An Integrated Moderation Model of Climate Change Risk Perception and Psychological Distress: The Roles of Self-Regulation, Resilience, and Self-Efficacy

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Abdallah, Hamed A. Ead, Attia M. El-Tantawy, Eman S. Swelam, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8340234/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 Background: Climate change is increasingly recognized as a serious threat to both physical and mental health in the present era. However, there remains a need for research specifically addressing the psychological effects of climate change on mental health. This study examined the correlation between climate change risk perception and psychological distress among emerging adults in Egypt. It also focused on the moderating roles of self-regulation, resilience, and self-efficacy, as well as gender differences, within the framework of an integrative model that conceptualizes these three variables as complementary psychological resources. Methods: A cross-sectional correlational method was conducted with 2,065 undergraduate students at Cairo University during the first semester of 2024. All participants of men and women completed validated Arabic versions of standardized psychological scales. Descriptive statistics and preliminary analyses, including tests for data bias were performed in SPSS (v.25), and structural equation modeling in AMOS (v.24) was used to test direct, interaction, and higher-order moderation effects between the moderating variables. Results: Climate change risk perception significantly correlated to psychological distress. Self-regulation and resilience consistently weakened this relationship, indicating their protective roles, while self-efficacy was unexpectedly associated with higher levels of distress. Significant interaction effects emerged primarily among men, with complex three-way interactions varying by gender, whereas the four-way interaction was not significant in both genders. Conclusions: The findings demonstrate the utility of an integrative model in reflecting gender-based differences in psychological responses to climate change. They also suggest that psychological resources are not enough when considered together, they remain independently important. Future research should address broader contextual and structural factors in the Egyptian culture. This study contributes to testing gendered moderation effects which reinforce cross-cultural studies, and provides actionable implications for education, psychosocial support, and policy development. Climate change Risk perception Self-regulation Resilience Self-efficacy Psychological distress Figures Figure 1 Introduction Climate change is one of the significant global challenges in the present era, which has a negative impact on the environmental, economic, social, psychological, and political domains. Its consequences extend beyond Environmental deterioration and loss, profoundly affecting human health and well-being [53, 28,14]. Rising temperatures, extreme weather events, and long-term ecological disruptions pose existential risks to communities worldwide [8,114,117]. Surpassing the 1.5 °C warming threshold is projected to result in potentially irreversible outcomes such as sea-level rise, biodiversity loss, and the degradation of aquatic ecosystems [8,60, 120]. Although the Arab region contributes minimal level to global emissions, it remains vulnerable to climate-related risks, including floods, forest fires, desertification, and extreme weather events [1, 33,114]. Egypt, and neighboring countries in the Gulf and North Africa, has already begun to experience severe adverse effects [51, 47]. Climate change exerts multifaceted effects on human health and well-being, extending beyond environmental damage to include both physical and mental health consequences [18, 31]. Rising temperatures, extreme weather events, and long-term environmental disruptions contribute to heat-related morbidity and mortality, cardiovascular and respiratory diseases, malnutrition resulting from food insecurity, and the re-emergence or spread of infectious diseases through altered ecosystems, are the most important manifestations of physical health [73, 18]. Climate change has affected mental health which manifested as heightened fear of the future, increased anxiety, future depression, post-traumatic stress disorder, insomnia, and reduced psychological well-being, particularly among populations repeatedly exposed to climate-related disasters [10, 24,99,115,116]. Accordingly, climate change has a double physical and mental health effects, emphasizing the need for integrated adaptation and mitigation strategies to protect populations public health, particularly among adolescents and young adults. In this context, perceived climate risk is an essential determinant of emotional and behavioral responses to environmental threats. Individuals who perceive climate change as serious threats or Near-term risks report higher levels of psychological distress, including anxiety, worry, and depression. On the other hand, individuals who perceive themselves as less vulnerable tend to downplay these risks or even deny them [24,98]. As a result, risk perception predicts eco-anxiety and climate-related distress, shaping coping patterns from adaptive engagement to maladaptive avoidance and denial [97,89]. Climate change risk perception has been associated with a wide range of negative mental health outcomes among, late adolescents and young adults [13,14,47]. This developmental stage is characterized by increased emotional sensitivity and identity formation, which may make individuals more vulnerable to environmental threats [74,75,18]. These emotional distresses such as fear, anxiety, depressive symptoms, and reduced well-being, underscoring the significance of understanding how perception of climate risk correlates to psychological distress, particularly among young adults [10, 82,49,24]. Individual psychological resources underscore a vital role in shaping how people cope with perceived climate change risks and how they can adapt to them or mitigate across different contexts and populations. Resilience helps young adults’ recovery and adaptation in the face of environmental stressors, enabling individuals sustain functioning when confronted with climate-related adversities [104]. Self-regulation also supports the control of excessive emotional responses and facilitates constructive responses to ambiguity, that minimizing the risk of maladaptive coping strategies such as denial or avoidance [67, 45]. Also, self-efficacy fosters proactive coping and engagement in adaptive behaviors, including sustainable practices and community-level actions [6, 40]. While these psychological resources are often studied separately, some studies emphasize the importance of exploring their interaction. For example, resilience and self-efficacy have been shown to work together in reducing climate anxiety and promoting adaptive engagement [78, 11]. Similarly, self-regulation represents a crucial resource that links climate change risk perception to both emotional stability and adaptive psychological responses to environmental threats [80]. This perspective extends beyond such individual protective factors and provides a more understanding of how multiple psychological resources jointly influence adaptation to climate hazard or risks. Understanding climate change risk perception is crucial for understanding the psychological impact of environmental threat and for guiding culturally appropriate intervention in vulnerable contexts. Emerging evidence from Egyptian context indicates that eco-anxiety and climate change–related worry are associated with increased psychological problems and decreased well-being among young populations in adolescence and early adulthood [77, 64]. Additional cross-national studies further demonstrate that climate change knowledge and attitudes are significantly linked to psychological distress among university students across Arab contexts, including Egypt, Jordan, and Saudi Arabia [36,1,33]. Together, these findings illustrate the importance of understanding how risk perception affects mental health outcomes within sociocultural settings that are vulnerable to climate risks, and poorly represented in research [19 ,22]. According to the study aim and hypotheses, there are four research gaps that can be inferred from the findings of previous studies. First, most studies have investigated the moderating role of one or two resources only, offering lack of insight into how these factors may jointly shape this relationship [11]. Second, despite consistent evidence that men and women differ in their climate risk perceptions and emotional responses, research on gender differences in the relationship between climate risk perception and psychological distress considering psychological resources remains scarce, [24,101]. Third, adolescents and emerging adults are the most vulnerable groups to climate-related psychological impacts. Developmental changes in identity, cognition, and emotion make them particularly susceptible to eco-anxiety and climate-related psychological distress when confronted with increased risk perception [ 82, 3]. Forth, empirical work in the Egyptian and broader Arab context is limited, even though these regions are vulnerable to climate-related risks and their psychological consequences [112, 111]. By addressing these four gaps, the study provides theoretically grounded evidence on the psychological variables linking climate risk perception to psychological distress and offers insights for psychosocial interventions and policy measures that may strengthen emerging adults’ capacity in the face of climate change threats [105, 35]. It is essential to situate the study within relevant psychological theories or theoretical framework that explains how and why these relationships emerge, and how they operate in practice. Relevant perspectives include resilience frameworks [65], social-cognitive theory concerning self-efficacy [6], and theoretical models of self-regulation, particularly self-determination theory [95]. This theoretical framework enhances the conceptual clarity and situates the study’s contribution to the field. Finally, integrating insights from stress and coping models highlights the importance of placing these individual-level perspectives within a general explanatory framework [56, 54, 44]. Therefore, the present study is based on the following theoretical framework. Theoretical Framework This theoretical framework guiding the present study by focusing on the relationship between perceived climate change risk and psychological distress from one side and the moderating effects of self-regulation, resilience, and self-efficacy from the other side. It draws upon established theories and prior empirical evidence to develop the proposed conceptual model (Figure 1). 2.1. Perception of Climate Change Risk and Psychological Distress Perception of climate change risks shape how individuals understand environmental threats and determine their emotional and behavioral reactions to these threats [57]. This area has gained growing attention in climate psychology [22,88]. While some studies report positive correlations between risk perception and psychological distress [28], others find weak or non-significant correlations [90, 74]. Longitudinal research showed reciprocal and evolving relationships between climate awareness and eco-anxiety, showing evidence of the mixed results of these associations over time [57,58]. Other research demonstrated that extreme weather experiences and environmental sensitivity significantly predicted increased risk perception; however, its correlations with distress yielded mixed results [31]. Climate risk perception may be related to behavioral engagement than to emotional distress [62, 92]. Some cross-cultural analyses indicate that higher perceived risk may associated with climate activism or pro-environmental behaviors instead of increased anxiety or worry [90]. These mixed findings emphasize the influence of cultural, contextual, and methodological factors, which in turn limit the external validity or restricting the generalizability of findings across different societies [85,105]. Theoretical perspectives help explain these discrepancies between previous results. Self-Determination Theory [95,94], Terror Management Theory [42], and Cognitive Appraisal Theory [56] emphasize the role of existential threat appraisals, perceived control, and personal traits in shaping psychological responses. Given their ongoing identity formation and developmental changes in cognition and emotion, young youth appear more vulnerable [24]. Collectively, this evidence underscores the need to consider both individual differences, cultural contexts and community factors when examining how climate risk perception correlates with psychological distress [86]. Most previous research in Egypt, have focused on attitudes, awareness, beliefs and public awareness rather than the psychological impacts of climate change. In addition, research on its mental health effects remains limited, particularly among adolescents and emerging adults. This gap highlights the need for climate psychological research in different cultural contexts [10, 49, 34]. Consequently, the present study examines how the perception of climate change risk relates to psychological distress considering individual resources among younger populations, where gender, age, education, and cultural context, collectively shape vulnerability. 2.2. The Roles of Moderator Variables Self-regulation, resilience, and self-efficacy are critical in shaping how individuals perceive climate risks, regulate emotions, and maintain adaptive functioning. Collectively, these resources form a basis for understanding their moderating role in the relationship between climate change risk perception and psychological distress. 2.2.1. Moderating Role of Self-Regulation Self-regulation is the ability to manage emotions, thoughts, and behaviors in a systematic manner. Therefore, it functions as an important moderator variable may modify the relationship between climate change risk perception and psychological distress. Self-regulation skills often enable adolescents and emerging adults experience lower levels of distress even when perceiving higher climate risks levels, they respond with adaptive coping strategies such as mindfulness and cognitive reappraisal [113, 26,67] Self-Determination Theory, suggest that independence and competence enhance the capacity to manage long-term stressors by enhancing intrinsic motivation and adaptive coping behaviors [95]. Therefore, self-regulation may moderate the relationship between risk perception and psychological distress by helping young adults to reinterpret environmental threats and use adaptive strategies such as reappraisal [100, 29]. Emerging adults with high self-regulation capacities tend to utilize adaptive coping strategies, such as reappraisal and problem-solving. This reduce the emotional burden of environmental stressors [110,70]. Similarly, self-regulation predicted more effective emotional adjustment and lower psychological distress across stress-inducing contexts, including environmental threats. Evidence from longitudinal research indicates that self-regulation protects against the escalation of stress into chronic distress, especially when individuals face ambiguity or unpredictable conditions [67, 32]. Despite this theoretical and empirical foundation, most research has investigated self-regulation as a psychological resource in applied developmental or clinical contexts rather than in relation to climate change risk perception. Research examining the moderating effect on climate-related psychological distress is still scarce. Most previous studies emphasize resilience and coping more broadly, with approximately low contribution of self-regulatory processes in this area [24, 79]. Evidence from Arab and Egyptian cultural contexts is particularly insufficient, with available studies focusing on awareness, adaptation, or descriptive accounts of eco-anxiety rather than testing that psychological resources [34]. This gap emphasizes the importance of exploring self-regulation as a specific moderating factor in the relationship between climate risk perception and psychological distress among young people in vulnerable cultural settings like Egypt. 2.2.2. Moderating Role of Resilience Resilience is an important moderating factor that may mitigate psychological distress among emerging adults who perceive climate risks. That means, resilience is the ability to adapt, endure, and recover from adverse circumstances and stressful events. Resilient individuals often employ proactive coping strategies, including problem-solving and seeking social support [114]. For example, they may transform emotional distress into constructive responses such as climate activism or prosocial engagement, which, in turn reduces feelings of helplessness and promoting a sense of meaning and purpose. Resilience further enables individuals to cognitively reinterpret stressors in more adaptive ways, thereby providing additional protection for mental health [105, 58]. Research consistently shows the mitigating role of resilience against psychological stressors, including those stemming from climate threats [43, 44]. Late adolescents and emerging adults with higher resilience are better able to manage the psychological consequences of climate change. They use proactive coping strategies, such as focusing on positive outcomes and seeking social support. Such adaptive responses help individuals to maintain emotional stability and well-being in the face of climate-related stressors [81, 114, 104]. Cross-cultural findings indicate that resilience not only reduces levels of anxiety but also enhances collective efficacy, motivating young people to engage in community-based adaptation efforts [105]. This interpretation is consistent with the Positive Adaptation in Context framework, which conceptualizes resilience as a dynamic developmental process shaped by the interaction between individual capacities and environmental resources. According to this model, resilience develops when individuals use both their personal strengths and external resources to adapt positively to major challenges such as climate-related threats, thereby reducing the impact of risk exposure on mental health [43, 44]. Evidence from developmental and disaster psychology indicates that a research gap remains. Few studies have directly examined the moderating role of resilience in the relationship between climate change risk perception and psychological distress. Available research has focused on general stress, trauma, or natural disaster contexts rather than on climate change specifically [105, 104]. Furthermore, while studies from Europe and North America have begun to examine how resilience mitigates eco-anxiety and climate-related worry, evidence from Egypt and the wider Arab region, is still limited [34, 47]. Although resilience is widely acknowledged as a protective factor, its specific role as a moderator in the psychological pathways linking perceived climate risks to distress among emerging adults in vulnerable cultural contexts has not been systematically examined. 2.2.3. Moderating Role of Self-Efficacy Self-efficacy is the belief in one’s ability to effectively perform the behaviors needed to attain specific outcomes [5,6]. It has been consistently correlated to lower psychological distress in the context of climate threats. Emerging adults with higher self-efficacy are more likely to adopt active coping and advocacy behaviors that strengthen their sense of control [94]. Such confidence handle’s anxiety and encourages engagement in sustainable practices, including reducing carbon consumption and promoting peer education. Self-efficacy also enables individuals to view environmental challenges as opportunities for growth and success [95,40,119]. Therefore, interventions aimed at enhancing self-efficacy may help alleviate climate-related distress by fostering individuals’ adaptive psychological resources [85, 102]. According to Bandura’s Social Cognitive Theory [7,6], beliefs in one’s efficacy regulates cognitive, emotional, and behavioral responses to challenges. In this model, emerging adults have a strong self-efficacy perceive threats as manageable, activate personal agency, and employ adaptive coping strategies, hence moderating the negative emotional effects of risk perception [26]. The emerging adults possess self-efficacy skills reported lower climate anxiety and greater engagement in adaptive responses such as activism and sustainable practices in face of climate threats[8]. Consistently, some findings conclude that interventions designed to enhance self-efficacy was significantly associated with distress among students facing environmental stressors [85]. Other studies further found that self-efficacy promotes resilience by promoting optimism and perceived control in the face of climate-related uncertainty [ 5,40]. Despite these results, most evidence comes from different cultural contexts, with limited exploration in Arab societies. Research in Arab region and especially Egypt has focused primarily on climate awareness, policy engagement, or descriptive accounts of eco-anxiety [34, 47], without examining self-efficacy as a moderator. This gap emphasis the importance of investigating its moderating role in the relationship between climate risk perception to psychological distress among emerging adults in the Egyptian contexts. Addressing this issue is essential for developing culturally grounded interventions that enhance agency, reduce vulnerability, and strengthen resilience in the face of climate threats. 2.3. Gender Differences Gender differences offering important insight into how emerging adults respond to climate change risks. In general women report higher climate risk perception .Young women display stronger climate anxiety and greater willingness to engage in mitigation behaviors[19, 87]. Men often adopt problem-focused coping strategies and report less emotional distress due to prevailing social norms[121,16,76]. Men often show stronger emotional self-regulation under stress [12 2, 66], whereas women may benefit more from interventions aimed at strengthening self-regulation and resilience [26]. Gender differences are also evident in self-efficacy: men tend to report stronger belief in one’s ability to act effectively, while women more often rely on relational efficacy, gaining confidence through social relationship and support systems [16, 35]. These findings suggest that psychological resource operate through gender-based coping patterns and strategies, in moderating the relationship between climate risk perception and psychological distress [87, 101,121]. Understanding how gender differences shape the combined moderating roles of self-regulation, resilience, and self-efficacy in the relationship between climate risk perception and psychological distress arises as a notable gap needs further investigations [16, 25,101]. While some previous research has documented a discriminant gendered patterns in climate anxiety and engagement, investigations that integrate these moderators in the same study remain scarce . Some previous studies have investigated the three moderating roles of the three psychological resources individually in isolation, which shortens our understanding of their interactive effects [ 26, 40, 45,58,104]. This gap is more pronounced in local literature. Research has primarily addressed climate awareness, adaptation policies, or eco-anxiety descriptively [34], without a focus on gender-specific psychological patterns . Traditional gender roles strongly shape how people express emotions and deal with challenges [87,16]. Therefore, addressing this knowledge gap is important to identify gender-specific pathways in the relationship between climate change risk perception and psychological distress along with its moderator resources and develop culturally appropriate interventions for vulnerable groups in different cultural contexts [25]. 2.4. Integrated Moderating Effects of Self-Regulation, Resilience, and Self-Efficacy In the integrative proposed framework, self-regulation, resilience, and self-efficacy are viewed as interrelated psychological resources that together contribute to buffer the mental health effects of climate change risk perception and adaptive functioning [14,18]. Self-regulation helps individuals to manage emotional responses and maintain psychological balance in confronting climate stressors [26,67]. Resilience represents the capacity to adapt over time, recover from adversity, and help maintain functioning during long-lasting challenges [104,105]. In accordance self-efficacy means confidence in one’s ability in adopt proactive coping strategies and engaging effectively with climate change demands [119, 9]. These resources together form a broader psychological system that supports both short-term adjustment and long-term adaptation [85, 54, 58]. Although climate-related mental health has received increasing attention [64,83], few studies have examined these moderators together. Research findings clearly indicate that eco-anxiety and climate-related distress are prevalent among adolescents and young adults. [24,28]. Little evidence exists on how these psychological resources interact in moderating the relationship between climate change risk perception and psychological distress within Arab Egyptian contexts. Existing work tends to examine self-regulation, resilience, or self-efficacy in isolation manner, yielding fragmented and context-specific insights in different cultures [2 6 ,40]. For instance, resilience seems as a protective factor in European and North American samples [81], while self-efficacy presents a predictor of adaptive coping in African and Arab region, and self-regulation as essential for reducing distress [51, 67]. The Integrative Model of Psychological Adaptation helps explain and connect these fragmented perspectives [66,88]. It suggests that adaptive responses to chronic stressors such as climate change involve dynamic interactions among regulatory, adaptive, and agentic resources, which collectively promote stability, regulation, and agency [35, 98, 91]. In addition, few studies have investigated these factors together in the climate domain, and cross-cultural validation in the Arab world remains particularly limited. To guide the present study and the development of its hypotheses, the following section outlines the underpinning theoretical frameworks that explain how individuals appraise stressors and mobilize psychological resources to cope with climate-related threats. 2.5. Underpinning Theory Lazarus and Folkman’s Transactional Model of Stress and Coping emphasizes that stress arises not simply from external events but from the dynamic interaction between the individual and the environment, mediated by cognitive appraisal processes [56]. In the primary appraisal, individuals evaluate whether an event constitutes a threat, whereas in the secondary appraisal, they assess the adequacy of their coping resources. According to this framework, climate change risk perception represents a primary appraisal of environmental threat, while psychological distress emerges as the outcome when available coping resources are insufficient [76, 119]. Self-regulation, resilience, and self-efficacy can thus be viewed as key psychological resources influencing secondary appraisal. Self-regulation enables adaptive reappraisal and flexible coping [67,45,26]. Resilience supports psychological stability under adverse circumstances and recovery [65,100,101]. Self-efficacy fosters persistence, and cognitive reframing of threats though under conditions of chronic and uncontrollable stressors such as climate change, it may also heighten responsibility and rumination [6, 9, 96]. The expectation is that resources will moderate the association between climate risk perception and psychological distress. Accordingly, The Resilience Portfolio Model [44, 43] emphasizing that adaptation relies on a constellation of interrelated assets rather than isolated traits. So, self-regulation, resilience, and self-efficacy represent components of a broader portfolio, whose breadth, balance, and accessibility determine whether climate threats are managed effectively or culminate in heightened distress. The combination between these perspectives represent the theoretical foundation for the present study. By integrating the Transactional Model of Stress guided by the Resilience Portfolio Model, the framework integrates the appraisal of environmental threats with the mobilization of psychological resources. This integration leads the current research in interpretation of how self-regulation, resilience, and self-efficacy moderate the relationship between climate change risk perception and psychological distress among emerging adults in Egypt. Accordingly, this framework guides the development of the study’s hypotheses. Hypotheses Development Building on the reviewed perspectives and underpinning theory, the following hypotheses were proposed: H1. Climate change risk perception is associated positively with psychological distress. H2. Self-regulation, resilience, and self-efficacy each independently moderate the relationship between climate change risk perception and psychological distress, which means that higher degrees of these resources reduce the relationship between the two variables. H3. The combined moderating effects of self-regulation, resilience, and self-efficacy moderate collectively the relationship between climate change risk perception and psychological distress, which means that higher degrees of these resources reduce the relationship between the two variables. H4 . Gender-based differences are anticipated in how self-regulation, resilience, and self-efficacy moderating the relationship between climate change risk perception and psychological distress , which means that these psychological resources reduce the relationship more strongly for one gender compared to the other. Methods 3.1. Research Design The present study employed a cross-sectional, correlational design to investigate the relationship between climate change risk perception and psychological distress from one side and the moderating roles of self-regulation, resilience, and self-efficacy from the other side among emerging adults at Cairo University. 3.2. Participants The study sample consisted of 2,065 emerging adults, recruited from different faculties at Cairo University during the first semester of 2024 .It includes men and women students(men: n = 996, women: n = 1,069) aged 18 to 22 years (The mean age for men was 19.60 years (SD = 1.35), while the mean age for women was 19.47 years (SD = 1.21). According to Cairo university population of approximately 200,000 students, the sampling error was calculated at ±2.1% with a 95% confidence level, indicating acceptable precision for population-level estimates. A priori power analysis was conducted by using G*Power 3.1. Assuming a small to medium effect size (f² = 0.02), α = .05, and power = 0.80, the required sample size to detect moderation effects in a multiple regression framework was 395 participants. The final sample of 2,065, including men and women, was higher than the required threshold. This ensured adequate statistical power for the proposed moderation analyses [38, 37, 55]. The study employed a stratified convenience sampling method, with the sample classified based on gender (men and women) and academic discipline (theoretical and practical faculties) to maintain proportional representation across major subgroups. Individuals with clinically diagnosed psychological disorders (e.g., major depressive disorder, anxiety disorders) were excluded from participation. Table 1 provides a detailed breakdown of the sample’s demographic characteristics, including gender, academic discipline, and academic year. Table 1: Sample's demographic characteristics Gender M en (N=996) Women (N=1069) College Theoretical Freq. 351 509 % 35.24 47.61 Practical Freq. 645 560 % 64.76 52.39 Academic Year First Freq. 275 260 % 27.61 24.32 Second Freq. 388 460 % 38.96 43.03 Third Freq. 165 179 % 16.56 16.74 Fourth Freq. 99 139 % 9.93 13.00 Fifth Freq. 69 31 % 6.93 2.90 Family Income Low Freq. 43 23 % 4.32 2.15 Below average Freq. 158 118 % 15.86 11.04 Average Freq. 698 783 % 70.08 73.25 High Freq. 88 130 % 8.84 12.16 Very high Freq. 9.00 15 % 0.90 1.40 Table 1 summarizes the demographic characteristics of the sample. The distribution of gender is relatively balanced, with 996 men and 1069 women. Most men were enrolled in practical colleges, though women were more represented in theoretical colleges. and approximately reflecting their actual distribution among men and women students at Cairo University. Most students were in the first and second academic years, with fewer in advanced years. In terms of family income, most respondents reported an average income, while very few fell into the extremes of very low or very high categories. Overall, the sample reflects diversity across gender, college type, academic year, and socioeconomic status. 3.3. Scales Five scales were used in the present study as follow 3.3.1. Climate Change Risk Perception Scale (CCRPS) Building on van der Linden’s integrative model of climate change risk perception [106,107,108], the present study employed an adapted version of this scale consisting of 20 items, equally distributed across four dimensions (five items per dimension). The Climate Change Risk Perception Scale (CCRPS) captures the cognitive appraisal of climate risks through four interrelated dimensions: Perceived Severity (beliefs about the seriousness of climate change impacts, e.g., Climate change will have very serious consequences for the environment), Perceived Vulnerability (personal susceptibility to climate risks, e.g., I feel personally vulnerable to the effects of climate change), Perceived Consequences (expected societal and ecological outcomes, e.g., Climate change will negatively affect public health), and Efficacy Beliefs (beliefs about human capacity to mitigate risks, e.g., Human actions can reduce the impact of climate change) [106,107,62]. To ensure cultural appropriateness, the items were reformulated with wording tailored to the Egyptian context, consistent with the operational definitions of the construct and its four dimensions. Previous research across different cultural settings has consistently demonstrated the suitable psychometric properties of the original version, including high internal consistency, evidence of convergent and discriminant validity, and a stable factorial structure established through exploratory and confirmatory factor analyses [108, 107 ,62,11]. 3.3.2. Self-Regulation Scale – Short Form (SRQ-SF) Carey et al. [17] developed this scale to evaluate individuals’ ability to plan, monitor, and regulate their behavior in pursuing personal goals , when faced with challenging or situations of emotional strain. It is consisted of 31-item derived from the original 63-item Self-Regulation Scale (SRQ) created by Brown et al. [12] and designed to provide a more efficient yet psychometrically robust measure. The SRQ-SF has demonstrated satisfactory internal consistency (e.g., Cronbach’s alpha) and evidence of construct and predictive validity across diverse populations, including adolescents, emerging adults, and adults [80, 81,110,69,72]. 3.3.3. Connor-Davidson Resilience Scale (CD-RISC-25) Connor and Davidson [27] developed this scale to assess resilience, using a 25-item version that evaluates five components: personal competence, tolerance of negative affect, positive acceptance of change, control, and spiritual influences. It has demonstrated a good psychometric property : test-retest reliability, internal consistency (Cronbach’s alpha), and convergent validity with related constructs, as well as cross-cultural validity, particularly in adolescent and youth populations [43,60]. 3.3.4. General Self-Efficacy Scale (GSES) Schwarzer and Jerusalem [82] developed this 10-item scale, which is designed to assess individuals’ beliefs in their capacity to cope effectively with a broad range of stressful situations and challenges. It has been extensively applied across diverse cultural contexts, age groups, and populations, and is available in several language adaptations. The scale consistently demonstrates suitable internal consistency, and evidence of construct and criterion validity in cross-cultural research [61, 91,93,102]. 3.3.5. General Health Scale-28 (GHQ-28) The General Health Scale-28 (GHQ-28), developed by Goldberg and Hillier [41] is a widely used self-report screening scale for identifying minor psychiatric disorders and assessing general psychological well-being in both community and clinical populations [39,41]. The scale comprises 28 items organized into four subscales: somatic symptoms (physical distress), anxiety and insomnia, social dysfunction, and severe depression. It is designed to asses’ short-term fluctuations in mental functioning and to detect early indicators of psychological distress. The scale has been adapted across different cultural contexts, demonstrating satisfactory internal consistency, test–retest reliability, and different forms of construct and convergent validity [68, 109, 39]. 3.4. Scales Adaptation for the Egyptian Sample To make it suitable for the Egyptian culture, all scales were translated into Arabic, reviewed by bilingual experts, and back-translated to verify both linguistic and conceptual accuracy. A two-phase pilot study was conducted. In the first phase, cognitive interviews with 20 students were carried out to assess item clarity and cultural appropriateness. In the second phase, the revised scales were administered to a sample of 200 students equivalent to the main study population. Reliability coefficients (Cronbach’s alpha and split-half) for the scales ranged from α = 0.76 to 0.94. Evidence of concurrent and construct validity was supported by correlations with established psychological instruments and results from exploratory factor analysis [ 34,1]. All responses were measured using a 5-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree.” Table 2 presents the reliability coefficients for each scale, separately for Men and Women (*) . Table 2: The reliability coefficients for each scale across Men and Women participants. Scales Men Women Alpha Spilt Half Alpha Spilt Half Climate Change Risk Perception 0.872 0.761 0.869 0.770 Self-Regulation 0.917 0.844 0.926 0.851 Resilience 0.937 0.890 0.934 0.894 General Self-Efficacy 0.904 0.870 0.920 0.888 Psychological Distress 0.928 0.774 0.935 0.797 (*) The reliability of the subscales for the five study measures was also assessed using both Cronbach’s alpha and split-half methods. Most reliability coefficients were satisfactory, except for the Perceived Likelihood subscale of the Climate Change Risk Perception scale, which demonstrated relatively low reliability, with coefficients around 0.50. 3.5. Data Collection Data were collected over two months during the first semester of the 2024–2025 academic year after obtaining IRB approval and university authorization. Following these approvals, faculty members facilitated access to classrooms across different faculties and study levels. In each classroom, students were invited to participate voluntarily; the study purpose, confidentiality safeguards, and the right to withdraw at any time were explained. Oral informed consent was obtained immediately before administration, and eligibility was confirmed (current enrollment and absence of clinical psychological diagnoses) prior to completing the survey. The inclusion criteria were being an enrolled student at Cairo University during the data collection period, falling within the age range of 18–22 years (emerging adulthood), achieving at least a “Good” grade in the previous academic year, and providing informed consent (or assent, when applicable). Data were gathered using a structured, self-administered printed scales during university hours. Administration was supervised by 15 trained master’s students under the guidance of members of the research team. Each session involved 15–25 participants and lasted approximately 20–25 minutes. Participation was voluntary, and students who preferred not to complete the survey could withdraw quietly without penalty. To protect privacy, responses were anonymously coded. Only minimal missing data were observed, and incomplete scales were excluded. 3.6. Statistical Analysis Data analyses were conducted using IBM SPSS Statistics (Version 25) and AMOS (Version 24) [2, 15]. Descriptive statistics and testing the bias of data were computed. Pearson’s correlation coefficients were calculated to examine bivariate relationships among the variables. Because the study included three moderating variables, structural equation modeling was conducted in AMOS [15, 46], because the analytical capacity of commonly used tools such as Hayes’s PROCESS macro, accommodates a maximum of two moderators [48]. Manual computations were performed to specify and estimate higher-order interaction effects, following recommended approaches for latent and observed interactions in SEM [59, 63]. Prior to the creation of interaction terms, all predictor variables were mean-centered to minimize multicollinearity [46]. Two-way, three-way, and four-way interaction terms were generated in SPSS and incorporated into the AMOS model as observed variables. Moderation analyses proceeded in four hierarchical stages: estimation of main effects, evaluation of two-way interaction effects, evaluation of three-way interaction effects, and evaluation of the four-way interaction effect. This modeling approach allowed for a systematic and comprehensive assessment of both the individual and combined moderating effects [46, 59]. Results 4.1. Descriptive statistics Table 3 displays the descriptive statistics of the study variables for Men and Women participants. Table 3: The descriptive statistics of the study variables For men and women participants Gender Variables Mean Std. Dev Median Kurtosis* Skewness** Men (n= 996) Climate change risk perception 55.32 10.44 56 -0.006 -0.450 Self-regulation 106.73 17.73 108 0.100 -0.164 Resilience 90.37 16.71 90 0.009 -0.193 General self- efficacy 34.81 7.59 35 -0.107 -0.088 Psychological distress 76.10 21.76 76 -0.467 0.209 Women (n= 1069) Climate change risk perception 56.32 9.87 57 -0.216 -0.522 Self-regulation 106.28 18.08 107 -0.050 -0.117 Resilience 89.82 15.81 90 0.027 -0.247 General self- efficacy 33.98 7.74 34 0.038 -0.209 Psychological distress 78.96 22.49 79 -0.625 0.206 * St. Error for kurtosis Men 0.155 Women 0.149 ** St. Error for skewness Men 0.077 Women 0.075 The descriptive statistics in Table 3 for both genders indicate that all study variables, including total scores and subcomponents, are normally distributed. The skewness coefficients for most psychological variables fall within acceptable limits and are not statistically significant, confirming that the data are appropriate for statistical analysis and hypothesis testing. In addition to the large sample size, which further strengthens this conclusion 4.2. Testing the bias of data The results of Harman’s single-factor test indicated that common method bias was not a serious concern in the present data. For males, the first unrotated factor accounted for 21.70% of the total variance, while for females it explained 22.78%. In both cases, these percentages fall well below the commonly accepted threshold of 40% that would suggest substantial common method variance [2,15,37,38]. This suggests that no single factor dominated the variance structure of the data, and therefore the observed relationships among the study variables are unlikely to be artifacts of common method bias. 4.3. Correlation between total scores of study variables Table 4 presents the correlations between the total scores of the study variables among men and women. Table 4: The correlations among total scores of the study variables for men and women Gender Variables Climate change risk perception Self-regulation Resilience General self- efficacy Psychological distress Men N= (996) Climate change risk perception 1 Self-regulation 0.222*** 1 Resilience 0.228*** 0.795*** 1 General self- efficacy 0.020 0.009 -0.018 1 Psychological distress 0.112*** -0.299*** -0.236*** -0.087** 1 Women N= (1069) Climate change risk perception 1 Self-regulation 0.129*** 1 Resilience 0.134*** 0.806*** 1 General self- efficacy 0.062* 0.045 0.062* 1 Psychological distress 0.094** -0.380*** -0.335*** -0.094** 1 * Significant at 0.05 ** Significant at 0.01 *** Significant at 0.001(2 tailed) Table 4 shows the correlations among the study variables for men and women. Climate change risk perception was positively correlated with psychological distress in both groups, indicating that higher perceived climate risks were associated with greater levels of distress. At the same time, self-regulation and resilience displayed strong positive intercorrelations suggesting considerable overlap in their functioning and were both negatively associated with psychological distress, suggesting their protective role. These negative associations were somewhat stronger among women. Self-efficacy, however, showed negligible or weak relationships with the other variables and only minimal correlations with distress. Overall, the pattern highlights that while risk perception is linked to higher distress, psychological resources such as self-regulation and resilience are consistently related to lower distress, with some gender differences in the strength of these associations. 4. 4. Correlations between climate change risk perception and psychological distress Table 5 Presents the correlations between climate change risk perception and psychological distress among Women participants: Table 5: The correlations between climate change risk perception and psychological distress among Men and Women participants Gender Variables Climate change risk perception 1-Perceived Severity 2- Perceived vulnerability 3- Perceived likelihood 4- Efficacy Beliefs Males N= (996) Psychological distress 0.112** 0.128** 0.143 ** 0.006 0.084** 1 - Somatic symptoms 0.185** 0.179** 0.178** 0.120** 0.193** 2 - Anxiety and insomnia 0.079* 0.092** 0.117** -0.019 0.040 3 - Social dysfunction 0.062 .075* .084** -0.009 0.027 4 - Severe Depression 0.048 0.075* 0.091** -0.058 0.024 Females N= (1069) Psychological distress 0.094** 0.084** 0.129** 0.022 0.114** 1 - Somatic symptoms 0.144** 0.122** 0.153** 0.095** 0.126** 2 - Anxiety and insomnia 0.059 0.058 0.106** -0.022 0.082** 3 - Social dysfunction 0.045 0.039 0.068* 0.006 0.081** 4 - Severe Depression 0.068* .063* 0.103** 0.004 0.092** * Significant at the 0.05 level ** Significant at the 0.01 level (2-tailed). According to the information in previous Table 5 , most correlation coefficients between perceptions of climate change risk and psychological distress, including their sub-components, were statistically significant. Given the large sample sizes for both men and women, these correlations reached significance even when the effect sizes were relatively small. In the men’s sample, 16 correlations were significant, while in the women’s sample, 17 correlations were significant. The perceived vulnerability and likelihood showed most consistent correlations with psychological distress, efficacy beliefs were more broadly significant among women than men, and the overall pattern of results did not differ substantially between genders. 4.5.Moderation Analysis The present study aimed to assess the moderating roles of self-regulation, resilience, and self-efficacy, with their interaction effects, in the relationship between climate change risk perception and psychological distress. Moderation analyses were conducted for men and women university students to identify gender-specific patterns and effects. The visual representations of the significant moderation results for men and women are provided in Figures 2 and 3, respectively, which are included in Appendix 1 for reference. 4.5.1. Results of the Men’s sample Table 6 presents the standardized effects of independent and moderating variables among Men participants. Table 6. Standardized Effects of Independent and Moderating Variables Among Men Participants (N = 966) Variables Standardized Estimates(β) Significance (p) Risk perception .127 001 Self-regulation -.319 001 Resilience -.096 001 Self-efficacy .073 007 Risk perception x Self-regulation -.156 001 Risk perception x Resilience -.127 001 Risk perception x Self-efficacy .218 001 Risk perception x Self-regulation x Resilience .070 010 Risk perception x Self-regulation x Self-efficacy -.117 001 Risk perception x Resilience x Self-efficacy .158 001 Risk perception x Self-regulation x Resilience x Self-efficacy .027 .316* *Non-significant - Direct Effects Results showed that higher climate change risk perception significantly predicted increased psychological distress. Each of Self-regulation and resilience had a negative effect, confirming its protective role, and demonstrated a significant attenuating effect. Unexpectedly, self-efficacy was positively associated with distress, indicating that higher self-efficacy slightly exacerbated psychological distress. - Interaction Effects Results showed a significant negative interaction between risk perception and both self-regulation and resilience, suggesting these variables mitigate the psychological impact of climate threats. However, self-efficacy interacted positively with risk perception, unexpectedly intensifying distress rather than reducing it. - Higher-Order Interaction The three-way interaction of risk perception, self-regulation, and resilience was positive significant, indicating that may increase distress, which means a complex interplay. Also, risk perception and resilience combined with self-efficacy amplified distress. In contrast, the combination of self-regulation and self-efficacy with risk perception had a significant negative effect, reflecting a joint attenuating role. The four-way interaction among all variables was non-significant. 4.5.2. Results of the Women’s sample Table 7 presents the standardized effects of independent and moderating variables among women participants. Table 7: Standardized Effects of Independent and Moderating Variables Among Women Participants (N = 1069) Variables Standardized Estimates(β) Significance (p) Risk perception .123 001 Self-regulation -.322 001 Resilience -.194 001 Self-efficacy .121 001 Risk perception x Self-regulation -.038 .158* Risk perception x Resilience -.011 .678* Risk perception x Self-efficacy -.021 .442* Risk perception x Self-regulation x Resilience .032 .234* Risk perception x Self-regulation x Self-efficacy -.161 001 Risk perception x Resilience x Self-efficacy .162 001 Risk perception x Self-regulation x Resilience x Self-efficacy .050 .062* *Non-significant - Direct Effects Among Women, the results indicated that higher climate change risk perception significantly predicted increased psychological distress. Self-regulation had a negative effect, confirming its protective role, and resilience also demonstrated a significant attenuating effect. The unexpected result was the positive association between self-efficacy and distress, indicating that higher self-efficacy was associated with a slight increase in psychological stress. - Interaction Effects The interaction between climate change risk perception and any of the three variables: self-regulation, resilience, and self-efficacy, was non- significant - Higher-Order Interactions The three-way interaction of the climate change risk perception, self-regulation and self-efficacy showed a significant negative relationship, suggesting these variables mitigate the psychological impact of climate threats. However, the interaction between the climate change risk perception, resilience and self-efficacy showed a significant positive relationship as an unexpected finding that amplified distress. The four-way interaction remained non-significant. After presenting the study results, which included Pearson’s simple correlation coefficients and the analysis of the three moderator variables, and considering the statistically significant findings revealed, we now move on to discuss these results and interpret their psychological implications. Discussion Based on the integrative model and the underlying theory adopted in the present study, it is possible to interpret and understand the associations of climate change risk perception with psychological distress among emerging adults. The transactional perspective explains how stress outcomes result from the interaction between how people assess threats and the coping resources they adopt [56]. The resilience portfolio Model focuses on protective resources that support positive adaptation [44, 43]. These propositions provide a framework for understanding how personal and contextual factors shape the correlation between perceived climate risks and psychological distress. We will discuss the results of each hypothesis in the next section according to previous research results and theoretical models. According to the first hypothesis that proposed a positive correlation between climate change risk perception and psychological distress, the results of correlation coefficient confirmed partly this expectation. There was a modest significant positive relationship between the two variables in both genders. This means that emerging adults who view climate change as a serious threat or risk tend to experience higher levels of psychological distress. These findings are consistent with the results of previous research showing that heightened awareness of environmental risks correlate to negative mental health outcomes, including fear, anxiety, stress, and depressive symptoms [14,24, 80]. Some empirical studies support that climate-related worry was significantly correlated with psychological distress, and others showed that exposure to climate change effects predicted increased worry and poorer well-being [83,73,4]. These findings consisted with regional evidence suggesting that adolescents and emerging adults in Egypt also display growing vulnerability to eco-anxiety [47,34]. This result must see according to proposition that the relationship may varies across different cultural contexts. This suggests that the predictive ability of risk perception depends on factors such as cultural norms, traditions, political attitudes, value system, and the perceived immediacy of climate impacts [88,84]. Climate change threats may appear less immediate in some places like Greater Cairo, than in coastal or rural regions, perceptions of risk may not consistently cause severe psychological distress. These findings assert that climate change risk perception is an important variable but not exclusive determinant of psychological distress. The second hypothesis proposed that the moderating role of self-regulation, resilience, and self-efficacy, predicting that higher levels of these resources would weaken the relationship between climate change risk perception and psychological distress independently. The results consisted with this hypothesis by demonstrating that each moderator exerted significant independent effects. Self-regulation as a protective factor, may support the findings that people who exhibit higher executive control and intentional regulation exhibit lower emotional reactivity to climate-related threats [101, 26]. This suggests that regulatory skills help emerging adults to reframe threatening appraisals and employ constructive coping strategies. Resilience likewise showed a protective effect, consistent with evidence that resilience enables adaptive adjustment and reduces vulnerability to eco-anxiety [50, 83]. Finally, self-efficacy independently moderated the relationship, some studies [119 ,89] emphasized the role of efficacy beliefs in reducing helplessness and fostering adaptive responses. Overall, the evidence supports the view that each psychological resource serves as an independent adaptive asset. They converge with previous studies that emphasized the buffering capacity of self-regulation, resilience, and self-efficacy when examined separately [16,43,45,66]. At the same time, the absence of significant higher-order interaction effects suggests developmental or contextual limits emerging adults’ ability to mobilize these resources simultaneously. According to the third hypothesis individuals with high levels of self-regulation, resilience, and self-efficacy integrally would exhibit a protective effect when facing threats . Contrary to this expectation, the results revealed no significant evidence of higher order moderation between the three moderator variables. This absence of integrative effects may reflect some developmental constraints in adolescence and emerging adulthood. According to developmental theory, using different coping strategies together requires mature executive and emotional integration, which may not yet be fully developed at this stage [29, 84]. Instead, emerging adults may rely on discrete coping strategies rather than integrating them in a cohesive manner. These results diverge from interaction-based models that assume additive or multiplicative benefits when protective resources combine. Rather, they are consistent with studies that question whether such synergies operate universally in younger populations, particularly in adolescent and emerging adult groups. [101, 26]. The implication is that while each resource is protective, interventions should focus on strengthening them individually rather joint activation will produce amplified effects in emerging adults. The results supported the expectation of fourth hypothesis that gender differences play an important moderating role in the effects of self-regulation, resilience, and self-efficacy on the relationship between climate change risk perception and psychological distress. These psychological resources function differently across genders. This illustrate that there is a distinct mechanism shaped by socialization patterns, emotion regulation styles, and cognitive appraisals . Men exhibited more significant moderating interactions between internal resources and perceived environmental threat. In contrast, women showed fewer significant moderation interactions and more consistent linear patterns, possibly reflecting higher emotional sensitivity and lower executive integration during emerging adulthood [25,16]. Previous research aimed to investigate coping strategies in face of environmental stress, and climate threats assert the gender differences. Women apply emotion-focused approaches such as rumination in general, whereas men tend to adopt task-oriented or distancing strategies [23,24]. These patterns are shaped by sociocultural context in the Egyptian society, where gender norms strongly influence emotional expression and coping behaviors in different situations [34]. The socialization of women enabled her to express vulnerability and seek support, while socialization encouraged men to display restraint and independence, illustrating the gender gap in the use of psychological resources [101, 84]. Contrary to Bandura’s model [5] an unexpected finding was related to self-efficacy, that was positively correlated with distress among women. This conception may indicate a contradictory between strong efficacy beliefs and limited real-world opportunities for climate action [ 9, 119]. When perceived responsibility exceeds perceived control, self-efficacy may generate frustration, overload, or internalized pressure, producing “motivated helplessness” [62, 99]. In such cultural contexts, self-efficacy may amplify distress rather than attenuating it, emphasizing the contextual dependency of psychological resources. The developmental appropriateness is an important factor in the interpretation of results as the study focuses on a life stage characterized by emerging regulatory capacities and limited integration of emotional experiences. During emerging adulthood, cognitive control, emotional regulation, and moral reasoning are still developing, which may restrict the ability to process complex and abstract threats such as climate change [29, 66]. The peer dynamics in social interactions have a marked influence on emerging adults and often lead them to display heightened emotional reactions. As a result, they become more vulnerable to negative emotions or disengagement when they perceive limited support for climate action. [24]. These results highlight the need for age-specific theories and measurement tools that interpret how youth perceive and cope with environmental threats [84, 101]. Perhaps, these developmental considerations are associated with the characteristics of the study’s sample, which consisted of Egyptian university students in emerging adulthood. This age group faces different demands and life challenges, including academic demands, career ambiguity, and high exposure to climate discourse through formal education, especially students in the practical colleges [ 40,76]. Such factors may intensify both the perception of climate risks and the psychological distress associated with them. They may have access to knowledge and cognitive resources comparing with their non-student peers. This means that their coping strategies may not represent the broader youth population. These sample-specific characteristics highlight the need for caution in generalization. So, such results reinforcing the importance of tailoring climate–mental health research to the lived realities of distinct subgroups within emerging adulthood [24,91]. The findings may also be interpreted considering broader cultural and contextual realities in Egypt. Psychological resources such as self-regulation and resilience are not culturally neutral in many Egyptian contexts. Self-regulation is often viewed as self-restraint or obedience rather than adaptive flexibility strategy [34, 66]. Resilience in the other side may characterize more by endurance than by active coping strategies. Likewise, self-efficacy may be experienced less as personal confidence and more as an internalized moral obligation to succeed or remain strong, particularly within academic and familial domains. These culturally shaped meanings may help explain why psychological strengths did not consistently act as an expected and, in some cases, intensified emotional conflict rather than reducing it [24,21]. In line with this conclusion, how Egyptian culture mediates individual and collective psychological resources? Personal resources like resilience and self-efficacy may interact with community-level resources such as resilience and collective efficacy [96,119] In light of Egypt’s cultural emphasis on social cohesion and mutual interdependence., communal coping may often take precedence over individual strategies [34, 26]. Acceptable responses to adversity shape by Socialization norms including climate-related threats [47]. These dynamics may help explain why individual resources were not enough, and at times were associated with greater distress [24]. The lack of social and community-level moderators that act at broader ecological levels may reflect the absence of the higher-order moderating effect. Programs that simultaneously enhance individual coping skills and strengthen community cohesion—through environmental education, civic participation, and localized climate initiatives—may be especially effective in reducing climate-related psychological distress and promoting sustainable adaptation [88, 71,20]. The present study supports the integrative framework that combines the Transactional Model of Stress and Coping [56] with the Resilience Portfolio Model [44, 43]. In line with the transactional model, the positive correlation between climate change risk perception and psychological distress confirms that perceiving a severe climate change and uncontrollable threat can increase emotional discomfort [24, 80]. At the same time, the moderating roles of self-regulation, resilience, and self-efficacy reflect the importance of secondary appraisals, whereby individuals evaluate their coping resources to determine whether they can manage perceived threats [26, 101]. These psychological resources functioned more effectively as independent moderators. This is consistent with the Resilience Portfolio perspective, which views protective assets as distinct components, each of them contributes separately to adaptation. Such assets may not always interact synergistically, especially during adolescence and emerging adulthood, when executive and emotional systems are still maturing [29, 84]. Furthermore, the observed gendered patterns underscore the contextual nature of stress and resilience processes, interpreting how sociocultural norms influence the accessibility, use, and impact of psychological resources [84 ,50]. Taken together, these findings demonstrate that the proposed integrative model provides a coherent and culturally sensitive explanation of how climate change risk perception translates into psychological distress, while also clarifying the moderating roles of key psychological capacities across developmental and gendered contexts. Theoretical Implications There are some important theoretical implications that the present study carries for enhancing the area of climate change psychology. First, the correlation found between climate change risk perception and psychological distress supports Lazarus and Folkman’s Transactional Model of Stress [56] and the Resilience Portfolio Model [44, 43]. Accordingly. climate-related threats act as primary appraisals, and distress occurs when people believe their coping resources are not enough. This means that climate change functions both as an environmental event and as a psychologically interpreted stressor integrated into daily meaning-making. Second, the moderating roles of self-regulation, resilience, and self-efficacy support the Resilience Portfolio Model [44,43], which views adaptive outcomes as shaped by distinct yet related assets. Specifically, self-regulation aids cognitive flexibility, resilience promotes recovery, and self-efficacy strengthens a sense of agency [26,101]. Third, the results emphasize the importance of context-sensitive models, where interactions differ according to factors such as age, culture, and the duration of stress exposure [29,84]. Fourth, the study adds a gendered and cultural dimension to future studies, especially in non-western countries( ). Practical Implications The present findings carry some practical implications that are especially relevant for the Egyptian and broader Arab context. The protective roles of self-regulation and resilience emphasize the need for university-based programs that incorporate stress management, resilience training, and problem-solving workshops into student support services [30,68]. Initiative efforts may include, peer-support networks, counseling units, and campus-led can offer structured spaces for building coping skills and sustain emotional stability emerging adults [29,84]. Considering that the complex role of self-efficacy sometimes increases rather than reduces distress, indicating the need for culturally sensitive and realistic interventions. Self-efficacy is shaped in the Arab societies, in general and especially in Egypt by family expectations, social reputation, and moral duty [34]. Enhancing efficacy should emphasize realistic, value-based opportunities, such as community volunteering and student-led environmental projects, that translate personal agency into collective action [91,119,21]. Interventions should put into consideration the central role of family and community that foster collective resilience [24]. Awareness programs grounded in religious and cultural values of stewardship can strengthen both acceptance and impact [24]. Integrating climate–mental health initiatives into national strategies such as Egypt’s Vision 2030 and the National Climate Change Strategy ensures sustainable alignment with WHO, IPCC, and UNESCO recommendations [52,53,103,117,118], may help designing future programs for mitigation and adaptation. Overall, the empirical findings with culturally grounded strategies can help reduce climate-related mental health risks among Egyptian and Arab youth. Limitations This study has several limitations. First, The cross-sectional correlational design limits causal interpretation for the direction of relationships among climate change risk perception, psychological distress, and the moderating roles of self-regulation, resilience, and self-efficacy. So, coming studies are needed to adopt longitudinal and experimental designs to clarify causal pathways. Second, the non-random convenience sample of Cairo University students may not represent the broader diversity of Egyptian youth, which limits generalizability, Third, social desirability in the self-report measures may cause biases in findings. So, it is important to rely on behavioral and physiological indicators to improve validity. Fourth, despite cultural adaptation, constructs like self-regulation, resilience, and self-efficacy may carry distinct cultural meanings in Egypt related to obedience or endurance. Qualitative and mixed-method approaches are needed to confirm conceptual equivalence. Fifth, factors such as prior mental health status, socioeconomic background, and exposure to climate-related information may have confounded the observed relationships. Therefore, these variables should be controlled for in future research. Finally, the focus on individual-level moderators may ignore the broader social and structural factors such as social support, collective efficacy, and economic or political contexts that also contribute to shaping psychological well-being. Above all, using qualitative and mixed-method approaches are important to confirm conceptual equivalence. Future Research Recommendations Future studies should investigate the vital subjects by integrating the longitudinal and mixed-method designs behavioral, qualitative, and physiological data in methodology. Research should also examine collective efficacy, coping styles, environmental values, family influence, and culturally specific coping strategies as additional moderators. Also integrate individual and collective resources Interdisciplinary collaboration across psychology, environmental science, and public health is essential to develop culturally and developmentally appropriate interventions. unmeasured confounding (e.g., prior mental health, socioeconomic status, media exposure) must be considered. Based on these directions, several key research questions emerge for future investigation Are there a specific developmental stage do self-regulation, resilience, and self-efficacy begin to interact synergistically rather than independently? What mechanisms explain the paradoxical finding that self-efficacy may amplify distress, particularly among women? How do coping strategies such as rumination, avoidance, or problem-focused engagement mediate the relation between climate risk perception and distress? What is the relationship between climate change risk perception and climate change denial among emerging adults? What are mediators between climate change risk perception and climate change denial? How do climate change risk perceptions and psychological distress influence each other over time? What longitudinal patterns can be observed concerning the relationship between climate change risk perception and climate change denial among emerging adults. How can multi-method approaches (e.g., behavioral, physiological, and qualitative scales) improve the validity of research on climate-related psychological adaptation? How do collective-level resources, such as community resilience and institutional trust, combine with personal traits to buffer psychological distress in Egypt and similar Global South settings? Declarations Ethics Approval and Consent to Participate The authors received ethical approval from the Research Ethics Committee at Cairo University according to the study proposal and was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (1964) and its subsequent amendments, which emphasize respect for human dignity, autonomy, and the protection of participants’ well-being. Verbal informed consent was obtained from all participants prior to each session, in alignment with these ethical standards, after they had been fully briefed on the importance of scientific research and the assurance of confidentiality. The use of verbal rather than written consent was approved by the ethics committee due to the minimal-risk nature of the study and the absence of sensitive or identifying information. Consent for Publication Not applicable Availability of Data and Materials The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Competing Interests The authors declare that they have no competing interests. Funding This research was funded by the General Administration of Scientific Research at Cairo University . Authors' Contributions All authors collaboratively formulated the research problem, conducted the literature review, structured the scientific content, and determined the research methodology and procedures. Eman Swelam, and Eman Abdallah coordinated and supervised data collection and verified the accuracy and integrity of the dataset. Osama Abosree conducted the statistical analyses and contributed to data interpretation and descriptive reporting, in collaboration with Hamed Ead and Attia El-Tantawy. 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Hollenstein (Eds.), Emotion regulation: A matter of time (pp. 87–108). Routledge. https://doi.org/10.4324/9781351001328-6 Additional Declarations No competing interests reported. Supplementary Files AppendixA.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:13:16","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":234545,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8340234/v1/23b98b85e884d6f9c0964ad3.html"},{"id":99790909,"identity":"597d4918-8bf0-4810-9dfa-a05a21e91503","added_by":"auto","created_at":"2026-01-08 12:58:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32272,"visible":true,"origin":"","legend":"\u003cp\u003eThe Moderating Roles of Self-Regulation, Resilience, and Self-efficacy in the Relationship Between Climate Change Risk Perception\u003c/p\u003e\n\u003cp\u003eand Psychological Distress in Emerging adults.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8340234/v1/55ae72f29f7add3c4f2e57a1.png"},{"id":102964010,"identity":"dea5995f-5516-4bb2-9d8c-a69df126ef28","added_by":"auto","created_at":"2026-02-19 04:21:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2823807,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8340234/v1/ce733ae1-5a1b-44f5-adf8-f4c5f1494909.pdf"},{"id":99515436,"identity":"31816f20-2219-4510-b24d-87d540b90ef0","added_by":"auto","created_at":"2026-01-05 10:13:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":230382,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340234/v1/454e2bd9ad5634cef71d78b0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Integrated Moderation Model of Climate Change Risk Perception and Psychological Distress: The Roles of Self-Regulation, Resilience, and Self-Efficacy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClimate change is one of the significant global challenges in the present era, which has a negative impact on the environmental, economic, social, psychological, and political domains. Its consequences extend beyond Environmental deterioration and loss, profoundly affecting human health and well-being [53, 28,14]. Rising temperatures, extreme weather events, and long-term ecological disruptions pose existential risks to communities worldwide\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e[8,114,117]. Surpassing the 1.5 \u0026deg;C warming threshold is projected to result in potentially irreversible outcomes such as sea-level rise, biodiversity loss, and the degradation of aquatic ecosystems [8,60, 120]. Although the Arab region contributes minimal level to global emissions, it remains vulnerable to climate-related risks, including floods, forest fires, desertification, and extreme weather events [1, 33,114]. Egypt, and neighboring countries in the Gulf and North Africa, has already begun to experience severe adverse effects [51, 47].\u003c/p\u003e\n\u003cp\u003eClimate change exerts multifaceted effects on human health and well-being, extending beyond environmental damage to include both physical and mental health consequences [18, 31]. Rising temperatures, extreme weather events, and long-term environmental disruptions contribute to heat-related morbidity and mortality, cardiovascular and respiratory diseases, malnutrition resulting from food insecurity, and the re-emergence or spread of infectious diseases through altered ecosystems, are the most important manifestations of physical health [73, 18]. Climate change has affected mental health which manifested as heightened fear of the future, increased anxiety, future depression, post-traumatic stress disorder, insomnia, and reduced psychological well-being, particularly among populations repeatedly exposed to climate-related disasters [10, 24,99,115,116].\u003c/p\u003e\n\u003cp\u003eAccordingly, climate change has a double physical and mental health effects, emphasizing the need for integrated adaptation and mitigation strategies to protect populations public health, particularly\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eamong adolescents and young adults. In this context, perceived climate risk is an essential determinant of emotional and behavioral responses to environmental threats. Individuals who perceive climate change as serious threats or \u003cstrong\u003eNear-term\u0026nbsp;\u003c/strong\u003erisks\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ereport higher levels of psychological distress, including anxiety, worry, and depression. On the other hand, individuals who perceive themselves as less vulnerable tend to downplay these risks or even deny them [24,98].\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAs a result, risk perception predicts eco-anxiety\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand climate-related distress, shaping coping patterns from adaptive engagement to maladaptive avoidance and denial [97,89].\u003c/p\u003e\n\u003cp\u003eClimate change risk perception has been associated with a wide range of negative mental health outcomes among, late adolescents and young adults [13,14,47]. This developmental stage \u003cstrong\u003eis characterized by increased\u0026nbsp;\u003c/strong\u003eemotional sensitivity and identity formation,\u0026nbsp;which may make individuals more vulnerable to environmental threats\u0026nbsp;[74,75,18].\u0026nbsp;These emotional distresses\u0026nbsp;such as fear, anxiety, depressive symptoms, and\u0026nbsp;\u003cstrong\u003ereduced\u0026nbsp;\u003c/strong\u003ewell-being,\u0026nbsp;underscoring the significance of understanding how perception of climate risk correlates to psychological distress, particularly among young adults [10, 82,49,24].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Individual psychological resources underscore a vital role in shaping how people cope with perceived climate change risks and how they can adapt to them or mitigate across different contexts and populations. Resilience helps young adults\u0026rsquo; recovery and adaptation in the face of environmental stressors, enabling individuals sustain functioning when confronted with climate-related adversities [104]. Self-regulation also supports the control of excessive emotional responses and facilitates constructive responses to ambiguity, that minimizing the risk of maladaptive coping strategies such as denial or avoidance [67, 45]. Also, self-efficacy fosters proactive coping and engagement in adaptive behaviors, including sustainable practices and community-level actions [6, 40].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile these psychological resources are often studied separately, some studies emphasize the importance of exploring their interaction. For example, resilience and self-efficacy have been shown to work together in reducing climate anxiety and promoting adaptive engagement [78, 11]. Similarly, self-regulation represents a crucial resource that links climate change risk perception to both emotional stability and adaptive psychological responses to environmental threats [80]. This perspective extends beyond such individual protective factors and provides a more understanding of how multiple psychological resources jointly influence adaptation to climate hazard or risks.\u003c/p\u003e\n\u003cp\u003eUnderstanding climate change risk perception is crucial for understanding the psychological impact of environmental threat and for guiding culturally appropriate intervention in vulnerable contexts. Emerging evidence from Egyptian context indicates that eco-anxiety and climate change\u0026ndash;related worry are associated with increased psychological problems and decreased well-being among young populations in adolescence and early adulthood [77, 64]. \u0026nbsp;Additional cross-national studies further demonstrate that climate change knowledge and attitudes are significantly linked to psychological distress among university students across Arab contexts, including Egypt, Jordan, and Saudi Arabia [36,1,33]. Together, these findings illustrate the importance of understanding how risk perception affects mental health outcomes within sociocultural settings that are vulnerable to climate risks, and poorly represented in research [19 ,22].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to the study aim and hypotheses, there are four research gaps that can be inferred from the findings of previous studies.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eFirst, most studies have investigated the moderating role of one or two resources only, offering lack of insight into how these factors may jointly shape this relationship [11]. Second, despite consistent evidence that men and women differ in their climate risk perceptions and emotional responses, research on gender differences in the relationship between climate risk perception and psychological distress considering psychological resources remains scarce, [24,101]. Third, adolescents and emerging adults are the most vulnerable groups to climate-related psychological impacts. Developmental changes in identity, cognition, and emotion make them particularly susceptible to eco-anxiety and climate-related psychological distress when confronted with increased risk perception [ 82, 3]. Forth, empirical work in the Egyptian and broader Arab context is limited, even though these regions are vulnerable to climate-related risks and their psychological consequences [112, 111].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBy addressing these four gaps, the study provides theoretically grounded evidence on the psychological variables linking climate risk perception to psychological distress and offers insights for psychosocial interventions and policy measures that may strengthen emerging adults\u0026rsquo; capacity in the face of climate change threats [105, 35].\u003c/p\u003e\n\u003cp\u003eIt is essential to situate the study within relevant psychological theories or theoretical framework that explains how and why these relationships emerge, and how they operate in practice. Relevant perspectives include resilience frameworks [65], social-cognitive theory concerning self-efficacy [6], and theoretical models of self-regulation, particularly self-determination theory [95]. This theoretical framework enhances the conceptual clarity and situates the study\u0026rsquo;s contribution to the field. Finally, integrating insights from stress and coping models highlights the importance of placing these individual-level perspectives within a general explanatory framework [56, 54, 44]. Therefore, the present study is based on the following theoretical framework.\u003c/p\u003e"},{"header":"Theoretical Framework","content":"\u003cp\u003eThis theoretical framework guiding the present study by focusing on the relationship between perceived climate change risk and psychological distress from one side and the moderating effects of self-regulation, resilience, and self-efficacy from the other side. It draws upon established theories and prior empirical evidence to develop the proposed conceptual model (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1. Perception of Climate Change Risk and Psychological Distress\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerception of climate change risks shape how individuals understand environmental threats and determine their emotional and behavioral reactions to these threats [57]. This area has gained growing attention in climate psychology [22,88]. While some studies report positive correlations between risk perception and psychological distress [28], others find weak or non-significant correlations [90, 74]. Longitudinal research showed reciprocal and evolving relationships between climate awareness and eco-anxiety,\u0026nbsp;\u003cstrong\u003eshowing evidence of the mixed results of these associations over time\u003c/strong\u003e [57,58]. Other research demonstrated that extreme weather experiences and\u0026nbsp;environmental sensitivity significantly predicted increased risk perception; however, its correlations with distress yielded mixed results\u0026nbsp;[31].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClimate risk perception may be related to behavioral engagement than to emotional distress [62, 92]. Some cross-cultural analyses indicate that higher perceived risk may associated with climate activism or pro-environmental behaviors instead of increased anxiety or worry [90]. These mixed findings emphasize the influence of cultural, contextual, and methodological factors, \u003cstrong\u003ewhich in turn limit\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe external validity\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eor\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003erestricting the generalizability\u003c/strong\u003e of findings across different societies [85,105].\u003c/p\u003e\n\u003cp\u003eTheoretical perspectives help explain these discrepancies between previous \u0026nbsp;results. Self-Determination Theory [95,94], Terror Management Theory [42], and Cognitive Appraisal Theory [56] emphasize the role of existential threat appraisals, perceived control, and personal traits in shaping psychological responses. Given their ongoing identity formation and developmental changes in cognition and emotion, young youth appear more vulnerable [24]. Collectively, this evidence underscores the need to consider both individual differences, cultural contexts and community factors when examining how climate risk perception correlates with psychological distress [86].\u003c/p\u003e\n\u003cp\u003eMost previous research in Egypt,\u003cstrong\u003e\u0026nbsp;have focused on attitudes, awareness, beliefs and public awareness rather than the psychological impacts of climate change.\u003c/strong\u003e In addition, \u003cstrong\u003eresearch on its mental health effects remains limited, particularly among adolescents and emerging adults. This gap\u0026nbsp;\u003c/strong\u003ehighlights\u003cstrong\u003e\u0026nbsp;the need for climate psychological research in different cultural contexts [10, 49, 34].\u003c/strong\u003e Consequently, the present study examines how the perception of\u003cstrong\u003e\u0026nbsp;climate change risk relates to psychological distress considering individual resources among younger populations, where gender, age, education, and cultural context,\u0026nbsp;\u003c/strong\u003ecollectively\u003cstrong\u003e\u0026nbsp; shape vulnerability.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. The Roles of Moderator Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelf-regulation, resilience, and self-efficacy\u0026nbsp;\u003c/strong\u003eare critical in\u003cstrong\u003e\u0026nbsp;shaping how individuals perceive climate risks, regulate emotions, and maintain adaptive functioning.\u0026nbsp;\u003c/strong\u003eCollectively, these resources form\u003cstrong\u003e\u0026nbsp;a basis for understanding their moderating role in the relationship between climate change risk perception and psychological distress.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1. Moderating Role of Self-Regulation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-regulation is the ability to manage emotions, thoughts, and behaviors in a systematic manner. Therefore, it functions as an important moderator variable may modify the relationship between climate change risk perception and psychological distress. Self-regulation skills often enable adolescents and emerging adults experience lower levels of distress even when perceiving higher climate risks levels, they respond with adaptive coping strategies such as mindfulness and cognitive reappraisal [113, 26,67] Self-Determination Theory, suggest that\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eindependence and competence enhance the capacity to manage long-term stressors by enhancing intrinsic motivation and adaptive coping behaviors [95]. Therefore, self-regulation may moderate the relationship between risk perception and psychological distress by helping young adults to reinterpret environmental threats and use adaptive strategies such as reappraisal [100, 29].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEmerging adults with high self-regulation capacities tend to utilize adaptive coping strategies, such as reappraisal and problem-solving. This reduce the emotional burden of environmental stressors [110,70]. Similarly, self-regulation predicted more effective emotional adjustment and lower psychological distress across stress-inducing contexts, including environmental threats. Evidence from longitudinal research indicates that self-regulation protects against the escalation of stress into chronic distress, especially when individuals face ambiguity or unpredictable conditions [67, 32].\u003c/p\u003e\n\u003cp\u003eDespite this theoretical and empirical foundation, most research has investigated self-regulation as a psychological resource in applied developmental or clinical contexts rather than in relation to climate change risk perception. Research examining the moderating effect on climate-related psychological distress is still scarce. Most previous studies emphasize resilience and coping more broadly, with approximately low contribution of self-regulatory processes in this area [24, 79]. Evidence from Arab and Egyptian cultural contexts is particularly insufficient, with available studies focusing on awareness, adaptation, or descriptive accounts of eco-anxiety rather than testing that psychological resources [34]. This gap emphasizes the importance of exploring self-regulation as a specific moderating factor in the relationship between climate risk perception and psychological distress among young people in vulnerable cultural settings like Egypt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2. Moderating Role of Resilience\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResilience is an important moderating factor that may mitigate psychological distress among emerging adults who perceive climate risks. \u0026nbsp;That means, resilience is the ability to adapt, endure, and recover from adverse circumstances and stressful events. Resilient individuals often employ proactive coping strategies, including problem-solving and seeking social support [114]. For example, they may transform emotional distress into constructive responses such as climate activism or prosocial engagement, which, in turn reduces feelings of helplessness and promoting a sense of meaning and purpose. Resilience further enables individuals to cognitively reinterpret stressors in more adaptive ways, \u0026nbsp;thereby providing additional protection for mental health\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e[105, 58].\u003c/p\u003e\n\u003cp\u003eResearch consistently shows the mitigating role of resilience against psychological stressors, including those stemming from climate threats [43, 44]. Late adolescents and emerging adults with higher resilience are better able to manage the psychological consequences of climate change. They use proactive coping strategies, such as focusing on positive outcomes and seeking social support. Such adaptive responses help individuals to maintain emotional stability and well-being in the face of climate-related stressors [81, 114, 104]. Cross-cultural findings indicate that resilience not only reduces levels of anxiety but also enhances collective efficacy, motivating young people to engage in community-based adaptation efforts [105].\u003c/p\u003e\n\u003cp\u003eThis interpretation is consistent with\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003ethe Positive Adaptation in Context framework, which conceptualizes resilience as a dynamic developmental process shaped by the interaction between individual capacities and environmental resources.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eAccording to this model, resilience develops when individuals use both their personal strengths and external resources to adapt positively to major challenges such as climate-related threats, thereby reducing the impact of risk exposure on mental health [43, 44].\u003c/p\u003e\n\u003cp\u003eEvidence from developmental and disaster psychology indicates that a research gap remains. Few studies have directly examined the moderating role of resilience in the relationship between climate change risk perception and psychological distress. Available research has focused on general stress, trauma, or natural disaster contexts rather than on climate change specifically [105, 104]. Furthermore, while studies from Europe and North America have begun to examine how resilience mitigates eco-anxiety and climate-related worry, evidence from Egypt and the wider Arab region, is still limited [34, 47]. Although resilience is widely acknowledged as a protective factor, its specific role as a moderator in the psychological pathways linking perceived climate risks to distress among emerging adults in vulnerable cultural contexts has not been systematically examined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3. Moderating Role of Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-efficacy is the belief in one\u0026rsquo;s ability to effectively perform the behaviors needed to attain specific outcomes [5,6]. It has been consistently correlated to lower psychological distress in the context of climate threats. Emerging adults with higher self-efficacy are more likely to adopt active coping and advocacy behaviors that strengthen their sense of control [94]. Such confidence handle\u0026rsquo;s anxiety and encourages engagement in sustainable practices, including reducing carbon consumption and promoting peer education. Self-efficacy also enables individuals to view environmental challenges as opportunities for growth and success [95,40,119]. Therefore, interventions aimed at enhancing self-efficacy may help alleviate climate-related distress by fostering individuals\u0026rsquo; adaptive psychological resources [85, 102].\u003c/p\u003e\n\u003cp\u003eAccording to Bandura\u0026rsquo;s Social Cognitive Theory [7,6], beliefs in one\u0026rsquo;s efficacy regulates cognitive, emotional, and behavioral responses to challenges. In this model, emerging adults have a strong self-efficacy perceive threats as manageable, activate personal agency, and employ adaptive coping strategies, hence moderating the negative emotional effects of risk perception [26].\u003c/p\u003e\n\u003cp\u003eThe emerging adults possess self-efficacy skills \u0026nbsp;reported lower climate anxiety and greater engagement in adaptive responses such as activism and sustainable practices in face of climate threats[8]. Consistently, some findings \u0026nbsp;conclude \u0026nbsp;that interventions designed to enhance self-efficacy was significantly associated with distress among students facing environmental stressors [85]. Other studies further found that self-efficacy promotes resilience by promoting optimism and perceived control in the face of climate-related uncertainty [ 5,40].\u003c/p\u003e\n\u003cp\u003eDespite these results, most evidence comes from different cultural \u0026nbsp;contexts, with limited exploration in Arab societies. Research in Arab region and especially Egypt has focused primarily on climate awareness, policy engagement, or descriptive accounts of eco-anxiety [34, 47], without examining self-efficacy as a moderator. This gap emphasis the importance of investigating its \u0026nbsp;moderating role in the relationship between climate risk perception to psychological distress among emerging adults in the Egyptian contexts. Addressing this issue is essential for developing culturally grounded interventions that enhance agency, reduce vulnerability, and strengthen resilience in the face of climate threats.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Gender Differences\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGender differences offering important insight into how emerging adults respond to climate change risks. In general women report higher climate risk perception .Young women display stronger climate anxiety and greater willingness to engage in mitigation behaviors[19, 87]. Men often adopt problem-focused coping strategies and report less emotional distress due to prevailing social norms[121,16,76].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Men often show stronger emotional self-regulation under stress [12\u003cspan dir=\"RTL\"\u003e2, 66],\u0026nbsp;\u003c/span\u003ewhereas women may benefit more from interventions aimed at strengthening self-regulation and resilience [26]. Gender differences are also evident in self-efficacy: men tend to report\u0026nbsp;stronger belief in one\u0026rsquo;s ability to act effectively, while women more often rely on relational efficacy, gaining\u0026nbsp;confidence through social relationship\u0026nbsp;and support systems [16, 35]. These findings suggest that psychological resource operate\u0026nbsp;through gender-based coping patterns and strategies, in moderating the relationship between climate risk perception and psychological distress [87, 101,121].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnderstanding how gender differences shape the combined moderating roles of self-regulation, resilience, and self-efficacy in the relationship between climate risk perception and psychological distress arises as a notable gap needs further investigations [16, 25,101]. While some previous research has documented a discriminant gendered patterns in climate anxiety and engagement, investigations that integrate these moderators in the same study remain scarce\u003cspan dir=\"RTL\"\u003e.\u0026nbsp;\u003c/span\u003eSome previous studies have investigated the three moderating roles of the three psychological resources individually in isolation, which shortens our understanding of their interactive effects [ 26, 40, 45,58,104]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis gap is more pronounced in local literature. Research has primarily addressed climate awareness, adaptation policies, or eco-anxiety descriptively [34],\u0026nbsp;\u003cstrong\u003ewithout a focus on gender-specific psychological patterns\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eTraditional gender roles strongly shape how people express emotions and deal with challenges [87,16]. Therefore, addressing this knowledge gap is important to identify gender-specific pathways in the relationship between climate change risk perception and psychological distress along with its moderator resources and develop culturally appropriate interventions for vulnerable groups\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003ein different cultural contexts [25].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Integrated Moderating Effects of Self-Regulation, Resilience, and Self-Efficacy\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;In the integrative proposed framework, self-regulation, resilience, and self-efficacy are viewed as interrelated psychological resources that together contribute to buffer the mental health effects of climate change risk perception and adaptive functioning [14,18]. Self-regulation helps individuals to manage emotional responses and maintain psychological balance in confronting climate stressors [26,67]. Resilience represents the capacity to adapt over time, recover from adversity, and help maintain functioning during long-lasting challenges [104,105]. In accordance self-efficacy means confidence in one\u0026rsquo;s ability in adopt proactive coping strategies and engaging effectively with climate change demands [119, 9].\u0026nbsp;\u003cstrong\u003eThese resources together form a broader psychological system\u003c/strong\u003e that supports both short-term adjustment and long-term adaptation [85, 54, 58].\u003c/p\u003e\n\u003cp\u003eAlthough climate-related mental health has received increasing attention [64,83], few studies have examined these moderators together.\u0026nbsp;\u003cstrong\u003eResearch findings clearly indicate that eco-anxiety and climate-related distress are prevalent among adolescents and young adults.\u003c/strong\u003e [24,28]. Little evidence exists on how these psychological resources interact in moderating the relationship between climate change risk perception and psychological distress within Arab\u0026nbsp;Egyptian\u0026nbsp;contexts. Existing work tends to examine self-regulation, resilience, or self-efficacy in isolation manner, yielding fragmented and context-specific insights in different cultures [2\u003cspan dir=\"RTL\"\u003e6\u003c/span\u003e,40]. For instance, resilience seems as a protective factor in European and North American samples [81], while self-efficacy presents a predictor of adaptive coping in African and Arab region, and self-regulation as essential for reducing distress [51, 67].\u003c/p\u003e\n\u003cp\u003eThe Integrative Model of Psychological Adaptation helps explain and connect these fragmented perspectives [66,88]. It suggests that adaptive responses to chronic stressors such as climate change involve dynamic interactions among regulatory, adaptive, and agentic resources, which collectively promote stability, regulation, and agency [35, 98, 91]. In addition, few studies have investigated these factors together in the climate domain, and cross-cultural validation in the Arab world remains particularly limited. To guide the present study and the development of its hypotheses, the following section outlines the underpinning theoretical frameworks that explain how individuals appraise stressors and mobilize psychological resources to cope with climate-related threats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Underpinning Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLazarus and Folkman\u0026rsquo;s Transactional Model of Stress and Coping emphasizes that stress arises not simply from external events but from the dynamic interaction between the individual and the environment, mediated by cognitive appraisal processes [56]. In the primary appraisal, individuals evaluate whether an event constitutes a threat, whereas in the secondary appraisal, they assess the adequacy of their coping resources. According to this framework, climate change risk perception represents a primary appraisal of environmental threat, while psychological distress emerges as the outcome when available coping resources are insufficient [76, 119].\u003c/p\u003e\n\u003cp\u003eSelf-regulation, resilience, and self-efficacy can thus be viewed as key psychological resources influencing secondary appraisal. Self-regulation enables adaptive reappraisal and flexible coping [67,45,26]. Resilience supports psychological stability under adverse circumstances and recovery [65,100,101]. Self-efficacy fosters persistence, and cognitive reframing of threats though under conditions of chronic and uncontrollable stressors such as climate change, it may also heighten responsibility and rumination [6, 9, 96].\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe expectation is that resources will moderate the association between climate risk perception and psychological distress.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccordingly, The Resilience Portfolio Model [44, 43] emphasizing that adaptation relies on a constellation of interrelated assets rather than isolated traits. So, self-regulation, resilience, and self-efficacy represent components of a broader portfolio, whose breadth, balance, and accessibility determine whether climate threats are managed effectively or culminate in heightened distress.\u003c/p\u003e\n\u003cp\u003eThe combination between these perspectives represent the theoretical foundation for the present study. By integrating the Transactional Model of Stress\u0026nbsp;\u003cstrong\u003eguided by the Resilience Portfolio Model, the framework integrates the appraisal of environmental threats with the mobilization of psychological resources.\u003c/strong\u003e This integration\u0026nbsp;leads\u0026nbsp;the current research in interpretation of how self-regulation, resilience, and self-efficacy moderate the relationship between climate change risk perception and psychological distress among emerging adults in Egypt. Accordingly, this framework guides the development of the study\u0026rsquo;s hypotheses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses Development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on the reviewed perspectives and underpinning theory, the following hypotheses were proposed:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1.\u003c/strong\u003eClimate change risk perception is associated positively with psychological distress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2.\u003c/strong\u003e Self-regulation, resilience, and self-efficacy each independently moderate the relationship between climate change risk perception and psychological distress, which means that higher degrees of these resources reduce the relationship between the two variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3.\u003c/strong\u003e The combined moderating effects of self-regulation, resilience, and self-efficacy moderate collectively the relationship between climate change risk perception and psychological distress, which means that higher degrees of these resources reduce the relationship between the two variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e. Gender-based differences are anticipated in how self-regulation, resilience, and self-efficacy moderating the relationship between climate change risk perception and psychological distress , which means that these psychological resources reduce the relationship more strongly for one gender compared to the other.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e3.1. Research Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study employed a cross-sectional, correlational design to investigate the relationship between climate change risk perception and psychological distress from one side and the moderating roles of self-regulation, resilience, and self-efficacy from the other side among emerging adults at Cairo University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study sample consisted of 2,065 emerging adults, recruited from different faculties at Cairo University during the first semester of 2024 .It includes men and women students(men: n = 996, women: n = 1,069) aged 18 to 22 years (The mean age for men was 19.60 years (SD = 1.35), while the mean age for women was 19.47 years (SD = 1.21). According to Cairo university population of approximately 200,000 students, the sampling error was calculated at \u0026plusmn;2.1% with a 95% confidence level, indicating acceptable precision for population-level estimates. A priori power analysis was conducted \u0026nbsp;by using G*Power 3.1. Assuming a small to medium effect size (f\u0026sup2; = 0.02), \u0026alpha; = .05, and power = 0.80, the required sample size to detect moderation effects in a multiple regression framework was 395 participants. The final sample of 2,065, including men and women, was higher than the required threshold. This ensured adequate statistical power for the proposed moderation analyses [38, 37, 55].\u003c/p\u003e\n\u003cp\u003eThe study employed a stratified convenience sampling method, with the sample classified based on gender (men and women) and academic discipline (theoretical and practical faculties) to maintain proportional representation across major subgroups. Individuals with clinically diagnosed psychological disorders (e.g., major depressive disorder, anxiety disorders) were excluded from participation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e provides a detailed breakdown of the sample\u0026rsquo;s demographic characteristics, including gender, academic discipline, and academic year.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSample\u0026apos;s demographic characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003een\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=996)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=1069)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCollege\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTheoretical\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e509\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractical\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcademic Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFirst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSecond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eThird\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFourth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFifth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily Income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eBelow average\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e783\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFreq.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cstrong\u003e\u003cstrong\u003e\u003c/strong\u003e\u003c/strong\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e summarizes the demographic characteristics of the sample. The distribution of gender is relatively balanced, with 996 men and 1069 women. Most men were enrolled in practical colleges, though women were more represented in theoretical colleges. and approximately reflecting their actual distribution among men and women students at Cairo University. Most students were in the first and second academic years, with fewer in advanced years. In terms of family income, most respondents reported an average income, while very few fell into the extremes of very low or very high categories. Overall, the sample reflects diversity across gender, college type, academic year, and socioeconomic status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Scales\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFive scales were used in the present study as follow\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.1. Climate Change Risk Perception Scale (CCRPS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on van der Linden\u0026rsquo;s integrative model of climate change risk perception [106,107,108], the present study employed an adapted version of this scale consisting of 20 items, equally distributed across four dimensions (five items per dimension). The Climate Change Risk Perception Scale (CCRPS) captures the cognitive appraisal of climate risks through four interrelated dimensions: Perceived Severity (beliefs about the seriousness of climate change impacts, e.g., Climate change will have very serious consequences for the environment), Perceived Vulnerability (personal susceptibility to climate risks, e.g., I feel personally vulnerable to the effects of climate change), Perceived Consequences (expected societal and ecological outcomes, e.g., Climate change will negatively affect public health), and Efficacy Beliefs (beliefs about human capacity to mitigate risks, e.g., Human actions can reduce the impact of climate change) [106,107,62].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo ensure cultural appropriateness, the items were reformulated with wording tailored to the Egyptian context, consistent with the operational definitions of the construct and its four dimensions. Previous research across different cultural settings has consistently demonstrated the suitable psychometric properties of the original version, including high internal consistency, evidence of convergent and discriminant validity, and a stable factorial structure established through exploratory and confirmatory factor analyses [108, 107 ,62,11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.2. Self-Regulation Scale \u0026ndash; Short Form (SRQ-SF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCarey et al. [17] developed this scale to evaluate individuals\u0026rsquo; ability to plan, monitor, and regulate their behavior \u003cstrong\u003ein\u003c/strong\u003e pursuing \u003cstrong\u003epersonal goals\u003c/strong\u003e, when faced with challenging or\u0026nbsp;situations of emotional strain. It is consisted of 31-item derived from the original 63-item Self-Regulation Scale (SRQ) created by Brown et al. [12] and designed to provide a more efficient yet psychometrically robust measure. The SRQ-SF has demonstrated satisfactory internal consistency (e.g., Cronbach\u0026rsquo;s alpha) and evidence of construct and predictive validity across diverse populations, including adolescents, emerging adults, and adults [80, 81,110,69,72].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.3. Connor-Davidson Resilience Scale (CD-RISC-25)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConnor and Davidson [27] developed this scale to assess resilience, using a 25-item version that evaluates five components: personal competence, tolerance of negative affect, positive acceptance of change, control, and spiritual influences. It has demonstrated a good psychometric property : test-retest reliability, internal consistency (Cronbach\u0026rsquo;s alpha), and convergent validity with related constructs, as well as cross-cultural validity, particularly in adolescent \u0026nbsp;and youth populations [43,60].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.4. General Self-Efficacy Scale (GSES)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSchwarzer and Jerusalem [82] developed this 10-item scale, which is designed to assess \u0026nbsp;individuals\u0026rsquo; beliefs in their capacity to cope effectively with a broad range of stressful situations and challenges. It has been extensively applied across diverse cultural contexts, age groups, and populations, and is available in several language adaptations. The scale consistently demonstrates suitable internal consistency, and evidence of construct and criterion validity in cross-cultural research [61, 91,93,102].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.5. General Health Scale-28 (GHQ-28)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe General Health Scale-28 (GHQ-28), developed by Goldberg and Hillier [41] is a widely used self-report screening scale for identifying minor psychiatric disorders and assessing general psychological well-being in both community and clinical populations [39,41]. The scale comprises 28 items organized into four subscales: somatic symptoms (physical distress), anxiety and insomnia, social dysfunction, and severe depression. It is designed to asses\u0026rsquo; short-term fluctuations in mental functioning and to detect early indicators of psychological distress. The scale has been adapted across different cultural contexts, demonstrating satisfactory internal consistency, test\u0026ndash;retest reliability, and different forms of construct and convergent validity [68, 109, 39].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Scales Adaptation for the Egyptian Sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo make it suitable for the Egyptian\u0026nbsp;culture, all scales were translated into Arabic, reviewed by bilingual experts, and back-translated to verify both linguistic and conceptual accuracy. A two-phase pilot study was conducted. In the first phase, cognitive interviews with 20 students were carried out to assess item clarity and cultural appropriateness. In the second phase, the revised scales were administered to a sample of 200 students equivalent to the main study population. Reliability coefficients (Cronbach\u0026rsquo;s alpha and split-half) for the scales ranged from \u0026alpha; = 0.76 to 0.94. Evidence of concurrent and construct validity was supported by correlations with established psychological instruments and results from exploratory factor analysis [ 34,1]. All responses were measured using a 5-point Likert scale ranging from \u0026ldquo;Strongly Disagree\u0026rdquo; to \u0026ldquo;Strongly Agree.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e presents the reliability coefficients for each scale, separately for Men and Women\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003e(*)\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eThe reliability coefficients for each scale across Men and Women participants.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eScales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpilt Half\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpilt Half\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClimate Change Risk Perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-Regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneral Self-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological Distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e(*)\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp; The reliability of the subscales for the five study measures was also assessed using both Cronbach\u0026rsquo;s alpha and split-half methods. Most reliability coefficients were satisfactory, except for the Perceived Likelihood subscale of the Climate Change Risk Perception scale, which demonstrated relatively low reliability, with coefficients around 0.50.\u003c/p\u003e\n\u003c/div\u003e\u003cp\u003e\u003cstrong\u003e3.5. Data Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were collected over two months during the first semester of the 2024\u0026ndash;2025 academic year after obtaining IRB approval and university authorization. Following these approvals, faculty members facilitated access to classrooms across different faculties and study levels. In each classroom, students were invited to participate voluntarily; the study purpose, confidentiality safeguards, and the right to withdraw at any time were explained. Oral informed consent was obtained immediately before administration, and eligibility was confirmed (current enrollment and absence of clinical psychological diagnoses) prior to completing the survey. The inclusion criteria were being an enrolled student at Cairo University during the data collection period, falling within the age range of 18\u0026ndash;22 years (emerging adulthood), achieving at least a \u0026ldquo;Good\u0026rdquo; grade in the previous academic year, and providing informed consent (or assent, when applicable). Data were gathered using a structured, self-administered printed scales during university hours. Administration was supervised by 15 trained master\u0026rsquo;s students under the guidance of members of the research team. Each session involved 15\u0026ndash;25 participants and lasted approximately 20\u0026ndash;25 minutes. Participation was voluntary, and students who preferred not to complete the survey could withdraw quietly without penalty. To protect privacy, responses were anonymously coded. Only minimal missing data were observed, and incomplete scales were excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6. Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analyses were conducted using IBM SPSS Statistics (Version 25) and AMOS (Version 24) [2, 15]. Descriptive statistics and testing the bias of data were computed. Pearson\u0026rsquo;s correlation coefficients were calculated to examine bivariate relationships among the variables. Because the study included three moderating variables, structural equation modeling was conducted in AMOS [15, 46], because the analytical capacity of commonly used tools such as Hayes\u0026rsquo;s PROCESS macro, accommodates a maximum of two moderators [48]. Manual computations were performed to specify and estimate higher-order interaction effects, following recommended approaches for latent and observed interactions in SEM [59, 63]. Prior to the creation of interaction terms, all predictor variables were mean-centered to minimize multicollinearity [46]. Two-way, three-way, and four-way interaction terms were generated in SPSS and incorporated into the AMOS model as observed variables. Moderation analyses proceeded in four hierarchical stages: estimation of main effects, evaluation of two-way interaction effects, evaluation of three-way interaction effects, and evaluation of the four-way interaction effect. This modeling approach allowed for a systematic and comprehensive assessment of both the individual and combined moderating effects [46, 59].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e4.1.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDescriptive statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003edisplays the descriptive statistics of the study variables for Men and Women participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eThe descriptive statistics of the study variables For men and women participants\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStd. Dev\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKurtosis*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSkewness**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003cp\u003e(n= 996)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf-regulation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResilience\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGeneral self- efficacy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychological distress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003cp\u003e(n= 1069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf-regulation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResilience\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGeneral self- efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychological distress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.206\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\u003e* St. Error for kurtosis \u0026nbsp; Men \u0026nbsp;0.155 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Women 0.149 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e** St. Error for skewness Men 0.077 \u0026nbsp; \u0026nbsp; Women 0.075\u003c/p\u003e\n\u003cp\u003eThe descriptive statistics in \u003cstrong\u003eTable 3\u003c/strong\u003e for both genders indicate that all study variables, including total scores and subcomponents, are normally distributed. The skewness coefficients for most psychological variables fall within acceptable limits and are not statistically significant, confirming that the data are appropriate for statistical analysis and hypothesis testing. In addition to the large sample size, which further strengthens this conclusion\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. Testing the bias of data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of Harman\u0026rsquo;s single-factor test indicated that common method bias was not a serious concern in the present data. For males, the first unrotated factor accounted for 21.70% of the total variance, while for females it explained 22.78%. In both cases, these percentages fall well below the commonly accepted threshold of 40% that would suggest substantial common method variance [2,15,37,38]. This suggests that no single factor dominated the variance structure of the data, and therefore the observed relationships among the study variables are unlikely to be artifacts of common method bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3. Correlation between total scores of study variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e presents the correlations between the total scores of the study variables among men and women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4:\u003c/strong\u003e The correlations among total scores of the study variables \u0026nbsp;for men and women\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGeneral self- efficacy \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychological distress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003cp\u003eN= (996)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.222***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.228***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.795***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneral self- efficacy \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.112***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.299***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.236***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.087**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003cp\u003eN= (1069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.129***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.134***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.806***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGeneral self- efficacy \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.062*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.062*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.094**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.380***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.335***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.094**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Significant at 0.05 \u0026nbsp; ** Significant at 0.01 \u0026nbsp; \u0026nbsp; \u0026nbsp; *** Significant at 0.001(2 tailed)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e shows the correlations among the study variables for men and women. Climate change risk perception was positively correlated with psychological distress in both groups, indicating that higher perceived climate risks were associated with greater levels of distress. At the same time, self-regulation and resilience displayed strong positive intercorrelations suggesting considerable overlap in their functioning and were both negatively associated with psychological distress, suggesting their protective role. These negative associations were somewhat stronger among women. Self-efficacy, however, showed negligible or weak relationships with the other variables and only minimal correlations with distress. Overall, the pattern highlights that while risk perception is linked to higher distress, psychological resources such as self-regulation and resilience are consistently related to lower distress, with some gender differences in the strength of these associations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.\u003c/strong\u003e\u003cstrong\u003e4.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCorrelations between climate change risk perception and psychological distress\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u0026nbsp;\u003c/strong\u003ePresents the correlations between climate change risk perception and psychological distress among Women participants:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5:\u003c/strong\u003e The correlations between climate change risk perception and psychological distress among Men and Women participants\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;Variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eClimate change risk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1-Perceived\u003c/p\u003e\n \u003cp\u003eSeverity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2- Perceived vulnerability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3- Perceived likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4- Efficacy\u003c/p\u003e\n \u003cp\u003eBeliefs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003cp\u003eN= (996)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological distress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.112**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.128**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.143\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.084**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 - Somatic symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.185**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.179**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.178**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.120**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.193**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 - Anxiety and insomnia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.079*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.092**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.117**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 - Social dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.075*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.084**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 - Severe Depression\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.075*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.091**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003cp\u003eN= (1069)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePsychological distress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.094**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.084**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.129**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.114**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 - Somatic symptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.144**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.122**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.153**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.095**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.126**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 - Anxiety and insomnia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.106**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.082**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 - Social dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.068*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.081**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 - Severe Depression\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.068*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.063*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.103**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.092**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Significant at the 0.05 level \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; ** Significant at the 0.01 level (2-tailed).\u003c/p\u003e\n\u003cp\u003eAccording to the information in previous \u003cstrong\u003eTable 5\u003c/strong\u003e, most correlation coefficients between perceptions of climate change risk and psychological distress, including their sub-components, were statistically significant. Given the large sample sizes for both men and women, these correlations reached significance even when the effect sizes were relatively small. In the men\u0026rsquo;s sample, 16 correlations were significant, while in the women\u0026rsquo;s sample, 17 correlations were significant. The perceived vulnerability and likelihood showed most consistent correlations with psychological distress, efficacy beliefs were more broadly significant among women than men, and the overall pattern of results did not differ substantially between genders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5.Moderation Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe present study aimed to assess the moderating roles of self-regulation, resilience, and self-efficacy, with their interaction effects, in the relationship between climate change risk perception and psychological distress. Moderation analyses were conducted for men and women university students to identify gender-specific patterns and effects.\u0026nbsp;\u003c/strong\u003eThe visual representations of the significant moderation results for men and women are provided in Figures 2 and 3, respectively, which are included in \u003cstrong\u003eAppendix 1\u003c/strong\u003e for reference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5.1. Results of the Men\u0026rsquo;s sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e presents the standardized effects of independent and moderating variables among Men participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eStandardized Effects of Independent and Moderating Variables Among Men Participants (N = 966)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStandardized Estimates(\u0026beta;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003cp\u003e(p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Resilience x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Resilience x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.316*\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\u003e*Non-significant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Direct Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults showed that higher climate change risk perception significantly predicted increased psychological distress. \u0026nbsp;Each of Self-regulation and resilience had a negative effect, confirming its protective role, and demonstrated a significant attenuating effect. Unexpectedly, self-efficacy was positively associated with distress, indicating that higher self-efficacy slightly exacerbated psychological distress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Interaction Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults showed a significant negative interaction between risk perception and both self-regulation and resilience, suggesting these variables mitigate the psychological impact of climate threats. However, self-efficacy interacted positively with risk perception, unexpectedly intensifying distress rather than reducing it.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Higher-Order Interaction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe three-way interaction of risk perception, self-regulation, and resilience was positive significant, indicating that may increase distress, which means a complex interplay. Also, risk perception and resilience combined with self-efficacy amplified distress. In contrast, the combination of self-regulation and self-efficacy with risk perception had a significant negative effect, reflecting a joint attenuating role. The four-way interaction among all variables was non-significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5.2. Results of the Women\u0026rsquo;s sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e presents the standardized effects of independent and moderating variables among women participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7:\u0026nbsp;\u003c/strong\u003eStandardized Effects of Independent and Moderating Variables Among Women Participants (N = 1069)\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStandardized Estimates(\u0026beta;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003cp\u003e(p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.158*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.678*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.442*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.234*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Resilience x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk perception x Self-regulation x Resilience x Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.062*\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\u003e*Non-significant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Direct Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong Women, the results indicated that higher climate change risk perception significantly predicted increased psychological distress. Self-regulation had a negative effect, confirming its protective role, and resilience also demonstrated a significant attenuating effect. The unexpected result was the positive association between self-efficacy and distress, indicating \u003cstrong\u003ethat higher self-efficacy was associated with a slight increase in psychological stress.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Interaction Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe interaction between climate change risk perception and any of the three variables: self-regulation, resilience, and self-efficacy, was non- significant\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Higher-Order Interactions \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe three-way interaction of the climate change risk perception, self-regulation and self-efficacy showed a significant negative relationship, suggesting these variables mitigate the psychological impact of climate threats. However, the interaction between the climate change risk perception, resilience and self-efficacy showed a significant positive relationship as an unexpected finding that amplified distress. The four-way interaction remained non-significant.\u003c/p\u003e\n\u003cp\u003eAfter presenting the study results, which included Pearson\u0026rsquo;s simple correlation coefficients and the analysis of the three moderator variables, and considering the statistically significant findings revealed, we now move on to discuss these results and interpret their psychological implications.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on the integrative model and the underlying theory adopted in the present study, it is possible to interpret and understand the associations of climate change risk perception with psychological distress among emerging adults.\u0026nbsp;The transactional perspective explains how stress outcomes result from the interaction between how people assess threats and the coping resources they adopt [56]. The resilience portfolio Model focuses on protective resources that support positive adaptation [44, 43]. These propositions provide a framework for understanding how personal and contextual factors shape the correlation between perceived climate risks and psychological distress. We will discuss the results of each hypothesis in the next section according to previous research results and theoretical models.\u003c/p\u003e\n\u003cp\u003eAccording to the\u003cstrong\u003e\u0026nbsp;first hypothesis\u0026nbsp;\u003c/strong\u003ethat\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eproposed a positive correlation between climate change risk perception and psychological distress, the results of correlation coefficient confirmed partly this expectation. There was a modest significant positive relationship between the two variables in both genders. This means that emerging adults who view climate change as a serious threat or risk tend to experience higher levels of psychological distress.\u0026nbsp;These findings are consistent with the results of previous research showing that heightened awareness of environmental risks correlate to negative mental health outcomes, including fear, anxiety, stress, and depressive symptoms [14,24, 80].\u003c/p\u003e\n\u003cp\u003eSome empirical studies support that climate-related worry was significantly correlated with psychological distress, and others showed that exposure to climate change effects predicted increased worry and poorer well-being [83,73,4]. These findings consisted with regional evidence suggesting that adolescents and emerging adults in Egypt also display growing vulnerability to eco-anxiety [47,34]. This result must see according to proposition that the relationship may varies across different cultural contexts. This suggests that the predictive ability of risk perception depends on factors such as cultural norms, traditions, political attitudes, value system, and the perceived immediacy of climate impacts [88,84]. Climate change threats may appear less immediate in some places like Greater Cairo, than in coastal or rural regions, perceptions of risk may not consistently cause severe psychological distress. These findings assert that climate change risk perception is an important variable but not exclusive determinant of psychological distress.\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003esecond hypothesis\u003c/strong\u003e proposed that the moderating role of self-regulation, resilience, and self-efficacy, predicting that higher levels of these resources would weaken the relationship between climate change risk perception and psychological distress independently. The results consisted with this hypothesis by demonstrating that each moderator exerted significant independent effects. Self-regulation as a protective factor, may support the findings that people who exhibit higher executive control and intentional regulation exhibit lower emotional reactivity to climate-related threats [101, 26]. This suggests that regulatory skills help emerging adults to reframe threatening appraisals and employ constructive coping strategies. Resilience likewise showed a protective effect, consistent with evidence that resilience enables adaptive adjustment and reduces vulnerability to eco-anxiety [50, 83]. Finally, self-efficacy independently moderated the relationship, some studies [119 ,89] emphasized the role of efficacy beliefs in reducing helplessness and fostering adaptive responses.\u003c/p\u003e\n\u003cp\u003eOverall, the evidence supports the view that each psychological resource serves as an independent adaptive asset. They converge with previous studies that emphasized the buffering capacity of self-regulation, resilience, and self-efficacy when examined separately [16,43,45,66]. At the same time, the absence of significant higher-order interaction effects suggests developmental or contextual limits emerging adults’ ability to mobilize these resources simultaneously.\u003c/p\u003e\n\u003cp\u003eAccording to the \u003cstrong\u003ethird hypothesis\u003c/strong\u003e individuals with \u003cstrong\u003ehigh levels of self-regulation, resilience, and self-efficacy integrally\u003c/strong\u003e would exhibit a \u003cstrong\u003eprotective effect when facing threats\u003c/strong\u003e.\u0026nbsp;Contrary to this expectation, the results revealed no significant evidence of higher order moderation between the three moderator variables. This absence of integrative effects may reflect some developmental constraints in adolescence and emerging adulthood. According to developmental theory, using different coping strategies together requires mature executive and emotional integration, which may not yet be fully developed at this stage [29, 84]. Instead, emerging adults may rely on discrete coping strategies rather than integrating them in a cohesive manner.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;These results diverge from interaction-based models that assume additive or multiplicative benefits when protective resources combine. Rather, they are consistent with studies that question whether such synergies operate universally in younger populations, particularly in adolescent and emerging adult groups. [101, 26]. The implication is that while each resource is protective, interventions should focus on strengthening them individually rather joint activation will produce amplified effects in emerging adults.\u003c/p\u003e\n\u003cp\u003eThe results supported the expectation of \u003cstrong\u003efourth hypothesis\u0026nbsp;\u003c/strong\u003ethat gender differences play an important moderating role in the effects of self-regulation, resilience, and self-efficacy\u0026nbsp;on the relationship between climate change risk perception and psychological distress. These psychological resources function differently across genders. This illustrate that there is a distinct mechanism shaped by \u003cstrong\u003esocialization patterns, emotion regulation styles, and cognitive appraisals\u003c/strong\u003e. Men exhibited more significant moderating interactions between internal resources and perceived environmental threat. In contrast, women showed fewer significant moderation interactions and more consistent linear patterns, possibly reflecting higher emotional sensitivity and lower executive integration during emerging adulthood [25,16].\u003c/p\u003e\n\u003cp\u003ePrevious research aimed to investigate coping strategies in face of environmental stress, and climate threats assert the gender differences. Women apply emotion-focused approaches such as rumination in general, whereas men tend to adopt task-oriented or distancing strategies [23,24].\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThese patterns are shaped by sociocultural context in the Egyptian society, where gender norms strongly influence emotional expression and coping behaviors in different situations [34]. The socialization of women enabled her to express vulnerability and seek support, while socialization encouraged men to display restraint and independence, illustrating the gender gap in the use of psychological resources [101, 84].\u003c/p\u003e\n\u003cp\u003eContrary to Bandura’s model [5] an unexpected finding was related to self-efficacy, that was positively correlated with distress among women. \u003cstrong\u003eThis conception may indicate a contradictory between\u003c/strong\u003e strong efficacy beliefs and limited real-world opportunities for climate action [ 9, 119]. When perceived responsibility exceeds perceived control, self-efficacy may generate frustration, overload, or internalized pressure, producing “motivated helplessness” [62, 99]. In such cultural contexts, self-efficacy may amplify distress rather than attenuating it, emphasizing the contextual dependency of psychological resources.\u003c/p\u003e\n\u003cp\u003eThe developmental appropriateness is an important factor in the interpretation of results as the study focuses on a life stage characterized by emerging regulatory capacities and limited integration of emotional experiences. During emerging adulthood, cognitive control, emotional regulation, and moral reasoning are still developing, which may restrict the ability to process complex and abstract threats such as climate change [29, 66]. The peer dynamics in social interactions have a marked influence on emerging adults and often lead them to display heightened emotional reactions. As a result, they become more vulnerable to negative emotions or disengagement when they perceive limited support for climate action.\u003cstrong\u003e\u0026nbsp;[24].\u003c/strong\u003e These results highlight \u003cstrong\u003ethe\u003c/strong\u003e need for age-specific theories and measurement tools that interpret how youth perceive and cope with environmental threats [84, 101].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePerhaps, these developmental considerations \u003cstrong\u003eare associated\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewith the characteristics of the study’s sample, which consisted of Egyptian university students in emerging adulthood. This age group faces different demands and life challenges, including academic demands, career ambiguity, and high exposure to climate discourse through formal education, especially students in the practical colleges [ 40,76]. Such factors may intensify both the perception of climate risks and the psychological distress associated with them. They may have access to knowledge and cognitive resources comparing with their non-student peers. This means that their coping strategies may not represent the broader youth population. These sample-specific characteristics highlight the need for caution in generalization. So, such results reinforcing the importance of tailoring climate–mental health research to the lived realities of distinct subgroups within emerging adulthood [24,91].\u003c/p\u003e\n\u003cp\u003eThe findings may also be interpreted considering broader cultural and contextual realities in Egypt. Psychological resources such as self-regulation and resilience are not culturally neutral in many Egyptian contexts. Self-regulation is often viewed as self-restraint or obedience rather than adaptive flexibility strategy [34, 66].\u003c/p\u003e\n\u003cp\u003eResilience in the other side may characterize more by endurance than by active coping strategies. Likewise, self-efficacy may be experienced less as personal confidence and more as an internalized moral obligation to succeed or remain strong, particularly within academic and familial domains. These culturally shaped meanings may help explain why psychological strengths did not consistently act as an expected and, in some cases, intensified emotional conflict\u0026nbsp;\u003cstrong\u003erather than reducing it\u003c/strong\u003e\u003cstrong\u003e \u003c/strong\u003e[24,21].\u003c/p\u003e\n\u003cp\u003eIn line with this conclusion, how Egyptian culture mediates individual and collective psychological resources? Personal resources like resilience and self-efficacy may interact with community-level resources such as resilience and collective efficacy [96,119] In light of Egypt’s cultural emphasis on social cohesion and mutual interdependence., communal coping may often take precedence over individual strategies [34, 26]. Acceptable responses to adversity shape by Socialization norms including climate-related threats [47]. These dynamics may help explain why individual resources were not enough, and at times were associated with greater distress [24].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe lack of social and community-level moderators that act at broader ecological levels may reflect the absence of the higher-order moderating effect. Programs that simultaneously enhance individual coping skills and strengthen community cohesion—through environmental education, civic participation, and localized climate initiatives—may be especially effective in reducing climate-related psychological distress and promoting sustainable adaptation [88, 71,20].\u003c/p\u003e\n\u003cp\u003eThe present study supports the integrative framework that combines the Transactional Model of Stress and Coping [56] with the Resilience Portfolio Model [44, 43]. In line with the transactional model, the positive correlation between climate change risk perception and psychological distress confirms that perceiving a severe climate change and uncontrollable threat can increase emotional discomfort [24, 80]. At the same time, the moderating roles of self-regulation, resilience, and self-efficacy reflect the importance of secondary appraisals, whereby individuals evaluate their coping resources to determine whether they can manage perceived threats [26, 101].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese psychological resources functioned more effectively as independent moderators. This is consistent with the Resilience Portfolio perspective, which views protective assets as distinct components, each of them contributes separately to adaptation. Such assets may not always interact synergistically, especially during adolescence and emerging adulthood, when executive and emotional systems are still maturing [29, 84].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, the observed gendered patterns underscore the contextual nature of stress and resilience processes, interpreting how sociocultural norms influence the accessibility, use, and impact of psychological resources [84 ,50]. Taken together, these findings demonstrate that the proposed integrative model provides a coherent and culturally sensitive explanation of how climate change risk perception translates into psychological distress, while also clarifying the moderating roles of key psychological capacities across developmental and gendered contexts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTheoretical Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are some important theoretical implications that the present study carries for \u003cstrong\u003eenhancing\u003c/strong\u003e the area of climate change psychology. First, the correlation found between climate change risk perception and psychological distress supports Lazarus and Folkman’s Transactional Model of Stress [56] and the Resilience Portfolio Model [44, 43]. Accordingly. climate-related threats act as primary appraisals, and distress occurs when people believe their coping resources are not enough. This means that climate change functions both as an environmental event and as a psychologically interpreted stressor integrated into daily meaning-making. Second, the moderating roles of self-regulation, resilience, and self-efficacy support the Resilience Portfolio Model [44,43], which views adaptive outcomes as shaped by distinct yet related assets. Specifically, self-regulation aids cognitive flexibility, resilience promotes recovery, and self-efficacy strengthens a sense of agency [26,101].\u0026nbsp;Third, the results emphasize the importance of context-sensitive models, where interactions differ according to factors such as age, culture, and the duration of stress exposure [29,84]. Fourth, the study adds a gendered and cultural dimension to future studies, especially in non-western countries( \u0026nbsp; \u0026nbsp; ).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractical Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present findings carry some practical implications that are especially relevant for the Egyptian and broader Arab context. The protective roles of self-regulation and resilience emphasize the need for university-based programs that incorporate stress management, resilience training, and problem-solving workshops into student support services [30,68]. Initiative efforts may include, peer-support networks, counseling units, and campus-led can offer structured spaces for building coping skills and sustain emotional stability emerging adults [29,84]. Considering that the complex role of self-efficacy sometimes increases rather than reduces distress, indicating the need for culturally sensitive and realistic interventions.\u003c/p\u003e\n\u003cp\u003eSelf-efficacy is shaped in the Arab societies, in general and especially in Egypt by family expectations, social reputation, and moral duty [34].\u0026nbsp;Enhancing efficacy should emphasize realistic, value-based opportunities, such as community volunteering and student-led environmental projects, that translate personal agency into collective action [91,119,21]. Interventions should put into consideration the central role of family and community that foster collective resilience [24]. Awareness programs grounded in religious and cultural values of stewardship can strengthen both acceptance and impact [24]. Integrating climate–mental health initiatives into national strategies such as Egypt’s Vision 2030 and the National Climate Change Strategy ensures sustainable alignment with WHO, IPCC, and UNESCO recommendations [52,53,103,117,118], may help designing future programs for mitigation and adaptation. Overall, the empirical findings with culturally grounded strategies can help reduce climate-related mental health risks among Egyptian and Arab youth.\u003cbr\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, The cross-sectional correlational design limits causal interpretation for the direction of relationships among climate change risk perception, psychological distress, and the moderating roles of self-regulation, resilience, and self-efficacy. So, coming studies are needed to adopt longitudinal and experimental designs to clarify causal pathways. Second, the non-random convenience sample of Cairo University students may not represent the broader diversity of Egyptian youth, which limits generalizability, Third, social desirability in the self-report measures may cause biases in findings. So, it is important to rely on behavioral and physiological indicators to improve validity.\u0026nbsp;Fourth, despite cultural adaptation, constructs like self-regulation, resilience, and self-efficacy may carry distinct cultural meanings in Egypt related to obedience or endurance. Qualitative and mixed-method approaches are needed to confirm conceptual equivalence.\u003cstrong\u003e\u0026nbsp;Fifth, factors such as prior mental health status, socioeconomic background, and exposure to climate-related information may have confounded the observed relationships. Therefore, these variables should be controlled for in future research.\u003c/strong\u003e Finally, the focus on individual-level moderators may ignore the broader social and structural factors such as social support, collective efficacy, and economic or political contexts that also contribute to shaping psychological well-being. Above all, using qualitative and mixed-method approaches are important to confirm conceptual equivalence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFuture Research Recommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFuture studies should investigate the vital subjects by integrating the longitudinal and mixed-method designs behavioral, qualitative, and physiological data in methodology. Research should also examine collective efficacy, coping styles, environmental values, family influence, and culturally specific coping strategies as additional moderators. Also integrate individual and collective resources Interdisciplinary collaboration across psychology, environmental science, and public health is essential to develop culturally and developmentally appropriate interventions.\u0026nbsp;unmeasured confounding (e.g., prior mental health, socioeconomic status, media exposure) must be considered.\u003c/p\u003e\n\u003cp\u003eBased on these directions, several key research questions emerge for future investigation\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eAre there a specific developmental stage do self-regulation, resilience, and self-efficacy begin to interact synergistically rather than independently?\u003c/li\u003e\n \u003cli\u003eWhat mechanisms explain the paradoxical finding that self-efficacy may amplify distress, particularly among women?\u003c/li\u003e\n \u003cli\u003eHow do coping strategies such as rumination, avoidance, or problem-focused engagement mediate the relation between climate risk perception and distress?\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eWhat is the relationship between climate change risk perception and climate change denial among emerging adults?\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eWhat are mediators between climate change risk perception and climate change denial?\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003eHow do climate change risk perceptions and psychological distress influence each other over time?\u003c/li\u003e\n \u003cli\u003eWhat longitudinal patterns can be observed concerning the relationship between \u003cstrong\u003eclimate change risk perception and climate change denial among emerging adults.\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003eHow can multi-method approaches (e.g., behavioral, physiological, and qualitative scales) improve the validity of research on climate-related psychological adaptation?\u003c/li\u003e\n \u003cli\u003eHow do collective-level resources, such as community resilience and institutional trust, combine with personal traits to buffer psychological distress in Egypt and similar Global South settings?\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received ethical approval from the Research Ethics Committee at Cairo University according to the study proposal and was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (1964) and its subsequent amendments, which emphasize respect for human dignity, autonomy, and the protection of participants\u0026rsquo; well-being. Verbal informed consent was obtained from all participants prior to each session, in alignment with these ethical standards, after they had been fully briefed on the importance of scientific research and the assurance of confidentiality. The use of verbal rather than written consent was approved by the ethics committee due to the minimal-risk nature of the study and the absence of sensitive or identifying information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the General Administration of Scientific Research at Cairo University .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors collaboratively formulated the research problem, conducted the literature review, structured the scientific content, and determined the research methodology and procedures. Eman Swelam, and Eman Abdallah coordinated and supervised data collection and verified the accuracy and integrity of the dataset.\u003cstrong\u003e\u0026nbsp;Osama Abosree conducted the statistical analyses and contributed to data interpretation and descriptive reporting, in collaboration with Hamed Ead and Attia El-Tantawy.\u003c/strong\u003e Authors also jointly reviewed the results, contributed to the preparation and revision of the final manuscript, and approved the version submitted for publication. . Moataz Abdallah led the interpretation and discussion of the results in collaboration with all co-authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all participants for their cooperation and valuable time.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-Awadhi, T., Al-Sarmi, S., \u0026amp; Al-Buloshi, A. (2023). 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Emotion regulation from early adolescence to emerging adulthood and middle adulthood: Age differences, gender differences, and emotion-specific developmental variations. \u003cem\u003eInternational Journal of Behavioral Development, 38\u003c/em\u003e(2), 182\u0026ndash;194. https://doi.org/10.1177/0165025413515405\u003c/li\u003e\n\u003cli\u003eZimmermann, P., \u0026amp; Iwanski, A. (2018). Development and timing of developmental changes in emotional reactivity and emotion regulation during adolescence. In P. M. Cole \u0026amp; T. Hollenstein (Eds.), \u003cem\u003eEmotion regulation: A matter of time\u003c/em\u003e (pp. 87\u0026ndash;108). Routledge. https://doi.org/10.4324/9781351001328-6\u003c/li\u003e\n\u003c/ol\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":false,"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":"Climate change, Risk perception, Self-regulation, Resilience, Self-efficacy, Psychological distress","lastPublishedDoi":"10.21203/rs.3.rs-8340234/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8340234/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Climate change is increasingly recognized as a serious threat to both physical and mental health in the present era. However, there remains a need for research specifically addressing the psychological effects of climate change on mental health. This study examined the correlation between climate change risk perception and psychological distress among emerging adults in Egypt. It also focused on the moderating roles of self-regulation, resilience, and self-efficacy, as well as gender differences, within the framework of an integrative model that conceptualizes these three variables as complementary psychological resources.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: A cross-sectional correlational method was conducted with 2,065 undergraduate students at Cairo University during the first semester of 2024. All participants of men and women completed validated Arabic versions of standardized psychological scales. Descriptive statistics and preliminary analyses, including tests for data bias were performed in SPSS (v.25), and structural equation modeling in AMOS (v.24) was used to test direct, interaction, and higher-order moderation effects between the moderating variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Climate change risk perception significantly correlated to psychological distress. Self-regulation and resilience consistently weakened this relationship, indicating their protective roles, while self-efficacy was unexpectedly associated with higher levels of distress. Significant interaction effects emerged primarily among men, with complex three-way interactions varying by gender, whereas the four-way interaction was not significant in both genders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: The findings demonstrate the utility of an integrative model in reflecting gender-based differences in psychological responses to climate change. They also suggest that psychological resources are not enough when considered together, they remain independently important. Future research should address broader contextual and structural factors in the Egyptian culture. This study contributes to testing gendered moderation effects which reinforce cross-cultural studies, and provides actionable implications for education, psychosocial support, and policy development.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"An Integrated Moderation Model of Climate Change Risk Perception and Psychological Distress: The Roles of Self-Regulation, Resilience, and Self-Efficacy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-05 10:13:10","doi":"10.21203/rs.3.rs-8340234/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":"ed00a2a7-8ca5-4f80-a72f-03fab8efad29","owner":[],"postedDate":"January 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-18T08:26:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-05 10:13:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8340234","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8340234","identity":"rs-8340234","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}