The Moderating Roles of Self-Regulation, Resilience, and Self-Efficacy in the Relationship Between Climate Change Risk Perception and Psychological Distress: An Integrated Theoretical Model

The Moderating Roles of Self-Regulation, Resilience, and Self-Efficacy in the Relationship Between Climate Change Risk Perception and Psychological Distress: An Integrated Theoretical Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Moderating Roles of Self-Regulation, Resilience, and Self-Efficacy in the Relationship Between Climate Change Risk Perception and Psychological Distress: An Integrated Theoretical Model Moataz Abdallah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7048646/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 This study adopts an integrative model to examine the relationship between climate change risk perception and psychological distress among young adults, focusing on the moderating roles of self-regulation, resilience, and self-efficacy. A cross-sectional survey was conducted with 2,065 undergraduate students from Cairo University during the first academic semester of 2024, representing approximately 1% of the university’s total student population. Participants completed validated Arabic versions of standardized psychological scales. Data were analyzed using SPSS for descriptive statistics and preliminary analyses, and AMOS for structural equation modeling to assess direct, interaction, and higher-order moderation effects. Findings revealed that climate change risk perception significantly predicted increased psychological distress. Self-regulation and resilience were negatively associated with distress, indicating their protective roles. Unexpectedly, self-efficacy was positively associated with distress. Significant interaction effects emerged only among males, with three-way interactions varying by gender. The four-way interaction was non-significant for both groups. These results illustrate the potential utility of an integrative model in capturing gender-specific psychological responses to climate change. However, they also suggest that individual psychological resources alone may be insufficient to fully explain the mental health impacts of climate risk perception, highlighting the need to consider broader contextual and structural factors in future research and interventions. Climate change Risk perception Self-regulation Resilience Self-efficacy and psychological distress Figures Figure 1 Introduction Climate change is increasingly recognized as a pressing global threat, with far-reaching consequences including rising temperatures, extreme weather events, and long-term ecological disruptions (Virkkala et al., 2025; IPCC, 2023). Surpassing the 1.5°C warming threshold may trigger irreversible outcomes such as sea-level rise, biodiversity loss, and the degradation of aquatic ecosystems (Lee et al., 2024; Menden-Deuer et al., 2023; Diffenbaugh & Burke, 2023; Bevacqua et al., 2025). Although the Arab region contributes minimally to global emissions, it remains highly vulnerable to climate-related risks such as floods, forest fires, desertification, and adverse weather, as observed in Egypt and neighboring countries in the Gulf and North Africa, particularly Morocco and Algeria (Baumert & Kloos, 2017; Ads et al., 2023; Elsayed et al., 2024; ESCWA, 2022). In Egypt, most research has focused on the economic, legal, and environmental aspects of climate change, while studies on climate change psychology and the psychological impacts of climate change remain limited (Abousoliman et al., 2024; Elshirbiny & Abrahamse, 2020). Climate change affects not only physical health, as seen in heat-related illnesses, cardiovascular and respiratory diseases, metabolic disorders, pulmonary conditions, asthma, and allergies (Dilaver et al., 2025; Bernhardt & Roy, 2024), but also mental health, contributing to anxiety, depression, insomnia, PTSD, and chronic psychological distress, particularly following exposure to extreme weather events or displacement (Cosh et al., 2024; Burrows, 2024; Schwartz et al., 2023; Niedzwiedz & Kariuki, 2025). Given this dual burden, integrating mental health considerations into climate adaptation strategies is increasingly vital (Burrows et al.,2024; WHO, 2024). Perception of climate change risk plays a central role in shaping psychological responses and may exacerbate vulnerability among high-risk populations, particularly adolescents, due to ongoing cognitive and emotional development (Gianfredi et al., 2024; Cash et al.,2024). Gender differences also influence these effects (Albrecht et al., 2024; Wang et al., 2023). To address this research gap, the current study adopts an integrative psychological approach to examine the relationship between climate change risk perception and psychological distress among young adults in Egypt. It also investigates whether personal psychological resources—specifically self-regulation, resilience, and self-efficacy—moderate this relationship and serve as protective factors in the context of environmental threats. Theoretical Framework This section outlines the theoretical foundations of the study by examining the relationship between perceived climate change risk and psychological distress, as well as the moderating roles of self-regulation, resilience, and self-efficacy. It is grounded in established theories and supported by prior empirical research, culminating in the proposed conceptual model (Figure 1) 2.1 Climate Change Risk Perception and Psychological Distress Perceptions of climate change risks influence how individuals interpret environmental threats and respond emotionally and behaviorally (Lee et al., 2024). This area has received increasing attention within the field of climate psychology (Gianfredi et al., 2024). However, in the Egyptian context, existing research has primarily focused on aspects of public awareness, attitudes, and policy development (Abousoliman et al., 2024; Elshirbiny & Abrahamse, 2020). Empirical findings on the link between risk perception and psychological distress are mixed, with studies reporting positive, weak, or non-significant associations (Cosh et al., 2024; Burke et al., 2024; Reyes et al., 2023; Ogunbode et al., 2021). Some evidence suggests that risk perception may relate more strongly to behavioral engagement than emotional distress (Lutz et al., 2023; Schwartz et al., 2023). Theories such as Individual Environmental Sensitivity (Whitmarsh et al., 2022), Terror Management Theory (Goldenberg & Pyszczynski, 2015), and Cognitive Appraisal Theory (Lazarus & Folkman, 1984) propose that personal traits, perceived control, and existential threat appraisals contribute to these discrepancies, especially among adolescents (Albrecht et al., 2024). Additionally, methodological limitations and contextual variability further complicate results and their generalization across different cultural settings (Wang et al., 2024; Jarrett et al., 2024). Accordingly, this study addresses these gaps by examining the relationship between climate risk perception and psychological distress among young adults in Egypt. 2-2: The Roles of Moderator Variables Resilience, self-regulation, and self-efficacy are fundamental psychological resources that enable individuals to respond effectively to stressors such as climate change. Collectively, these capacities foster adaptive self-development, reinforce a sense of personal competence, and promote emotional stability in the face of global climate challenges, as follows: 2-2-1: Moderating Role of Self-Regulation Self-regulation—the capacity to manage emotions, thoughts, and behaviors—represents a potential buffer between climate change risk perception and psychological distress. Adolescents with stronger self-regulation skills tend to experience lower levels of distress despite perceiving elevated climate risks, as they employ adaptive strategies such as cognitive reappraisal and mindfulness (Dong et al., 2022; Compas et al., 2017). Theoretical models of self-regulation, particularly Self-Determination Theory, suggest that autonomy and competence enhance individuals’ ability to manage long-term stressors by fostering internal motivation and adaptive coping (Spitzer et al., 2023). Within the climate change context, self-regulation may thus moderate the association between risk perception and psychological distress. Adolescents with well-developed self-regulatory skills are better able to cognitively reinterpret environmental threats and apply flexible, adaptive strategies—such as cognitive reappraisal—thereby mitigating climate-related psychological distress (Treble et al., 2022; Crone & Dahl, 2012). Empirical evidence supports the moderating role of self-regulation in stressful contexts (Varas -Julca et al. (2024), demonstrated that adolescents with higher self-regulation capacities were more likely to engage in adaptive coping strategies, including cognitive reappraisal and problem-solving, which in turn reduced the emotional impact of environmental stressors. Similarly, Wolff et al. (2023) and Murray et al. (2022) found that self-regulation predicted more effective emotional adjustment and lower psychological distress in response to various stress-inducing circumstances, including environmental threats. 2-2-2: Moderating Role of Resilience Resilience—the ability to adapt and recover from adversity—represents a key moderating factor that may reduce psychological distress in adolescents who perceive climate risks. Resilient individuals often employ proactive coping strategies such as problem-solving and seeking social support (Wang et al., 2024). For example, resilient adolescents may channel their distress into activism or prosocial engagement, thereby reducing feelings of helplessness and fostering a sense of meaning and purpose. Additionally, resilience supports cognitive reinterpretation of stressors, offering further protection to mental health (Ungar, 2022, 2023; Luo et al., 2025). Empirical research has consistently emphasized the buffering role of resilience against a wide range of psychological stressors, including those stemming from environmental threats (Alford et al., 2023; Chen et al.,2024). So, adolescents with higher resilience were better equipped to manage the psychological consequences of climate change through proactive coping approaches such as problem-solving and social support-seeking, which helped them preserve psychological well-being and optimism (Pihkala et al., 2024; Wang et al., 2024; Luo et al., 2025; Johnson & Brækstad, 2024). This interpretation aligns 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 emerges when individuals draw upon both personal strengths and external supports to adapt positively under conditions of significant adversity—such as climate-related threats—thus moderating the impact of risk exposure on psychological outcomes (Alford et al., 2023; Luo et al., 2025; Cosentino et al.,2024). 2-2-3: Moderating Role of Self-Efficacy Self-efficacy—the belief in one's ability to effect change—is associated with lower psychological distress in the context of climate threats. Adolescents with higher self-efficacy are more likely to engage in active coping and advocacy behaviors, which enhance their sense of personal control (Schwarzer & Luszczynska, 2023; Schwarzer & Luszczynska, 2023). This confidence contributes to the mitigation of anxiety and fosters involvement in sustainability practices such as reducing carbon consumption or promoting peer education. Moreover, self-efficacy facilitates a positive cognitive framing, enabling adolescents to view environmental challenges as opportunities for personal growth (Spitzer et al., 2023; Luo et al., 2025). Accordingly, interventions aimed at strengthening adolescents’ self-efficacy may play a pivotal role in alleviating the mental health burdens associated with climate-related stressors (Qin et al., 2024; Luo et al., 2025; Johnson & Brækstad, 2024). This perspective is consistent with Bandura’s Social Cognitive Theory (2009), which posits that self-efficacy beliefs shape individuals’ thoughts, emotions, and behaviors when confronting challenges. In the context of climate change, adolescents with strong self-efficacy perceive environmental threats as manageable, activate personal agency, and employ adaptive coping strategies, thereby moderating the negative psychological consequences of climate risk perception (Becht et al., 2024; Xue et al., 2024; Dong et al., 2022). 2.2.4 Integrated Moderating Effects of Self-Regulation, Resilience, and Self-Efficacy In this framework, self-regulation facilitates immediate emotional control, resilience supports long-term adaptation and recovery, and self-efficacy enhances proactive coping and engagement. Together, these capacities may complement one another to contribute to a broader psychological framework that supports adaptive functioning under climate-related stressors. (Qin et al., 2024; Sayın-Kılıç et al., 2024; Li et al., 2024). Despite growing global interest in climate-related mental health, empirical integration of these moderators remains limited in young adults’ samples, particularly within cultural contexts such as Egypt, where systematic investigation is still emerging . Although considerable research has addressed climate-related mental health among adolescents, most studies have examined self-regulation, resilience, orself-efficacy in isolation, with limited exploration of their potential interactive effects (Qin et al., 2024; Sayın-Kılıç et al., 2024; Li et al., 2024; Crone & Dahl, 2012; Whitmarsh et al., 2022). The Integrative Model of Psychological Adaptation (Masten, 2018) posits that adaptive responses to chronic stressors, such as climate change, involve dynamic interactions among these regulatory capacities, collectively promoting emotional stability, behavioral regulation, and a sense of agency (Epel et al., 2025; Stoll-Kleemann & O’Riordan, 2020; Albrecht et al., 2024). However, empirical studies rarely examined these factors simultaneously, leaving a notable gap that this study seeks to fill by investigating their combined moderating roles in the relationship between climate change risk perception and psychological distress. 2.2.5 Gender Differences in the Integrative Model Gender differences are an essential component of the study's integrative framework, enhancing understanding of adolescents’ psychological responses to climate change risks. Females generally report higher climate risk perception and emotional sensitivity, linked to greater empathy and environmental concern (Chawla, 2020), while males tend to adopt problem-focused coping and may underreport distress (Clayton et al., 2023; Shtessel, 2023). These patterns extend to psychological resources. Males often exhibit stronger emotional self-regulation under stress (Zimmermann & Iwanski, 2014; Masten, 2018), whereas females may benefit more from interventions targeting self-regulation and resilience (Compas et al., 2017; Luo et al., 2025). Gender variations also appear in self-efficacy, with males displaying higher agentic efficacy and females relying more on relational efficacy (Cabello et al., 2023; Anderson & Sandler, 2023; Park et al., 2024; Wang et al., 2024). Importantly, in the Egyptian sociocultural context, traditional gender roles and expectations shape the development and application of key psychological resources, thereby influencing young adults’ adaptive responses to climate-related stressors (Abousoliman et al., 2024; Elshirbiny & Abrahamse, 2020). In this framework, self-regulation, resilience, and self-efficacy are conceptualized as psychological moderators linking climate change risk perception to psychological distress (Luo et al., 2025; Johnson & Brækstad, 2024). Gender is incorporated into the model to examine whether the strength and direction of these moderating effects differ between male and female young adults (Albrecht et al., 2024). Hypotheses Development Based on the integrative model, the following hypotheses are proposed: Hypothesis1: High climate change risk perception is positively correlated with psychological distress. Hypothesis2: Self-regulation, resilience, and self-efficacy each independently and collectively moderate the relationship between climate change risk perception and psychological distress. Hypothesis 3: Gender differences exist in the relationship between climate change risk perception and psychological distress, as well as in the moderating effects of self-regulation, resilience, and self-efficacy. Methodology 4.1 Research Design This study employed a cross-sectional, correlational design to examine the moderating roles of self-regulation, resilience, and self-efficacy in the relationship between climate change risk perception and psychological distress among young adults at Cairo University. The design was selected to efficiently assess correlations among variables and identify potential interaction effects across a broad adolescent sample at a single point in time. 4.2 Participants The study sample comprised 2,065 young adults aged 18 to 22 years, recruited from multiple faculties at Cairo University. This number represents approximately 1% of the total student population, estimated at 200,000 students. Based on this population size, the sampling error was calculated at ±2.1% with a 95% confidence level, indicating acceptable precision for population estimates. An a priori power analysis confirmed that the sample size was sufficient to detect moderation effects with adequate statistical power. Due to practical constraints associated with the large population size, a stratified convenience sampling method was adopted. Stratification was performed by gender (male and female) and academic discipline (theoretical and practical faculties) to ensure balanced representation across key subgroups. To minimize confounding variables, individuals with clinically diagnosed psychological disorders (e.g., major depressive disorder, anxiety disorders) were excluded. Table:1 provides a detailed breakdown of the sample's demographic characteristics : Table 1: Sample's demographic characteristics Gender Males (N= 996) Females (N= 1069) Age Mean 19.60 19.47 St. Dev. 1.35 1.21 College Theoretical Freq. 351 509 Percent. % 35.24 47.61 Practical Freq. 645 560 Percent. % 64.76 52.39 4.3 Measures 4-3-1: Climate Change Risk Perception Scale (CCRPS) Building on the original theoretical model developed by van der Linden (2015), the scale employed in the present study was constructed in alignment with the conceptual framework proposed by Böhm and Doran (2023). The instrument consists of 20 items, equally distributed across four core dimensions of climate change risk perception: perceived severity, perceived vulnerability, perceived consequences, and efficacy beliefs (five items per dimension). Previous research employing this scale across various cultural settings has consistently supported its strong psychometric properties, including satisfactory internal consistency and multiple forms of validity, such as convergent, discriminant, and construct validity (e.g., Aksit, 2025; Antronico et al., 2023). 4-3-2: Connor-Davidson Resilience Scale (CD-RISC-25) The scale was developed by Connor and Davidson (2003) 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 high internal consistency (Cronbach’s alpha), test-retest reliability, and convergent validity with related constructs, as well as cross-cultural validity, particularly in adolescent populations (Luo et al., 2025; Johnson & Brækstad, 2024). Other recent studies have further supported the robustness of its psychometric properties, including reliability and validity (Minnett & Stephenson, 2024; Windle et al., 2022). 4-3-3: Self-Regulation Questionnaire – Short Form (SRQ-SF) It is a 31-item self-report instrument developed by Carey et al. (2004) to assess individuals’ ability to plan, monitor, and regulate their behavior toward goal attainment, particularly in challenging or emotionally demanding situations. Derived from the original 63-item Self-Regulation Questionnaire by Brown et al. (1999), it has demonstrated good internal consistency (Cronbach’s alpha), as well as strong construct and predictive validity across various populations, including young adults and adults (Neal & Carey, 2005; Motamed‑Jahromi et al.,2022). 4-3-4: General Self-Efficacy Scale (GSES) It is a 10-item self-report measure developed by Schwarzer and Jerusalem (1995) to assess individuals’ perceived ability to cope with life challenges. The scale has been widely applied across diverse cultures and age groups and has been translated into multiple languages. It demonstrates strong internal consistency as well as robust construct and criterion validity n different cultures (Luszczynska et al.,2005; Das et al.,2024). 4-3-5 General Health Questionnaire-28 (GHQ-28) The General Health Questionnaire-28 (GHQ-28), developed by Goldberg and Hillier (1979), is a widely validated screening instrument for detecting minor psychiatric symptoms in both general and clinical populations. It consists of 28 items divided into four subscales: somatic symptoms, anxiety/insomnia, social dysfunction, and severe depression, capturing short-term changes in mental functioning. The GHQ-28 has demonstrated high internal consistency and strong convergent validity across diverse populations and cultural contexts (Moreta-Herrera et al., 2021; McElroy et al., 2018; Friedman & Keane, 2023). 4-3-6: Measures Adaptation for the Egyptian Sample To ensure cultural relevance, all measures 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 measures were administered to a sample of 200 students similar to the main study population. Reliability coefficients (Cronbach’s alpha and split-half) for the scales ranged from α = 0.76 to 0.91. Evidence of concurrent and construct validity was supported by correlations with established psychological instruments and results from exploratory factor analysis (Abdallah, 2025; Abdallah et al., in press). 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 males and females (*) . Table 2 :The reliability coefficients for each scale across male and female participants . Scales Males Females 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 4-4 Data Collection Data collection was conducted over two months at the beginning of the 2024–2025 academic year. Following IRB approval and university authorization, participants provided oral informed consent immediately before the questionnaire administration session. Data were collected in classrooms during university hours by a team of 15 trained master’s students, who supervised the implementation procedures under the guidance of some members of the research team. Each session included 15–25 participants and lasted approximately 20–25 minutes. Confidentiality was ensured through anonymous coding. Minimal missing data were observed; incomplete responses were excluded. 4-5 Statistical Analysis Data analyses were conducted using IBM SPSS Statistics (Version XX) and AMOS (Version XX). Descriptive statistics were computed to summarize demographic characteristics and the distributions of all study variables. Pearson’s correlation coefficients were calculated to examine bivariate relationships among the variables. Because the study included three moderating variables—exceeding the analytical capacity of commonly used tools such as Hayes’s PROCESS macro, which accommodates a maximum of two moderators (Hayes, 2022, p. 293)—structural equation modeling was conducted in AMOS. Manual computations were performed to specify and estimate higher-order interaction effects. Prior to the creation of interaction terms, all predictor variables were mean-centered to minimize multicollinearity. 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 stepwise modeling approach allowed for a systematic and comprehensive assessment of both the unique and combined moderating effects. (*) 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. Results 5.1 Descriptive statistics Table 3 displays the descriptive statistics of the study variables for male and female participants. Table 3: The descriptive statistics of the study variables for male and female participants Gender Variables Minimum Maximum Mean Std. Dev Median Kurtosis Skewness* Males (n= 996) Climate change risk perception 15.00 75.00 55.32 10.44 56 -0.006 -0.20 Psychological distress 29.00 136.00 76.10 21.76 76 -0.467 0.01 Self-regulation 44.00 150.00 106.73 17.73 108 0.100 -0.22 Resilience 25.00 125.00 90.37 16.71 90 0.009 0.07 Self- efficacy 10.00 50.00 34.81 7.59 35 -0.107 -0.08 Females (n= 1069) Climate change risk perception 24.00 75.00 56.32 9.87 57 -0.156 -0.207 Psychological distress 28.00 137.00 78.96 22.49 79 -0.625 -0.005 Self-regulation 42.00 150.00 106.28 18.08 107 -0.077 -0.120 Resilience 29.00 125.00 89.82 15.81 90 0.027 -0.035 Self- efficacy 10.00 50.00 33.98 7.74 34 0.038 -0.009 * Pearson indices of skewness The descriptive statistics in Table 3 for both genders indicate that all personality variables, including total scores and subcomponents, are normally distributed. The skewness coefficients for all psychological variables fall within acceptable limits and are not statistically significant, confirming that the data are appropriate for statistical analysis and hypothesis testing. 5.2 Correlations between climate change risk perception and psychological distress Table 4 presents the correlations between climate change risk perception and psychological distress among female participants: Table 4: The correlations between climate change risk perception and psychological distress among male and female participants Gender Variables Climate change risk perception 1-Perceived Severity 2 - Perceived vulnerability 3 - Perceived likelihood Males N= (996) Psychological distress 0.112** 0.128** 0.143 ** 0.006 1 - Physical distress 0.185** 0.179** 0.178** 0.120** 2 - Anxiety distress 0.079* 0.092** 0.117** -0.019 3 - Social distress 0.062 .075* .084** -0.009 4 - Severe Depression 0.048 0.075* 0.091** -0.058 Females N= (1069) Psychological distress 0.094** 0.084** 0.129** 0.022 1 - physical distress 0.144** 0.122** 0.153** 0.095** 2 - anxiety distress 0.059 0.058 0.106** -0.022 3 - social distress 0.045 0.039 0.068* 0.006 4 - depression distress 0.068* .063* 0.103** 0.004 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). According to the information in Table 2, 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 males and females, these COR reached significance even when the strength of the relationships was relatively low. In the male sample, three correlation coefficients were significant at the p < 0.05 level, and eleven were significant at the p < 0.01 level. These accounted for 70 % of all correlations between the two variables and their sub-components. Similarly, in the female sample, three correlations (representing 60% of the total) were significant at the p < 0.05 level, and nine at the p < 0.01 level. Notably, the patterns of these associations did not differ significantly between males and females. 5.3-Moderation Analysis To examine the moderating roles of self-regulation, resilience, and self-efficacy—as well as their interaction effects—in the relationship between climate change risk perception and psychological distress. The analyses were conducted separately for male and female university student samples to identify gender-specific patterns and effects. 5.3.1: Results of the male’s sample Table 5 presents the standardized effects of independent and moderating variables among female participants. Table 5. Standardized Effects of Independent and Moderating Variables Among Male Participants (N = 966) Variables Standardized Estimates Significance 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. Self-regulation had a negative effect, confirming its protective role, and resilience also demonstrated a significant buffering effect. Unexpectedly, self-efficacy was positively associated with distress, indicating that higher self-efficacy slightly exacerbated psychological distress. - Interaction Effects Significant negative interactions were found 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 a complex interplay that may increase distress. 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 buffering role. The four-way interaction among all variables was non-significant. 5.3.2 Results of the female’s sample Table 6 presents the standardized effects of independent and moderating variables among female participants. Table 6: Standardized Effects of Independent and Moderating Variables Among Female Participants (N = 1069) Variables Standardized Estimates Significance 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 Sel-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 females, 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 buffering effect. Unexpectedly, self-efficacy was positively associated with distress, indicating that higher self-efficacy slightly exacerbated psychological stress. - Interaction Effects No significant interaction was found between climate change risk perception and any of the three variables: self-regulation, resilience, and self-efficacy. - 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. Discussion Guided by an integrative framework, this study explored the relationship between climate change risk perception and psychological distress among young adults, focusing on the moderating roles of self-regulation, resilience, and self-efficacy. The findings partially supported the proposed hypotheses, confirming a significant direct association between risk perception and distress. However, the moderating effects varied: while self-regulation and resilience demonstrated protective roles, self-efficacy showed an unexpected amplifying effect. Gender-based differences and the broader sociocultural background shaped these patterns, emphasizing the ne ed for context-sensitive interpretations of adolescent coping mechanisms in response to climate threats. Specifically, for the first hypothesisو the findings offered partial support, revealing a statistically significant—though modest—positive association between climate change risk perception and psychological distress(Gianfredi et al.,2024). This indicates that young adults who view climate change as a serious threat report higher emotional discomfort (Prates-Baldez et al., 2024), consistent with prior research linking psychological responses to broader contextual factors, particularly in regions like Greater Cairo where climate impacts may feel less immediate (Carreiro et al., 2024 ). Concerning the second hypothesis focused on the moderating role of psychological traits, results showed that self-regulation, resilience, and self-efficacy tended to function independently rather than interactively, likely due to developmental constraints in executive and emotional integration during adolescence (Treble et al., 2022; Proulx et al., 2024; Crone & Dahl, 2012; Luo et al., 2025).The absence of consistent higher-order interaction effects suggests that coordinating multiple coping mechanisms under environmental stress may exceed Young adults’ developmental capacities. These findings challenge assumptions in interaction-based models and underscore the need to incorporate developmental and contextual factors when examining psychological adaptation to climate-related risks (Crone & Dahl, 2012; Proulx et al., 2024; Treble et al., 2022; Compas et al., 2017). Extending these findings, the third hypothesis identified gender as a critical contextual factor influencing both the structure and presence of moderation effects) Albrecht et al.,2024; Cabello et al.,2023; Anderson & Sandler, 2023; Luo et al.,2025) The findings suggest that psychological resources such as self-regulation, resilience, and self-efficacy may operate through gender-specific mechanisms shaped by differing socialization patterns, cognitive appraisals, and emotional regulation styles. Males exhibited a more diverse range of significant interactions—some exerting protective effects and others amplifying distress—indicating a more complex interplay between internal traits and perceived environmental threat (Becht et al., 2024; Luo et al., 2025). In contrast, females showed fewer significant moderation effects and more consistent, linear relationships across variables, potentially reflecting greater emotional sensitivity and lower executive integration during adolescence (Xue et al.,2025; Johnson & Brækstad, 2024 ). Gender-based differences in coping strategies are evident, with females more inclined toward emotion-focused responses such as rumination and expressive processing, whereas males typically adopt task-oriented or cognitively distancing approaches (Albrecht et al., 2024; Clayton et al., 2023).These contrasting coping styles influence not onlyhow psychological resources are accessed but also how they interact under stress, underscoring the importance of treating gender as a structural variable in future models(Clayton & Manning, 2023 ; Becht et al.,2024). Additionally, such gendered patterns may be further reinforced or shaped by the sociocultural context of Egyptian society, where traditional gender norms influence emotional expression, coping styles, and access to supportive environments (Elshirbiny & Abrahamse, 2020). In many Egyptian settings, females are often socialized to express vulnerability and seek emotional support, while males are typically encouraged to exhibit emotional restraint and adopt more autonomous, action-oriented coping strategies (Albrecht et al., 2024). These normative expectations deepen the observed differences in how Young adults engage with psychological resources under climate-related stress (Treble et al.,2023 Proulx et al.,2024). Furthermore, culturally embedded values such as familial obligation, collective identity, and social reputation impose distinct psychological burdens on males and females, influencing their perception of climate risks and their capacity to adapt (Gianfredi et al., 2024). Such findings underscore the need for culturally grounded models that integrate both gender and sociocultural dynamics when addressing adolescent mental health in the context of environmental challenges. Building upon these sociocultural considerations, the findings concerning self-efficacy partially contradict Bandura’s (2009) theoretical model, which posits that self-efficacy serves as a protective factor against psychological distress by enhancing individuals’ perceived control over adverse situations. However, in the present study, self-efficacy was positively associated with distress, particularly among females (Gianfredi et al., 2024). This paradox may reflect a mismatch between young adults’ strong belief in their capacity to act and the limited real-world opportunities available to address complex and large-scale issues such as climate change (Jarrett et al., 2024). As Bandura emphasized, self-efficacy must be grounded in actual, actionable contexts; otherwise, it may result in frustration, emotional overload, or internalized pressure—especially in sociocultural environments where individual environmental agency is constrained (Clayton et al., 2023; Albrecht et al., 2024). This dynamic aligns with the concept of motivated helplessness that describes a psychological state in which individuals experience high perceived responsibility but low perceived control, leading to increased anxiety rather than empowerment (Lutz et al., 2023; Strizhitskaya et al., 2024). In such contexts, self-efficacy, instead of buffering distress, may amplify it by intensifying the emotional burden of perceived inaction or ineffectiveness. These findings must also be interpreted in light of broader cultural and contextual realities in Egypt. Psychological traits such as self-regulation and resilience are not culturally neutral. In many Egyptian social contexts, self-regulation is often conceptualized as self-restraint or obedience rather than adaptive flexibility (Elshirbiny & Abrahamse, 2020; Masten, 2018), while resilience may be viewed as silent endurance rather than proactive coping (Gianfredi et al., 2024). Similarly, self-efficacy may not be experienced as personal confidence but rather as an internalized moral obligation to succeed or remain strong, particularly within academic and familial domains (Albrecht et al., 2024). These culturally shaped meanings may help explain why psychological strengths did not always function as expected and, in some cases, intensified emotional conflict instead of alleviating it (Clayton et al., 2023). This raises the broader question of how Egyptian culture mediates between individual and collective psychological resources. Personal traits like resilience and self-efficacy may interact with community-level resilience and collective efficacy (Cosentino et al., 2024; Šrol et al., 2023). Given Egypt’s emphasis on social cohesion and interdependence, communal coping may take precedence over individual strategies (Elshirbiny & Abrahamse, 2020; Albrecht et al., 2024). Socialization also shapes norms around acceptable responses to adversity, including climate threats (Abdallah et al., in press). These cultural dynamics may help explain why individual traits were not sufficient—and at times even associated with increased distress (Clayton et al., 2023; Gianfredi et al., 2024). Future models should integrate such sociocultural factors to more accurately reflect non-Western coping processes. Furthermore, it is important at this point to highlight several critical methodological and theoretical issues that may help advance research in this domain. While the study adopted a comprehensive integrative model incorporating self-regulation, resilience, and self-efficacy, the findings suggest that these factors were more effective independently than in combination (Luo et al., 2025). The weak interaction effects—especially among females—point to the influence of other variables, such as emotion regulation, social support, cultural norms, and broader societal pressures (Jarrett et al., 2024; Lutz et al., 2023; Albrecht et al., 2024). Therefore, the current model provides a helpful but incomplete framework, emphasizing the need to expand theoretical approaches to better capture the complexity of young adults’ responses to climate risk (Clayton et al., 2023; Gianfredi et al., 2024). Accordingly, this calls for a conceptual shift—from an integrative model assuming simultaneous and cumulative moderation, to a conditional model that recognizes context-driven variability and the uneven contribution of internal resources (Chen et al., 2024; Luo et al., 2025). Such a revision enhances the ecological validity of the model and better reflects the psychological realities faced by Young adults confronting abstract and large-scale threats like climate change (Clayton et al., 2023; Carmen et al.,2022). This consideration becomes especially important when designing tailored interventions or developing gender-sensitive mental health strategies (Albrecht et al., 2024; Gianfredi et al., 2024). The second issue concerns developmental appropriateness, as the study focuses on a developmental phase characterized by emerging regulatory capacities and limited emotional integration. During adolescence, cognitive control, emotional regulation, and moral reasoning remain in development, which may limit the ability to process complex and abstract threats such as climate change (Crone & Dahl, 2012; Masten, 2018). Moreover, young adults often display heightened emotional reactivity and are strongly influenced by peers and social context, rendering them more vulnerable to feelings of helplessness or disengagement when they perceive limited support for climate action (Gianfredi et al., 2024). These factors underscore the necessity for age-specific theories and measurement tools that accurately capture how youth perceive and cope with environmental threats (Proulx et al., 2024; Treble et al., 2022). A key third methodological issue involves the conceptual overlap among commonly used terms in the field, such as eco-anger (Stanley et al., 2021), eco-anxiety (Lutz et al., 2023; Betrò, 2024), climate anxiety (Whitmarsh et al., 2022), environmental worry, ecological grief, eco-depression, climate distress, climate worry, and climate trauma (Strizhitskaya et al., 2024; Jarrett et al., 2024). The lack of clear distinctions among these constructs creates psychometric challenges and contributes to inconsistent findings across studies (Ramsay et al., 2025). Cultural variations in emotional norms and climate awareness further complicate interpretation (Shtessel, 2023). This definitional variability makes it difficult to distinguish normative concern from clinical distress, and raises questions about whether current definitions of eco-anxiety fully capture the complexity of climate-related psychological responses (Cosh et al., 2024; Meo et al., 2025). A fourth issue relates to the possibility that eco-anxiety and similar constructs may, in some cases, lead to psychological denial, especially among adolescents and young adults (DeLay, 2024; Veijonaho et al.,2023). When climate threats seem overwhelming, denial may act as a defense mechanism to reduce emotional strain—particularly in youth whose emotional and cognitive systems are still developing (Proulx et al., 2024; Stanley et al., 2021). In such cases, denial may reflect motivated disengagement rather than apathy (Whitmarsh et al., 2022). Cultural beliefs in collectivist or fatalistic societies may further support this reaction by portraying climate change as beyond personal or collective control (Stoll-Kleemann & O’Riordan, 2020). Denial, therefore, should be seen as one form of emotional coping, not simply a lack of concern (Veijonaho et al.,2023). A fifth issue highlights the lack of climate change education in university-wide curricula. At Cairo University, general education courses rarely address climate change or its relevance to Egypt’s context (Elshirbiny & Abrahamse, 2020; Abousoliman et al., 2024). This gap was reflected in participant discussions, with many students showing limited awareness or questioning its relevance. In contrast, students in faculties like agriculture and science were more informed, likely due to curricular exposure (Aksit, 2025). This disparity stresses the importance of integrating climate education across disciplines. Comparative studies from other climate-affected regions or environmentally focused faculties offer useful insights into these gaps. Theoretical and Practical Implications Theoretically, the study questions the assumption that self-regulation, resilience, and self-efficacy work synergistically during adolescence, suggesting these factors may act independently and are influenced by developmental and contextual variables. Practically, the results support the need for interventions tailored by age and gender that offer both cognitive and emotional support. Culturally sensitive digital and AI-based tools also offer promising avenues for delivering mental health support. Limitations Several limitations should be considered when interpreting the findings of this study. The use of a cross-sectional design restricts the ability to draw conclusions about the temporal or causal direction of the relationships among the study variables. Although the analytical approach captured complex interactions, it remains limited in establishing causality. The exclusive reliance on self-reported data may have introduced response biases, especially considering potential variability in self-awareness and consistency among young adults. The sample was drawn entirely from students at Cairo University, which limits the generalizability of the findings to populations from other universities, age groups, or cultural backgrounds within and beyond Egypt. Furthermore, while the study focused on self-regulation, resilience, and self-efficacy as key psychological moderators, it did not account for other potentially significant variables—such as collective efficacy, society resilience, cognitive appraisals, environmental identity, or sociocultural influences—that may also shape individual responses to perceived climate risks. Acknowledging and addressing these limitations in future studies would enhance the robustness, applicability, and external validity of research in this field. Recommendations for Future Research Future studies should broaden the psychological and contextual scope of climate change research among young adults and other populations by promoting climate literacy, locally relevant education, and meaningful adolescent and youth engagement. Methodologically, it is essential to adopt longitudinal, explanatory, and mixed-methods designs that include behavioral measures, informant reports, focus groups, or physiological indicators. It is also recommended to examine a broader range of psychological and contextual moderators—such as collective efficacy, cognitive coping styles, environmental values, and community-based influences—to capture the complexity of individual responses to climate threats. Family support, media exposure, and context-specific coping strategies, including faith-based and digital approaches, are also crucial. Finally, interdisciplinary collaboration among researchers in psychology, environmental sciences, education, and public health is essential for developing culturally grounded interventions that support climate resilience among youth in Egypt and similar contexts. Conclusion This study examined the relationship between perceived climate change risk and psychological distress among young adults in Egypt, considering the moderating roles of self-regulation, resilience, and self-efficacy. A modest but significant correlations was found across both genders. Self-regulation and resilience showed protective effects for both males and females. However, self-efficacy unexpectedly increased distress in both groups, with no clear gender differences in its effect. Higher-order interaction effects were mostly non-significant, suggesting that young adults—regardless of gender—may find it difficult to manage multiple coping mechanisms simultaneously. These results emphasize the importance of gender-sensitive and culturally appropriate interventions that strengthen specific psychological capacities to support young adults’ mental health in the face of climate challenges. Declarations Ethics Approval and Consent to Participate The study received ethical approval from the Research Ethics Committee at Cairo University 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 and confidentiality. 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 No personal identifying information is presented in this manuscript. All participants were informed that anonymized data would be used exclusively for scientific research purposes. They were assured that all data would be statistically processed and presented in aggregate form, with no individual-level information disclosed 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 as part of the research development projects in the humanities and social sciences, in alignment with global scientific advancement . Authors' Contributions All authors have accepted full responsibility for the content of this manuscript and consented to its submission to the journal. They collaboratively formulated the research problem, conducted the literature review, structured the scientific content, and determined the appropriate research methodology and procedures. They also jointly reviewed the results, contributed to the preparation and revision of the final manuscript, and approved the version submitted for publication. Hamed Eid, Eman Soilam, and Eman Moataz coordinated and supervised data collection and verified the accuracy and integrity of the dataset. Usama Abosree conducted the statistical analyses and contributed to data interpretation and descriptive reporting. Moataz Abdallah led the theoretical interpretation and discussion of the results in collaboration with all co-authors. Acknowledgements The authors would like to thank all participants and reviewers who contributed to this research in all its stages. Authors' information [1] - Professor of psychology, Faculty of Arts, Cairo University. 2 -Professor of chemistry, Faculty of Science, Cairo University. 3 - Professor of climate geography Faculty of African studies, Cairo university. 4 -Professor of Pesticides Toxicology, Faculty of agricultural. Cairo university. 5 -Assistant professor of psychology, Faculty of Arts, Cairo University. 6 -Lecturer of psychology, Faculty of Arts, Cairo University. References Abdallah, E. M., Abdallah, M. S., & Mabrouk, A. A. (in press). Self-regulation, emotional regulation, Self-efficacy and sleep problems among typically developing young adults and adolescents with attention deficit/hyperactivity disorder (ADHD). Journal of Education and Childhood . 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Resilience and climate adaptation among adolescents: Psychological buffers against eco-anxiety. BMC Psychology, 12 , Article 241. https://doi.org/10.1186/s40359-024-01746-1 Whitmarsh, L., Player, L., Jiongco, A., James, M., Williams, M. O., Marks, E., & Kennedy-Williams, P. (2022). Climate anxiety: What predicts it and how is it related to climate action? Journal of Environmental Psychology, 83 , Article 101866. https://doi.org/10.1016/j.jenvp.2022.101866 Windle, G., MacLeod, C., Algar‑Skaife, K., Stott, J., Waddington, C., Camic, P. M., Sullivan, M. P., Brotherhood, E., & Crutch, S. (2022). Resilience measurement in later life: a systematic review and psychometric analysis . BMC Medical Research Methodology , 22 , Article 298. https://doi.org/10.1186/s12874-022-01747-x Wolff, J. C., Kühn, S., & Reinecker, M. (2023). Self‑regulation as a resource for coping with developmental challenges in adolescence: A prospective longitudinal study. BMC Psychology, 11 , Article 104. https://doi.org/10.1186/s40359-023-01140-3 World Health Organization. (2024). COP29 special report on climate change and health: Health is the argument for climate action. Geneva: WHO. Retrieved from https://cdn.who.int/media/docs/default-source/environment-climate-change-and-health/58595-who-cop29-special-report_layout_9web.pdf(cdn.who.int) Xue, Y., Wang, L., Chen, Z., & Li, J. (2024). Rethinking adolescent climate resilience: Disentangling the roles of self-efficacy, regulation, and contextual support. Journal of Adolescence, 102 , 45–58. https://doi.org/10.1016/j.adolescence.2024.01.005 Additional Declarations No competing interests reported. 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. 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Surpassing the 1.5°C warming threshold may trigger irreversible outcomes such as sea-level rise, biodiversity loss, and the degradation of aquatic ecosystems (Lee et al., 2024; Menden-Deuer et al., 2023; Diffenbaugh \u0026amp; Burke, 2023; Bevacqua et al., 2025). Although the Arab region contributes minimally to global emissions, it remains highly vulnerable to climate-related risks such as floods, forest fires, desertification, and adverse weather, as observed in Egypt and neighboring countries in the Gulf and North Africa, particularly Morocco and Algeria (Baumert \u0026amp; Kloos, 2017; Ads et al., 2023; Elsayed et al., 2024; ESCWA, 2022).\u003c/p\u003e\n\u003cp\u003eIn Egypt, most research has focused on the economic, legal, and environmental aspects of climate change, while studies on climate change psychology and the psychological impacts of climate change remain limited (Abousoliman et al., 2024; Elshirbiny \u0026amp; Abrahamse, 2020). Climate change affects not only physical health, as seen in heat-related illnesses, cardiovascular and respiratory diseases, metabolic disorders, pulmonary conditions, asthma, and allergies (Dilaver et al., 2025; Bernhardt \u0026amp; Roy, 2024), but also mental health, contributing to anxiety, depression, insomnia, PTSD, and chronic psychological distress, particularly following exposure to extreme weather events or displacement (Cosh et al., 2024; Burrows, 2024; Schwartz et al., 2023; Niedzwiedz \u0026amp; Kariuki, 2025).\u003c/p\u003e\n\u003cp\u003eGiven this dual burden, integrating mental health considerations into climate adaptation strategies is increasingly vital (Burrows et al.,2024; WHO, 2024). Perception of climate change risk plays a central role in shaping psychological responses and may exacerbate vulnerability among high-risk populations, particularly adolescents, due to ongoing cognitive and emotional development (Gianfredi et al., 2024; Cash et al.,2024). Gender differences also influence these effects (Albrecht et al., 2024; Wang et al., 2023).\u003c/p\u003e\n\u003cp\u003eTo address this research gap, the current study adopts an integrative psychological approach to examine the relationship between climate change risk perception and psychological distress among young adults in Egypt. It also investigates whether personal psychological resources—specifically self-regulation, resilience, and self-efficacy—moderate this relationship and serve as protective factors in the context of environmental threats.\u003c/p\u003e"},{"header":"Theoretical Framework","content":"\u003cp\u003eThis section outlines the theoretical foundations of the study by examining the relationship between perceived climate change risk and psychological distress, as well as the moderating roles of self-regulation, resilience, and self-efficacy. It is grounded in established theories and supported by prior empirical research, culminating in the proposed conceptual model (Figure 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1 Climate Change Risk Perception and Psychological Distress\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerceptions of climate change risks influence how individuals interpret environmental threats and respond emotionally and behaviorally (Lee et al., 2024).\u0026nbsp;This area has received increasing attention within the field of climate psychology (Gianfredi et al., 2024). However, in the Egyptian context, existing research has primarily focused on aspects of public awareness, attitudes, and policy development (Abousoliman et al., 2024; Elshirbiny \u0026amp; Abrahamse, 2020).\u003c/p\u003e\n\u003cp\u003eEmpirical findings on the link between risk perception and psychological distress are mixed, with studies reporting positive, weak, or non-significant associations (Cosh et al., 2024; Burke et al., 2024; Reyes et al., 2023; Ogunbode et al., 2021). Some evidence suggests that risk perception may relate more strongly to behavioral engagement than emotional distress (Lutz et al., 2023; Schwartz et al., 2023). Theories such as Individual Environmental Sensitivity (Whitmarsh et al., 2022), Terror Management Theory (Goldenberg \u0026amp; Pyszczynski, 2015), and Cognitive Appraisal Theory (Lazarus \u0026amp; Folkman, 1984) propose that personal traits, perceived control, and existential threat appraisals contribute to these discrepancies, especially among adolescents (Albrecht et al., 2024). Additionally, methodological limitations and contextual variability further complicate results and their generalization across different cultural settings (Wang et al., 2024; Jarrett et al., 2024). Accordingly, this study addresses these gaps by examining the relationship between climate risk perception and psychological distress among young adults in Egypt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2-2: The Roles of Moderator Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResilience, self-regulation, and self-efficacy are fundamental psychological resources that enable individuals to respond effectively to stressors such as climate change. Collectively, these capacities foster adaptive self-development, reinforce a sense of personal competence, and promote emotional stability in the face of global climate challenges, as follows:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2-2-1: Moderating Role of Self-Regulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-regulation\u0026mdash;the capacity to manage emotions, thoughts, and behaviors\u0026mdash;represents a potential buffer between climate change risk perception and psychological distress. Adolescents with stronger self-regulation skills tend to experience lower levels of distress despite perceiving elevated climate risks, as they employ adaptive strategies such as cognitive reappraisal and mindfulness (Dong et al., 2022; Compas et al., 2017). Theoretical models of self-regulation, particularly Self-Determination Theory, suggest that autonomy and competence enhance individuals\u0026rsquo; ability to manage long-term stressors by fostering internal motivation and adaptive coping (Spitzer et al., 2023). Within the climate change context, self-regulation may thus moderate the association between risk perception and psychological distress. Adolescents with well-developed self-regulatory skills are better able to cognitively reinterpret environmental threats and apply flexible, adaptive strategies\u0026mdash;such as cognitive reappraisal\u0026mdash;thereby mitigating climate-related psychological distress (Treble et al., 2022; Crone \u0026amp; Dahl, 2012).\u003c/p\u003e\n\u003cp\u003eEmpirical evidence supports the moderating role of self-regulation in stressful contexts (Varas -Julca et al. (2024), demonstrated that adolescents with higher self-regulation capacities were more likely to engage in adaptive coping strategies, including cognitive reappraisal and problem-solving, which in turn reduced the emotional impact of environmental stressors. Similarly, Wolff et al. (2023) and Murray et al. (2022) found that self-regulation predicted more effective emotional adjustment and lower psychological distress in response to various stress-inducing circumstances, including environmental threats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2-2-2: Moderating Role of Resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResilience\u0026mdash;the ability to adapt and recover from adversity\u0026mdash;represents a key moderating factor that may reduce psychological distress in adolescents who perceive climate risks. Resilient individuals often employ proactive coping strategies such as problem-solving and seeking social support (Wang et al., 2024). For example, resilient adolescents may channel their distress into activism or prosocial engagement, thereby reducing feelings of helplessness and fostering a sense of meaning and purpose. Additionally, resilience supports cognitive reinterpretation of stressors, offering further protection to mental health (Ungar, 2022, 2023; Luo et al., 2025).\u003c/p\u003e\n\u003cp\u003eEmpirical research has consistently emphasized the buffering role of resilience against a wide range of psychological stressors, including those stemming from environmental threats\u0026nbsp;(Alford et al., 2023; Chen et al.,2024). So, adolescents with higher resilience were better equipped to manage the psychological consequences of climate change through proactive coping approaches such as problem-solving and social support-seeking, which helped them preserve psychological well-being and optimism (Pihkala et al., 2024; Wang et al., 2024; Luo et al., 2025; Johnson \u0026amp; Br\u0026aelig;kstad, 2024).\u003c/p\u003e\n\u003cp\u003eThis interpretation aligns 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 emerges when individuals draw upon both personal strengths and external supports to adapt positively under conditions of significant adversity\u0026mdash;such as climate-related threats\u0026mdash;thus moderating the impact of risk exposure on psychological outcomes (Alford et al., 2023; Luo et al., 2025;\u0026nbsp;Cosentino et al.,2024).\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\u0026mdash;the belief in one\u0026apos;s ability to effect change\u0026mdash;is associated with lower psychological distress in the context of climate threats. Adolescents with higher self-efficacy are more likely to engage in active coping and advocacy behaviors, which enhance their sense of personal control (Schwarzer \u0026amp; Luszczynska, 2023; Schwarzer \u0026amp; Luszczynska, 2023). This confidence contributes to the mitigation of anxiety and fosters involvement in sustainability practices such as reducing carbon consumption or promoting peer education. Moreover, self-efficacy facilitates a positive cognitive framing, enabling adolescents to view environmental challenges as opportunities for personal growth\u0026nbsp;(Spitzer et al., 2023; Luo et al., 2025). Accordingly, interventions aimed at strengthening adolescents\u0026rsquo; self-efficacy may play a pivotal role in alleviating the mental health burdens associated with climate-related stressors (Qin et al., 2024; Luo et al., 2025; Johnson \u0026amp; Br\u0026aelig;kstad, 2024).\u003c/p\u003e\n\u003cp\u003eThis perspective is consistent with Bandura\u0026rsquo;s Social Cognitive Theory (2009), which posits that self-efficacy beliefs shape individuals\u0026rsquo; thoughts, emotions, and behaviors when confronting challenges. In the context of climate change, adolescents with strong self-efficacy perceive environmental threats as manageable, activate personal agency, and employ adaptive coping strategies, thereby moderating the negative psychological consequences of climate risk perception (Becht et al., 2024; Xue et al., 2024; Dong et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.4 Integrated Moderating Effects of Self-Regulation, Resilience, and Self-Efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this framework, self-regulation facilitates immediate emotional control, resilience supports long-term adaptation and recovery, and self-efficacy enhances proactive coping and engagement. Together, these capacities may complement one another to contribute to a broader psychological framework that supports adaptive functioning under climate-related stressors. (Qin et al., 2024; Sayın-Kılı\u0026ccedil; et al., 2024; Li et al., 2024).\u003c/p\u003e\n\u003cp\u003eDespite growing global interest in climate-related mental health, empirical integration of these moderators remains limited in young adults\u0026rsquo; samples, particularly within cultural contexts such as Egypt, where systematic investigation is still emerging\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough considerable research has addressed climate-related mental health among adolescents, most studies have examined self-regulation, resilience, orself-efficacy in isolation, with limited exploration of their potential interactive effects (Qin et al., 2024; Sayın-Kılı\u0026ccedil; et al., 2024; Li et al., 2024; Crone \u0026amp; Dahl, 2012; Whitmarsh et al., 2022). The Integrative Model of Psychological Adaptation (Masten, 2018) posits that adaptive responses to chronic stressors, such as climate change, involve dynamic interactions among these regulatory capacities, collectively promoting emotional stability, behavioral regulation, and a sense of agency (Epel et al., 2025; Stoll-Kleemann \u0026amp; O\u0026rsquo;Riordan, 2020; Albrecht et al., 2024).\u003c/p\u003e\n\u003cp\u003eHowever, empirical studies rarely examined these factors simultaneously, leaving a\u0026nbsp;notable\u0026nbsp;gap that this study seeks to fill by\u0026nbsp;investigating their combined moderating roles in the relationship between climate change risk perception and psychological distress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.5 Gender Differences in the Integrative Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGender differences are an essential component of the study\u0026apos;s integrative framework, enhancing understanding of adolescents\u0026rsquo; psychological responses to climate change risks. Females generally report higher climate risk perception and emotional sensitivity, linked to greater empathy and environmental concern (Chawla, 2020), while males tend to adopt problem-focused coping and may underreport distress (Clayton et al., 2023; Shtessel, 2023).\u003c/p\u003e\n\u003cp\u003eThese patterns extend to psychological resources. Males often exhibit stronger emotional self-regulation under stress (Zimmermann \u0026amp; Iwanski, 2014; Masten, 2018), whereas females may benefit more from interventions targeting self-regulation and resilience (Compas et al., 2017; Luo et al., 2025). Gender variations also appear in self-efficacy, with males displaying higher agentic efficacy and females relying more on relational efficacy (Cabello et al., 2023; Anderson \u0026amp; Sandler, 2023; Park et al., 2024; Wang et al., 2024).\u003c/p\u003e\n\u003cp\u003eImportantly, in the Egyptian sociocultural context, traditional gender roles and expectations shape the development and application of key psychological resources, thereby influencing young adults\u0026rsquo; adaptive responses to climate-related stressors (Abousoliman et al., 2024; Elshirbiny \u0026amp; Abrahamse, 2020). In this framework, self-regulation, resilience, and self-efficacy are conceptualized as psychological moderators linking climate change risk perception to psychological distress (Luo et al., 2025; Johnson \u0026amp; Br\u0026aelig;kstad, 2024). Gender is incorporated into the model to examine whether the strength and direction of these moderating effects differ between male and female young adults (Albrecht et al., 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses Development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the integrative model, the following hypotheses are proposed:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis1:\u003c/strong\u003e High climate change risk perception is positively correlated with psychological distress.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis2:\u003c/strong\u003e Self-regulation, resilience, and self-efficacy each independently and collectively moderate the relationship between climate change risk perception and psychological distress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 3:\u003c/strong\u003e Gender differences exist in the relationship between climate change risk perception and psychological distress, as well as in the moderating effects of self-regulation, resilience, and self-efficacy.\u003c/p\u003e"},{"header":"Methodology ","content":"\u003cp\u003e\u003cstrong\u003e4.1 Research Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a cross-sectional, correlational design to examine the moderating roles of self-regulation, resilience, and self-efficacy in the relationship between climate change risk perception and psychological distress among young adults at Cairo University. The design was selected to efficiently assess correlations among variables and identify potential interaction effects across a broad adolescent sample at a single point in time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2 Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study sample comprised 2,065 young adults aged 18 to 22 years, recruited from multiple faculties at Cairo University. This number represents approximately 1% of the total student population, estimated at 200,000 students. Based on this population size, the sampling error was calculated at \u0026plusmn;2.1% with a 95% confidence level, indicating acceptable precision for population estimates. An a priori power analysis confirmed that the sample size was sufficient to detect moderation effects with adequate statistical power.\u003c/p\u003e\n\u003cp\u003eDue to practical constraints associated with the large population size, a stratified convenience sampling method was adopted. Stratification was performed by gender (male and female) and academic discipline (theoretical and practical faculties) to ensure balanced representation across key subgroups. To minimize confounding variables, individuals with clinically diagnosed psychological disorders (e.g., major depressive disorder, anxiety disorders) were excluded. \u003cstrong\u003eTable:1\u0026nbsp;\u003c/strong\u003eprovides a detailed breakdown of the sample\u0026apos;s demographic characteristics\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cstrong\u003eTable 1: Sample\u0026apos;s demographic characteristics\u003c/strong\u003e\u003c/strong\u003e\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 valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(N= 996)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(N= 1069)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSt. Dev.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.21\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\u003eTheoretical\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\u003ePercent. %\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\u003ePractical\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\u003ePercent. %\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 \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;4-3-1: Climate Change Risk Perception Scale (CCRPS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on the original theoretical model developed by van der Linden (2015), the scale employed in the present study was constructed in alignment with the conceptual framework proposed by B\u0026ouml;hm and Doran (2023). The instrument consists of 20 items, equally distributed across four core dimensions of climate change risk perception: perceived severity, perceived vulnerability, perceived consequences, and efficacy beliefs (five items per dimension).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevious research employing this scale across various cultural settings has consistently supported its strong psychometric properties, including satisfactory internal consistency and multiple forms of validity, such as convergent, discriminant, and construct validity (e.g., Aksit, 2025; Antronico et al., 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;4-3-2: Connor-Davidson Resilience Scale (CD-RISC-25)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scale was developed by Connor and Davidson (2003) 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 high internal consistency (Cronbach\u0026rsquo;s alpha), test-retest reliability, and convergent validity with related constructs, as well as cross-cultural validity, particularly in adolescent populations (Luo et al., 2025; Johnson \u0026amp; Br\u0026aelig;kstad, 2024). \u0026nbsp;Other recent studies have further supported the robustness of its psychometric properties, including reliability and validity (Minnett \u0026amp; Stephenson, 2024; Windle et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-3-3: Self-Regulation Questionnaire \u0026ndash; Short Form (SRQ-SF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is a 31-item self-report instrument developed by Carey et al. (2004) to assess individuals\u0026rsquo; ability to plan, monitor, and regulate their behavior toward goal attainment, particularly in challenging or emotionally demanding situations. Derived from the original 63-item Self-Regulation Questionnaire by Brown et al. (1999), it has demonstrated good internal consistency (Cronbach\u0026rsquo;s alpha), as well as strong construct and predictive validity across various populations, including young adults and adults (Neal \u0026amp; Carey, 2005; Motamed‑Jahromi et al.,2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-3-4: General Self-Efficacy Scale (GSES)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is a 10-item self-report measure developed by Schwarzer and Jerusalem (1995) to assess individuals\u0026rsquo; perceived ability to cope with life challenges. The scale has been widely applied across diverse cultures and age groups and has been translated into multiple languages. It demonstrates strong internal consistency as well as robust construct and criterion validity n different cultures (Luszczynska\u0026nbsp;et al.,2005; Das\u0026nbsp;et al.,2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-3-5 General Health Questionnaire-28 (GHQ-28)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe General Health Questionnaire-28 (GHQ-28), developed by Goldberg and Hillier (1979), is a widely validated screening instrument for detecting minor psychiatric symptoms in both general and clinical populations. It consists of 28 items divided into four subscales: somatic symptoms, anxiety/insomnia, social dysfunction, and severe depression, capturing short-term changes in mental functioning. The GHQ-28 has demonstrated high internal consistency and strong convergent validity across diverse populations and cultural contexts (Moreta-Herrera et al., 2021; McElroy et al., 2018; Friedman \u0026amp; Keane, 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-3-6: Measures Adaptation for the Egyptian Sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo ensure cultural relevance, all measures 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 measures were administered to a sample of 200 students similar to the main study population. Reliability coefficients (Cronbach\u0026rsquo;s alpha and split-half) for the scales ranged from \u0026alpha; = 0.76 to 0.91. Evidence of concurrent and construct validity was supported by correlations with established psychological instruments and results from exploratory factor analysis (Abdallah, 2025; Abdallah et al., in press). All responses were measured using a 5-point Likert scale ranging from \u0026ldquo;Strongly Disagree\u0026rdquo; to \u0026ldquo;Strongly Agree.\u0026rdquo; Table 2\u0026nbsp;presents the reliability coefficients for each scale, separately for males and females\u003csup\u003e(*)\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003cstrong\u003e:The reliability coefficients for each scale across\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;male and female participants\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\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\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\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\u003cp\u003e\u003cstrong\u003e4-4 Data Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection was conducted over two months at the beginning of the 2024\u0026ndash;2025 academic year. Following IRB approval and university authorization, participants provided oral informed consent immediately before the questionnaire administration session. Data were collected in classrooms during university hours by a team of 15 trained master\u0026rsquo;s students, who supervised the implementation procedures under the guidance of some members of the research team. Each session included 15\u0026ndash;25 participants and lasted approximately 20\u0026ndash;25 minutes. Confidentiality was ensured through anonymous coding. Minimal missing data were observed; incomplete responses were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-5 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analyses were conducted using IBM SPSS Statistics (Version XX) and AMOS (Version XX). Descriptive statistics were computed to summarize demographic characteristics and the distributions of all study variables. Pearson\u0026rsquo;s correlation coefficients were calculated to examine bivariate relationships among the variables.\u0026nbsp;Because the study included three moderating variables\u0026mdash;exceeding the analytical capacity of commonly used tools such as Hayes\u0026rsquo;s PROCESS macro, which accommodates a maximum of two moderators (Hayes, 2022, p. 293)\u0026mdash;structural equation modeling was conducted in AMOS. Manual computations were performed to specify and estimate higher-order interaction effects. Prior to the creation of interaction terms, all predictor variables were mean-centered to minimize multicollinearity. Two-way, three-way, and four-way interaction terms were generated in SPSS and incorporated into the AMOS model as observed variables.\u0026nbsp;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 stepwise modeling approach allowed for a systematic and comprehensive assessment of both the unique and combined moderating effects.\u003c/p\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\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"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e5.1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDescriptive statistics\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003edisplays the descriptive statistics of the study variables for male and female participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe descriptive statistics of the study variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efor male and female participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"686\"\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\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMaximum\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\u003eMales\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\u003e15.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.00\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\u003e\n \u003cp\u003e-0.20\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\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e136.00\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\u003e\n \u003cp\u003e0.01\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\u003e44.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e150.00\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\u003e\n \u003cp\u003e-0.22\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\u003e25.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125.00\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\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf- efficacy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.00\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\u003e\n \u003cp\u003e-0.08\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\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\u003e24.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.00\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\u003e\n \u003cp\u003e-0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.207\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\u003e28.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137.00\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\u003e\n \u003cp\u003e-0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.005\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\u003e42.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e150.00\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\u003e\n \u003cp\u003e-0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.120\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\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125.00\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\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf- efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.00\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\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Pearson indices of skewness\u003c/p\u003e\n\u003cp\u003eThe descriptive statistics in Table 3\u0026nbsp;for both genders indicate that all personality variables, including total scores and subcomponents, are normally distributed. The skewness coefficients for all psychological variables fall within acceptable limits and are not statistically significant, confirming that the data are appropriate for statistical analysis and hypothesis testing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2 Correlations between climate change risk perception and psychological distress\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;4\u0026nbsp;\u003c/strong\u003epresents the correlations between climate change risk perception and psychological distress among female participants:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4:\u003c/strong\u003e \u003cstrong\u003eThe correlations between climate change risk perception and psychological distress among male and female participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\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 valign=\"bottom\"\u003e\n \u003cp\u003e1-Perceived\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eSeverity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 - Perceived vulnerability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3 - Perceived likelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 - Physical distress\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 - Anxiety distress\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 - Social distress\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 \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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 - physical distress\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 - anxiety distress\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 - social distress\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 \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 - depression distress\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 \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e*. Correlation is significant at the 0.05 level (2-tailed).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the information in Table 2, 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 males and females, these COR reached significance even when the strength of the relationships was relatively low. In the male sample, three correlation coefficients were significant at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 level, and eleven were significant at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 level. These accounted for 70 % of all correlations between the two variables and their sub-components. Similarly, in the female sample, three correlations (representing 60% of the total) were significant at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 level, and nine at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 level. Notably, the patterns of these associations did not differ significantly between males and females.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3-Moderation Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine the moderating roles of self-regulation, resilience, and self-efficacy\u0026mdash;as well as their interaction effects\u0026mdash;in the relationship between climate change risk perception and psychological distress. The analyses were conducted separately for male and female university student samples to identify gender-specific patterns and effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3.1: Results of the male\u0026rsquo;s sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 presents the standardized effects of independent and moderating variables among female participants.\u003c/p\u003e\n\u003cp\u003eTable 5.\u0026nbsp;Standardized Effects of Independent and Moderating Variables Among Male Participants (N = 966)\u003c/p\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\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificance\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\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. Self-regulation had a negative effect, confirming its protective role, and resilience also demonstrated a significant buffering 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\u003eSignificant negative interactions were found 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 a complex interplay that may increase distress. 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 buffering role. The four-way interaction among all variables was non-significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3.2 Results of the female\u0026rsquo;s sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 6 presents the standardized effects of independent and moderating variables among female participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003eStandardized Effects of Independent and Moderating Variables Among Female Participants (N = 1069)\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\" class=\"fr-table-selection-hover\"\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\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificance\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 Sel-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 females, 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 buffering effect. Unexpectedly, self-efficacy was positively associated with distress, indicating that higher self-efficacy slightly exacerbated psychological stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Interaction Effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo significant interaction was found between climate change risk perception and any of the three variables: self-regulation, resilience, and self-efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e- Higher-Order Interactions\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"},{"header":"Discussion","content":"\u003cp\u003eGuided by an integrative framework, this study explored the relationship between climate change risk perception and psychological distress among young adults, focusing on the moderating roles of self-regulation, resilience, and self-efficacy. The findings partially supported the proposed hypotheses, confirming a significant direct association between risk perception and distress. However, the moderating effects varied: while self-regulation and resilience demonstrated protective roles, self-efficacy showed an unexpected amplifying effect. Gender-based differences and the broader sociocultural background shaped these patterns, emphasizing the ne\u0026nbsp;ed for context-sensitive interpretations of adolescent coping mechanisms in response to climate threats.\u003c/p\u003e\n\u003cp\u003eSpecifically, for the first hypothesisو the findings offered partial support, revealing a statistically significant—though modest—positive association between climate change risk perception and psychological distress(Gianfredi et al.,2024). This indicates that young adults who view climate change as a serious threat report higher emotional discomfort (Prates-Baldez et al., 2024), consistent with prior research linking psychological responses to broader contextual factors, particularly in regions like Greater Cairo where climate impacts may feel less immediate (Carreiro et al., 2024\u0026nbsp;).\u003c/p\u003e\n\u003cp\u003eConcerning the second hypothesis focused on the moderating role of psychological traits, results showed that self-regulation, resilience, and self-efficacy tended to function independently rather than interactively, likely due to developmental constraints in executive and emotional integration during adolescence (Treble et al., 2022; Proulx et al., 2024; Crone \u0026amp; Dahl, 2012; Luo et al., 2025).The absence of consistent higher-order interaction effects suggests that coordinating multiple coping mechanisms under environmental stress may exceed Young adults’ developmental capacities. These findings challenge assumptions in interaction-based models and underscore the need to incorporate developmental and contextual factors when examining psychological adaptation to climate-related risks (Crone \u0026amp; Dahl, 2012; Proulx et al., 2024; Treble et al., 2022; Compas et al., 2017). Extending these findings, the third hypothesis identified gender as a critical contextual factor influencing both the structure and presence of moderation effects)\u0026nbsp;Albrecht et al.,2024; Cabello et al.,2023; Anderson \u0026amp; Sandler, 2023; Luo et al.,2025)\u003c/p\u003e\n\u003cp\u003eThe findings suggest that psychological resources such as self-regulation, resilience,\u0026nbsp;and self-efficacy may operate through gender-specific mechanisms shaped by differing socialization patterns, cognitive appraisals, and emotional regulation styles. Males exhibited a more diverse range of significant interactions—some exerting protective effects and others amplifying distress—indicating a more complex interplay between internal traits and perceived environmental threat (Becht et al., 2024; Luo et al., 2025). In contrast, females showed fewer significant moderation effects and more consistent, linear relationships across variables, potentially reflecting greater emotional sensitivity and lower executive integration during adolescence (Xue et al.,2025;\u0026nbsp;Johnson \u0026amp; Brækstad, 2024 ).\u003c/p\u003e\n\u003cp\u003eGender-based differences in coping strategies are evident, with females more inclined toward emotion-focused responses such as rumination and expressive processing, whereas males typically adopt task-oriented or cognitively distancing approaches (Albrecht et al., 2024; Clayton et al., 2023).These contrasting coping styles influence not onlyhow psychological resources are accessed but also how they interact under stress, underscoring the importance of treating gender as a structural variable in future models(Clayton\u0026nbsp;\u0026amp; Manning, 2023\u0026nbsp;;\u0026nbsp;Becht et al.,2024).\u003c/p\u003e\n\u003cp\u003eAdditionally, such gendered patterns may be further reinforced or shaped by the sociocultural context of Egyptian society, where traditional gender norms influence emotional expression, coping styles, and access to supportive environments (Elshirbiny \u0026amp; Abrahamse, 2020). In many Egyptian settings, females are often socialized to express vulnerability and seek emotional support, while males are typically encouraged to exhibit emotional restraint and adopt more autonomous, action-oriented coping strategies (Albrecht et al., 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese normative expectations deepen the observed differences in how Young adults engage with psychological resources under climate-related stress (Treble et al.,2023\u0026nbsp;Proulx et al.,2024). Furthermore, culturally embedded values such as familial obligation, collective identity, and social reputation impose distinct psychological burdens on males and females, influencing their perception of climate risks and their capacity to adapt (Gianfredi et al., 2024). Such findings underscore the need for culturally grounded models that integrate both gender and sociocultural dynamics when addressing adolescent mental health in the context of environmental challenges.\u003c/p\u003e\n\u003cp\u003eBuilding upon these sociocultural considerations, the findings concerning self-efficacy partially contradict Bandura’s (2009) theoretical model, which posits that self-efficacy serves as a protective factor against psychological distress by enhancing individuals’ perceived control over adverse situations. However, in the present study, self-efficacy was positively associated with distress, particularly among females (Gianfredi et al., 2024). This paradox may reflect a mismatch between young adults’ strong belief in their capacity to act and the limited real-world opportunities available to address complex and large-scale issues such as climate change (Jarrett et al., 2024). As Bandura emphasized, self-efficacy must be grounded in actual, actionable contexts; otherwise, it may result in frustration, emotional overload, or internalized pressure—especially in sociocultural environments where individual environmental agency is constrained (Clayton et al., 2023; Albrecht et al., 2024). This dynamic aligns with the concept of motivated helplessness that describes a psychological state in which individuals experience high perceived responsibility but low perceived control, leading to increased anxiety rather than empowerment (Lutz et al., 2023; Strizhitskaya et al., 2024). In such contexts, self-efficacy, instead of buffering distress, may amplify it by intensifying the emotional burden of perceived inaction or ineffectiveness.\u003c/p\u003e\n\u003cp\u003eThese findings must also be interpreted in light of broader cultural and contextual realities in Egypt. Psychological traits such as self-regulation and resilience are not culturally neutral. In many Egyptian social contexts, self-regulation is often conceptualized as self-restraint or obedience rather than adaptive flexibility (Elshirbiny \u0026amp; Abrahamse, 2020; Masten, 2018), while resilience may be viewed as silent endurance rather than proactive coping (Gianfredi et al., 2024). Similarly, self-efficacy may not be experienced as personal confidence but rather as an internalized moral obligation to succeed or remain strong, particularly within academic and familial domains (Albrecht et al., 2024). These culturally shaped meanings may help explain why psychological strengths did not always function as expected and, in some cases, intensified emotional conflict instead of alleviating it (Clayton et al., 2023).\u003c/p\u003e\n\u003cp\u003eThis raises the broader question of how Egyptian culture mediates between individual and collective psychological resources. Personal traits like resilience and self-efficacy may interact with community-level resilience and collective efficacy (Cosentino et al., 2024; Šrol et al., 2023). Given Egypt’s emphasis on social cohesion\u0026nbsp;and interdependence, communal coping may take precedence over individual strategies (Elshirbiny \u0026amp; Abrahamse, 2020; Albrecht et al., 2024). Socialization also shapes norms around acceptable responses to adversity, including climate threats (Abdallah et al., in press). These cultural dynamics may help explain why individual traits were not sufficient—and at times even associated with increased distress (Clayton et al., 2023; Gianfredi et al., 2024). Future models should integrate such sociocultural factors to more accurately reflect non-Western coping processes.\u003c/p\u003e\n\u003cp\u003eFurthermore, it is important at this point to highlight several critical methodological and theoretical issues that may help advance research in this domain. While the study adopted a comprehensive integrative model incorporating self-regulation, resilience, and self-efficacy, the findings suggest that these factors were more effective independently than in combination (Luo et al., 2025). The weak interaction effects—especially among females—point to the influence of other variables, such as emotion regulation, social support, cultural norms, and broader societal pressures (Jarrett et al., 2024; Lutz et al., 2023; Albrecht et al., 2024). Therefore, the current model provides a helpful but incomplete framework, emphasizing the need to expand theoretical approaches to better capture the complexity of young adults’ responses to climate risk (Clayton et al., 2023; Gianfredi et al., 2024).\u003c/p\u003e\n\u003cp\u003eAccordingly, this calls for a conceptual shift—from an integrative model assuming simultaneous and cumulative moderation, to a conditional model that recognizes context-driven variability and the uneven contribution of internal resources (Chen et al., 2024; Luo et al., 2025). Such a revision enhances the ecological validity of the model and better reflects the psychological realities faced by Young adults confronting abstract and large-scale threats like climate change (Clayton et al., 2023;\u0026nbsp;Carmen et al.,2022). This consideration becomes especially important when designing tailored interventions or developing gender-sensitive mental health strategies (Albrecht et al., 2024; Gianfredi et al., 2024).\u003c/p\u003e\n\u003cp\u003eThe second issue concerns developmental appropriateness, as the study focuses on a developmental phase characterized by emerging regulatory capacities and limited emotional integration. During adolescence, cognitive control, emotional regulation, and moral reasoning remain in development, which may limit the ability to process complex and abstract threats such as climate change (Crone \u0026amp; Dahl, 2012; Masten, 2018). Moreover, young adults often display heightened emotional reactivity and are strongly influenced by peers and social context, rendering them more vulnerable to feelings of helplessness or disengagement when they perceive limited support for climate action (Gianfredi et al., 2024). These factors underscore the necessity for age-specific theories and measurement tools that accurately capture how youth perceive and cope with environmental threats (Proulx et al., 2024; Treble et al., 2022).\u003c/p\u003e\n\u003cp\u003eA key third methodological issue involves the conceptual overlap among commonly used terms in the field, such as eco-anger (Stanley et al., 2021), eco-anxiety (Lutz et al., 2023; Betrò, 2024), climate anxiety (Whitmarsh et al., 2022), environmental worry, ecological grief, eco-depression, climate distress, climate worry, and climate trauma (Strizhitskaya et al., 2024; Jarrett et al., 2024). The lack of clear distinctions among these constructs creates psychometric challenges and contributes to inconsistent findings across studies (Ramsay et al., 2025). Cultural variations in emotional norms and climate awareness further complicate interpretation (Shtessel, 2023). This definitional variability makes it difficult to distinguish normative concern from clinical distress, and raises questions about whether current definitions of eco-anxiety fully capture the complexity of climate-related psychological responses (Cosh et al., 2024; Meo et al., 2025).\u003c/p\u003e\n\u003cp\u003eA fourth issue relates to the possibility that eco-anxiety and similar constructs may, in some cases, lead to psychological denial, especially among adolescents and young adults (DeLay, 2024;\u0026nbsp;Veijonaho et al.,2023). When climate threats seem overwhelming, denial may act as a defense mechanism to reduce emotional strain—particularly in youth whose emotional and cognitive systems are still developing (Proulx et al., 2024; Stanley et al., 2021).\u0026nbsp;In such cases, denial may reflect motivated disengagement rather than apathy (Whitmarsh et al., 2022). Cultural beliefs in collectivist or fatalistic societies may further support this reaction by portraying climate change as beyond personal or collective control (Stoll-Kleemann \u0026amp; O’Riordan, 2020). Denial, therefore, should be seen as one form of emotional coping, not simply a lack of concern (Veijonaho et al.,2023).\u003c/p\u003e\n\u003cp\u003eA fifth issue highlights the lack of climate change education in university-wide curricula. At Cairo University, general education courses rarely address climate change or its relevance to Egypt’s context (Elshirbiny \u0026amp; Abrahamse, 2020; Abousoliman et al., 2024). This gap was reflected in participant discussions, with many students showing limited awareness or questioning its relevance. In contrast, students in faculties like agriculture and science were more informed, likely due to curricular exposure (Aksit, 2025). This disparity stresses the importance of integrating climate education across disciplines. Comparative studies from other climate-affected regions or environmentally focused faculties offer useful insights into these gaps.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTheoretical and Practical Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheoretically, the study questions the assumption that self-regulation, resilience, and self-efficacy work synergistically during adolescence, suggesting these factors may act independently and are influenced by developmental and contextual variables. \u0026nbsp;Practically, the results support the need for interventions tailored by age and gender that offer both cognitive and emotional support. \u0026nbsp;Culturally sensitive digital and AI-based tools also offer promising avenues for delivering mental health support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations should be considered when interpreting the findings of this study. The use of a cross-sectional design restricts the ability to draw conclusions about the temporal or causal direction of the relationships among the study variables. Although the analytical approach captured complex interactions, it remains limited in establishing causality. The exclusive reliance on self-reported data may have introduced response biases, especially considering potential variability in self-awareness and consistency among young adults. The sample was drawn entirely from students at Cairo University, which limits the generalizability of the findings to populations from other universities, age groups, or cultural backgrounds within and beyond Egypt. Furthermore, while the study focused on self-regulation, resilience, and self-efficacy as key psychological moderators, it did not account for other potentially significant variables—such as collective efficacy, society resilience, cognitive appraisals, environmental identity, or sociocultural influences—that may also shape individual responses to perceived climate risks. Acknowledging and addressing these limitations in future studies would enhance the robustness, applicability, and external validity of research in this field.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations for Future Research\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFuture studies should broaden the psychological and contextual scope of climate change research among young adults and other populations by promoting climate literacy, locally relevant education, and meaningful adolescent and youth engagement. Methodologically, it is essential to adopt longitudinal, explanatory, and mixed-methods designs that include behavioral measures, informant reports, focus groups, or physiological indicators. It is also recommended to examine a broader range of psychological and contextual moderators—such as collective efficacy, cognitive coping styles, environmental values, and community-based influences—to capture the complexity of individual responses to climate threats. Family support, media exposure, and context-specific coping strategies, including faith-based and digital approaches, are also crucial. Finally, interdisciplinary collaboration among researchers in psychology, environmental sciences, education, and public health is essential for developing culturally grounded interventions that support climate resilience among youth in Egypt and similar contexts.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examined the relationship between perceived climate change risk and psychological distress among young adults in Egypt, considering the moderating roles of self-regulation, resilience, and self-efficacy. A modest but significant correlations was found across both genders. Self-regulation and resilience showed protective effects for both males and females. However, self-efficacy unexpectedly increased distress in both groups, with no clear gender differences in its effect. Higher-order interaction effects were mostly non-significant, suggesting that young adults\u0026mdash;regardless of gender\u0026mdash;may find it difficult to manage multiple coping mechanisms simultaneously. These results emphasize the importance of gender-sensitive and culturally appropriate interventions that strengthen specific psychological capacities to support young adults\u0026rsquo; mental health in the face of climate challenges.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from the Research Ethics Committee at Cairo University 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 and confidentiality. 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\u003eNo personal identifying information is presented in this manuscript. All participants were informed that anonymized data would be used exclusively for scientific research purposes. They were assured that all data would be statistically processed and presented in aggregate form, with no individual-level information disclosed\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 as part of the research development projects in the humanities and social sciences, in alignment with global scientific advancement\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have accepted full responsibility for the content of this manuscript and consented to its submission to the journal. They collaboratively formulated the research problem, conducted the literature review, structured the scientific content, and determined the appropriate research methodology and procedures. They also jointly reviewed the results, contributed to the preparation and revision of the final manuscript, and approved the version submitted for publication. Hamed Eid, Eman Soilam, and Eman Moataz coordinated and supervised data collection and verified the accuracy and integrity of the dataset. Usama Abosree conducted the statistical analyses and contributed to data interpretation and descriptive reporting. Moataz Abdallah led the theoretical 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 would like to thank all participants and reviewers who contributed to this research\u0026nbsp;in all its stages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors'\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u003csup\u003e[1]\u003c/sup\u003e\u003c/sup\u003e-\u0026nbsp;Professor \u0026nbsp;of psychology, Faculty of Arts, Cairo University.\u003csup\u003e\u0026nbsp;2\u003c/sup\u003e-Professor of chemistry, Faculty of Science, Cairo University.\u003csup\u003e3\u003c/sup\u003e-\u0026nbsp;Professor of climate geography Faculty of African studies, Cairo university.\u003csup\u003e4\u003c/sup\u003e-Professor of Pesticides Toxicology, Faculty of agricultural. Cairo university. \u003csup\u003e5\u003c/sup\u003e-Assistant professor of psychology, Faculty of Arts, Cairo University. \u003csup\u003e6\u003c/sup\u003e-Lecturer of psychology, Faculty of Arts, Cairo University.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdallah, E. M., Abdallah, M. S., \u0026amp; Mabrouk, A. A. (in press). Self-regulation, emotional regulation, Self-efficacy and sleep problems among typically developing young adults and adolescents with attention deficit/hyperactivity disorder (ADHD). \u003cem\u003eJournal of Education and Childhood\u003c/em\u003e. [In Arabic]\u003c/li\u003e\n\u003cli\u003eAbdallah, M. S. (2025). Confirmatory factor analysis for climate change risk perception in adolescent males and females. \u003cem\u003eJournal of Scientific Methodology and Behavior\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(2), 100\u0026ndash;133. [In Arabic].\u003c/li\u003e\n\u003cli\u003eAbousoliman, A. D., Ibrahim, A. 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Rethinking adolescent climate resilience: Disentangling the roles of self-efficacy, regulation, and contextual support. \u003cem\u003eJournal of Adolescence, 102\u003c/em\u003e, 45\u0026ndash;58. https://doi.org/10.1016/j.adolescence.2024.01.005\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":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 and psychological distress","lastPublishedDoi":"10.21203/rs.3.rs-7048646/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7048646/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study adopts an integrative model to examine the relationship between climate change risk perception and psychological distress among young adults, focusing on the moderating roles of self-regulation, resilience, and self-efficacy. A cross-sectional survey was conducted with 2,065 undergraduate students from Cairo University during the first academic semester of 2024, representing approximately 1% of the university’s total student population. Participants completed validated Arabic versions of standardized psychological scales. Data were analyzed using SPSS for descriptive statistics and preliminary analyses, and AMOS for structural equation modeling to assess direct, interaction, and higher-order moderation effects.\nFindings revealed that climate change risk perception significantly predicted increased psychological distress. Self-regulation and resilience were negatively associated with distress, indicating their protective roles. Unexpectedly, self-efficacy was positively associated with distress. Significant interaction effects emerged only among males, with three-way interactions varying by gender. The four-way interaction was non-significant for both groups.\nThese results illustrate the potential utility of an integrative model in capturing gender-specific psychological responses to climate change. However, they also suggest that individual psychological resources alone may be insufficient to fully explain the mental health impacts of climate risk perception, highlighting the need to consider broader contextual and structural factors in future research and interventions.","manuscriptTitle":"The Moderating Roles of Self-Regulation, Resilience, and Self-Efficacy in the Relationship Between Climate Change Risk Perception and Psychological Distress: An Integrated Theoretical Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-01 10:05:43","doi":"10.21203/rs.3.rs-7048646/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":"September 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T09:08:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-01 10:05:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7048646","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7048646","identity":"rs-7048646","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}