The impact of Social leadership on psychological Resilience under Natural Environmental Hazards

The impact of Social leadership on psychological Resilience under Natural Environmental Hazards | 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 impact of Social leadership on psychological Resilience under Natural Environmental Hazards Naser Valizadeh, Armin Artang, Morteza Akbari, Ezatollah Ghazani, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6965895/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 Many rural areas face significant challenges in managing natural environmental hazards due to their geographical location and limited access to formal disaster management resources. While rural communities often rely on indigenous knowledge and adaptive strategies, their capacity to respond effectively to hazards like droughts and floods can be constrained by socio-economic and infrastructural limitations. Measuring the psychological resilience of rural people against natural environmental hazards including droughts and floods and its predictors was the aim of this research. By reviewing theoretical perspectives explaining psychological resilience against natural environmental hazards, we aim to provide a framework for such a research program. To this end, the Theory of Planned Behavior was reconstructed using hypothesizing new mediated and moderated relationships. The study results were analyzed in two steps by testing two distinctive models with a comparative perspective. “Livelihood-based vulnerability mitigating strategies” and “internet and mass media-based vulnerability mitigating strategies” were used as the moderators of the effects of constructs including normative considerations, self-efficacy, attitude, and social leadership on the psychological resilience against natural environmental hazards in the first and second models, respectively. The results demonstrated that moderating effect of the Internet and mass-media-based strategies in Model 2 is greater than the moderating effect of livelihood-based mitigation strategies on psychological resilience in model 1. By presenting new practical implications and prioritizing the effectiveness of employing two different mitigation strategies, the results of the present study improve the operation of sustainable intervention programs. Psychological Resilience Natural Environmental Hazard Management Social Leadership Vulnerability Mitigating Strategies Sustainability Intervention Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Natural environmental hazards dramatically affect socio-economic conditions all over the world. However, these effects and their negative consequences were more evident in developing countries (IFAD, 2020; WHO, 2020; Yazdanpanah et al., 2020). Poor households with low economic power suffered more from the impacts of natural environmental hazards than other groups and social classes (Fang et al., 2028). The consequences of natural environmental hazards are very diverse. Several studies state that these natural environmental hazards mainly affect poor groups in villages (Ur Rahman et al., 2021). The rural-urban contrast is essential in the understanding of the socio-economic impacts of environmental natural hazards (Chai et al., 2021). Rural areas, in general, are characterised by lower population sizes, agricultural economies, and accessibility to fewer infrastructure facilities and public amenities compared to urban areas (Chotia & Rao, 2017). Urban areas typically are characterised by a higher number of people, diversified economies, and easier access to healthcare, education, and emergency services (Vlahov & Galea, 2002). These inequalities play a significant part in determining the risk and resilience of communities to natural environmental hazards, with rural communities tending to face more challenges due to economic constraints and insufficient institutional support (Mododi Arkhodi et al., 2020). Phillipson et al. (2020) stated that natural environmental hazards can negatively affect rural businesses, agricultural activities, food security, and the income of rural households. Rural communities differ in their exposure to risk sources, susceptibility to risks, adaptive capacity, and access to socio-economic resources in hazardous conditions (Fahad et al., 2023; Rusmayandi et al., 2023). Some researchers (Horton, 2003; Savari et al., 2023) argue that after natural hazards occur, most studies focus on privileged communities, while less attention is given to vulnerable rural populations. However, effective hazard management requires attention to these communities, as they often rely on traditional knowledge and localized coping mechanisms. The interaction between traditional knowledge and modern influences can shape their resilience, with urbanization and financial resources either bridging or widening the gap between these two knowledge systems. Understanding how villagers perceive natural environmental hazards is crucial for strengthening resilience (Ngcamu, 2023; Phuong et al., 2023). This highlights the need for participatory assessments and co-developed methods that incorporate local knowledge into risk management strategies. Although research on the socio-psychological dimensions of natural hazards remains limited, some scholars (Xu et al., 2020; Cahigas et al., 2023; Ma et al., 2023; Faryabi et al., 2023; Peng et al., 2023; Opiyo et al., 2024) emphasize the importance of public perceptions and socio-psychological factors in disaster preparedness and response. Xu et al. (2021) state that such studies can help develop appropriate training programs for resilience against natural environmental hazards’ shocks and finally end in control and eradication of their rebound effects (Asare-Nuamah et al., 2022; Shah et al., 2023; Dehghani Pour et al., 2023). Considering the wide and deep impacts of natural environmental hazards on the subjective and objective well-being of individuals all over the world (Qi et al., 2023; Cannings et al., 2024), it is necessary to identify the constructs influencing the psychological resilience of people (Ballesteros et al., 2023). Psychological resilience refers to a person's positive reactions that allow him/her to deal effectively with stressful situations such as natural environmental hazards (Ehrich et al., 2017; Wang et al., 2024; Elshaer, 2024). To the best of our knowledge, there is no study focusing on the psychological resilience of rural people against natural environmental hazards and the constructs influencing it. Thus, investigating the psychological resilience of rural people against natural environmental hazards and their determinants in Iran was considered the aim of this research. Statistics show that an average of 5583 people is killed daily due to natural environmental hazards, and most of this figure is in developing countries, especially in rural areas (Kim et al., 2013). Iran is one of the countries that have always been struggling with natural environmental hazards such as floods and earthquakes. In developing countries like Iran, rural areas are highly vulnerable to earthquakes and floods. This vulnerability stems from deep-rooted challenges in various dimensions, including environmental-physical, socio-cultural, economic, and historical-political factors. These challenges have become institutionalized over time (Parishan, 2012). Many rural areas of Iran are more vulnerable to natural environmental hazards compared to other human settlements due to their geographical and natural location and the low level of knowledge and awareness of earthquake and flood crisis management (Savari et al., 2024). According to Iran's official statistics, every ten years an earthquake with a magnitude greater than M7 on Richter-scale, every 3 years an earthquake with a magnitude between 6 to 7 Richter, and ten earthquakes with a magnitude of 5 to 6 Richter have occurred in Iran. The consequence of the earthquake was the destruction of nearly 90% of the rural units in the area where the earthquake occurred in Iran. This shows that rural structures are the most vulnerable buildings, which are damaged by even the smallest earthquake. The destruction of 20 to 70 percent of Bam villages (Sharifi, 2009) and the 100 percent destruction of 45 percent of villages in Sarpol Zahab city are examples of the high level of destruction of rural areas in Iran (Sanjabi, 2019). In addition to earthquakes, floods are one of the natural environmental hazards that have always caused human, economic, and infrastructure damage in rural areas of Iran (Shokri et al., 2020; Pazhuhan et al., 2023). In the rural areas of Iran, the intervention of unplanned anthropogenic factors has significantly increased the risks of floods. The anthropogenic factors resulting in floods include deforestation, land degradation, improper irrigation practices, and unplanned construction. These factors alter natural water flow and reduce soil absorption capacity. As a result, even in the arid regions of Iran that have low rainfall levels, the runoff coefficient has increased due to multi-year droughts and non-compliance with the sustainability of irrigation and watershed management. Another reason for increasing the runoff coefficient is the reduction of vegetation. These factors have caused damaging floods to form despite low rainfall. Investigating the psychological resilience of rural people against natural environmental hazards and their determinants in Iran, which was the aim of present research, can be one of the most important steps to solve these problems. To achieve this goal, several specific objectives were set: Developing a theoretical framework to explain psychological resilience of rural people against natural environmental hazards based on the theory of planned behavior (TPB); Implementing a measurement and structural model to test the validity and reliability of data and instruments and test hypotheses; and Providing practical suggestions based on the research results to increase psychological resilience of rural people against natural environmental hazards. The contributions of this study are as follows. First, recent studies have used TPB (a psychological theory) to investigate behavioral responses toward flood hazards, typhoons, earthquakes, and haze pollution (Xu et al., 2021; Cahigas et al., 2023). However, none of them have focused on the psychological resilience of villagers against natural environmental hazards. We attempted to examine the determinants of psychological resilience against natural environmental hazards using the TPB. Second, although the predictive power of the TPB has been supported by previous studies (Rahimi-Feyzabad et al., 2022; Xu et al., 2021; Cahigas et al., 2023), it only employs a limited number of variables to predict the intention. Therefore, the present study extends this theory by incorporating new constructs into that. For instance, social leadership and mitigation strategies are the most important constructs the effects of their incorporation into TPB will be examined for the first time in the present study. In addition, the third contribution of the present study to the body of knowledge is that the present study has ended with innovative recommendations in the field of methods of dealing with natural environmental hazards, which can pave the way for preventive and post-disaster interventions in rural areas. In other words, this study ends up providing strategies that can help policy-makers, managers, and practitioners after the occurrence of natural environmental hazards so that they can improve the psychological resilience of villagers more effectively. The most important research questions pursued in this study are as follows: How can a theoretical framework based on the Theory of Planned Behavior (TPB) be developed to explain the psychological resilience of rural people against natural environmental hazards? How valid and reliable are the measurement and structural models used to assess psychological resilience, and what do the test results reveal about the proposed hypotheses? What practical recommendations can be derived from the research findings to enhance the psychological resilience of rural people against natural environmental hazards? 2. Theoretical background: Towards extending the TPB 2.1. TPB In the present study, the TPB was used to analyze the psychological resilience of Iranian villagers. This theory is a psychological theory to explain the human behavior. According to many researchers (see Ong et al., 2021; Rahimi-Feyzabad et al., 2022; Xu et al., 2021), this theory is one of the best theories for analyzing people's behavior in different contexts and is of great ability to predict their behavior. Many researchers (see Shi et al., 2021; Ahmmadi et al., 2021; Tama et al., 2021; Kurata et al., 2022) have used this theory for analyzing the behavior of local communities in rural areas. The results of these studies show that TPB has an acceptable predictive power and validity to encourage people's behaviors. TPB is based on the position that behavior appears immediately after behavioral intention (Ajzen, 1991; Dorce et al., 2021; Zaremohzzabieh et al., 2021; Lavuri, 2022). In this theory, behavioral intention is influenced by three variables: attitude toward behavior, subjective norms, and perceived behavioral control (PBC) (Wan et al., 2021; Alavion & Taghdisi, 2021; Qaid et al., 2022). In other words, in TPB, these three variables play a key role in activating the behavioral intention and immediately the actual behavior of individuals (Tama et al., 2021; Lavuri, 2022). Attitude towards behavior is one of the triads that directly affects the psychological resilience of villagers based on TPB. Ajzen (1991) states that attitude is a person's favorable or unfavorable evaluation of the consequences of performing a behavior. Based on this definition, the attitude towards preparedness against the disaster is defined as the favorable or unfavorable psychological evaluation of the villagers regarding preparedness against the natural disaster. Subjective norms are also reflecting the social pressure imposed on a person by others to perform or not perform a specific behavior in coping with the natural disaster (Esposito et al., 2016; Ahmmadi et al., 2021; Tama et al., 2021). Ajzen points out that subjective norms can be descriptive and injunctive. However, the theories of moral approach in environmental psychology consider not paying attention to moral norms as one of the criticisms of TPB (Pradhananga et al., 2019). Therefore, in the present study, instead of the term "subjective norms", the more general term "normative considerations" was used. Accordingly, the structure of normative considerations includes descriptive, injunctive, and moral norms. Normative considerations in the present study refer to the level of control on the villagers' participation in the management of the natural disasters (by three norms). Perceived behavioral control or self-efficacy also shows the difficulty or ease of performing a behavior for a person (Cahigas et al., 2023; Dorce et al., 2021; Kumar, 2021). Based on this definition, self-efficacy in dealing with the natural disasters shows that it is easy or difficult for the villagers to deal with the risks of the disasters. 2-2. Resilience Resilience is a measure of the stability and collapse state of a social, economic, physical, and ecological system (Khezri et al., 2021). This term was first proposed in the field of ecology and was considered one of the main characteristics of measuring the strength of an ecosystem (Alizadeh & Sharifi, 2021; Xiao et al., 2021). Resilience is defined as the ability of a system (social, economic, physical, and ecological) to adapt to changes and maintain its initial state against external shocks (Borrion et al., 2020; He et al., 2021). In other words, resilience can help explain nonlinear changes in a particular system (Xiao et al., 2021). Today, the definition of resilience is not limited to ecological and physical systems, and many social and psychological researchers also use this term to explain the behavior of human subjects (Maleksaeidi et al., 2015; Shojaei‐Miandoragh et al., 2021). Reviewing the research literature in this field shows that many studies (see Maleksaeidi et al., 2015) have recently been done in the field of psychological preparedness against various shocks (such as climate change, floods, drought, diseases, etc.). Psychological resilience is defined as a reactive response or behavior of people in a stressful situation to effectively deal with the effects of disaster (Ehrich et al., 2017). In the present study, following the study of Maleksaeidi et al. (2021), psychological resilience refers to the effective use or use of coping strategies against natural disasters by villagers. In this study, some context-specific variables explaining psychological resilience were entered into the original TPB. In addition, unlike the original version of this theory, which regards the intention to psychological resilience as the main dependent variable, actual behavior or psychological resilience is considered as the dependent variable. There were several major justifications for this. First, the behavior investigated in this study (psychological resilience) was not based on the individuals’ future-oriented actions. In other words, resilience against natural disasters was not a behavior that villagers are supposed to do in the not-so-distant future; rather, it was a behavior that they know to do now. In addition, some studies (see Sheeran & Webb, 2016; Barth & De Jong, 2017) show that in some cases individuals’ intentions do not necessarily end in behavior. In other words, there is a significant discrepancy between intention (future behavior) and behavior (actual behavior). Therefore, some factors may delay the transformation of intention into actual behavior. In this study, resilience against natural disasters was considered as an actual behavior. As mentioned earlier, in the original version of TPB, people's behavior is explained by the three antecedents of attitude towards behavior, subjective norms, and PBC (Ong et al., 2021; Rahimi-Feyzabad et al., 2022). However, studies show that in practice the effects of these three variables on behavior are mediated by other variables (Sheeran & Webb, 2016; Barth & De Jong, 2017). For example, according to TPB, PBC or self-efficacy directly affects the resilience of villagers against natural disasters. However, it is easy to see that the use or non-use of livelihood or mass media-based mitigation strategies can increase or decrease its impact. In other words, adopting mitigation strategies can be considered a moderator of the effect of self-efficacy on psychological resilience against natural disasters. Such a moderating effect can be set for the effects of normative considerations and attitudes on psychological resilience against natural disasters. In this regard, mitigation strategies were added to the original TPB as moderators. Based on the study of Maleksaeidi et al. (2015), mitigation strategies in this study refer to the methods that villagers use to reduce the impacts of natural disasters. In other words, these strategies reduce the vulnerability of villagers to the unfortunate consequences of the shock related tot the natural disasters. For example, diversification of income sources is one of the mitigation strategies that can play a key role in increasing the psychological resilience of villagers against natural disasters. Moreover, the theoretical literature (see Stodd, 2014; Asrar-ul-Haq & Kuchinke, 2016; Wu et al., 2020; O'Sullivan & Sakr, 2022) shows that the constructs of attitude, self-efficacy, and normative considerations can be explained by other antecedents. For example, villagers’ self-efficacy in the field of coping with natural disasters can be influenced by social leadership. 3. Hypotheses Development 3.1. Social leadership and normative considerations Social leadership refers to the act of orchestrating adaptive change in groups, organizations, communities, and nations (Stodd, 2014; Melania et al., 2021; Cheng, 2024). Social leadership recognizes that many social challenges are characterized by competitive approaches, ethical dilemmas, and emerging situations that community members may never have faced before (Porteous, 2013). Due to their high understanding power, experience, leadership spirit, and effectiveness, they try to push the existing norms in society to be more compatible with the challenge and create appropriate norms (Friedman, 2013; O'Sullivan & Sakr, 2022). In this regard, we hypothesized that: Hypothesis 1 : Social leadership positively influences the normative considerations of villagers. 3.2. Social leadership and self-efficacy Social leaders are generally from among the people of the target communities and live with them. In other words, many of them have common experiences with other members of society. This issue is important from two aspects. First, social leaders, due to their great influence among community members, can increase their sense of self-efficacy by providing guidance and accurate information (Alizadeh & Sharifi, 2021). Second, it is easier for community members to accept the recommendations of social leaders. Therefore, if the leader him /herself takes a step to solve a specific problem (such as the shock of natural environmental hazards) and this action is effective, the members of the society will accept it faster and easier (Wu et al., 2020), because the results of its effectiveness have been seen concretely in the actions of the leader. In other words, in this way, the self-efficacy of society members improves (Valizadeh et al., 2022). Therefore, we hypothesized that: Hypothesis 2 : Social leadership positively influences the self-efficacy of villagers. 3.3. Social leadership and attitude Many researchers (see Asrar-ul-Haq & Kuchinke, 2016) claim that leaders can positively or negatively influence the attitudes of followers and community members. This is generally due to the trust that community members and followers have in social leaders (Stodd, 2014). Alizadeh and Sharifi (2021) consider social leadership as a key factor in the formation of positive attitudes toward strategies to deal with natural hazard shocks. In this regard, we hypothesized that: Hypothesis 3 : Social leadership positively influences the attitude of villagers. 3.4. Normative considerations and psychological resilience Normative considerations refer to the level of control of people's behavior (resilience) by various descriptive, injunctive, and moral norms (Ajze, 1991; Cahigas et al., 2023). The formation of positive normative considerations towards natural environmental hazards can play a positive role in increasing the resilience of rural and agricultural communities against the shock (Valizadeh et al., 2022; Mutyebere et al., 2024; Xu et al., 2024; Tao et al., 2024; Sawaneh et al., 2024). Therefore, we hypothesized that: Hypothesis 4 : Normative considerations positively affect the psychological resilience of rural people. 3.5. Self-efficacy and psychological resilience Perceived behavioral control or self-efficacy emphasizes the difficulty or ease of performing a behavior for a person (Innocenti et al., 2023; Baldwin et al., 2023). Cahigas et al. (2023) claim that perceived behavioral control or self-efficacy can reduce people's resistance to receiving natural hazard-reducing measures. Considering that many other studies such as Kumar (2021) and Yagoubi et al. (2021) have supported the effect of self-efficacy on psychosocial resilience against natural environmental hazards, we hypothesized that: Hypothesis 5 : Self-efficacy positively influences the psychological resilience of villagers. 3.6. Attitude and psychological resilience Attitude refers to a person's favorable or unfavorable evaluation of the consequences of performing a behavior (Ajzen, 1991; Mutyebere et al., 2023; Nguyen et al., 2024). The theoretical justification of the relationship between attitude and behavior is that unless people have a favorable or positive attitude toward action, they will not do it (Kurata et al., 2023; Gansser & Reich, 2023). Although in some situations this assumption may not be true, in general attitude is considered a key determinant for behaviors such as resilience against natural environmental hazards (Yazdanpanah et al., 2021). In this regard, we hypothesized that: Hypothesis 6 : Attitude positively influences the psychological resilience of villagers. 3.7. Social leadership and psychological resilience Porteous (2013) claims that social leadership contributes to adaptive changes in groups, organizations, communities, and nations and thus increases their resilience against various shocks such as natural environmental hazards. Social leaders effectively contribute to the resilience of societies in the face of crises through their interventionist role (Valizadeh et al., 2022). Many studies (Alizadeh & Sharifi, 2021) have recently confirmed the significant and positive effect of social leadership on resilient behaviors against diverse natural environmental hazards. In this regard, it was hypothesized that: Hypothesis 7 : Social leadership positively influences the psychological resilience of villagers. 3.8. Mediating role of normative considerations, self-efficacy, and attitude In the eighth hypothesis, it was shown that social leadership can directly affect psychological resilience against natural hazards. However, it should be noted that social leadership can also indirectly affect resilience through the constructs of normative considerations, self-efficacy, and attitude. Based on the first, second, and third hypotheses, social leadership directly affects these three constructs (Stodd, 2014; Wu et al., 2020). In addition, since these three variables directly affect psychological resilience against natural environmental hazards (Rahimi-Feyzabad et al., 2022), we hypothesized that: Hypotheses 8, 9, 10 : Normative considerations, self-efficacy, and attitude mediate the relationship between the social leadership of rural people and their psychological resilience. 3.9. Moderating role of livelihood-based mitigation strategies As stated in the theoretical background, attitude, normative considerations, and self-efficacy directly affect psychological resilience against natural environmental hazards (Rahimi-Feyzabad et al., 2022). However, their effects on psychological resilience are moderated by other variables. According to the fourth, fifth, and sixth hypotheses, the three constructs of normative considerations, self-efficacy, and attitude directly affect the resilience of villagers against natural environmental hazards. Nevertheless, the use or non-use of livelihood-based mitigation strategies can reduce or increase the impact of their direct effect on resilience. Livelihood-based mitigation strategies in this study refer to strategies that their employee has a positive effect on improving villagers' livelihoods during and after the occurrence of the natural environmental hazards. In this regard, we hypothesized that: Hypotheses 11, 12, 13 : Livelihood-based mitigation strategies moderate the relationship between normative considerations, self-efficacy, attitude, and the psychological resilience of villagers. 3.10. Moderating role of Internet and mass media-based mitigation strategies Currie et al. (2021) state that in addition to livelihood-based mitigation strategies, Internet-based mitigation strategies are also effective in moderating the effects of variables influencing villagers' resilience against natural environmental hazards (such as normative considerations, self-efficacy, and attitude). These researchers state that during and after the occurrence of natural environmental hazards, many villagers try to use the capacity of virtual space, social networks, and the Internet to obtain information about the shocks and buy and sell products. Considering that the use or non-use of these strategies can influence the effects of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards, we hypothesized that: Hypotheses 14, 15, and 16 : Internet and mass media-based mitigation strategies moderate the relationship between normative considerations, self-efficacy, and attitude and the psychological resilience of villagers. In general, to visually explain the relationships between the variables, the conceptual framework of the research was formulated in Figure 1. The theoretical model presented in Figure 1 illustrates the inter-relationships between the primary constructs in the study, with a focus on the determinants of psychological resilience to natural environmental hazards. Social leadership is an antecedent that influences normative considerations, self-efficacy, and attitude, which are considered mediators influencing psychological resilience. Psychological resilience is theorized to be a sixth-order construct composed of six root dimensions, namely hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of effects, and creativity. The framework also highlights the moderating role of livelihood-oriented coping strategies and internet and mass media-oriented coping strategies in shaping psychological resilience into correlation with mediators (normative considerations, efficacy, and attitude). Such strategies may facilitate or dampen the influence of the mediators on resilience and suggest that villagers' adaptation strategies are pivotal in shaping or constraining resilience-promoting processes. The causal associations as hypothesized are depicted by the arrows in the figure, and the location of the mitigation strategies indicates their moderating function and not the direct effect. This system provides for the possibility of developing a theoretical underpinning for understanding how cognitive process, adaptation actions, and leadership influence one another to contribute to resilience in natural environmental disasters. 4. Methodology This study used a quantitative cross-sectional survey method to test relationships between the variables. This research is an applied study, the results of which can be used in various interventions and programs related to management of the natural environmental hazards, rural preparedness development policies, and rebound effects’ management in natural environmental hazards. 4.1. Population, sample, and sampling The population of the research included villagers who lived in Sirjan County and Eghlid County of the Fars and Kerman provinces in the south of Iran. The two provinces of Fars and Kerman were chosen as the study area because floods and earthquakes are two natural disasters in these provinces that cause great damage to the villagers (Figure 2). The number of villagers living in the rural areas of these two counties was 101,934 according to the latest official census of the Iran Statistics Center (https://amar.org.ir/en). Out of this rural population, about 66,775 cases lived in Sirjan county of Kerman province. Furthermore, 35159 cases of the studied rural population were from Eghlid county of Fars province. The total number of samples that needed to be selected from these two counties was calculated using Cochran's sample estimation formula. Therefore, 206 villagers were selected as samples. Villagers were selected in the form of a multi-stage purposeful-random sampling process. The first stage of the sampling process was done purposefully. According to the limitations of the research (economic limitations, social distancing during the COVID-19, traveling limitations), the two counties mentioned above were purposefully selected as samples. Another reason for selecting these regions as the study area was related to the fact that in the last two decades, these regions have experienced many natural environmental hazards such as droughts, floods, and even earthquakes. Considering that these hazards may occur in the future, conducting research like the present one can help management and preparation to deal with these hazards. At this stage, the sample calculated for the entire population (206 cases) was divided proportionally between the two counties of Eghlid and Sirjan. The country divisions of Iran divide the rural areas of each county into smaller units called Dehestan, each of which has several villages. Therefore, in the second stage, some Dehestans were randomly selected by the research team. Like the previous stage, the sample estimated for each county was divided according to the population size of the villages. The third step of the sampling process included the randomized selection of one village from each of the Dehestans of Sirjan and Eghlid counties. In the fourth step, the villagers were randomly selected from the selected villages. 4.2. Specification of the measures’ typology In the present study, two types of constructs were considered: higher-order constructs and lower-order constructs. Lower-order constructs are typically measured by multiple individual items, with each item directly assessing a specific aspect of the construct. Importantly, a lower-order construct does not contain additional latent dimensions that could be further broken down into subcomponents. In contrast, higher-order constructs are more complex because they consist of multiple latent dimensions. These dimensions serve as an intermediary layer between the main construct and its associated measurement items (Wan et al., 2021). In this study, psychological resilience against natural environmental hazards was identified as a higher-order construct. It was composed of six latent dimensions: hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of impacts, and creativity. Each of these latent dimensions was measured by multiple individual items, reflecting different aspects of psychological resilience. The measurement model followed a reflective-reflective structure, meaning that the individual items reflected their respective latent dimensions, and these dimensions collectively represented the overarching construct of psychological resilience against natural environmental hazards. 4.3. Measures of the study The study included five measures. The development of these measures was done using a multi-step process. In the first stage, an effort was made to ensure that the constructs of the research framework were compatible with the context of the study population. Ajzen (1991) stated that TPB requires researchers to directly extract the items measuring the constructs from the studied community. The items that are chosen arbitrarily and intuitively may end up with relationships that are not very consistent with the realities of the study area (Fishbein & Ajzen, 2010). In this regard, first, an attempt was made to identify the concepts related to the measuring items of each of the measures using an open-ended questionnaire. In the second stage, these concepts were formulated in the form of a close-ended questionnaire to be a basis for the main quantitative phase. It should be mentioned that in the second stage, the concepts suggested by previous studies were used to enrich the measures that had few items. The structures of the research were as follows: Psychological resilience : Psychological resilience against natural environmental hazards was one of the higher-order constructs in the present study. According to the studies of Maleksaeidi et al. (2014) and Kumpfer (1999), six latent dimensions were determined for psychological resilience against natural environmental hazards. The dimensions of psychological resilience included hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of impacts, and creativity (18 questions). Some of these questions were researcher-made and some were adapted from the studies of other researchers (Maleksaeidi et al., 2014). Attitude : To measure attitude, we used three items so that we can evaluate the positive or negative evaluation of the villagers towards the natural environmental hazards (Yazdanpanah et al., 2021). Self-efficacy : Three items were used to measure this construct. To measure this construct, a questionnaire developed by previous scholars such as Abadi et al. (2021) was used. Of course, it should be mentioned that two items measuring self-efficacy were developed by the researchers and were identified by using the primary study and the open-ended questionnaire from the perspectives of the target community. A five-point Likert scale was employed to measure self-efficacy items. Normative considerations : Normative considerations were measured using three items. To measure this construct, the concepts extracted from the open-ended questionnaire were applied. Social leadership : Social leadership was measured in this study using four items. These four items are based on the primary study and the concepts extracted from it, as well as the questionnaire designed by Salas-Vallina et al. (2021). Livelihood-based mitigation strategies : This contrusct was measured using three items. The items were adapted from Maleksaeidi et al. (2015). Internet-based mitigation strategies : This construct was also measured using three items that were adapted from Yazdanpanah et al. (2021). A five-point Likert scale was adapted to measure all items. 4.4. Data collection and analysis The data in this study consists of survey responses collected from villagers in Sirjan County (Kerman Province) and Eghlid County (Fars Province) in southern Iran. These data were gathered through a structured questionnaire designed to measure various psychological and behavioral constructs related to resilience against natural environmental hazards. The questionnaire was developed using a multi-step process, including an initial open-ended survey to identify relevant concepts, followed by a close-ended questionnaire refined with items adapted from previous studies. Data analysis was done using structural equation modeling (SEM). For this purpose, Partial Least Square (PLS) statistical software was employed. The authors have used a commercial domain of the PLS (available at: https://www.smartpls.com/). To articulate the results, model analysis was done in the form of two structural and measurement models. The structural model was used to explain the relationships. The results of inner model and the measurement model was used to estimate the estimates of the outer model. It should be noted that the bootstrapping method was used to estimate the moderator and mediator effects. PLS structural equation modeling provides the users with several advantages over traditional regression models in social and/or behavioral studies. First, it enables the researchers to deal with multicollinearity well. This advantage makes PLS an ideal tool for situations where there are high correlated predictors. Secondly, PLS structural equation modeling is also effective is situations where there are many independent variables or a smaller sample size for the study. Increasing independent variables in a study, avoids overfitting of the model. In contrast to the traditional regression models, which put their emphasize on estimating parameter, PLS focuses on predictive accuracy of the model. Focusing on the predictive accuracy of the model improves the explanation of the outcome variables. These strengths make PLS especially useful for complex, real-world social science data where accurate predictions are essential. 5. Results The assessment of the demographic characteristics of the respondents showed that the average age of the sample was close to 37 years. The minimum and maximum ages of the respondents were 17 and 67 years, respectively. In terms of education, most of the respondents (nearly 43 percent) had a diploma. In other words, most of the respondents had completed high school. Participation in training courses related to coping with environmental hazard shocks was one of the key questions asked in the demographic characteristics, and the results showed that only seven percent of the respondents had participated in these courses. The study of the occupational status of the respondents showed that nearly 80 percent of the respondents were engaged in agriculture as their main occupation. Also, 73 percent of the respondents were also engaged in animal husbandry in addition to agriculture. Before evaluating and analyzing the inner model, the reliability and validity of outer or measurement models should always be examined. This allows researchers to identify issues of collinearity in the data and avoid biased conclusions. In this study, explanatory variables of psychological resilience against natural environmental hazards were investigated using lower-order reflective measurement models. The results related to the validity and reliability of the variables used in the conceptual framework of the research was presented in Tables 1-10. In this study, considering that the two moderator variables of “livelihood strategies” and “internet and mass media-based strategies” were entered into the analysis separately, the analysis of measurement and structural models was investigated in the form of two distinctive models. In the measurement and structural model 1, livelihood strategies were considered as a moderator of the relationship between the constructs of normative considerations, self-efficacy, attitude, and social leadership with psychological resilience against natural environmental hazards. Meanwhile, in the measurement and structural model 2, Internet and mass media-based strategies were considered as the moderators of the relationship of these variables with psychological resilience against natural environmental hazards. 5.1. Measurement model 1 (livelihood Strategies as the mediating variable) 5.1.1. Internal consistency reliability We used a composite reliability index, rho-A index, and alpha coefficients to evaluate the internal consistency reliability of reflective models of constructs such as psychological resilience against natural environmental hazards, attitude, self-efficacy, normative considerations, and social leadership. Reliable statistical sources (see Hair et al., 2017) state that if the values of these three indicators for a reflective model are greater than or equal to 70, it can be concluded that the given construct is of acceptable internal consistency reliability. Nevertheless, some items with loading factors less than 0.7 can also be kept in the model, provided that their t values are significant. From the results of Table 1 and the comparison of the results obtained for the constructs of the present study, it can be concluded that all the structures used in the present study have sufficient reliability. Table 1. Measurement items and indicators of fitness for model 1 Cronbach’s Alpha rho-A Composite Reliability Average Variance Extracted (AVE) Livelihood Strategies 0.730 0.742 0.882 0.603 Attitude 0.738 0.863 0.853 0.672 Normative considerations 0.851 0.862 0.818 0.607 Resilience 0.826 0.888 0.875 0.585 Social leadership 0.795 0.828 0.792 0.564 Self-Efficacy 0.747 0.763 0.794 0.662 Acceptable values for the reported indices: Alpha > 0.7; rho-A> 0.7; p 0.7; and AVE > 0.5 5.1.2. Convergent and divergent/discriminant validity The convergent validity of the constructs of the theoretical framework was investigated using outer loadings and AVE indices. All values related to outer loadings and AVE exceeded acceptable values (Tables 1-2). Therefore, it can be concluded that the seven constructs used in this study had good convergent validity. Table 2. Measurement items, loading factors, and T - value of the model 1 Factors Indicators Loading Factor T - value Significance Result Livelihood strategies LS1 0.776 6.032 0.001 Approved LS3 0.778 6.592 0.001 Approved Attitude A1 0.001 5.499 0.001 Approved A2 0.929 50.912 0.001 Approved A3 0.938 66.799 0.001 Approved Normative considerations NC1 0.598 6.259 0.001 Approved NC2 0.860 26.866 0.001 Approved NC3 0.852 5.118 0.001 Approved Resilience C 0.871 56.931 0.001 Approved CI 0.706 16.319 0.001 Approved FA 0.670 13.322 0.001 Approved H 0.808 25.600 0.001 Approved SE 0.751 16.693 0.001 Approved Social leadership SL1 0.880 28.461 0.001 Approved SL2 0.729 8.442 0.001 Approved SL3 0.621 5.781 0.001 Approved Self-efficacy SE1 0.918 49.955 0.001 Approved SE2 0.693 9.295 0.001 Approved Acceptable values for the reported indices: all loadings > 0.7; p 0.7; and AVE > 0.5; T value > ±1.9 In addition, the Heterotrait-Monotrait Ratio (HTMT), Fornell-Larcker Criterion, and Variance Inflation (VIF) criteria were applied to assess the discriminant validity in the outer and inner models (Tables 3-5). As Table 3 shows, all HTMT values for the variables included in model 1 are less than the critical value of 0.85. According to the Fornell-Larcker criterion, if the values in the diameter of the matrix are greater than the values in the corresponding columns, it proves that the research constructs have sufficient discriminant validity. Based on the results of performing measurement model 1, this preassumption was proved in the present study. Therefore, we can conclude that the research tool has suitable discriminant validity. Table 3. Discriminant validity (FLC and HTMT) Model Num. Criteria Construct Livelihood Strategies Attitude Normative considerations Resilience Social leadership Self-Efficacy Model 1 FLC Livelihood Strategies 0.777 -- -- -- -- -- Attitude 0.306 0.820 -- -- -- -- Normative considerations 0.244 0.245 0.688 -- -- -- Resilience 0.279 0.446 0.471 0.765 -- -- Social leadership 0.288 0.274 0.685 0.462 0.751 -- Self-Efficacy 0.296 0.269 0.663 0.557 0.617 0.814 HTMT Livelihood Strategies -- -- -- -- -- -- Attitude 0.563 -- -- -- -- -- Normative considerations 0.555 0.341 -- -- -- -- Resilience 0.483 0.518 0.639 -- -- -- Social leadership 0.410 0.336 0.409 0.467 -- -- Self-Efficacy 0.625 0.407 0.319 0.703 0.657 In addition, the results of Tables 4 -5 showed the VIF values for the outer and inner models in model 1. As the results show, the VIF values are lower than the acceptable value of 5. This result was another proof of the discriminant validity of the constructs. Table 4. Outer VIF values for the measuring items Item VIF value Item VIF value IMMS1 1.713 C 2.033 IMMS2 1.811 CI 1.705 IMMS3 1.078 FA 1.623 LS1 1.045 H 1.905 LS3 1.045 SE 1.556 A1 1.120 SL1 1.174 A2 3.246 SL2 1.516 A3 3.217 SL3 1.438 NC1 1.120 SE1 1.141 NC2 1.139 SE2 1.141 NC3 1.050 Table 5. Inner VIF values for the latent constructs Model Num. Construct Attitude Normative considerations Resilience Self-efficacy Model 1 Livelihood Strategies 1.212 Attitude 1.239 Normative considerations 2.451 Resilience Social leadership 1 1 2.126 1 Self-Efficacy 2.261 5.2. Measurement model 2 (Internet and mass media-based strategies as the mediating variable) 5.2.1. Internal consistency reliability The results of implementing the measurement model of model 2 showed that the values of composite reliability, rho-A, and Cronbach's alpha coefficients are greater than 0.7 (Table 6). Therefore, it can be concluded that all the constructs used in model 2 have acceptable internal consistency reliability. Table 6. Measurement items (model 2 ) Cronbach’s Alpha rho-A Composite Reliability Average Variance Extracted (AVE) Internet and mass media-based strategies 0.715 0.742 0.776 0.565 Attitude 0.738 0.863 0.853 0.672 Normative considerations 0.851 0.862 0.818 0.607 Resilience 0.826 0.888 0.875 0.585 Social leadership 0.795 0.828 0.792 0.564 Self-Efficacy 0.747 0.763 0.794 0.662 Acceptable values for the reported indices: Alpha > 0.7; rho-A> 0.7; p 0.7; and AVE > 0.5 5.2.2. Convergent and divergent/discriminant validity Examination of outer loadings and AVE for model 2 demonstrated that their values are higher than 0.7 and 0.5, respectively (Tables 6-7). Therefore, the convergent validity of the item used in model 2 was confirmed. The examination of HTMT and FLC indices for model 2 revealed that their values exceed the required acceptable values (Table 8). In addition, VIF indices (for outer and inner models) also revealed that there is no significant variance in inflation among the variables (Table 9 and Table 10). Therefore, the divergent validity of Model 2 was also confirmed. Table 7. Measurement items, loading factors, and T - value of the model 2 Factors Indicators Loading Factor T - value Significant Result IMMS1 0.888 40.593 0.001 Accepted Internet and mass media-based strategies IMMS2 0.887 47.496 0.001 Accepted IMMS3 0.348 4.003 0.001 Accepted Attitude A1 0.526 5.374 0.001 Accepted A2 0.928 49.526 0.001 Accepted A3 0.937 64.314 0.001 Accepted Normative considerations NC1 0.598 6.518 0.001 Accepted NC2 0.859 27.452 0.001 Accepted NC3 0.570 4.830 0.001 Accepted Resilience C 0.858 47.526 0.001 Accepted CI 0.722 19.519 0.001 Accepted FA 0.686 14.928 0.001 Accepted H 0.804 26.453 0.001 Accepted SE 0.752 18.346 0.001 Accepted Social leadership SL1 0.880 27.600 0.001 Accepted SL2 0.730 8.071 0.001 Accepted SL3 0.621 5.899 0.001 Accepted Self-efficacy SE1 0.918 44.272 0.001 Accepted SE2 0.694 8.598 0.001 Accepted Acceptable values for the reported indices: all loadings > 0.7; p 0.7; and AVE > 0.5; T value > ±1.9 Table 8. Assessment of the discriminant validity using FLC and HTMT Construct Internet and mass media-based strategies Attitude Normative considerations Resilience Social leadership Self-Efficacy Model 2 FLC Attitude 0.820 -- -- -- -- -- Internet and mass media-based strategies 0.361 0.752 -- -- -- -- Normative considerations 0.244 0.288 0.688 -- -- -- Resilience 0.437 0.599 0.466 0.767 -- -- Social leadership 0.274 0.395 0.684 0.458 0.751 -- Self-Efficacy 0.268 0.334 0.663 0.548 0.617 0.814 HTMT Attitude -- -- -- -- -- -- Internet and mass media-based strategies 0.617 -- -- -- -- -- Normative considerations 0.341 0.555 -- -- -- -- Resilience 0.518 0.809 0.639 -- -- -- Social leadership 0.336 0.471 1.109 0.467 -- -- Self-Efficacy 0.407 0.617 1.219 0.703 0.857 -- Table 9. Outer VIF values for the measuring items Item VIF value Item VIF value IMMS1 1.713 C 2.033 IMMS2 1.811 CI 1.705 IMMS3 1.078 FA 1.623 LS1 1.045 H 1.905 LS3 1.045 SE 1.556 A1 1.120 SL1 1.174 A2 3.246 SL2 1.516 A3 3.217 SL3 1.438 NC1 1.120 SE1 1.141 NC2 1.139 SE2 1.141 NC3 1.050 Table 10. Inner VIF values for the latent constructs Model 2 Attitude 1.271 Internet and mass media-based strategies 1.367 Normative considerations 2.365 Resilience Social leadership 1 1 2.126 1 Self-Efficacy 2.261 5.2. Structural/inner models and testing hypotheses The test of the hypotheses related to the relationships between the research constructs was done using the implementation of structural or inner models. Also, the effects of independent variables on dependent variables were investigated in the form of direct and indirect effects. In addition, indirect effects included mediated and moderated effects. The bootstrapping method was used to calculate the significant level and t values of indirect effects. Like the measurement models, the structural models of the research were implemented in the form of two models (structural model 1 and structural model 2). This work was done to investigate the moderation effects of “livelihood strategies” and “Internet and mass media-based strategies” on the effects of independent variables on the dependent variable (psychological resilience against natural environmental hazards). 5.2.1. Structural/ Inner model 1 In structural model 1, first, the direct effects of the constructs on each other were examined. Examining the direct effects of social leadership on normative considerations (β=0.685; p<0.01), self-efficacy (β=0.617; p<0.01), and attitude (β=0.274; p<0.01) showed that social leadership has significant and positive direct effects on these three variables (Table 11; Figure 3). By obtaining such results, the first, second, and third hypotheses in structural model 1 were supported. In addition, self-efficacy (β=0.391; p<0.01) and attitude (β=0.281; p<0.01) had positive and significant direct effects on psychological resilience against natural environmental hazards (Table 11; Figure 3). These results also confirmed the fifth and sixth hypotheses in structural model 1. This was while the constructs of normative considerations (β=0.071; n.s.) and social leadership (β=0.082; n.s.) did not have a significant direct effect on psychological resilience against natural environmental hazards. In this way, the fourth and seventh hypotheses were rejected in structural model 1. The results of mediation analysis using the bootstrapping method showed that normative considerations cannot mediate the impact of social leadership of rural people on their psychological resilience against natural environmental hazards (β = 0.048; n.s.). This result demonstrates that the present research does not support the eighth hypothesis. On the other hand, the results of mediation structural analysis revealed that self-efficacy (β=0.241; p<0.01) and attitude (β=0.077; p<0.01) can positively and significantly mediate the effects of social leadership on psychological resilience against natural environmental hazards (Table 11; Figure 3). In this way, the ninth and tenth hypotheses were supported in structural model 1. In the third step, moderated indirect hypotheses were tested. Therefore, in structural model 1, livelihood strategies were considered as the moderator of the direct effects of independent variables on the dependent variable (psychological resilience against natural environmental hazards). The results indicated that livelihood strategies cannot moderate the effects of normative considerations (β=0.058; n.s.) and self-efficacy (β=0.096; n.s.) on psychological resilience against natural environmental hazards. In this way, the eleventh and twelfth hypotheses were rejected. On the other hand, the research results supported the thirteenth and fourteenth hypotheses. In other words, the results showed that livelihood strategies could positively and significantly moderate the effects of attitude (β=0.182; p<0.01) and social leadership (β=0.125; p<0.01) on psychological resilience against natural environmental hazards (Table 11; Figure 3). Table 11. Hypotheses testing (model 1) Model Num. Hypothesis Path Beta values t-value P-value Result of a hypothesis test Model 1 Direct hypotheses H1 Social leadership -> Normative considerations 0.685 14.688 0.001 Supported H2 Social leadership -> Self-efficacy 0.617 13.180 0.001 Supported H3 Social leadership -> Attitude 0.274 4.486 0.001 Supported H4 Normative considerations -> Psychological resilience 0.071 0.757 0.449 Rejected H5 Self-efficacy -> Psychological resilience 0.391 4.851 0.001 Supported H6 Attitude -> Psychological resilience 0.281 4.171 0.001 Supported H7 Social leadership -> Psychological resilience 0.082 0.936 0.350 Rejected Indirect (mediation) hypotheses H8 Social leadership -> Normative considerations -> Psychological resilience 0.048 0.743 0.458 Rejected H9 Social leadership -> Self-efficacy -> Psychological resilience 0.241 4.513 0.001 Supported H10 Social leadership -> Attitude -> Psychological resilience 0.077 3.114 0.002 Supported Indirect (moderation) hypotheses H11 Normative considerations -> Psychological resilience 0.058 0.842 0.400 Rejected H12 Self-efficacy -> Psychological resilience 0.096 0.744 0.457 Rejected H13 Attitude -> Psychological resilience 0.182 4.699 0.001 Supported H14 Social leadership -> Psychological resilience 0.125 2.782 0.003 Supported 5.2.2. Structural/ Inner model 2 The results obtained from running the structural model 2 indicated that social leadership positively, significantly, and directly affects normative considerations (β=0.684; p<0.01), self-efficacy (β=0.617; p<0.01), and attitude (β=0.274; p<0.01) (Table 12; Figure 4). These results were evidence to support the first, second, and third hypotheses in structural model 2. The direct effects of normative considerations (β=0.090; n.s.) and social leadership (β=0.006; n.s.) on psychological resilience against natural environmental hazards were also not significant. In this way, the fourth and seventh hypotheses were rejected in structural model 2. Meanwhile, self-efficacy (β=0.290; p<0.01) and attitude (β=0.162; p<0.01) had positive and significant effects on psychological resilience against natural environmental hazards (Table 12; Figure 4). These results provided evidence to confirm the fifth and sixth hypotheses. Examining the mediated indirect effects revealed that normative considerations cannot mediate the impact of social leadership of rural people on their psychological resilience against natural environmental hazards (β = 0.061; n.s.). In this way, the eighth hypothesis was not supported. Self-efficacy (β=0.179; p<0.01) and attitude (β=0.044; p<0.01) positively and significantly mediated the effects of social leadership on psychological resilience against natural environmental hazards. According to these results, the ninth and tenth hypotheses were confirmed (Table 12; Figure 4). The test of moderated indirect effects indicated that Internet and mass media-based strategies could positively and significantly moderate the effects of normative considerations (β= 0.154; p<0.01), self-efficacy (β= 0.107; p<0.01), and attitude (β = 0.131; p<0.01) on psychological resilience against natural environmental hazards. Based on these results, the eleventh, twelfth, and thirteenth hypotheses were confirmed. However, Internet and mass media-based strategies could not moderate the impact of social leadership of rural people on their psychological resilience against natural environmental hazards (β=0.023; n.s.) and this result led to the rejection of the fourteenth hypothesis (Table 12; Figure 4). Table 12. Summary of testing hypotheses for model 2 Model 2 Direct hypotheses H1 Social leadership -> Normative considerations 0.684 15.447 0.001 Supported H2 Social leadership -> Self-efficacy 0.617 13.307 0.001 Supported H3 Social leadership -> Attitude 0.274 4.196 0.001 Supported H4 Normative considerations -> Psychological resilience 0.090 1.030 0.304 Rejected H5 Self-efficacy -> Psychological resilience 0.290 3.775 0.001 Supported H6 Attitude -> Psychological resilience 0.162 2.687 0.007 Supported H7 Social leadership -> Psychological resilience 0.006 00.072 0.943 Rejected Indirect (mediation) hypotheses H8 Social leadership -> Normative considerations -> Psychological resilience 0.061 1.016 0.310 Rejected H9 Social leadership -> Self-efficacy -> Psychological resilience 0.179 3.603 0.029 Supported H10 Social leadership -> Attitude -> Psychological resilience 0.044 2.188 0.001 Supported Indirect (moderation) hypotheses H11 Normative considerations -> Psychological resilience 0.154 2.026 0.043 Supported H12 Self-efficacy -> Psychological resilience 0.107 2.446 0.011 Supported H13 Attitude -> Psychological resilience 0.131 2.363 0.018 Supported H14 Social leadership -> Psychological resilience 0.023 0.269 0.788 Rejected 6. Discussions, policy implications, limitations, and future perspectives Based on the results of direct effects analysis, self-efficacy in structural models 1 and 2 had positive and significant effects on psychological resilience against natural environmental hazards. Self-efficacy refers to the extent to which villagers perceive themselves and their actions to be effective in better managing the risks of natural environmental hazards. It also refers to the perceived difficulty or ease of measures to deal with natural environmental hazards. This result is consistent with the results of other researchers such as Cahigas et al. (2023), Kumar (2021) and Rahimi-Feyzabad et al. (2022). Considering the positive impact of self-efficacy on psychological resilience against natural environmental hazards, it is suggested to increase the self-efficacy of villagers to deal with the risks of natural environmental hazards. This work can be done by the experts of hazard risk management programs in rural areas or the workers of other organizations such as the Ministry of Agriculture and Red Crescent Organization. Three major strategies are proposed to strengthen villagers' self-efficacy in the face of natural environmental hazards. First of all, it is necessary to help the villagers to become fundamentally and completely familiar with the most practical methods of dealing with the different natural environmental hazards and their impacts. This will help them to see and understand the results of following recommended protocols and methods of dealing with and preparedness for natural environmental hazards in a completely experimental way. This stage can be called the mastery stage of using methods to deal with natural environmental hazards. The second stage is observation. At this stage, the villagers should see examples of people around them who could use the strategies and measures of dealing with natural environmental hazards and in this way have helped to reduce the risks and better management of the hazards. It is recommended that the interventionists identify such people in advance and introduce them to the villagers during the implementation of hazard risk management programs. The third stage is persuasion. In fact, at this stage, the interventionists and field workers of the hazard risk management systems interact with the rural communities practically and discuss with them the way(s) to manage the hazards and their consequences. This process can take place in the form of forming discussion groups in the village environment or the form of virtual groups. The analysis of direct effects on psychological resilience against natural environmental hazards showed that the attitude towards the natural environmental hazards’ risk management measures and the methods of dealing with it in both structural models 1 and 2 have positive and significant effects on psychological resilience against natural environmental hazards. This result indicates that having a suitable and favorable attitude towards natural environmental hazards’ risk management measures and the methods of dealing with them can improve the psychological resilience of the villagers against the hazard. This result is aligned with the results of Ajzen (1991), Cahigas et al. (2023) and Kumar (2021). Considering the positive effect of attitude on psychological resilience against natural environmental hazards, it is suggested that educational and extensional programs be designed and implemented to improve villagers' attitudes towards natural environmental hazards’ risk management measures. This work can be implemented by hazard risk management bodies or the Red Crescent Organizations that are directly connected with rural communities. In these programs, natural hazard risk management officials can talk about the benefits and effectiveness of certain methods of dealing with the hazards and share the experiences of other regions of the country (or the world) in the field of management and preparedness methods with the villagers. This can create a positive attitude toward the use of hazard risk management measures in the villages. With the formation of such an attitude, their psychological resilience against natural environmental hazards will improve. The results of the analysis of structural models 1 and 2 demonstrated that although the direct impact of social leadership on the psychological resilience of rural people against natural environmental hazards was not significant, its indirect effect (mediated by attitude and self-efficacy) on psychological resilience was positive and statistically significant. It means that the more the villagers have a higher social leadership spirit in natural hazards, the more their psychological resilience against natural environmental hazards increases. Findings similar to this result can be found in the results of Alizadeh and Sharifi (2021), Robertson et al. (2021), and Grote (2019). From this result, it can be concluded that one of the prerequisites for the psychological resilience of rural people against natural environmental hazards is the development of social leadership. In this regard, it is suggested to develop the skills of social leadership among members of rural communities. For the development of social leadership in the field of natural hazard risk reduction, it is recommended that special strategies be applied by practitioners of hazard risk management and recovery programs. First, mutual trust must be established among the members of the village community. This means that the interventionists of natural hazard risk reduction services and people should trust each other's activities to manage the shocks. Second, collective identity should become another pillar of strengthening the social leadership of rural people in the field of hazard risk management. In other words, villagers and hazard risk management operators should consider successes and failures in dealing with the shock as the outcome of the collective work of all actors. This can lead to the formation of a collective identity in the first stage and improve social leadership among the members of rural communities in the second stage. Thirdly, to strengthen social leadership, it is suggested to identify the most effective communication channels among community members. During natural environmental hazards, the communication and influence of people in society are mostly through virtual communication channels. By identifying and activating these communication channels, people can experience a high quality of communication between themselves. In this way, people who have the ability of collective leadership can easily influence other members of the villages in the field of natural environmental hazards, and collective leadership and consequently psychological resilience against natural environmental hazards will be strengthened. Of course, it should be mentioned that the application of these strategies can directly improve the attitude and self-efficacy of villagers toward the management of natural environmental hazards. This issue is important because the two constructs of attitude and self-efficacy had positive effects on psychological resilience against natural environmental hazards according to the results of structural analysis. Moreover, these two constructs mediated the effect of social leadership on psychological resilience against natural environmental hazards. The results of the analysis of moderated effects in structural model 1 revealed that including livelihood strategies in TPB could successfully and positively moderate the impacts of attitude and social leadership of rural people on their psychological resilience against natural hazards. In other words, this result indicates that if programs and strategies to improve attitudes and strengthen social leadership in rural communities are combined with income and livelihood diversification projects, they can have positive synergistic effects on villagers’ psychological resilience against natural environmental hazards. Thus, it is recommended that managers, decision-makers, implementers, and practitioners of sustainable livelihood development projects invest more in diversifying the income and livelihood sources of villagers. For example, due to transportation and sale restrictions for livestock and agricultural products during natural environmental hazards, many of them have tried to earn from other sources of income such as handicrafts and governmental subsidies. This matter is very important because of its contribution to the livelihood and economy of rural households during natural environmental hazards. Therefore, agents of livelihood development programs are suggested to have detailed plans for creating options for rural households to earn income and encouraging them to use them. The results of the moderated effects in inner model 2 showed that the inclusion of Internet and mass-media-based strategies in TPB could positively and significantly affect the impacts of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards. This result shows that it is better for any program related to changing attitudes, self-efficacy, and normative considerations in rural communities to be accompanied by the development of livelihood strategies that are based on the Internet and virtual space. In this regard, it is recommended that managers, decision-makers, executives, and operators of sustainable development projects in rural areas invest more in the potential of virtual space and mass media. For example, studies show that internet-based businesses have developed a lot in different regions of the world in recent years. This issue is visible even in some rural areas. However, it should not be forgotten that Internet-based businesses in rural areas are less developed than in urban areas. Therefore, many villagers are facing problems in selling and marketing their products due to Internet access. In such a situation, it is recommended that sustainable livelihood development programs in rural areas focus on training methods and platforms for selling and marketing agricultural and livestock products of villagers. The results of the research also demonstrated that the effect of incorporating Internet and mass-media-based strategies into TPB on increasing the explanation of resilience against natural environmental hazards is greater than the effect of incorporating livelihood strategies into it. In other words, when Internet and mass-media-based strategies are entered as moderators in the model, the explained variance of resilience against natural environmental hazards is about 0.542. Meanwhile, the explanation of resilience against natural environmental hazards is about 0.413 when we consider livelihood strategies as the moderator. This issue is important because it gives hazard risk management executives the knowledge that the effectiveness of using the Internet and mass-media-based strategies is higher than livelihood strategies. Therefore, these strategies should be prioritized. There were limitations in this research that explanation of which can pave the way for further research by future researchers. First of all, in the current research, psychological resilience against natural environmental hazards has been examined only from the psychological-social aspect. Future researchers can examine the determinants of the economic and environmental resilience of villagers. Second in the current research, due to the economic limitations and the time available to conduct the research, only the moderating effects of two types of strategies (livelihood and Internet and mass media-based strategies) were examined in the model. Nevertheless, future researchers may use other strategies according to the context in which they conduct their research. Third, in structural models 1 and 2, part of the variance of the psychological resilience against natural environmental hazards remained unexplained. This demonstrates that there are still constructs that can be used to extend TPB. Future researchers can use social, economic, and even structural constructs to develop theory. 7. Conclusion, limitations, and future research directions The general purpose of this study was to analyze the psychological resilience of villagers against natural environmental hazards through the lens of an extended TPB. The study ended with five key conclusions. First, incorporating social leadership into the TPB is a positive step that can strengthen normative considerations, self-efficacy, and attitudes (as key predictors of resilience against natural environmental hazards). Second, self-efficacy and attitude can improve the effectiveness of social leadership of rural people on psychological resilience against natural environmental hazards in TPB. Third, adding livelihood strategies to the model can significantly moderate the impacts of attitude and social leadership on psychological resilience against natural environmental hazards in TPB. Fourthly, adding Internet and mass media-based strategies to TPB can result in constructive moderation for the effects of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards. Fifthly, the effect of including Internet and mass-media-based strategies in TPB on increasing the explanation of psychological resilience against natural environmental hazards is greater than the effect of including livelihood strategies in it. In general, it can be argued that this research contributes to the development of this theory by adding new hypotheses to the original TPB. In other words, incorporating these new constructs into the TPB and clarifying their relationships with the previous constructs helps to evolve the TPB and understand the mechanisms of behavior formation (psychological resilience against natural environmental hazards). In addition, the understanding of the relationships between these constructs and the mechanisms of their influence on each other ended with practical suggestions in the discussion section that can be put into practice by policy-makers, decision-makers, risk managers, and practitioners to improve the natural environmental hazards’ preparedness and recovery. Declarations 1. Originality & Plagiarism Free Work: This manuscript is original, has not been published elsewhere, and does not contain any plagiarized material. 2. Exclusive Submission : The manuscript is not under consideration by any other journal and will not be submitted elsewhere until the editorial decision is finalized. 3. Authorship & Consent: All coauthors have contributed significantly to the research and writing process, and they have approved the final version of the manuscript for submission. 4. Ethical Compliance: The research adheres to the highest standards of academic integrity and complies with all applicable ethical guidelines (e.g., data privacy, informed consent if involving human subjects). 5. Conflict of Interest: No financial, professional, or personal conflicts of interest could influence the research outcomes or interpretations. 6. Funding Disclosure: No external funding was received for this study. 7. Data Transparency: All data presented are accurate, and any third-party materials (e.g., tables, figures) have been properly cited or permitted for reuse. I take full responsibility for the content of this manuscript and affirm that all information provided above is correct. DATA AVAILABILITY STATEMENT: The datasets generated during and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable request. Ethics statement and Consent to participate : This research was approved by the Research Committee of the University of Tehran. Additionally, all participants provided informed consent prior to their involvement in the study. Also, at the beginning of the survey, the purpose of the research was thoroughly explained to participants to ensure they could provide informed consent and participate with full understanding Acknowledgements The authors would like to acknowledge the use of OpenAI’s ChatGPT for language editing and clarity improvement during the preparation of this manuscript. No generative AI tools were used to create or generate any original content, data, or analysis presented in this paper. All findings, interpretations, and discussions are solely the result of the authors’ own research and intellectual effort. References Ahmmadi, P., Rahimian, M., & Movahed, R. G. (2021). 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Tehran","correspondingAuthor":false,"prefix":"","firstName":"Armin","middleName":"","lastName":"Artang","suffix":""},{"id":492144637,"identity":"510ad907-3422-481f-ad52-901c89f40eb1","order_by":2,"name":"Morteza Akbari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDADCQkgkVAB5SXgV8zYgNByhkGCRC2MbVAt+IBue+/zBx/+2MlLzm5+9uHhvMN1DOyHHzA83INbi9mZ44aNM3iSDWfLHDOekbjtsAQDT5oBQ8IzPFpupDE280gwM86TSDBmAGthyAH65QABLX8M6u3nSaR/ZkicA9TC/4YILQwJhxNnS+QAbWkAapEgZMuZY4wzew4cT54550wxQ8KxdMk2iWcGB/BqOd7G8OHHn2rbGbfbNzP+qLHm5+dPfvjwBx4tmIANiEnSMApGwSgYBaMAEwAAFtFRFPFtaB4AAAAASUVORK5CYII=","orcid":"","institution":"University of Tehran","correspondingAuthor":true,"prefix":"","firstName":"Morteza","middleName":"","lastName":"Akbari","suffix":""},{"id":492144638,"identity":"6ca7bd47-d506-4b1e-b343-c6d77641152b","order_by":3,"name":"Ezatollah Ghazani","email":"","orcid":"","institution":"Tarbiat Modares University","correspondingAuthor":false,"prefix":"","firstName":"Ezatollah","middleName":"","lastName":"Ghazani","suffix":""},{"id":492144639,"identity":"9a5d6cec-09e1-4fda-978b-05ada96de20d","order_by":4,"name":"Hamid Padash","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"prefix":"","firstName":"Hamid","middleName":"","lastName":"Padash","suffix":""}],"badges":[],"createdAt":"2025-06-24 12:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6965895/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6965895/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87821587,"identity":"48016789-2986-470e-a3ab-138726150b15","added_by":"auto","created_at":"2025-07-29 11:08:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22131,"visible":true,"origin":"","legend":"\u003cp\u003eResearch Model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6965895/v1/fa53b8141b914fda127f761e.png"},{"id":87821591,"identity":"26d0d7d5-1a60-4763-a0be-e7d055ede952","added_by":"auto","created_at":"2025-07-29 11:08:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":239583,"visible":true,"origin":"","legend":"\u003cp\u003eThe sites of study (Source: Iran Statistics Center, 2023)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6965895/v1/11766cb5b7afc60aedb4a94e.png"},{"id":87823404,"identity":"54b21e8f-fb58-4960-ba8e-5bbb03d443ba","added_by":"auto","created_at":"2025-07-29 11:24:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":21758,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural model 1 with standardized path coefficients (when livelihood strategies acted as the moderating variable)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6965895/v1/e8104e62845a1ffc20eb450d.png"},{"id":87822418,"identity":"583ebacf-bf12-4a19-b1a6-ca0aac3534ae","added_by":"auto","created_at":"2025-07-29 11:16:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":21883,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural model 2 with standardized path coefficients (when Internet and mass media-based strategies acted as the moderating variable)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6965895/v1/76ec695d362d53fbf9aa6b84.png"},{"id":92570917,"identity":"c69894de-9834-4ece-8085-b6f2be6e26d0","added_by":"auto","created_at":"2025-10-01 07:40:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2606314,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6965895/v1/6c2a72ff-ccfd-43c5-ad40-81b52fdb9fe7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of Social leadership on psychological Resilience under Natural Environmental Hazards","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNatural environmental hazards dramatically affect socio-economic conditions all over the world. However, these effects and their negative consequences were more evident in developing countries (IFAD, 2020; WHO, 2020; Yazdanpanah et al., 2020). Poor households with low economic power suffered more from the impacts of natural environmental hazards than other groups and social classes (Fang et al., 2028). The consequences of natural environmental hazards are very diverse. Several studies state that these natural environmental hazards mainly affect poor groups in villages (Ur Rahman et al., 2021).\u0026nbsp;The\u0026nbsp;rural-urban\u0026nbsp;contrast\u0026nbsp;is essential in\u0026nbsp;the\u0026nbsp;understanding\u0026nbsp;of\u0026nbsp;the socio-economic impacts of environmental natural hazards (Chai et al., 2021).\u0026nbsp;Rural areas,\u0026nbsp;in general,\u0026nbsp;are\u0026nbsp;characterised\u0026nbsp;by lower population\u0026nbsp;sizes, agricultural\u0026nbsp;economies, and\u0026nbsp;accessibility\u0026nbsp;to\u0026nbsp;fewer\u0026nbsp;infrastructure\u0026nbsp;facilities\u0026nbsp;and public\u0026nbsp;amenities\u0026nbsp;compared to urban areas (Chotia \u0026amp; Rao, 2017).\u0026nbsp;Urban areas typically\u0026nbsp;are\u0026nbsp;characterised by a\u0026nbsp;higher\u0026nbsp;number\u0026nbsp;of people, diversified economies, and\u0026nbsp;easier\u0026nbsp;access to healthcare, education, and emergency\u0026nbsp;services (Vlahov \u0026amp; Galea, 2002). These\u0026nbsp;inequalities\u0026nbsp;play a\u0026nbsp;significant\u0026nbsp;part\u0026nbsp;in determining the\u0026nbsp;risk\u0026nbsp;and resilience of communities to\u0026nbsp;natural\u0026nbsp;environmental\u0026nbsp;hazards, with rural\u0026nbsp;communities\u0026nbsp;tending\u0026nbsp;to\u0026nbsp;face\u0026nbsp;more\u0026nbsp;challenges due to economic constraints and\u0026nbsp;insufficient\u0026nbsp;institutional support (Mododi Arkhodi et al., 2020).\u003c/p\u003e\n\u003cp\u003ePhillipson et al. (2020) stated that natural environmental hazards can negatively affect rural businesses, agricultural activities, food security, and the income of rural households. Rural communities differ in their exposure to risk sources, susceptibility to risks, adaptive capacity, and access to socio-economic resources in hazardous conditions (Fahad et al., 2023; Rusmayandi et al., 2023). Some researchers (Horton, 2003; Savari et al., 2023) argue that after natural hazards occur, most studies focus on privileged communities, while less attention is given to vulnerable rural populations. However, effective hazard management requires attention to these communities, as they often rely on traditional knowledge and localized coping mechanisms. The interaction between traditional knowledge and modern influences can shape their resilience, with urbanization and financial resources either bridging or widening the gap between these two knowledge systems. Understanding how villagers perceive natural environmental hazards is crucial for strengthening resilience (Ngcamu, 2023; Phuong et al., 2023). This highlights the need for participatory assessments and co-developed methods that incorporate local knowledge into risk management strategies. Although research on the socio-psychological dimensions of natural hazards remains limited, some scholars (Xu et al., 2020; Cahigas et al., 2023; Ma et al., 2023; Faryabi et al., 2023; Peng et al., 2023; Opiyo et al., 2024) emphasize the importance of public perceptions and socio-psychological factors in disaster preparedness and response.\u003c/p\u003e\n\u003cp\u003eXu et al. (2021) state that such studies can help develop appropriate training programs for resilience against natural environmental hazards\u0026rsquo; shocks and finally end in control and eradication of their rebound effects (Asare-Nuamah et al., 2022; Shah et al., 2023; Dehghani Pour et al., 2023). Considering the wide and deep impacts of natural environmental hazards on the subjective and objective well-being of individuals all over the world (Qi et al., 2023; Cannings et al., 2024), it is necessary to identify the constructs influencing the psychological resilience of people (Ballesteros et al., 2023). Psychological resilience refers to a person\u0026apos;s positive reactions that allow him/her to deal effectively with stressful situations such as natural environmental hazards (Ehrich et al., 2017; Wang et al., 2024; Elshaer, 2024). To the best of our knowledge, there is no study focusing on the psychological resilience of rural people against natural environmental hazards and the constructs influencing it. Thus, investigating the psychological resilience of rural people against natural environmental hazards and their determinants in Iran was considered the aim of this research.\u003c/p\u003e\n\u003cp\u003eStatistics show that an average of 5583 people is killed daily due to natural environmental hazards, and most of this figure is in developing countries, especially in rural areas (Kim et al., 2013). Iran is one of the countries that have always been struggling with natural environmental hazards such as floods and earthquakes. In developing countries like Iran, rural areas are highly vulnerable to earthquakes and floods. This vulnerability stems from deep-rooted challenges in various dimensions, including environmental-physical, socio-cultural, economic, and historical-political factors. These challenges have become institutionalized over time (Parishan, 2012). Many rural areas of Iran are more vulnerable to natural environmental hazards compared to other human settlements due to their geographical and natural location and the low level of knowledge and awareness of earthquake and flood crisis management (Savari et al., 2024). According to Iran\u0026apos;s official statistics, every ten years an earthquake with a magnitude greater than M7 on Richter-scale, every 3 years an earthquake with a magnitude between 6 to 7 Richter, and ten earthquakes with a magnitude of 5 to 6 Richter have occurred in Iran. The consequence of the earthquake was the destruction of nearly 90% of the rural units in the area where the earthquake occurred in Iran. This shows that rural structures are the most vulnerable buildings, which are damaged by even the smallest earthquake. The destruction of 20 to 70 percent of Bam villages (Sharifi, 2009) and the 100 percent destruction of 45 percent of villages in Sarpol Zahab city are examples of the high level of destruction of rural areas in Iran (Sanjabi, 2019). In addition to earthquakes, floods are one of the natural environmental hazards that have always caused human, economic, and infrastructure damage in rural areas of Iran (Shokri et al., 2020; Pazhuhan et al., 2023). In the rural areas of Iran, the intervention of unplanned anthropogenic factors has significantly increased the risks of floods. The anthropogenic factors resulting in floods include deforestation, land degradation, improper irrigation practices, and unplanned construction. These factors alter natural water flow and reduce soil absorption capacity. As a result, even in the arid regions of Iran that have low rainfall levels, the runoff coefficient has increased due to multi-year droughts and non-compliance with the sustainability of irrigation and watershed management. Another reason for increasing the runoff coefficient is the reduction of vegetation. These factors have caused damaging floods to form despite low rainfall. Investigating the psychological resilience of rural people against natural environmental hazards and their determinants in Iran, which was the aim of present research, can be one of the most important steps to solve these problems. To achieve this goal, several specific objectives were set:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eDeveloping a theoretical framework to explain psychological resilience of rural people against natural environmental hazards based on the theory of planned behavior (TPB);\u003c/li\u003e\n \u003cli\u003eImplementing a measurement and structural model to test the validity and reliability of data and instruments and test hypotheses; and\u003c/li\u003e\n \u003cli\u003eProviding practical suggestions based on the research results to increase psychological resilience of rural people against natural environmental hazards.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe contributions of this study are as follows. First, recent studies have used TPB (a psychological theory) to investigate behavioral responses toward flood hazards, typhoons, earthquakes, and haze pollution (Xu et al., 2021; Cahigas et al., 2023). However, none of them have focused on the psychological resilience of villagers against natural environmental hazards. We attempted to examine the determinants of psychological resilience against natural environmental hazards using the TPB. Second, although the predictive power of the TPB has been supported by previous studies (Rahimi-Feyzabad et al., 2022; Xu et al., 2021; Cahigas et al., 2023), it only employs a limited number of variables to predict the intention. Therefore, the present study extends this theory by incorporating new constructs into that. For instance, social leadership and mitigation strategies are the most important constructs the effects of their incorporation into TPB will be examined for the first time in the present study. In addition, the third contribution of the present study to the body of knowledge is that the present study has ended with innovative recommendations in the field of methods of dealing with natural environmental hazards, which can pave the way for preventive and post-disaster interventions in rural areas. In other words, this study ends up providing strategies that can help policy-makers, managers, and practitioners after the occurrence of natural environmental hazards so that they can improve the psychological resilience of villagers more effectively.\u003c/p\u003e\n\u003cp\u003eThe most important research questions pursued in this study are as follows:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eHow can a theoretical framework based on the Theory of Planned Behavior (TPB) be developed to explain the psychological resilience of rural people against natural environmental hazards?\u003c/li\u003e\n \u003cli\u003eHow valid and reliable are the measurement and structural models used to assess psychological resilience, and what do the test results reveal about the proposed hypotheses?\u003c/li\u003e\n \u003cli\u003eWhat practical recommendations can be derived from the research findings to enhance the psychological resilience of rural people against natural environmental hazards?\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"2. Theoretical background: Towards extending the TPB","content":"\u003cp\u003e\u003cstrong\u003e2.1. TPB\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, the TPB was used to analyze the psychological resilience of Iranian villagers. This theory is a psychological theory to explain the human behavior. According to many researchers (see Ong et al., 2021; Rahimi-Feyzabad et al., 2022; Xu et al., 2021), this theory is one of the best theories for analyzing people's behavior in different contexts and is of great ability to predict their behavior. Many researchers (see Shi et al., 2021; Ahmmadi et al., 2021; Tama et al., 2021; Kurata et al., 2022) have used this theory for analyzing the behavior of local communities in rural areas. The results of these studies show that TPB has an acceptable predictive power and validity to encourage people's behaviors. TPB is based on the position that behavior appears immediately after behavioral intention (Ajzen, 1991; Dorce et al., 2021; Zaremohzzabieh et al., 2021; Lavuri, 2022). In this theory, behavioral intention is influenced by three variables: attitude toward behavior, subjective norms, and perceived behavioral control (PBC) (Wan et al., 2021; Alavion \u0026amp; Taghdisi, 2021; Qaid et al., 2022). In other words, in TPB, these three variables play a key role in activating the behavioral intention and immediately the actual behavior of individuals (Tama et al., 2021; Lavuri, 2022).\u003c/p\u003e\n\u003cp\u003eAttitude towards behavior is one of the triads that directly affects the psychological resilience of villagers based on TPB. Ajzen (1991) states that attitude is a person's favorable or unfavorable evaluation of the consequences of performing a behavior. Based on this definition, the attitude towards preparedness against the disaster is defined as the favorable or unfavorable psychological evaluation of the villagers regarding preparedness against the natural disaster. Subjective norms are also reflecting the social pressure imposed on a person by others to perform or not perform a specific behavior in coping with the natural disaster (Esposito et al., 2016; Ahmmadi et al., 2021; Tama et al., 2021). Ajzen points out that subjective norms can be descriptive and injunctive. However, the theories of moral approach in environmental psychology consider not paying attention to moral norms as one of the criticisms of TPB (Pradhananga et al., 2019). Therefore, in the present study, instead of the term \"subjective norms\", the more general term \"normative considerations\" was used. Accordingly, the structure of normative considerations includes descriptive, injunctive, and moral norms. Normative considerations in the present study refer to the level of control on the villagers' participation in the management of the natural disasters (by three norms). Perceived behavioral control or self-efficacy also shows the difficulty or ease of performing a behavior for a person (Cahigas et al., 2023; Dorce et al., 2021; Kumar, 2021). Based on this definition, self-efficacy in dealing with the natural disasters shows that it is easy or difficult for the villagers to deal with the risks of the disasters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2-2. Resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResilience is a measure of the stability and collapse state of a social, economic, physical, and ecological system (Khezri et al., 2021). This term was first proposed in the field of ecology and was considered one of the main characteristics of measuring the strength of an ecosystem (Alizadeh \u0026amp; Sharifi, 2021; Xiao et al., 2021). Resilience is defined as the ability of a system (social, economic, physical, and ecological) to adapt to changes and maintain its initial state against external shocks (Borrion et al., 2020; He et al., 2021). In other words, resilience can help explain nonlinear changes in a particular system (Xiao et al., 2021). Today, the definition of resilience is not limited to ecological and physical systems, and many social and psychological researchers also use this term to explain the behavior of human subjects (Maleksaeidi et al., 2015; Shojaei‐Miandoragh et al., 2021). Reviewing the research literature in this field shows that many studies (see Maleksaeidi et al., 2015) have recently been done in the field of psychological preparedness against various shocks (such as climate change, floods, drought, diseases, etc.). Psychological resilience is defined as a reactive response or behavior of people in a stressful situation to effectively deal with the effects of disaster (Ehrich et al., 2017). In the present study, following the study of Maleksaeidi et al. (2021), psychological resilience refers to the effective use or use of coping strategies against natural disasters by villagers.\u003c/p\u003e\n\u003cp\u003eIn this study, some context-specific variables explaining psychological resilience were entered into the original TPB. In addition, unlike the original version of this theory, which regards the intention to psychological resilience as the main dependent variable, actual behavior or psychological resilience is considered as the dependent variable. There were several major justifications for this. First, the behavior investigated in this study (psychological resilience) was not based on the individuals’ future-oriented actions. In other words, resilience against natural disasters was not a behavior that villagers are supposed to do in the not-so-distant future; rather, it was a behavior that they know to do now. In addition, some studies (see Sheeran \u0026amp; Webb, 2016; Barth \u0026amp; De Jong, 2017) show that in some cases individuals’ intentions do not necessarily end in behavior. In other words, there is a significant discrepancy between intention (future behavior) and behavior (actual behavior). Therefore, some factors may delay the transformation of intention into actual behavior. In this study, resilience against natural disasters was considered as an actual behavior.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs mentioned earlier, in the original version of TPB, people's behavior is explained by the three antecedents of attitude towards behavior, subjective norms, and PBC (Ong et al., 2021; Rahimi-Feyzabad et al., 2022). However, studies show that in practice the effects of these three variables on behavior are mediated by other variables (Sheeran \u0026amp; Webb, 2016; Barth \u0026amp; De Jong, 2017). For example, according to TPB, PBC or self-efficacy directly affects the resilience of villagers against natural disasters. However, it is easy to see that the use or non-use of livelihood or mass media-based mitigation strategies can increase or decrease its impact. In other words, adopting mitigation strategies can be considered a moderator of the effect of self-efficacy on psychological resilience against natural disasters. Such a moderating effect can be set for the effects of normative considerations and attitudes on psychological resilience against natural disasters. In this regard, mitigation strategies were added to the original TPB as moderators. Based on the study of Maleksaeidi et al. (2015), mitigation strategies in this study refer to the methods that villagers use to reduce the impacts of natural disasters. In other words, these strategies reduce the vulnerability of villagers to the unfortunate consequences of the shock related tot the natural disasters. For example, diversification of income sources is one of the mitigation strategies that can play a key role in increasing the psychological resilience of villagers against natural disasters.\u003c/p\u003e\n\u003cp\u003eMoreover, the theoretical literature (see Stodd, 2014; Asrar-ul-Haq \u0026amp; Kuchinke, 2016; Wu et al., 2020; O'Sullivan \u0026amp; Sakr, 2022) shows that the constructs of attitude, self-efficacy, and normative considerations can be explained by other antecedents. For example, villagers’ self-efficacy in the field of coping with natural disasters can be influenced by social leadership.\u003c/p\u003e"},{"header":"3. Hypotheses Development","content":"\u003cp\u003e\u003cstrong\u003e3.1. Social leadership and normative considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSocial leadership refers to the act of orchestrating adaptive change in groups, organizations, communities, and nations (Stodd, 2014;\u0026nbsp;Melania et al., 2021; Cheng, 2024). Social leadership recognizes that many social challenges are characterized by competitive approaches, ethical dilemmas, and emerging situations that community members may never have faced before (Porteous, 2013). Due to their high understanding power, experience, leadership spirit, and effectiveness, they try to push the existing norms in society to be more compatible with the challenge and create appropriate norms (Friedman, 2013; O\u0026apos;Sullivan \u0026amp; Sakr, 2022). In this regard, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 1\u003c/strong\u003e: Social leadership positively influences the normative considerations of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Social leadership and self-efficacy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSocial leaders are generally from among the people of the target communities and live with them. In other words, many of them have common experiences with other members of society. This issue is important from two aspects. First, social leaders, due to their great influence among community members, can increase their sense of self-efficacy by providing guidance and accurate information (Alizadeh \u0026amp; Sharifi, 2021). Second, it is easier for community members to accept the recommendations of social leaders. Therefore, if the leader him /herself takes a step to solve a specific problem (such as the shock of natural environmental hazards) and this action is effective, the members of the society will accept it faster and easier (Wu et al., 2020), because the results of its effectiveness have been seen concretely in the actions of the leader. In other words, in this way, the self-efficacy of society members improves (Valizadeh et al., 2022). Therefore, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 2\u003c/strong\u003e: Social leadership positively influences the self-efficacy of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Social leadership and attitude\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMany researchers (see Asrar-ul-Haq \u0026amp; Kuchinke, 2016) claim that leaders can positively or negatively influence the attitudes of followers and community members. This is generally due to the trust that community members and followers have in social leaders (Stodd, 2014). Alizadeh and Sharifi (2021) consider social leadership as a key factor in the formation of positive attitudes toward strategies to deal with natural hazard shocks. In this regard, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 3\u003c/strong\u003e: Social leadership positively influences the attitude of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Normative considerations and psychological resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNormative considerations refer to the level of control of people\u0026apos;s behavior (resilience) by various descriptive, injunctive, and moral norms (Ajze, 1991; Cahigas et al., 2023). The formation of positive normative considerations towards natural environmental hazards can play a positive role in increasing the resilience of rural and agricultural communities against the shock (Valizadeh et al., 2022; Mutyebere et al., 2024; Xu et al., 2024; Tao et al., 2024; Sawaneh et al., 2024). Therefore, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 4\u003c/strong\u003e: Normative considerations positively affect the psychological resilience of rural people.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Self-efficacy and psychological resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerceived behavioral control or self-efficacy emphasizes the difficulty or ease of performing a behavior for a person (Innocenti et al., 2023; Baldwin et al., 2023). Cahigas et al. (2023) claim that perceived behavioral control or self-efficacy can reduce people\u0026apos;s resistance to receiving natural hazard-reducing measures. Considering that many other studies such as Kumar (2021) and Yagoubi et al. (2021) have supported the effect of self-efficacy on psychosocial resilience against natural environmental hazards, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 5\u003c/strong\u003e: Self-efficacy positively influences the psychological resilience of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6. Attitude and psychological resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAttitude refers to a person\u0026apos;s favorable or unfavorable evaluation of the consequences of performing a behavior (Ajzen, 1991; Mutyebere et al., 2023; Nguyen et al., 2024). The theoretical justification of the relationship between attitude and behavior is that unless people have a favorable or positive attitude toward action, they will not do it (Kurata et al., 2023; Gansser \u0026amp; Reich, 2023). Although in some situations this assumption may not be true, in general attitude is considered a key determinant for behaviors such as resilience against natural environmental hazards (Yazdanpanah et al., 2021). In this regard, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 6\u003c/strong\u003e: Attitude positively influences the psychological resilience of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7. Social leadership and psychological resilience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePorteous (2013) claims that social leadership contributes to adaptive changes in groups, organizations, communities, and nations and thus increases their resilience against various shocks such as natural environmental hazards. Social leaders effectively contribute to the resilience of societies in the face of crises through their interventionist role (Valizadeh et al., 2022). Many studies (Alizadeh \u0026amp; Sharifi, 2021) have recently confirmed the significant and positive effect of social leadership on resilient behaviors against diverse natural environmental hazards. In this regard, it was hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 7\u003c/strong\u003e: Social leadership positively influences the psychological resilience of villagers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8. Mediating role of normative considerations, self-efficacy, and attitude\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the eighth hypothesis, it was shown that social leadership can directly affect psychological resilience against natural hazards. However, it should be noted that social leadership can also indirectly affect resilience through the constructs of normative considerations, self-efficacy, and attitude. Based on the first, second, and third hypotheses, social leadership directly affects these three constructs (Stodd, 2014; Wu et al., 2020). In addition, since these three variables directly affect psychological resilience against natural environmental hazards (Rahimi-Feyzabad et al., 2022), we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses 8, 9, 10\u003c/strong\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNormative considerations, self-efficacy, and attitude mediate the relationship between the social leadership of rural people and their psychological resilience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.9. Moderating role of livelihood-based mitigation strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs stated in the theoretical background, attitude, normative considerations, and self-efficacy directly affect psychological resilience against natural environmental hazards (Rahimi-Feyzabad et al., 2022). However, their effects on psychological resilience are moderated by other variables. According to the fourth, fifth, and sixth hypotheses, the three constructs of normative considerations, self-efficacy, and attitude directly affect the resilience of villagers against natural environmental hazards. Nevertheless, the use or non-use of livelihood-based mitigation strategies can reduce or increase the impact of their direct effect on resilience. Livelihood-based mitigation strategies in this study refer to strategies that their employee has a positive effect on improving villagers\u0026apos; livelihoods during and after the occurrence of the natural environmental hazards. In this regard, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses 11, 12, 13\u003c/strong\u003e: Livelihood-based mitigation strategies moderate the relationship between normative considerations, self-efficacy, attitude, and the psychological resilience of villagers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.10. Moderating role of Internet and mass media-based mitigation strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrie et al. (2021) state that in addition to livelihood-based mitigation strategies, Internet-based mitigation strategies are also effective in moderating the effects of variables influencing villagers\u0026apos; resilience against natural environmental hazards (such as normative considerations, self-efficacy, and attitude). These researchers state that during and after the occurrence of natural environmental hazards, many villagers try to use the capacity of virtual space, social networks, and the Internet to obtain information about the shocks and buy and sell products. Considering that the use or non-use of these strategies can influence the effects of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards, we hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses 14, 15, and 16\u003c/strong\u003e: Internet and mass media-based mitigation strategies moderate the relationship between normative considerations, self-efficacy, and attitude and the psychological resilience of villagers.\u003c/p\u003e\n\u003cp\u003eIn general, to visually explain the relationships between the variables, the conceptual framework of the research was formulated in Figure 1. The theoretical model presented in Figure 1 illustrates the inter-relationships between the primary constructs in the study, with a focus on the determinants of psychological resilience to natural environmental hazards. Social leadership is an antecedent that influences normative considerations, self-efficacy, and attitude, which are considered mediators influencing psychological resilience. Psychological resilience is theorized to be a sixth-order construct composed of six root dimensions, namely hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of effects, and creativity. The framework also highlights the moderating role of livelihood-oriented coping strategies and internet and mass media-oriented coping strategies in shaping psychological resilience into correlation with mediators (normative considerations, efficacy, and attitude). \u0026nbsp;Such strategies may facilitate or dampen the influence of the mediators on resilience and suggest that villagers\u0026apos; adaptation strategies are pivotal in shaping or constraining resilience-promoting processes. The causal associations as hypothesized are depicted by the arrows in the figure, and the location of the mitigation strategies indicates their moderating function and not the direct effect. This system provides for the possibility of developing a theoretical underpinning for understanding how cognitive process, adaptation actions, and leadership influence one another to contribute to resilience in natural environmental disasters.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Methodology ","content":"\u003cp\u003eThis study used a quantitative cross-sectional survey method to test relationships between the variables. This research is an applied study, the results of which can be used in various interventions and programs related to management of the natural environmental hazards, rural preparedness development policies, and rebound effects\u0026rsquo; management in natural environmental hazards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1. Population, sample, and sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe population of the research included villagers who lived in Sirjan County and Eghlid County of the Fars and Kerman provinces in the south of Iran. The two provinces of Fars and Kerman were chosen as the study area because floods and earthquakes are two natural disasters in these provinces that cause great damage to the villagers (Figure 2). The number of villagers living in the rural areas of these two counties was 101,934 according to the latest official census of the \u003cem\u003eIran Statistics Center\u003c/em\u003e (https://amar.org.ir/en). Out of this rural population, about 66,775 cases lived in Sirjan county of Kerman province. Furthermore, 35159 cases of the studied rural population were from Eghlid county of Fars province. The total number of samples that needed to be selected from these two counties was calculated using Cochran\u0026apos;s sample estimation formula. Therefore, 206 villagers were selected as samples. Villagers were selected in the form of a multi-stage purposeful-random sampling process. The first stage of the sampling process was done purposefully. According to the limitations of the research (economic limitations, social distancing during the COVID-19, traveling limitations), the two counties mentioned above were purposefully selected as samples. Another reason for selecting these regions as the study area was related to the fact that in the last two decades, these regions have experienced many natural environmental hazards such as droughts, floods, and even earthquakes. Considering that these hazards may occur in the future, conducting research like the present one can help management and preparation to deal with these hazards. At this stage, the sample calculated for the entire population (206 cases) was divided proportionally between the two counties of Eghlid and Sirjan. The country divisions of Iran divide the rural areas of each county into smaller units called Dehestan, each of which has several villages. Therefore, in the second stage, some Dehestans were randomly selected by the research team. Like the previous stage, the sample estimated for each county was divided according to the population size of the villages. The third step of the sampling process included the randomized selection of one village from each of the Dehestans of Sirjan and Eghlid counties. In the fourth step, the villagers were randomly selected from the selected villages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. Specification of the measures\u0026rsquo; typology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, two types of constructs were considered: higher-order constructs and lower-order constructs. Lower-order constructs are typically measured by multiple individual items, with each item directly assessing a specific aspect of the construct. Importantly, a lower-order construct does not contain additional latent dimensions that could be further broken down into subcomponents. In contrast, higher-order constructs are more complex because they consist of multiple latent dimensions. These dimensions serve as an intermediary layer between the main construct and its associated measurement items (Wan et al., 2021). In this study, psychological resilience against natural environmental hazards was identified as a higher-order construct. It was composed of six latent dimensions: hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of impacts, and creativity. Each of these latent dimensions was measured by multiple individual items, reflecting different aspects of psychological resilience. The measurement model followed a reflective-reflective structure, meaning that the individual items reflected their respective latent dimensions, and these dimensions collectively represented the overarching construct of psychological resilience against natural environmental hazards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3. Measures of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included five measures. The development of these measures was done using a multi-step process. In the first stage, an effort was made to ensure that the constructs of the research framework were compatible with the context of the study population. Ajzen (1991) stated that TPB requires researchers to directly extract the items measuring the constructs from the studied community. The items that are chosen arbitrarily and intuitively may end up with relationships that are not very consistent with the realities of the study area (Fishbein \u0026amp; Ajzen, 2010). In this regard, first, an attempt was made to identify the concepts related to the measuring items of each of the measures using an open-ended questionnaire. In the second stage, these concepts were formulated in the form of a close-ended questionnaire to be a basis for the main quantitative phase. It should be mentioned that in the second stage, the concepts suggested by previous studies were used to enrich the measures that had few items. The structures of the research were as follows:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePsychological resilience\u003c/em\u003e: Psychological resilience against natural environmental hazards was one of the higher-order constructs in the present study. According to the studies of Maleksaeidi et al. (2014) and Kumpfer (1999), six latent dimensions were determined for psychological resilience against natural environmental hazards. The dimensions of psychological resilience included hopefulness, emotion, self-esteem, flexibility and adaptation, perceived controllability of impacts, and creativity (18 questions). Some of these questions were researcher-made and some were adapted from the studies of other researchers (Maleksaeidi et al., 2014).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAttitude\u003c/em\u003e: To measure attitude, we used three items so that we can evaluate the positive or negative evaluation of the villagers towards the natural environmental hazards (Yazdanpanah et al., 2021).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSelf-efficacy\u003c/em\u003e: Three items were used to measure this construct. To measure this construct, a questionnaire developed by previous scholars such as Abadi et al. (2021) was used. Of course, it should be mentioned that two items measuring self-efficacy were developed by the researchers and were identified by using the primary study and the open-ended questionnaire from the perspectives of the target community. A five-point Likert scale was employed to measure self-efficacy items.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNormative considerations\u003c/em\u003e: Normative considerations were measured using three items. To measure this construct, the concepts extracted from the open-ended questionnaire were applied.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSocial leadership\u003c/em\u003e: Social leadership was measured in this study using four items. These four items are based on the primary study and the concepts extracted from it, as well as the questionnaire designed by Salas-Vallina et al. (2021).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLivelihood-based mitigation strategies\u003c/em\u003e: This contrusct was measured using three items. The items were adapted from Maleksaeidi et al. (2015).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eInternet-based mitigation strategies\u003c/em\u003e: This construct was also measured using three items that were adapted from Yazdanpanah et al. (2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA five-point Likert scale was adapted to measure all items.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4. Data collection and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data in this study consists of survey responses collected from villagers in Sirjan County (Kerman Province) and Eghlid County (Fars Province) in southern Iran. These data were gathered through a structured questionnaire designed to measure various psychological and behavioral constructs related to resilience against natural environmental hazards. The questionnaire was developed using a multi-step process, including an initial open-ended survey to identify relevant concepts, followed by a close-ended questionnaire refined with items adapted from previous studies. Data analysis was done using structural equation modeling (SEM). For this purpose, Partial Least Square (PLS) statistical software was employed. The authors have used a commercial domain of the PLS (available at: https://www.smartpls.com/). To articulate the results, model analysis was done in the form of two structural and measurement models. The structural model was used to explain the relationships. The results of inner model and the measurement model was used to estimate the estimates of the outer model. It should be noted that the bootstrapping method was used to estimate the moderator and mediator effects. PLS structural equation modeling provides the users with several advantages over traditional regression models in social and/or behavioral studies. First, it enables the researchers to deal with multicollinearity well. This advantage makes PLS an ideal tool for situations where there are high correlated predictors. Secondly, PLS structural equation modeling is also effective is situations where there are many independent variables or a smaller sample size for the study. Increasing independent variables in a study, avoids overfitting of the model. In contrast to the traditional regression models, which put their emphasize on estimating parameter, PLS focuses on predictive accuracy of the model. Focusing on the predictive accuracy of the model improves the explanation of the outcome variables. These strengths make PLS especially useful for complex, real-world social science data where accurate predictions are essential.\u003c/p\u003e"},{"header":"5. Results","content":"\u003cp\u003eThe assessment of the demographic characteristics of the respondents showed that the average age of the sample was close to 37 years. The minimum and maximum ages of the respondents were 17 and 67 years, respectively. In terms of education, most of the respondents (nearly 43 percent) had a diploma. In other words, most of the respondents had completed high school. Participation in training courses related to coping with environmental hazard shocks was one of the key questions asked in the demographic characteristics, and the results showed that only seven percent of the respondents had participated in these courses. The study of the occupational status of the respondents showed that nearly 80 percent of the respondents were engaged in agriculture as their main occupation. Also, 73 percent of the respondents were also engaged in animal husbandry in addition to agriculture.\u003c/p\u003e\n\u003cp\u003eBefore evaluating and analyzing the inner model, the reliability and validity of outer or measurement models should always be examined. This allows researchers to identify issues of collinearity in the data and avoid biased conclusions. In this study, explanatory variables of psychological resilience against natural environmental hazards were investigated using lower-order reflective measurement models. The results related to the validity and reliability of the variables used in the conceptual framework of the research was presented in Tables 1-10. In this study, considering that the two moderator variables of \u0026ldquo;livelihood strategies\u0026rdquo; and \u0026ldquo;internet and mass media-based strategies\u0026rdquo; were entered into the analysis separately, the analysis of measurement and structural models was investigated in the form of two distinctive models. In the measurement and structural model 1, livelihood strategies were considered as a moderator of the relationship between the constructs of normative considerations, self-efficacy, attitude, and social leadership with psychological resilience against natural environmental hazards. Meanwhile, in the measurement and structural model 2, Internet and mass media-based strategies were considered as the moderators of the relationship of these variables with psychological resilience against natural environmental hazards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.1. Measurement model 1 (livelihood Strategies as the mediating variable)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.1.1.\u003c/strong\u003e \u003cstrong\u003eInternal consistency reliability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used a composite reliability index, rho-A index, and alpha coefficients to evaluate the internal consistency reliability of reflective models of constructs such as psychological resilience against natural environmental hazards, attitude, self-efficacy, normative considerations, and social leadership. Reliable statistical sources (see Hair et al., 2017) state that if the values of these three indicators for a reflective model are greater than or equal to 70, it can be concluded that the given construct is of acceptable internal consistency reliability. Nevertheless, some items with loading factors less than 0.7 can also be kept in the model, provided that their t values are significant.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eFrom the results of Table 1 and the comparison of the results obtained for the constructs of the present study, it can be concluded that all the structures used in the present study have sufficient reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Measurement items and indicators of fitness for model 1\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\u0026nbsp;\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach\u0026rsquo;s Alpha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003erho-A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposite Reliability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Variance Extracted (AVE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eLivelihood Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 636px;\"\u003e\n \u003cp\u003eAcceptable values for the reported indices: Alpha \u0026gt; 0.7; rho-A\u0026gt; 0.7; p \u0026lt; 0.01; CR \u0026gt; 0.7; and AVE \u0026gt; 0.5\u003cspan dir=\"RTL\"\u003e\u0026nbsp; \u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e5.1.2.\u003c/strong\u003e \u003cstrong\u003eConvergent and divergent/discriminant validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe convergent validity of the constructs of the theoretical framework was investigated using outer loadings and AVE indices. All values related to outer loadings and AVE exceeded acceptable values (Tables 1-2). Therefore, it can be concluded that the seven constructs used in this study had good convergent validity.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Measurement items, loading factors, and\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eT\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003evalue of the model 1\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"749\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoading Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003e value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLivelihood strategies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eLS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eLS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e50.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e66.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormative considerations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eNC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eNC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e26.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eNC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResilience\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e56.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e16.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e13.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e25.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e16.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial leadership\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e28.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e8.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e49.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eSE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eApproved\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 749px;\"\u003e\n \u003cp\u003eAcceptable values for the reported indices: all loadings \u0026gt; 0.7; p \u0026lt; 0.01; CR \u0026gt; 0.7; and AVE \u0026gt; 0.5; T value \u0026gt; \u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn addition, the Heterotrait-Monotrait Ratio (HTMT), Fornell-Larcker Criterion, and Variance Inflation (VIF) criteria were applied to assess the discriminant validity in the outer and inner models (Tables 3-5). As Table 3 shows, all HTMT values for the variables included in model 1 are less than the critical value of 0.85. According to the Fornell-Larcker criterion, if the values in the diameter of the matrix are greater than the values in the corresponding columns, it proves that the research constructs have sufficient discriminant validity. Based on the results of performing measurement model 1, this preassumption was proved in the present study. Therefore, we can conclude that the research tool has suitable discriminant validity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Discriminant validity (FLC and HTMT)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eModel Num.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eCriteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eLivelihood Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"12\" style=\"width: 60px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 48px;\"\u003e\n \u003cp\u003eFLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eLivelihood Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.777\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.820\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.688\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.765\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.751\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.814\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 48px;\"\u003e\n \u003cp\u003eHTMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eLivelihood Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn addition, the results of Tables 4 -5 showed the VIF values for the outer and inner models in model 1. As the results show, the VIF values are lower than the acceptable value of 5. This result was another proof of the discriminant validity of the constructs.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Outer VIF values for the measuring items\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eIMMS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eIMMS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eIMMS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e3.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e3.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eNC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eNC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eSE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eNC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Inner VIF values for the latent constructs\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eModel Num.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstruct\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormative considerations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResilience\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 153px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eLivelihood Strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e2.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\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\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2. Measurement model 2 (Internet and mass media-based strategies as the mediating variable)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2.1. Internal consistency reliability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of implementing the measurement model of model 2 showed that the values of composite reliability, rho-A, and Cronbach\u0026apos;s alpha coefficients are greater than 0.7 (Table 6). Therefore, it can be concluded that all the constructs used in model 2 have acceptable internal consistency reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Measurement items (model 2\u003c/strong\u003e)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\u0026nbsp;\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach\u0026rsquo;s Alpha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003erho-A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposite Reliability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Variance Extracted (AVE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eInternet and mass media-based strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 636px;\"\u003e\n \u003cp\u003eAcceptable values for the reported indices: Alpha \u0026gt; 0.7; rho-A\u0026gt; 0.7; p \u0026lt; 0.01; CR \u0026gt; 0.7; and AVE \u0026gt; 0.5\u003cspan dir=\"RTL\"\u003e\u0026nbsp; \u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e5.2.2. Convergent and divergent/discriminant validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExamination of outer loadings and AVE for model 2 demonstrated that their values are higher than 0.7 and 0.5, respectively (Tables 6-7). Therefore, the convergent validity of the item used in model 2 was confirmed. The examination of HTMT and FLC indices for model 2 revealed that their values exceed the required acceptable values (Table 8). In addition, VIF indices (for outer and inner models) also revealed that there is no significant variance in inflation among the variables (Table 9 and Table 10). Therefore, the divergent validity of Model 2 was also confirmed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7. Measurement items, loading factors, and\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eT\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003evalue of the model 2\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"581\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoading Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003e value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eIMMS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e40.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternet and mass media-based strategies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eIMMS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e47.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eIMMS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e4.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e49.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e64.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormative considerations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e27.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eNC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e4.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResilience\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e47.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e19.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e14.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e26.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e18.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial leadership\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e27.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e8.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e44.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eSE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e8.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 581px;\"\u003e\n \u003cp\u003eAcceptable values for the reported indices: all loadings \u0026gt; 0.7; p \u0026lt; 0.01; CR \u0026gt; 0.7; and AVE \u0026gt; 0.5; T value \u0026gt; \u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8. Assessment of the discriminant validity using\u003c/strong\u003e \u003cstrong\u003eFLC and\u003c/strong\u003e \u003cstrong\u003eHTMT\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"637\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eConstruct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eInternet and mass media-based strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"12\" style=\"width: 60px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 48px;\"\u003e\n \u003cp\u003eFLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.820\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eInternet and mass media-based strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.752\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.688\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.767\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.751\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.814\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 48px;\"\u003e\n \u003cp\u003eHTMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eInternet and mass media-based strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9. Outer VIF values for the measuring items\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"530\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eIMMS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eIMMS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eIMMS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eLS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eLS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\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\u003cstrong\u003eTable 10. Inner VIF values for the latent constructs\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 153px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eAttitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eInternet and mass media-based strategies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e1.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eNormative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e2.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eSocial leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 154px;\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e2.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\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\u003cstrong\u003e5.2. Structural/inner models and testing hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe test of the hypotheses related to the relationships between the research constructs was done using the implementation of structural or inner models. Also, the effects of independent variables on dependent variables were investigated in the form of direct and indirect effects. In addition, indirect effects included mediated and moderated effects. The bootstrapping method was used to calculate the significant level and t values of indirect effects. Like the measurement models, the structural models of the research were implemented in the form of two models (structural model 1 and structural model 2). This work was done to investigate the moderation effects of \u0026ldquo;livelihood strategies\u0026rdquo; and \u0026ldquo;Internet and mass media-based strategies\u0026rdquo; on the effects of independent variables on the dependent variable (psychological resilience against natural environmental hazards).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2.1. Structural/ Inner model 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn structural model 1, first, the direct effects of the constructs on each other were examined. Examining the direct effects of social leadership on normative considerations (\u0026beta;=0.685; p\u0026lt;0.01), self-efficacy (\u0026beta;=0.617; p\u0026lt;0.01), and attitude (\u0026beta;=0.274; p\u0026lt;0.01) showed that social leadership has significant and positive direct effects on these three variables (Table 11; Figure 3). By obtaining such results, the first, second, and third hypotheses in structural model 1 were supported. In addition, self-efficacy (\u0026beta;=0.391; p\u0026lt;0.01) and attitude (\u0026beta;=0.281; p\u0026lt;0.01) had positive and significant direct effects on psychological resilience against natural environmental hazards (Table 11; Figure 3). These results also confirmed the fifth and sixth hypotheses in structural model 1. This was while the constructs of normative considerations (\u0026beta;=0.071; n.s.) and social leadership (\u0026beta;=0.082; n.s.) did not have a significant direct effect on psychological resilience against natural environmental hazards. In this way, the fourth and seventh hypotheses were rejected in structural model 1.\u003c/p\u003e\n\u003cp\u003eThe results of mediation analysis using the bootstrapping method showed that normative considerations cannot mediate the impact of social leadership of rural people on their psychological resilience against natural environmental hazards (\u0026beta; = 0.048; n.s.). This result demonstrates that the present research does not support the eighth hypothesis. On the other hand, the results of mediation structural analysis revealed that self-efficacy (\u0026beta;=0.241; p\u0026lt;0.01) and attitude (\u0026beta;=0.077; p\u0026lt;0.01) can positively and significantly mediate the effects of social leadership on psychological resilience against natural environmental hazards (Table 11; Figure 3). In this way, the ninth and tenth hypotheses were supported in structural model 1.\u003c/p\u003e\n\u003cp\u003eIn the third step, moderated indirect hypotheses were tested. Therefore, in structural model 1, livelihood strategies were considered as the moderator of the direct effects of independent variables on the dependent variable (psychological resilience against natural environmental hazards). The results indicated that livelihood strategies cannot moderate the effects of normative considerations (\u0026beta;=0.058; n.s.) and self-efficacy (\u0026beta;=0.096; n.s.) on psychological resilience against natural environmental hazards. In this way, the eleventh and twelfth hypotheses were rejected. On the other hand, the research results supported the thirteenth and fourteenth hypotheses. In other words, the results showed that livelihood strategies could positively and significantly moderate the effects of attitude (\u0026beta;=0.182; p\u0026lt;0.01) and social leadership (\u0026beta;=0.125; p\u0026lt;0.01) on psychological resilience against natural environmental hazards (Table 11; Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 11. Hypotheses testing (model 1)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel Num.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypothesis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult of a hypothesis test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"17\" style=\"width: 66px;\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003eDirect hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Normative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e14.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e13.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e4.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eNormative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSelf-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e4.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eAttitude -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e4.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 624px;\"\u003e\n \u003cp\u003eIndirect (mediation) hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Normative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Self-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e4.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt;\u0026nbsp;Attitude -\u0026gt;\u0026nbsp;Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e3.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003eIndirect (moderation) hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eNormative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSelf-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eAttitude -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e4.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\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\u003cstrong\u003e5.2.2. Structural/ Inner model 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results obtained from running the structural model 2 indicated that social leadership positively, significantly, and directly affects normative considerations (\u0026beta;=0.684; p\u0026lt;0.01), self-efficacy (\u0026beta;=0.617; p\u0026lt;0.01), and attitude (\u0026beta;=0.274; p\u0026lt;0.01) (Table 12; Figure 4). These results were evidence to support the first, second, and third hypotheses in structural model 2. The direct effects of normative considerations (\u0026beta;=0.090; n.s.) and social leadership (\u0026beta;=0.006; n.s.) on psychological resilience against natural environmental hazards were also not significant. In this way, the fourth and seventh hypotheses were rejected in structural model 2. Meanwhile, self-efficacy (\u0026beta;=0.290; p\u0026lt;0.01) and attitude (\u0026beta;=0.162; p\u0026lt;0.01) had positive and significant effects on psychological resilience against natural environmental hazards (Table 12; Figure 4). These results provided evidence to confirm the fifth and sixth hypotheses.\u003c/p\u003e\n\u003cp\u003eExamining the mediated indirect effects revealed that normative considerations cannot mediate the impact of social leadership of rural people on their psychological resilience\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eagainst natural environmental hazards (\u0026beta; = 0.061; n.s.). In this way, the eighth hypothesis was not supported. Self-efficacy (\u0026beta;=0.179; p\u0026lt;0.01) and attitude (\u0026beta;=0.044; p\u0026lt;0.01) positively and significantly mediated the effects of social leadership on psychological resilience against natural environmental hazards. According to these results, the ninth and tenth hypotheses were confirmed (Table 12; Figure 4).\u003c/p\u003e\n\u003cp\u003eThe test of moderated indirect effects indicated that Internet and mass media-based strategies could positively and significantly moderate the effects of normative considerations (\u0026beta;= 0.154; p\u0026lt;0.01), self-efficacy (\u0026beta;= 0.107; p\u0026lt;0.01), and attitude (\u0026beta; = 0.131; p\u0026lt;0.01) on psychological resilience against natural environmental hazards. Based on these results, the eleventh, twelfth, and thirteenth hypotheses were confirmed. However, Internet and mass media-based strategies could not moderate the impact of social leadership of rural people on their psychological resilience against natural environmental hazards (\u0026beta;=0.023; n.s.) and this result led to the rejection of the fourteenth hypothesis (Table 12; Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 12. Summary of testing hypotheses for model 2\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"17\" style=\"width: 66px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003eDirect hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Normative considerations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e15.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Self-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e13.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e4.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eNormative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e1.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSelf-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e3.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eAttitude -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e00.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 624px;\"\u003e\n \u003cp\u003eIndirect (mediation) hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt;\u0026nbsp;Normative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e1.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Self-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e3.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt;\u0026nbsp;Attitude -\u0026gt;\u0026nbsp;Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 624px;\"\u003e\n \u003cp\u003eIndirect (moderation) hypotheses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eNormative considerations -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSelf-efficacy -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eAttitude -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eH14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 330px;\"\u003e\n \u003cp\u003eSocial leadership -\u0026gt; Psychological resilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"6. Discussions, policy implications, limitations, and future perspectives","content":"\u003cp\u003eBased on the results of direct effects analysis, self-efficacy in structural models 1 and 2 had positive and significant effects on psychological resilience against natural environmental hazards. Self-efficacy refers to the extent to which villagers perceive themselves and their actions to be effective in better managing the risks of natural environmental hazards. It also refers to the perceived difficulty or ease of measures to deal with natural environmental hazards. This result is consistent with the results of other researchers such as Cahigas et al. (2023), Kumar (2021) and Rahimi-Feyzabad et al. (2022). Considering the positive impact of self-efficacy on psychological resilience against natural environmental hazards, it is suggested to increase the self-efficacy of villagers to deal with the risks of natural environmental hazards. This work can be done by the experts of hazard risk management programs in rural areas or the workers of other organizations such as the Ministry of Agriculture and Red Crescent Organization. Three major strategies are proposed to strengthen villagers\u0026apos; self-efficacy in the face of natural environmental hazards. First of all, it is necessary to help the villagers to become fundamentally and completely familiar with the most practical methods of dealing with the different natural environmental hazards and their impacts. This will help them to see and understand the results of following recommended protocols and methods of dealing with and preparedness for natural environmental hazards in a completely experimental way. This stage can be called the mastery stage of using methods to deal with natural environmental hazards. The second stage is observation. At this stage, the villagers should see examples of people around them who could use the strategies and measures of dealing with natural environmental hazards and in this way have helped to reduce the risks and better management of the hazards. It is recommended that the interventionists identify such people in advance and introduce them to the villagers during the implementation of hazard risk management programs. The third stage is persuasion. In fact, at this stage, the interventionists and field workers of the hazard risk management systems interact with the rural communities practically and discuss with them the way(s) to manage the hazards and their consequences. This process can take place in the form of forming discussion groups in the village environment or the form of virtual groups.\u003c/p\u003e\n\u003cp\u003eThe analysis of direct effects on psychological resilience against natural environmental hazards showed that the attitude towards the natural environmental hazards\u0026rsquo; risk management measures and the methods of dealing with it in both structural models 1 and 2 have positive and significant effects on psychological resilience against natural environmental hazards. This result indicates that having a suitable and favorable attitude towards natural environmental hazards\u0026rsquo; risk management measures and the methods of dealing with them can improve the psychological resilience of the villagers against the hazard. This result is aligned with the results of Ajzen (1991), Cahigas et al. (2023) and Kumar (2021). Considering the positive effect of attitude on psychological resilience against natural environmental hazards, it is suggested that educational and extensional programs be designed and implemented to improve villagers\u0026apos; attitudes towards natural environmental hazards\u0026rsquo; risk management measures. This work can be implemented by hazard risk management bodies or the Red Crescent Organizations that are directly connected with rural communities. In these programs, natural hazard risk management officials can talk about the benefits and effectiveness of certain methods of dealing with the hazards and share the experiences of other regions of the country (or the world) in the field of management and preparedness methods with the villagers. This can create a positive attitude toward the use of hazard risk management measures in the villages. With the formation of such an attitude, their psychological resilience against natural environmental hazards will improve.\u003c/p\u003e\n\u003cp\u003eThe results of the analysis of structural models 1 and 2 demonstrated that although the direct impact of social leadership on the psychological resilience of rural people against natural environmental hazards was not significant, its indirect effect (mediated by attitude and self-efficacy) on psychological resilience was positive and statistically significant. It means that the more the villagers have a higher social leadership spirit in natural hazards, the more their psychological resilience against natural environmental hazards increases. Findings similar to this result can be found in the results of Alizadeh and Sharifi (2021), Robertson et al. (2021), and Grote (2019). From this result, it can be concluded that one of the prerequisites for the psychological resilience of rural people against natural environmental hazards is the development of social leadership. In this regard, it is suggested to develop the skills of social leadership among members of rural communities. For the development of social leadership in the field of natural hazard risk reduction, it is recommended that special strategies be applied by practitioners of hazard risk management and recovery programs. First, mutual trust must be established among the members of the village community. This means that the interventionists of natural hazard risk reduction services and people should trust each other\u0026apos;s activities to manage the shocks. Second, collective identity should become another pillar of strengthening the social leadership of rural people in the field of hazard risk management. In other words, villagers and hazard risk management operators should consider successes and failures in dealing with the shock as the outcome of the collective work of all actors. This can lead to the formation of a collective identity in the first stage and improve social leadership among the members of rural communities in the second stage. Thirdly, to strengthen social leadership, it is suggested to identify the most effective communication channels among community members. During natural environmental hazards, the communication and influence of people in society are mostly through virtual communication channels. By identifying and activating these communication channels, people can experience a high quality of communication between themselves. In this way, people who have the ability of collective leadership can easily influence other members of the villages in the field of natural environmental hazards, and collective leadership and consequently psychological resilience against natural environmental hazards will be strengthened. Of course, it should be mentioned that the application of these strategies can directly improve the attitude and self-efficacy of villagers toward the management of natural environmental hazards. This issue is important because the two constructs of attitude and self-efficacy had positive effects on psychological resilience against natural environmental hazards according to the results of structural analysis. Moreover, these two constructs mediated the effect of social leadership on psychological resilience against natural environmental hazards.\u003c/p\u003e\n\u003cp\u003eThe results of the analysis of moderated effects in structural model 1 revealed that including livelihood strategies in TPB could successfully and positively moderate the impacts of attitude and social leadership of rural people on their psychological resilience against natural hazards. In other words, this result indicates that if programs and strategies to improve attitudes and strengthen social leadership in rural communities are combined with income and livelihood diversification projects, they can have positive synergistic effects on villagers\u0026rsquo; psychological resilience against natural environmental hazards. Thus, it is recommended that managers, decision-makers, implementers, and practitioners of sustainable livelihood development projects invest more in diversifying the income and livelihood sources of villagers. For example, due to transportation and sale restrictions for livestock and agricultural products during natural environmental hazards, many of them have tried to earn from other sources of income such as handicrafts and governmental subsidies. This matter is very important because of its contribution to the livelihood and economy of rural households during natural environmental hazards. Therefore, agents of livelihood development programs are suggested to have detailed plans for creating options for rural households to earn income and encouraging them to use them.\u003c/p\u003e\n\u003cp\u003eThe results of the moderated effects in inner model 2 showed that the inclusion of Internet and mass-media-based strategies in TPB could positively and significantly affect the impacts of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards. This result shows that it is better for any program related to changing attitudes, self-efficacy, and normative considerations in rural communities to be accompanied by the development of livelihood strategies that are based on the Internet and virtual space. In this regard, it is recommended that managers, decision-makers, executives, and operators of sustainable development projects in rural areas invest more in the potential of virtual space and mass media. For example, studies show that internet-based businesses have developed a lot in different regions of the world in recent years. This issue is visible even in some rural areas. However, it should not be forgotten that Internet-based businesses in rural areas are less developed than in urban areas. Therefore, many villagers are facing problems in selling and marketing their products due to Internet access. In such a situation, it is recommended that sustainable livelihood development programs in rural areas focus on training methods and platforms for selling and marketing agricultural and livestock products of villagers.\u003c/p\u003e\n\u003cp\u003eThe results of the research also demonstrated that the effect of incorporating Internet and mass-media-based strategies into TPB on increasing the explanation of resilience against natural environmental hazards is greater than the effect of incorporating livelihood strategies into it. In other words, when Internet and mass-media-based strategies are entered as moderators in the model, the explained variance of resilience against natural environmental hazards is about 0.542. Meanwhile, the explanation of resilience against natural environmental hazards is about 0.413 when we consider livelihood strategies as the moderator. This issue is important because it gives hazard risk management executives the knowledge that the effectiveness of using the Internet and mass-media-based strategies is higher than livelihood strategies. Therefore, these strategies should be prioritized.\u003c/p\u003e\n\u003cp\u003eThere were limitations in this research that explanation of which can pave the way for further research by future researchers. First of all, in the current research, psychological resilience against natural environmental hazards has been examined only from the psychological-social aspect. Future researchers can examine the determinants of the economic and environmental resilience of villagers. Second in the current research, due to the economic limitations and the time available to conduct the research, only the moderating effects of two types of strategies (livelihood and Internet and mass media-based strategies) were examined in the model. Nevertheless, future researchers may use other strategies according to the context in which they conduct their research. Third, in structural models 1 and 2, part of the variance of the psychological resilience against natural environmental hazards remained unexplained. This demonstrates that there are still constructs that can be used to extend TPB. Future researchers can use social, economic, and even structural constructs to develop theory.\u003c/p\u003e"},{"header":"7. Conclusion, limitations, and future research directions","content":"\u003cp\u003eThe general purpose of this study was to analyze the psychological resilience of villagers against natural environmental hazards through the lens of an extended TPB. The study ended with five key conclusions. First, incorporating social leadership into the TPB is a positive step that can strengthen normative considerations, self-efficacy, and attitudes (as key predictors of resilience against natural environmental hazards). Second, self-efficacy and attitude can improve the effectiveness of social leadership of rural people on psychological resilience against natural environmental hazards in TPB. Third, adding livelihood strategies to the model can significantly moderate the impacts of attitude and social leadership on psychological resilience against natural environmental hazards in TPB. Fourthly, adding Internet and mass media-based strategies to TPB can result in constructive moderation for the effects of normative considerations, self-efficacy, and attitude on psychological resilience against natural environmental hazards. Fifthly, the effect of including Internet and mass-media-based strategies in TPB on increasing the explanation of psychological resilience against natural environmental hazards is greater than the effect of including livelihood strategies in it. In general, it can be argued that this research contributes to the development of this theory by adding new hypotheses to the original TPB. In other words, incorporating these new constructs into the TPB and clarifying their relationships with the previous constructs helps to evolve the TPB and understand the mechanisms of behavior formation (psychological resilience against natural environmental hazards). In addition, the understanding of the relationships between these constructs and the mechanisms of their influence on each other ended with practical suggestions in the discussion section that can be put into practice by policy-makers, decision-makers, risk managers, and practitioners to improve the natural environmental hazards\u0026rsquo; preparedness and recovery.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e1. Originality \u0026amp; Plagiarism Free Work:\u003c/strong\u003e This manuscript is original, has not been published elsewhere, and does not contain any plagiarized material. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.\u003c/strong\u003e \u003cstrong\u003eExclusive Submission\u003c/strong\u003e: The manuscript is not under consideration by any other journal and will not be submitted elsewhere until the editorial decision is finalized. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Authorship \u0026amp; Consent:\u003c/strong\u003e All coauthors have contributed significantly to the research and writing process, and they have approved the final version of the manuscript for submission. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Ethical Compliance:\u003c/strong\u003e The research adheres to the highest standards of academic integrity and complies with all applicable ethical guidelines (e.g., data privacy, informed consent if involving human subjects). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Conflict of Interest:\u003c/strong\u003e No financial, professional, or personal conflicts of interest could influence the research outcomes or interpretations. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. Funding Disclosure:\u003c/strong\u003e No external funding was received for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Data Transparency:\u003c/strong\u003e All data presented are accurate, and any third-party materials (e.g., tables, figures) have been properly cited or permitted for reuse. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eI take full responsibility for the content of this manuscript and affirm that all information provided above is correct. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;DATA AVAILABILITY STATEMENT:\u003c/strong\u003e The datasets generated during and/or analysed during the current study are not publicly available but are available from the corresponding author on reasonable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003erequest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement and Consent to participate\u003c/strong\u003e: This research was approved by the Research Committee of the University of Tehran. Additionally, all participants provided informed consent prior to their involvement in the study. Also, at the beginning of the survey, the purpose of the research was thoroughly explained to participants to ensure they could provide informed consent and participate with full understanding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the use of OpenAI\u0026rsquo;s ChatGPT for language editing and clarity improvement during the preparation of this manuscript. No generative AI tools were used to create or generate any original content, data, or analysis presented in this paper. All findings, interpretations, and discussions are solely the result of the authors\u0026rsquo; own research and intellectual effort.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAhmmadi, P., Rahimian, M., \u0026amp; Movahed, R. G. (2021). Theory of planned behavior to predict consumer behavior in using products irrigated with purified wastewater in Iran consumer. 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Paediatric respiratory reviews, 5(4), 270-274. https://doi.org/10.1016/j.prrv.2004.07.011\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Psychological Resilience, Natural Environmental Hazard Management, Social Leadership, Vulnerability Mitigating Strategies, Sustainability Intervention","lastPublishedDoi":"10.21203/rs.3.rs-6965895/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6965895/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Many rural areas face significant challenges in managing natural environmental hazards due to their geographical location and limited access to formal disaster management resources. While rural communities often rely on indigenous knowledge and adaptive strategies, their capacity to respond effectively to hazards like droughts and floods can be constrained by socio-economic and infrastructural limitations. Measuring the psychological resilience of rural people against natural environmental hazards including droughts and floods and its predictors was the aim of this research. By reviewing theoretical perspectives explaining psychological resilience against natural environmental hazards, we aim to provide a framework for such a research program. To this end, the Theory of Planned Behavior was reconstructed using hypothesizing new mediated and moderated relationships. The study results were analyzed in two steps by testing two distinctive models with a comparative perspective. “Livelihood-based vulnerability mitigating strategies” and “internet and mass media-based vulnerability mitigating strategies” were used as the moderators of the effects of constructs including normative considerations, self-efficacy, attitude, and social leadership on the psychological resilience against natural environmental hazards in the first and second models, respectively. The results demonstrated that moderating effect of the Internet and mass-media-based strategies in Model 2 is greater than the moderating effect of livelihood-based mitigation strategies on psychological resilience in model 1. By presenting new practical implications and prioritizing the effectiveness of employing two different mitigation strategies, the results of the present study improve the operation of sustainable intervention programs.","manuscriptTitle":"The impact of Social leadership on psychological Resilience under Natural Environmental Hazards","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-29 11:07:59","doi":"10.21203/rs.3.rs-6965895/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":"b243443e-cf24-4339-8f2f-cb2a0cd41a0d","owner":[],"postedDate":"July 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-01T07:39:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-29 11:07:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6965895","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6965895","identity":"rs-6965895","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}