2)
Above average73 (36.1)
Type of residence, n (%)Urban173 (85.6)
Rural29 (14.4)
Health status, n (%)Not so good19 (9.4)
Good135 (66.8)
Excellent48 (23.8)
Table 2. Means, standard deviations, and F values for the study variables by time (N = 202).
Table 2. Means, standard deviations, and F values for the study variables by time (N = 202).
Time 1
Mean (SD)		Time 2
Mean (SD)		F (1, 198) (p)η2
Climate change worry2.50 (0.88)2.24 (0.83)7.20 (p = 0.008)0.035
Pro-environmental behaviors 2.52 (0.75)2.60 (0.79)0.35 (p = 0.558)0.002
Risk appraisal3.18 (0.75)2.97 (0.68)4.98 (p = 0.027)0.025
Note. ranges: 1–5.
Table 3. Pearson correlations between the study variables, by time (N = 202).
Table 3. Pearson correlations between the study variables, by time (N = 202).
Time 11.2.3.
Time 2
1. Climate change worry10.40 *0.59 *
2. Pro-environmental behaviors 0.39 *10.30 *
3. Risk appraisal0.53 *0.38 *1
* p < 0.05. Note: correlations for Time 1 are above the diagonal; correlations for Time 2 are below the diagonal.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hamama-Raz, Y.; Shinan-Altman, S. Does Climate Change Worry Decrease during Armed Conflicts? Climate 2024, 12, 162. https://doi.org/10.3390/cli12100162

AMA Style

Hamama-Raz Y, Shinan-Altman S. Does Climate Change Worry Decrease during Armed Conflicts? Climate. 2024; 12(10):162. https://doi.org/10.3390/cli12100162

Chicago/Turabian Style

Hamama-Raz, Yaira, and Shiri Shinan-Altman. 2024. "Does Climate Change Worry Decrease during Armed Conflicts?" Climate 12, no. 10: 162. https://doi.org/10.3390/cli12100162

APA Style

Hamama-Raz, Y., & Shinan-Altman, S. (2024). Does Climate Change Worry Decrease during Armed Conflicts? Climate, 12(10), 162. https://doi.org/10.3390/cli12100162

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop