{"paper_id":"461b14a4-e9d5-47dc-bd3b-a9346a6323a8","body_text":"Influence Mechanisms of Multidimensional Risk Communication Strategies on Public Altruistic Protective Behavior: Evidence from Public Health Emergencies | 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 Influence Mechanisms of Multidimensional Risk Communication Strategies on Public Altruistic Protective Behavior: Evidence from Public Health Emergencies Yunpeng Xu, Shuanglei Wu, Linxiu Jiang, Shuning Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7506021/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Altruistic protective behavior is pivotal to community resilience during public health emergencies, yet prior research has rarely integrated how multidimensional risk communication strategies shape such behavior. Drawing on the protective action decision model and risk communication theory, we examine how information sources, communication content, narrative style, and communication media influence public altruistic protective behavior through risk perception, and whether trust in authoritative information sources conditions these effects. Methods We conducted a cross-sectional online survey in mainland China (October–December 2023) using stratified site selection across 11 provincial-level regions. After data cleaning, 1,417 valid responses were retained. Validated multi-item scales were adapted to the Chinese context. Analyses included hierarchical ordinary least squares regressions, mediation tests with bias-corrected bootstrapping (PROCESS Model 4; 5,000 resamples), and moderation tests (PROCESS Model 1; 5,000 resamples). Multicollinearity and common-method bias were assessed (VIFs < 5; Harman single-factor test). Results Each communication dimension—information sources, communication content, narrative style, and communication media—was positively associated with altruistic protective behavior,albeit with heterogeneous effect sizes across dimensions. Risk perception exerted a significant positive mediating effect between risk communication and public altruistic protective behavior. Trust in authoritative information sources negatively moderated the path from information sources to risk perception, indicating a “high-trust attenuation” pattern whereby strong trust in authoritative sources reduces the incremental impact of non-authoritative sources on perceived risk. Conclusions Findings extend PADM to the collective-action domain by specifying how multidimensional risk communication promotes altruistic protection via risk perception and how trust calibrates source effects. Practice implications include building coordinated, multi-source messaging matrices; tailoring high-precision content to audience segments; combining story-based and data-based narratives; and orchestrating cross-media delivery. Risk Communication Strategies Public Altruistic Protective Behavior Risk Perception Trust in Authoritative Information Sources Public Health Emergencies Figures Figure 1 Background In the \"VUCA era\", when public health emergencies occur frequently, governments face tension between limited resources and complex risks, making it difficult to address systemic challenges through unilateral efforts. Stimulating proactive public participation and achieving multiactor cogovernance has become a crucial pathway for managing public crises. As the ultimate bearer of risk policies, the public's response behaviors have great impacts on the effectiveness of risk governance. Whether government policies can achieve the expected goals hinges on effective risk communication that provides timely information and guidelines that stimulate accurate risk perceptions and corresponding protective behaviors in the public [1]. Risk has the dual attributes of objective reality and a subjective construct. Owing to differences in cognitive foundation, social experience and cultural background, the public often constructs subjective judgments on the basis of limited information that is not entirely consistent with the actual risk, thus affecting their behavioral responses. Therefore, in public health emergencies, high-quality risk communication between the government and the public is not only a technical issue of information transfer but also the core element in fostering correct perceptions and guiding behavioral choices. Multidimensional, perceptible, and situationally adapted risk communication strategies can effectively bridge the information gap between the government and society, stimulate altruistic protective behaviors, and promote a shift toward collaborative governance in risk management [ 2 , 3 ]. Although risk communication research has yielded substantial theoretical insights, most studies have focused primarily on the accuracy of information and the choice of communication channels, with limited attention given to how different communication strategies shape prosocial protective behaviors under conditions of high uncertainty [ 4 ]. Public responses to risk are not driven solely by individual rationality but are deeply embedded in cultural norms, collectivist values, and institutional trust, particularly in the Chinese context [ 5 ]. Under such influences, individuals are more likely to engage in altruistic protective behaviors, which willingly incur personal costs without direct benefits to enhance the safety of others and the broader community, thereby contributing to greater social resilience[ 6 ]. However, during public health emergencies, individuals often exhibit bounded rationality in risk decision-making, making their behavioral responses highly susceptible to external information cues. In this context, government-led risk communication strategies are pivotal in shaping public risk perception, trust in information, and subsequent protective behavior [ 7 ]. While some studies have noted the impact of risk communication on protective behavior, these studies are mostly confined to theoretical deductions and case analyses. They tend to provide macrolevel descriptions and overlook the differential effects of specific risk communication elements—such as communication content, narrative style, and information source—on public protective behavior, especially given the lack of dedicated research on altruistic protective behavior. Therefore, investigating the underlying mechanisms through which multidimensional risk communication strategies influence prosocial protective behaviors is imperative. We use the COVID-19 pandemic as a canonical public health emergency because it combines extreme uncertainty, frequent policy shifts, and an “infodemic” of competing messages—conditions that foreground the role of risk communication. Many COVID-19 protective actions (e.g., mask wearing, vaccination, and self-isolation) carry strong positive externalities, making altruistic protection both salient and observable. The event also produced abundant, time-stamped communication and behavior data, enabling rigorous empirical assessment of messaging effects. This study aims to investigate how multidimensional governmental risk communication strategies affect public altruistic protective behavior. Key findings will provide empirical support for designing public-oriented, precise, and effective risk communication and emergency mobilization. Method Theoretical background The protective action decision model (PADM) is a classic model for analyzing how individuals or groups make decisions about protective behaviors in unexpected risk situations [ 8 ]. The PADM emphasizes that public behavior in a risk context is jointly influenced by three types of external information: environmental cues, social cues, and risk warnings [ 9 ]. Environmental cues include physical phenomena at the time of a risk event, such as disaster sights or sounds. Social cues refer to information that individuals obtain by observing and imitating others’ behaviors. Risk warnings consist of risk information released by official or authoritative sources. This information, moderated by individual characteristics (e.g., cognitive level, social network, and resource endowment), triggers the public's three core perceptions of risk, i.e., threat perception, protective behavior perception, and stakeholder perception, which in turn affect protective behavior decisions. However, the original PADM model has a complex structure containing multiple psychological processes and behavioral pathways, and in reality, the public often does not go through all stages in full [ 8 ]. For example, in highly urgent situations, an authoritative and credible source of information may prompt individuals to act quickly, skipping many stages of information processing[ 10 ]. Therefore, this study simplifies and reconstructs the theory based on the PADM to present a clearer picture of the mechanism of risk communication strategies on altruistic protective behaviors. From the perspective of communication, risk communication is essentially an information dissemination activity that covers five elements: the communication source, communication content, communication media, audience and communication effect [ 11 ]. The source of communication refers to the provider of risk information, such as the government, media and surrounding people, which directly affects the level of public trust in the information. The communication content includes aspects such as the nature of the risk event, its severity, and protective measures, which determine the effectiveness and relevance of the information. In addition, information is presented in different ways, which affects the public's understanding and emotional response to the information. The communication media, as a channel of information diffusion, influences the coverage and immediacy of risk information. Finally, the communication effect is reflected in the audience's (i.e., the public's) understanding, attitudes, and protective behavioral responses to risk information [ 12 ]. In the context of public health emergencies, this study divides the above elements into four dimensions of risk communication strategies: the information source strategy, the communication content strategy, the narrative style strategy, and the communication media strategy. These strategies aim to influence the public's risk perception and thereby guide their decisions to engage in altruistic protective behavior. Additionally, considering the special circumstances of public health emergencies—for example, home quarantine—can impede interpersonal information sources, and the Chinese government, through strong scrutiny and control of other information sources during emergencies, usually possesses more timely first-hand information about crisis events, giving authoritative information sources a marked advantage over others[ 13 ]. Therefore, this study introduces the public's trust in authoritative information sources to explore how trust affects the relationship between risk communication strategies and risk perception. In summary, by integrating communication and behavioral theories, this study developed the causal pathway of “risk communication strategies → risk perception → altruistic protective behavior” in stimulating collective behaviors, taking into consideration the moderating role of “trust in authoritative information sources”. We systematically analyze how different communication strategies, through the interactive effects of public risk perception and trust levels, influence the public’s choices of altruistic protective behavior in a public health crisis context. The theoretical analytical framework is depicted in Fig. 1 . For information sources, this study draws upon the classification framework proposed by [ 14 ] and categorizes risk information sources in public health emergencies into three types on the basis of their authority, accessibility, and degree of personalization: Authoritative information sources (AIS), mass media information sources (MMIS), and interpersonal information sources (IIS). For communication content, guided by the typology of [ 15 ], this study identifies three key categories of risk-related content: epidemic information (EI), institutional response information (IRI), and preventive information (PI). With respect to the narrative strategy dimension, following narrative transportation theory [ 16 ] and prior empirical classifications [ 17 ], risk messages are classified into two types: story-based styles (SS) and data-based styles (DS). Finally, for the communication media dimension, using the typology of [ 18 ] and established survey instruments such as the China General Social Survey (CGSS), this study categorizes communication media into internet (IT), television (TV), telephone calls and SMS (TCSMS), radio broadcasts (RB), newspapers and printed materials (NPM), and face-to-face communication with public officials (F2F). For the purpose of clarity and conciseness in subsequent tables and models, all variables are abbreviated using their initial letters. Research hypotheses Risk communication and public altruistic protective behavior The core function of risk communication lies in reshaping the internal structure of risk events through strategic information delivery [ 19 ]. In the context of public health emergencies, this process is often constrained by asymmetrical bidirectional communication dynamics between governments and the public [ 20 ]. Effective risk communication not only mitigates coordination failures between political and societal actors but also enhances individual threat perceptions and the sense of social responsibility. More importantly, it facilitates a synergistic interaction between information provision and trust, thereby stimulating prosocial motivation and fostering the transformation of citizens into active agents of altruistic protective behavior, a critical determinant of effective pandemic response[ 21 ]. By integrating the PADM with the structural components of risk communication, this study identifies four key dimensions—the information source, communication media, message content, and narrative style—as observable variables. These dimensions are used to examine how multidimensional risk communication strategies influence public altruistic protective behaviors, forming the basis for the formulation of corresponding research hypotheses. (1) Information sources and altruistic public protective behavior Public exposure to diverse sources of information during public health emergencies stimulates differential protective behaviors. Studies have shown that the public exhibits varying degrees of attention to information: they first pay attention to who provides the information and judge its credibility before focusing on the content[ 22 ]. In other words, who presents the information is more important than the specific content of the information. Scholars have found that authoritative information sources backed by high-quality information and government endorsement are favored by citizens and significantly influence citizens’ compliance behaviors [ 23 ]. However, because communications from authoritative sources must undergo strict vetting and are not driven by “click-rate” incentives, they often respond slower and with relatively limited content during public health emergencies. The public thus turns to mass media sources to obtain information and adjust their protective behaviors accordingly[ 24 ]. Moreover, studies indicate that interpersonal information sources, which are often overlooked by scholars, can sometimes have a stronger influence on changing public behavior than traditional authoritative sources do, significantly enhancing health-protective behaviors[ 25 ]. Therefore, we propose the following hypotheses and research questions: H1: Information sources have a significant positive influence on public altruistic protective behavior. H1a: Authoritative information sources have a significant positive influence on public altruistic protective behavior. H1b: Mass media information sources have a significant positive influence on public altruistic protective behavior. H1c: Interpersonal information sources have a significant positive effect on public altruistic protective behavior. R1: Which information source has the greatest impact on public altruistic protective behavior during public health emergencies? (2) Communication content and public altruistic protective behavior Risk messages with well-designed content and appropriate communication can increase the likelihood that the public will adopt protective behaviors[ 26 ]. Risk communicators should disseminate information that the public feels they need to know, including but not limited to, descriptions of the risk, consequences, likelihood of exposure, and knowledge of protection [ 27 ]. Friedman noted that simple and easy-to-use instructional prevention messages are more likely to promote public behavior change [ 28 ]. Research has shown that crisis information released by public health organizations, as well as organizations’ own risk response information, can positively influence public protective behaviors [ 29 ]. Decisive and timely information from the government in the early stages of an outbreak can enhance public trust and sense of security, thereby increasing altruistic protective behavior[ 30 ]. Additionally, epidemic information released by government departments often involves both self-interested and altruistic elements, which can stimulate public altruistic protective intentions [ 31 ]. Therefore, we propose the following hypotheses and research question: H2: Communication content has a significant positive effect on public altruistic protective behavior. H2a: Epidemic information has a significant positive effect on public protective behavior. H2b: Institutional response information has a significant positive effect on public altruistic protective behavior. H2c: Preventive information has a significant positive effect on public altruistic protective behavior. R2: Which communication content has the greatest influence on public altruistic protective behavior during a public health emergency? (3) Narrative style and public altruistic protective behavior Narrative transportation theory posits that the essence of crisis communication is narration and that citizens' attitudes and behaviors in response to a crisis are strongly influenced by narrative styles. An effective narrative of a crisis event can help the public comprehend the issue (Yang et al., 2010), shape civic identification, influence information acceptance, and alter perceptual attitudes[ 13 ]. This, in turn, encourages citizens to undertake protective behaviors and altruistic actions [ 32 ]. People draw lessons from stories; a narrative (story-based) style helps the public comprehend and contextualize real-world problems, enhances their sense of immersion, and evokes resonance. Witnessing others’ painful experiences can arouse sympathy and empathy, prompting actions that benefit others[ 33 ]. During the COVID-19 pandemic, narrative storytelling was able to communicate the attribution of crisis responsibility and promote public protective behaviors[ 34 ]. However, other research suggests that, compared with a storytelling style, a statistical (data-driven) style—owing to its concreteness and verifiability—can be more persuasive; when information is presented in a data-centric manner, it is more likely to strengthen public altruistic protective behavior [ 17 ]. Accordingly, the research hypotheses and questions are formulated as follows: H3: Narrative style has a significant positive effect on public altruistic protective behavior. H3a: Story-based style has a significant positive effect on public altruistic protective behavior. H3b: Data-based style has a significant positive effect on public altruistic protective behavior. R3: Which narrative style has a greater influence on public altruistic protective behavior in public health emergencies? (4) Communication media and public altruistic protective behavior The media influences public attitudes and behaviors through information dissemination [ 35 ], and different media vary in terms of the richness of the information conveyed and their communication effects. Traditional media, with their high authority and broad reach, play a leading role in guiding public opinion and public behavioral compliance [ 36 ]. However, with the diversification of communication media, social media, which allows information exchange across time and space, has “decentralized” the discourse power of traditional media, profoundly affecting public prosocial behaviors [ 37 ]; however, the internet has a “double-edged sword” effect—information distortion and emotionalization tendencies—that can undermine the effectiveness of protective behaviors [ 38 ]. In addition, the role of face-to-face communication between street-level bureaucrats and citizens, as well as the telephone and SMS, has been underestimated in research. On the one hand, street-level bureaucrats (grassroots public officials) act as transmitters, interpreters, and implementers of information; their role, credibility, and communication style significantly influence citizen behavior [ 39 ]. On the other hand, telephone calls and text messages, characterized by high coverage and immediacy, allow citizens to proactively seek advice or report relevant crisis information and enable them to receive prompts from government agencies and adjust their behavior accordingly [ 40 ]. The use of multiple communication media promotes mutual connection, trust, and reciprocity among the public, provides more opportunities to understand others’ needs, and can significantly enhance altruistic behaviors such as donations and contributions [ 41 ]. We therefore propose the following hypotheses and research questions: H4: Communication media has a significant positive influence on public altruistic protective behavior. H4a: The internet has a significantly positive influence on public altruistic protective behavior. H4b: Telephones and SMS have a significant positive effect on public altruistic protective behavior. H4c: Television has a significant positive effect on public altruistic protective behavior. H4d: Radio broadcasts have a significant positive influence on public altruistic protective behavior. H4e: Newspapers and other printed materials have a significant positive influence on public altruistic protective behavior. H4f: Face-to-face communication with public officials has a significant positive effect on public altruistic protective behavior. R4: Which communication media has the greatest influence on public protective behavior during public health emergencies? In this study, risk communication is divided into four core dimensions, namely, the information source, communication content, narrative style, and communication media, and corresponding hypotheses are proposed for each. Therefore, we employ an entropy method (EM) and the CRITIC method to assign combined weights to these four dimensions, derive an overall risk communication index, and propose the following hypothesis: H5: Overall, risk communication has a significant positive effect on public altruistic protective behavior. The mediating role of risk perception The core mechanism of risk communication lies in influencing public risk cognition through information dissemination, thereby driving protective behaviors. Different dimensions of risk communication strategies can have differential effects on individual risk perceptions [ 42 ]. First, the authority, professionalism, and intimacy of the information source influence the public's judgment of information credibility, which shapes risk perception [ 43 ]. Second, the completeness and relevance of the communication content directly shape individuals' threat assessment and perceived controllability. Third, narrative style, as a form of information expression, can induce different effects depending on its presentation. A contextualized, concrete story-based style can enhance emotional immersion and resonance [ 44 ], whereas a clearly structured, quantifiable data-based style reinforces the public’s rational judgment of risk [ 17 ]. Finally, the communication media, as a vehicle for transmitting risk information, has attributes such as accessibility, interactivity, and social recognition that influence how deeply the public engages with information and how they process it, thereby affecting their risk perception [ 45 ]. Both protection motivation theory and the health belief model suggest that an individual's perception of health risks, including their susceptibility, severity, and coping efficacy, is a key psychological variable that predicts their protective behavior [ 46 , 47 ]. In public health emergencies, increased public risk perception can stimulate both personal and altruistic protective intentions[ 48 ]. In summary, risk perception is expected to mediate the relationship between risk communication and public altruistic behavior. Accordingly, we propose the following hypothesis: H6: Risk perception plays a mediating role between risk communication and public altruistic protective behavior. H6a: Risk perception plays a positive mediating role between information sources and public protective behavior. H6b: Risk perception positively mediates the relationship between communication content and public protective behavior. H6c: Risk perception positively mediates the relationship between narrative style and public protective behavior H6d: Risk perception positively mediates the relationship between the communication media and public protective behavior. Moderating role of trust in authoritative information sources The degree of public trust in information sources usually depends on the source's authority, professionalism, transparency, and historical reliability [ 49 ]. Differences in trust manifest in two ways: On the one hand, within the same population, there are varying levels of trust in different information sources. Studies have shown that digital natives have significantly greater trust in information released by authoritative entities such as the government and experts than in information from commercial and social media [ 50 ]. Although conventional wisdom holds that medical professionals are the most trusted health information source for the public, in reality, when facing health issues, the public often first turns to mass media sources such as the internet[ 51 ]. A lack of trust in authoritative information sources heightens the public’s uncertainty and anxiety, thereby amplifying their risk perception [ 52 ]. On the other hand, different groups exhibit structural differences in their levels of trust in the same information source. This primarily stems from individual traits, information literacy, and experiential differences, leading to cognitive disparities in processing and accepting the same risk information and thus yielding different risk perceptions [ 53 ]. Trust functions as a heuristic, implicit mode of information processing that helps reduce cognitive complexity and processing costs. In the context of a pandemic, individuals with higher levels of trust are more inclined to accept risk communication recommendations, whereas low levels of trust may reinforce anxiety and risk perception[ 54 ]. Therefore, the following research hypothesis is proposed: H7: Trust in authoritative information sources has a significant negative moderating effect on the relationship between information sources and risk perception. Procedure and participants This study was conducted between October and December 2023 via the Credamo platform via questionnaires, and all participants were informed and participated voluntarily. To maximize sample coverage and enhance representativeness and external validity, we adopted a stratified site-selection strategy that balanced Chinese economic zones (east/central/west) and latitudinal regions (north/central/south). Within 11 provincial-level administrative units—including Beijing Municipality, Shandong Province, Hubei Province, and the Guangxi Zhuang Autonomous Region—we selected two cities in each. One was economically developed, and the other was comparatively less developed. These served as the primary sampling sites. In total, 1,491 questionnaires were collected; after excluding invalid responses, 1,417 valid cases remained (validity rate = 95.04%). Among the samples, women accounted for 51.7%, and in terms of age distribution, middle-aged and young people were predominant, accounting for 32.1% of the 18–26-year group, 42.6% of the 27–39-year group, and 19% of the 40–60-year group. The proportion of nonagricultural Hukous was 51.5%, and 80.4% of the respondents assessed themselves as being healthy. Measures The measurement scales used in this study were all established internationally and adapted with appropriate semantic localization to fit the Chinese sociocultural context while adhering to the structure of the original scales. The means, standard deviations, reliability coefficients, and measurement items for each variable are presented in Tables 1 and 2 . Table 1 Measurement Items of the Variable Variables Dimension Item Reference Information Source (IS) AIS Do you get information about public health emergencies from government departments or experts? [ 14 ] MMIS Do you obtain information related to public health emergencies from mass media such as television, the internet, or various social media influencers? IIS Do you get information related to public health emergencies from your family and friends? Communication Content (CC) EI Do you focus on the source of the epidemic, the hazards, the number of deaths and injuries, etc.? [ 15 ] IRI Do you focus on information about how relevant government departments are preventing and handling the epidemic? PI Do you focus on knowledge and information about the prevention and treatment of the epidemic? Narrative Style (NS) SS Do you prefer to learn about the epidemic through specific people and stories? [ 17 , 55 ] DS Do you prefer graphical data to learn information about the epidemic? communication media (CM) IT Do you rely on the internet to search for and receive information related to the epidemic? [ 18 ] TCSMS Do you rely on telephone calls or SMS to receive epidemic-related information? TV Do you rely on television to search for and watch epidemic-related information? RB Do you rely on radio to listen to information about the epidemic? NPM Do you rely on newspapers or printed materials to search and read information about the epidemic? F2F Do you rely on face-to-face communication from government officials to get information about the epidemic? Trust in Authoritative Information Source (TIAIS) Do you feel that the information released by government and healthcare professionals is professional and accurate? [ 56 ] Do you feel that the information released by government and healthcare professionals is transparent and credible? Do you feel that the information released by government and healthcare professionals is complete and unbiased? Risk Perceived (RP) Do you believe the epidemic poses a serious threat to you and your family's physical and mental health? [ 57 , 58 ] Do you think it is likely that you and your family will get infected or be infected? Do you think it would have a significant negative impact on your and your family's life and work? Do you feel worry about the epidemic? Do you feel anxious about the epidemic? Do you feel fearful about the epidemic? Altruistic Protective Behavior (APB) Will you cease work and production as required by the government? [ 59 ] [ 60 ] Will you actively donate money or materials? Will you participate in online epidemic prevention volunteer services,? Will you participate in offline epidemic prevention volunteer services? Table 2 Properties of the main variables Variables Cronbach's α Mean SD Dimension IS 0.677 4.08 1.03 AIS 4.18 0.948 MMIS 3.7 1.056 IIS CC 0.842 4.3 0.826 EI 4.31 0.809 IRI 4.41 0.76 PI NS 0.496 3.4 1.016 SS 4.04 0.933 DS CM 0.852 4.27 0.869 IT 3.12 1.228 TCSMS 3.42 1.153 TV 3.05 1.306 RB 2.84 1.301 NPM 3.41 1.209 F2F TIAIS 0.901 3.75 0.977 RP 0.833 3.67 0.8 APB 0.892 3.87 0.901 Statistical analyses To test for common method bias, we conducted Harman’s single-factor test. The results showed that in an unrotated principal component analysis, there were 14 factors with eigenvalues greater than 1, and the first factor accounted for 18.59% of the variance, which was well below the 40% threshold. This suggests that serious common method bias was not present. Considering that the four constituent dimensions of risk communication may have different importance in public cognition, we applied a weighting approach that combines the entropy and CRITIC methods to assign weights to the four dimensions (information source, communication content, narrative style, and communication media) and constructed a composite measurement index. The weighted composite score reflects the overall frequency of public exposure and reliance on each type of communication strategy in the context of a public health emergency. The weighting results are shown in Table 3 . In addition, for the measurements of risk perception, trust in authoritative information sources, and altruistic protective behavior, we used the arithmetic mean of the item scores on each scale as the overall score; higher scores indicated a higher level of the corresponding variable. All scale items were scored on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree), with higher scores indicating a greater degree of agreement with that dimension. SPSS 26.0 was used to conduct multiple linear regression analysis of the effect of risk communication on altruistic protective behavior. Stepwise regression analyses were conducted to test the mediating effect of risk perception. The PROCESS macro (Model 1) was used to test the moderating effect of trust in authoritative information sources (5,000 bootstrap samples, 95% confidence interval). Table 3 Risk Communication Dimensional Profiles Variable Dimension EM CRITIC CW Dimension EM CRITIC CW RC IS 22.20% 25.99% 24.095% AIS 33.05% 35.94% 34.50% MMIS 25.69% 31.35% 28.52% IIS 41.26% 32.71% 36.99% CC 15.11% 15.95% 15.53% EI 36.79% 33.59% 35.19% IRI 34.51% 32.53% 33.52% PI 28.7% 33.88% 31.29% NS 23.20% 24.49% 23.845% SS 58.41% 50% 54.21% DS 41.59% 50% 45.80% CM 39.49 35.57% 36.53% TCSMS 18.36% 14.75% 16.56% TV 12.76% 14.97% 13.87% RB 23.19% 13.89% 18.54% PM 27.1% 13.84% 20.47% F2F 14.61% 15.55% 15.08% ITS 3.98% 27% 15.49% Results Relationship between risk communication and public altruistic protective behavior Risk communication had a significant positive effect on public altruistic protective behavior (β = 0.648, p < 0.01), supporting H5 (Table 4 ). With respect to the control variables, gender and health status had consistently significant effects on altruistic protective behavior. Specifically, women were more willing than men to take protective actions, and individuals with better self-rated health were more willing to take protective actions. Age and education level also had significant positive effects on altruistic protective behavior: older and more highly educated members of the public were more willing to engage in altruistic protective behavior. This may be because higher education and older age correspond to having undergone more socialization and education processes, leading to a stronger sense of responsibility and greater appreciation—from life experience and knowledge—of the importance of epidemic prevention, thereby increasing the willingness to act altruistically. Interestingly, Hukou registration type had a significant negative effect on altruistic protective behavior: compared with those with nonagricultural (urban) Hukou, individuals with agricultural (rural) Hukou were more willing to take altruistic protective actions. This could be influenced by the “acquaintance society” social context of rural areas, where people tend to rely more on social capital and maintain closer ties with each other, forming strong social networks that foster higher levels of mutual aid, cooperation, and altruistic spirit. Table 4 Effects of Risk Communication and Information Sources on Public Altruistic Protective Behavior Variable Altruistic protective behavior Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Constant 3.951 *** 1.315 *** 3.639 *** 2.84 *** 2.896 *** 3.136 *** 2.498 *** Gender -0.167 *** -0.074 -0.108 * -0.102 * -0.074 -0.09 -0.082 Age 0.069 ** 0.088 *** 0.119 *** 0.101 *** 0.121 *** 0.127 *** 0.108 *** Occupation -0.15 -0.034* -0.03 -0.025 -0.027 -0.034 -0.026 Hukou -0.061 -0.182* -0.238 *** -0.241 *** -0.235 *** -0.244 *** -0.241 *** Education -0.061 *** -0.029 *** -0.109 *** -0.093 ** -0.098 ** -0.092 ** -0.086 ** Health status 0.127 *** 0.06 * 0.143 *** 0.111 *** 0.121 *** 0.118 *** 0.1 ** RC 0.648 *** AIS 0.216 *** 0.172 *** MMIS 0.182 *** 0.089 ** IIS 0.135 *** 0.039 R 2 0.06 0.255 0.078 0.137 0.114 0.102 0.149 F 12.867 *** 60.152 *** 16.987 *** 28.017 *** 22.568 *** 19.933 *** 24.69 *** Influence of information sources on public altruistic protective behavior As shown by Models 4, 5, and 6 in Table 4 , authoritative information sources (β = 0.216, p < 0.01), mass media information sources (β = 0.182, p < 0.01), and interpersonal information sources (β = 0.135, p < 0.01) all had significant positive effects on public altruistic protective behavior. This supports H1, H1a, H1b, and H1c. The results indicate that, in terms of influence on altruistic protective behavior, the sources rank as follows: authoritative information source > mass media information source > interpersonal information source. This finding highlights that authoritative information sources consistently play a pivotal role in driving citizens’ protective behavior, addressing R1. Moreover, considering the diverse nature of public risk information sources during a public health crisis, we included all three types of information sources in a single regression model (Model 7 in Table 3 ) for further analysis. The results show that mass media sources (β = 0.089, p < 0.01) and authoritative sources (β = 0.172, p < 0.01) still significantly influence public altruistic protective behavior when considered together, but the influence of interpersonal information sources is no longer significant when they are considered simultaneously. Influence of communication content on public altruistic protective behavior As shown in Table 5 , epidemic information (β = 0.276, p < 0.01), institutional response information (β = 0.352, p < 0.01), and preventive information (β = 0.317, p < 0.01) all had significant positive effects on public altruistic protective behavior. This supports H2, H2a, H2b, and H2c. The results indicate that the strength of influence on altruistic protective behavior is in the following order: institutional response information > preventive information > epidemic information, which answers R2. These three types of content often appear together during a public health crisis, for example, when government departments publicly release outbreak handling procedures alongside personal protective policies. We included all three content types in a single regression model for a comparative analysis. The results show that institutional response information (β = 0.247, p < 0.01) and preventive information (β = 0.113, p < 0.01) still have significant impacts on public altruistic protective behavior, whereas the effect of epidemic information is no longer significant when all content types are considered simultaneously. Table 5 Effects of Communication Content Dimensions on Public Altruistic Protective Behavior Variable Altruistic protective behavior Model 1 Model 2 Model 3 Model 4 Model 5 Constant 3.639 *** 2.684 *** 2.363 *** 2.423 *** 2.116 *** Gender -0.108 * -0.096 * -0.068 -0.077 -0.067 Age 0.119 *** 0.096 ** 0.092 ** 0.09 ** 0.085 ** Occupation -0.03 -0.027 * -0.027 -0.023 -0.025 Hukou -0.238 *** -0.26 *** -0.267 *** -0.266 *** -0.273 *** Education -0.109 *** -0.115 *** -0.107 *** -0.11 *** -0.109 *** Health status 0.143 *** 0.11 *** 0.09 ** 0.109 *** 0.087 ** EI 0.276 *** 0.056 IRI 0.352 *** 0.247 *** PI 0.317 *** 0.113 ** R 2 0.078 0.14 0.174 0.147 0.183 F 16.987 *** 28.704 *** 37.134 *** 30.433 *** 31.485 *** Influence of narrative style on public altruistic protective behavior As shown in Table 6 , both the story-based style (β = 0.287, p < 0.01) and the data-based style (β = 0.205, p < 0.01) had significant positive effects on public altruistic protective behavior, supporting H3, H3a, and H3b. When comparing the effects of the two narrative styles, we found that the story-based style had a stronger influence on altruistic protective behavior than the data-based style. Furthermore, when both narrative styles are included in the same regression model, both remain significant, and the standardized regression coefficient for the story-based style remains higher than that for the data-based style, indicating that narrative storytelling has a more pronounced guiding effect on public behavior. Table 6 Effects of Narrative Style Dimensions on Public Altruistic Protective Behavior Variable Altruistic protective behavior Model 1 Model 2 Model 3 Model 4 Constants 3.639 *** 2.455 *** 2.968 *** 2.23 *** Gender -0.108 * -0.063 -0.09 * -0.062 Age 0.119 *** 0.097 ** 0.116 *** 0.098 *** Occupation -0.03 -0.028 -0.038 * -0.033 Hukou -0.238 *** -0.183 *** -0.241 *** -0.192 *** Education -0.109 *** -0.063 * -0.114 *** -0.072 * Health status 0.143 *** 0.109 *** 0.122 *** 0.102 ** SS 0.287 *** 0.25 *** DS 0.205 *** 0.116 *** R 2 0.078 0.174 0.122 0.186 F 16.987 *** 36.99 *** 24.5 *** 35.791 *** Influence of communication media on public altruistic protective behavior Table 7 shows that the Internet (β = 0.219, p < 0.01), telephone and SMS (β = 0.224, p < 0.01), television (β = 0.248, p < 0.01), radio broadcasts (β = 0.242, p < 0.01), newspapers (β = 0.208, p < 0.01), and face-to-face communication with public officials (β = 0.231, p < 0.01) all had significant positive effects on altruistic protective behavior. This finding supports H4 ,H4a, H4b, H4c, H4d, H4e, and H4f. Considering the individual impact coefficients of each medium, the influence ranks are as follows: Television > Radio > Face-to-face (officials) > Telephone & SMS > Internet > Newspapers, which answers research question R4. When we entered multiple communication media into a single regression model, we found that the Internet, television, radio, telephone and SMS, and face-to-face communication with officials still significantly influenced public altruistic protective behavior, whereas the influence of newspapers was no longer significant in the full model. In Model 8, traditional media, such as television and radio, had a strong positive influence, indicating that they have significant guiding power for public protective behavior in a single context. However, in the full model that included multiple media, the Internet had the highest coefficient of influence, suggesting that the Internet holds a dominant position in dissemination and enjoys a higher frequency of use and degree of reliance in the information environment. This difference may stem from the overlapping usage of different media and differences in cognitive primacy. In other words, the Internet is not only a platform for initially issuing and receiving information but also serves as a channel for reprocessing and verifying information from other media. As a result, in a communication environment where multiple information sources coexist, the Internet wields a stronger influence on guiding behavior. Table 7 Effects of Communication Media Dimensions on Public Altruistic Protective Behavior Variables Altruistic protective behavior Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Constant 3.639 *** 2.795*** 2.843 *** 2.717 *** 2.692 *** 2.893 *** 2.62 *** 1.81 *** Gender -0.108 * -0.068 -0.134 *** -0.099 * -0.121 ** -0.144 ** -0.111 * -0.09 * Age 0.119 *** 0.133 *** 0.104 *** 0.098 *** 0.086 ** 0.096 ** 0.101 *** 0.096 *** Occupation -0.03 -0.028 -0.031 -0.033 -0.036 * -0.037 * -0.027* -0.031 Hukou -0.238 *** -0.246 *** -0.185 *** -0.204 *** -0.14 ** -0.194 *** -0.178 *** -0.152 ** Education -0.109 *** -0.121 *** -0.056 -0.057 -0.028 -0.04 -0.041 -0.028 Health status 0.143 *** 0.124 *** 0.104 ** 0.102 ** 0.107 *** 0.113 *** 0.118 *** 0.083 ** Internet 0.219 *** 0.143 *** TCSMS 0.224 *** 0.055 * TV 0.248 *** 0.079 ** RB 0.242 *** 0.118 *** NPM 0.208 *** -0.014 F2F 0.231 *** 0.085 *** R 2 0.078 0.121 0.161 0.169 0.179 0.154 0.163 0.232 F 16.987 *** 24.266 *** 33.888 *** 35.849 *** 38.471 *** 32.155 *** 34.346 *** 32.603 *** Mediating effect of risk perception As shown in Table 8 , risk communication had a significant positive effect on risk perception (β = 0.477, p < 0.01), and risk perception had a significantly positive effect on public altruistic protective behavior (β = 0.168, p < 0.01). This finding indicates that risk perception plays a significantly positive mediating role in the pathway by which risk communication affects public altruistic protective behavior, supporting H6. Specifically, information source (β = 0.249, p < 0.01), communication content (β = 0.546, p < 0.01), narrative style (β = 0.272, p < 0.01), and communication media (β = 0.267, p < 0.01) each had a significant positive effect on risk perception, which in turn had a significant positive effect on public altruistic protective behavior. These findings suggest that H6a, H6b, H6c, and H6d are supported. Table 8 Risk Perception Mediation Between Risk Communication and Altruistic Protective Behavior Variable Risk perception Altruistic protective behavior Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Constant 2.451 *** 3.211 *** 2.835 *** 3.145 *** 3.138 *** 1.149 *** 1.989 *** 1.749 *** 1.807 *** 1.745 *** Gender -0.069 -0.066 -0.056 -0.063 -0.102 * -0.069 -0.065 -0.058 -0.057 -0.109 Age -0.064 * -0.042 -0.071 ** -0.054 * -0.061 * 0.092 *** 0.125 *** 0.093 ** 0.109 *** 0.097 *** Occupation 0.006 0.009 0.014 0.005 0.006 -0.034 * -0.031 ** -0.026 -0.036 * -0.035 * Hukou 0.003 -0.042 -0.069 -0.012 0.018 -0.182 * -0.236 *** -0.265 *** -0.200 *** -0.156 ** Education -0.008 -0.045 -0.066 * -0.047 * -0.005 -0.028 *** -0.076 * -0.100 ** -0.075 ** -0.015 Health status -0.062 * -0.039 -0.047 -0.031 * -0.038 0.064 * 0.104 ** 0.095 ** 0.106 *** 0.091 ** RC 0.477 *** 0.616 *** RP 0.068 ** 0.167 *** 0.126 *** 0.139 *** 0.115 *** IS 0.249 *** 0.250 *** CC 0.546 *** 0.006 *** NS 0.272 *** 0.336 *** CM 0.267 *** 0.370 *** R 2 0.135 0.072 0.111 0.084 0.094 0.255 0.156 0.191 0.196 0.228 F 27.565 *** 13.728 *** 21.886 *** 16.191 *** 18.181 *** 60.152 *** 30.097 *** 36.858 *** 38.194 *** 46.299 *** Moderating effect of trust in authoritative information sources. Table 9 presents the results of the moderation analyses. The results indicate that trust in authoritative information sources has a significant negative moderating effect on the “information source → risk perception” path (interaction term β=-0.060, p < 0.05). In other words, when the public’s level of trust in authoritative sources is high, the positive impact of information sources on risk perception is weakened. This finding suggests that trust does not always amplify the effectiveness of information; its role is context dependent and complex. Further subgroup (interaction) analysis revealed that the moderating effect of authoritative source trust on the “authoritative source → risk perception” path was not significant (β=-0.029, p > 0.05). However, for the paths of “mass media source → risk perception” and “interpersonal source → risk perception,” trust in authoritative sources exhibited significant negative moderation (interaction terms β= -0.058 and β= -0.048, respectively, both p < 0.05). Therefore, H7 is supported. This result indicates that when the public has high trust in authoritative information sources, information from nonauthoritative sources (such as social media and interpersonal networks) has a reduced marginal effect on their risk perception. In this context, trust exhibits an “information selectivity suppression effect,” meaning that high-trust functions as a filter that diminishes the uptake of information from other sources. This phenomenon aligns with the heuristic information-processing pathway: under conditions of high trust, individuals tend to make quick judgments on the basis of their existing trust, thereby reducing deep processing of external information. This also explains why, when authoritative institutions are highly trusted, nonauthoritative information sources find it difficult to further increase the public’s risk perception. Table 9 Moderating effect test of trust in authoritative information sources on the influence of information sources and risk perception Variable Risk perception Model 1 Model 2 Model 3 Model 4 Constant 2.369 *** 3.260 *** 2.488 *** 2.837 *** Gender -0.066 * -0.087 * -0.063 ** -0.076 Age -0.041 -0.052 -0.042 *** -0.036 Occupation 0.009 0.012 0.011 0.005 Hukou -0.050 -0.038 -0.040 -0.049 Education -0.049 -0.059 -0.056 -0.047 Health status -0.031 -0.018 -0.024 -0.034 IS 0.462 *** AIS 0.220 *** MMIS 0.378 *** IIS 0.322 *** TIAIS 0.238 ** 0.134 * 0.283 ** 0.220 ** IS* TIAIS -0.060 ** AIS* TIAIS -0.029 MMIS* TIAIS -0.058 ** IIS*TIAIS -0.048 ** R 2 0.077 0.081 0.065 0.059 F 11.756 *** 12.444 *** 9.809 *** 8.766 *** Discussion Direct effects of risk communication on public altruistic protective behavior The findings show that information sources can exert a significant positive effect on public altruistic protective behavior, with authoritative information sources consistently playing a central role; their influence is significantly greater than that of mass media or interpersonal sources. Through an institutional trust anchoring effect, authoritative sources act as the core drivers of behavior [ 61 ], whereas mass media maintain a secondary influence due to their agenda-setting power. In an environment where multiple information sources coexist, mass media sources retain a robust influence (β = 0.089, p < 0.01), reflecting that in the modern digital era, the agenda-setting capacity of social media has become deeply embedded in the risk communication network[ 62 ]. In contrast, the marginal utility of interpersonal communication has been structurally compressed by changes in the media ecosystem, rendering its effect insignificant and weakening its supplementary role. These results not only reveal a gradient of influence — authoritative > mass media > interpersonal — but also highlight that in pandemic crisis contexts, the public prioritizes information sources that strike a balance between credibility and accessibility when processing information and making decisions [ 37 ]. This finding indicates that authoritative sources remain the critical trust foundation for eliciting altruistic behavior, whereas mass media need to strike a balance between expanding reach and maintaining content professionalism. Epidemic information, institutional response information, and preventive information all have significant positive effects on public altruistic protective behavior. However, when all three types of content are included together in the regression model, the effect of epidemic information is no longer significant. This result suggests that different types of information interact and carry different relative weights in influencing public protective behavior. From a social cognition theory perspective, the formation of individual behavior is influenced not only by objective information stimuli but also by the personal subjective interpretation of the context and cognitive processing of the information[ 63 ]. In public health emergencies, information released by authoritative institutions not only serves the functional role of communicating epidemic risk but also symbolizes the state’s governance capacity. The clarity and transparency of such institutional response information can enhance public identification with and compliance with government directives, thereby increasing the likelihood of engaging in altruistic protective behaviors [ 64 ]. Moreover, altruistic protective behavior—as a morally driven form of public action—typically requires individuals to exhibit a heightened sense of responsibility and collective consciousness. In this process, compared with the objective description of epidemic information, the government's demonstrated competence in crisis management through risk communication more effectively triggers prosocial behavioral responses among the public. Both narrative styles and data-based narrative styles can significantly and positively influence public altruistic protective behavior, with the effect of narrative style being more prominent. To some extent, this result echoes the basic judgment of narrative transportation theory on the effectiveness of crisis information dissemination; that is, narratives are not only a medium for transmitting facts but also an important path for stimulating emotional resonance and guiding the public's attitudes and behaviors [ 65 ]. Although some studies have emphasized that data-based information is more persuasive because of its objectivity, verifiability, and intuition [ 66 ], in highly uncertain situations such as public health emergencies, narratives are more effective in evoking emotional recognition and risk empathy through the construction of figurative scenarios and characters, thus stimulating altruistic behavior. Multiple communication media outlets each have a significant positive effect on public altruistic protective behavior, but in the multivariate regression model, the influence of newspapers becomes nonsignificant. This result can be interpreted in two ways. First, a collinearity diagnosis indicates that there is no severe multicollinearity among the communication media variables (all VIFs < 5, with VIF_max = 3.319), ruling out statistical interference from high overlap between predictors. Second, from the perspective of media development trends, the influence of traditional media on public behavior is gradually waning in the digital environment. Compared with print media, television and radio—due to their regulated content and censorship mechanisms—are more readily accepted by the public and are more likely to gain their identification[ 67 ]. In contrast, the Internet and other digital media grant the public greater agency, enabling people to filter and acquire information according to their own needs, and have become the dominant media form influencing public protective behavior[ 68 ] (Yoo, 2016). Therefore, the impact of media choice on public altruistic protective behavior is undergoing a structural shift characterized by digital media at the core and a differentiation of traditional media functions. Indirect effects of risk communication on public altruistic protective behavior The results of the mediation analysis demonstrate that risk perception plays a significant positive mediating role in the pathway through which risk communication affects public altruistic protective behavior. This finding corroborates the classic “cognitive–attitude–behavior” sequence in behavior change mechanisms, indicating that public risk perception serves as a bridge between information reception and behavioral conversion. The strong consistency and coherence observed between risk perception and protective behavior suggest that citizens are more likely to engage in socially responsible altruistic actions when they perceive higher levels of risk. Therefore, when designing crisis communication strategies, governments should emphasize appropriately stimulating the public’s level of risk perception, thereby promoting the occurrence of altruistic behavior. Trust in authoritative information sources has a significant negative moderating effect on the relationship between information sources and risk perception. Further detailed analysis indicates that this moderating effect is present mainly in the pathways for “mass media information sources” and “interpersonal information sources” but is not significant in the “authoritative information source” pathway. This suggests that trust in authoritative sources has an exclusive reinforcement effect: under conditions of high trust, the public tends to rely more on authoritative channels, thereby reducing their sensitivity to and acceptance of information from nonauthoritative sources, which weakens the influence of mass media and interpersonal communication on risk perception [ 69 ]. This finding offers a nuanced amendment to existing risk communication theory. Traditional views tend to emphasize that trust enhances the effectiveness of information dissemination. Our study, however, further reveals that trust not only is an “additive factor” for information adoption but can also act as an “interfering variable” for other information pathways. Through a cognitive filtering mechanism, trust influences the public’s willingness to accept and deeply process diverse information. This mechanism can be regarded as an “information focus effect”, stemming from the dual factors of the limited nature of risk cognition resources and the path dependence of trust. Conclusion On the basis of the PADM and risk communication theory, this study systematically explored the path and mechanism of the influence of multidimensional risk communication strategies on public altruistic protective behaviors during public health emergencies. The findings show that risk communication strategies across all dimensions—information sources, communication content, narrative styles, and communication media—have significant impacts on public altruistic protective behavior, with risk perception serving as a mediating bridge. Moreover, trust in authoritative information sources significantly moderates the relationship between information sources and risk perception, resulting in a ‘high-trust attenuation effect’, meaning that at high levels of trust, the marginal impact of information sources on risk perception is weakened. These insights enrich the theoretical understanding of the structure and mechanisms of risk communication in crisis contexts, extend the applicability of the PADM to the domain of altruistic behavior, and underscore the pivotal role of information trust as an intervention point in the digital era. From a practical perspective, this study offers the following policy recommendations for government and public health authorities to enhance communication strategies during public health emergencies. First, establish a diversified and interactive structure of information sources. Governments should actively integrate authoritative media, mass media platforms, and interpersonal communication networks to improve the efficiency and reach of information dissemination, thereby reducing dependence on any single source. Second, differentiated content delivery and tailored messaging of risk information should be promoted. Communication materials should be adapted to the informational preferences and psychological profiles of different target groups to enhance message persuasiveness and actionability, thereby bridging the gap between risk perception and behavioral response. Third, the strategic combination of narrative styles should be optimized. Integrating the credibility of data-based messaging with the emotional appeal of narrative storytelling can enhance audience identification, foster a sense of personal responsibility, and increase behavioral intention. Fourth, media synergy and cross-platform coordination should be strengthened. Greater alignment between traditional media and digital platforms should be encouraged to generate a multichannel amplification effect, increasing both the reach and retention of risk-related messages in critical moments. limitations This study has several limitations. First, we collected data through a questionnaire survey; although the sample covers a wide range and is representative, self-reported data can contain subjective bias. Second, while we examined the relationship between risk communication strategies and altruistic behavior, the causal chain linking the two requires more complex experimental designs or longitudinal studies for validation. Future research can be expanded in the following directions: (1) incorporate behavior tracking or experimental methods to strengthen causal inferences; (2) include additional psychosocial factors such as emotional variables and social norms to broaden the theoretical boundaries and empirical depth of altruistic protective behavior research. Abbreviations PADM Protective Action Decision Model EM Entropy Method CW Combined Weight. IS Information Source AIS Authoritative information sources MMIS Mass Media Information Sources IIS Interpersonal Information Sources CC Communication Content EI Epidemic Information IRI Institutional Response Information PI Preventive Information NS Narrative Style DS Data-based Styles SS Story-based Styles CM Communication Media IT Internet TCSMS Telephone Calls and SMS TV Television RB Radio Broadcasts NPM Newspapers and Printed Materials F2F Face-to-Face Communication with Public Officials Declarations Ethics approval and consent to participate This study was performed in line with the principles of the Declaration of Helsinki and has received ethical approval from theMedical Ethics Committee of Guangxi University (No:GXU-2025-089) . Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable Data availability The dataset generated and analyzed during the current study is available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests. Funding This work was supported by the Education Department of Guangxi Zhuang Autonomous Region under Grant No. 2025KY0003; and by the Key Research Base of Humanities and Social Sciences of Universities in Guangxi Zhuang Autonomous Region：Regional Social Governance Innovation Research Center under Grant No. 202501100. Authors' contributions Yunpeng Xu and Shuning Wang designed this work. Linxiu Jiang collected the data. YunpengXu, Shuanglei Wwang and Shuning Wangperformed the statistical analysis and wrote the draft manuscript.YunpengXu edited the manuscript. All authors approved the final version of the manuscript. Acknowledgements We would like to thank Shuai Li for his statistical support. References Hearit KM, Courtright JL: A social constructionist approach to crisis management: Allegations of sudden acceleration in the Audi 5000. COMMUN STUD 2003, 54(1):79-95. http://doi.org/10.1080/10510970309363267 Eiser J, Bostrom A, Burton I, Johnston D, McClure J, Paton D, van der Pligt J, White M: Risk interpretation and action: A conceptual framework for responses to natural hazards. INT J DISAST RISK RE 2012, 1:5-16.http://doi.org/10.1016/j.ijdrr.2012.05.002 Renn O: The role of risk perception for risk management. RELIAB ENG SYST SAFE 1998, 59(1):49-62.https://doi.org/10.1016/S0951-8320(97)00119-1 Van Bavel J, Baicker K, Boggio P, Capraro V, Cichocka A, Cikara M, Crockett M, Crum A, Douglas K, Druckman J et al : Using social and behavioural science to support COVID-19 pandemic response. NAT HUM BEHAV 2020, 4(5):460-471.http://doi.org/10.1038/s41562-020-0884-z Jordan J, Yoeli E, Rand D: Don't get it or don't spread it: comparing self-interested versus prosocial motivations for COVID-19 prevention behaviors. SCI REP-UK 2021, 11(1):20222. http://doi.org/10.1038/s41598-021-97617-5 Habib M, Kaur P, Sharma V, Talwar S: Analyzing the food waste reduction intentions of UK households. A Value-Attitude-Behavior (VAB) theory perspective. J RETAIL CONSUM SERV 2023, 75.http://doi.org/10.1016/j.jretconser.2023.103486 Heydari S, Zarei L, Sadati A, Moradi N, Akbari M, Mehralian G, Lankarani K: The effect of risk communication on preventive and protective Behaviours during the COVID-19 outbreak: mediating role of risk perception. BMC PUBLIC HEALTH 2021, 21(1):54. http://doi.org/10.1186/s12889-020-10125-5 Lindell M, Mumpower J, Huang S, Wu H, Samuelson C, Wei H: Perceptions of protective actions for a water contamination emergency. J RISK RES 2017, 20(7):887-908. http://doi.org/10.1080/13669877.2015.1121906 Terpstra T, Lindell M: Citizens’ Perceptions of Flood Hazard Adjustments An Application of the Protective Action Decision Model. ENVIRON BEHAV 2013, 45:993-1018. http://doi.org/10.1177/0013916512452427 Gladwin C, Gladwin H, Peacock W: Modelling Hurricane Evacuation Decisions With Ethnographic Method. International journal of mass emergencies and disasters 2001, 19:117-143. http://doi.org/10.1177/028072700101900201 Lasswell HD: The structure and function of communication in society. In L. Bryson (Ed.), The communication of ideas . New York: Harper and Row.; 1948. Rimal R, Real K: Perceived risk and efficacy beliefs as motivators of change: Use of the risk perception attitude (RPA) framework to understand health behaviors. HUM COMMUN RES 2003, 29(3):370-399.http://doi.org/10.1111/j.1468-2958.2003.tb00844.x Wojcieszak M, Kim N: How to Improve Attitudes Toward Disliked Groups. COMMUN RES 2016, 43:785-809.http://doi.org/10.1177/0093650215618480 Griffin R, Dunwoody S, Zabala F: Public reliance on risk communication channels in the wake of a Cryptosporidium outbreak. RISK ANAL 1998, 18(4):367-375. http://doi.org/10.1111/j.1539-6924.1998.tb00350.x DeYoung SE, Sutton JN, Farmer AK, Neal D, Nichols KA: “Death was not in the agenda for the day”: Emotions, behavioral reactions, and perceptions in response to the 2018 Hawaii Wireless Emergency Alert. INT J DISAST RISK RE 2019, 36:101078. http://doi.org/https://doi.org/10.1016/j.ijdrr.2019.101078 Yang S, Kang M, Johnson P: Effects of Narratives, Openness to Dialogic Communication, and Credibility on Engagement in Crisis Communication Through Organizational Blogs. COMMUN RES 2010, 37(4):473-497.http://doi.org/10.1177/1077699017750360 Zebregs S, van den Putte B, Neijens P, de Graaf A: The Differential Impact of Statistical and Narrative Evidence on Beliefs, Attitude, and Intention: A Meta-Analysis. HEALTH COMMUN 2015, 30(3):282-289.http://doi.org/10.1080/10410236.2013.842528 Chan MS, Winneg K, Hawkins L, Farhadloo M, Jamieson KH, Albarracín D: Legacy and social media respectively influence risk perceptions and protective behaviors during emerging health threats: A multi-wave analysis of communications on Zika virus cases. SOC SCI MED 2018, 212:50-59. https://doi.org/10.1016/j.socscimed.2018.07.007 Herovic E, Sellnow TL, Sellnow DD: Challenges and opportunities for pre-crisis emergency risk communication: lessons learned from the earthquake community. J RISK RES 2020, 23(3):349-364.http://doi.org/10.1080/13669877.2019.1569097 Camaj L: The Consequences of Attribute Agenda-Setting Effects for Political Trust, Participation, and Protest Behavior. J BROADCAST ELECTRON 2014, 58(4):634-654. http://doi.org/10.1080/08838151.2014.966363 Miao Q, Schwarz S, Schwarz G: Responding to COVID-19: Community volunteerism and coproduction in China. WORLD DEV 2021, 137:105128. http://doi.org/https://doi.org/10.1016/j.worlddev.2020.105128 Candelario DM, Vazquez V, Jackson W, Reilly T: Completeness, accuracy, and readability of Wikipedia as a reference for patient medication information. J AM PHARM ASSOC 2017, 57(2):197-200.http://doi.org/https://doi.org/10.1016/j.japh.2016.12.063 Freberg K: Intention to comply with crisis messages communicated via social media. PUBLIC RELAT REV 2012, 38(3):416-421.https://doi.org/10.1016/j.pubrev.2012.01.008 Tai Z STJ: Media dependencies in a changing media environment: The case of the 2003 SARS epidemic in China. NEW MEDIA SOC 2007, 6(9):987-1009. http://doi.org/https://doi.org/10.1177/1461444807082691 Lee C: The Interplay Between Media Use and Interpersonal Communication in the Context of Healthy Lifestyle Behaviors: Reinforcing or Substituting? MASS COMMUN SOC 2010, 13(1):48-66. http://doi.org/10.1080/15205430802694869 Lindell MK, Prater CS, Gregg CE, Apatu EJI, Huang S, Wu HC: Households' immediate Responses to the 2009 American Samoa Earthquake and Tsunami. INT J DISAST RISK RE 2015, 12:328-340.http://doi.org/https://doi.org/10.1016/j.ijdrr.2015.03.003 Kahlor L, Dunwoody S, Griffin R, Neuwirth K, Giese J: Studying heuristic-systematic processing of risk communication. RISK ANAL 2003, 23(2):355-368. http://doi.org/10.1111/1539-6924.00314 Singhal A: Effective health risk messages: A step-by-step guide. J HEALTH COMMUN 2004, 9(5):485-486.http://doi.org/10.1080/10810730490504350 Jin Y: Making Sense Sensibly in Crisis Communication: How Publics' Crisis Appraisals Influence Their Negative Emotions, Coping Strategy Preferences, and Crisis Response Acceptance. COMMUN RES 2010, 37(4):522-552.http://doi.org/10.1177/0093650210368256 Wong L, AbuBakar S: Health Beliefs and Practices Related to Dengue Fever: A Focus Group Study. PLOS NEGLECT TROP D 2013, 7(7):e2310.http://doi.org/10.1371/journal.pntd.0002310 Luttrell A, Petty R: Evaluations of Self-Focused Versus Other-Focused Arguments for Social Distancing: An Extension of Moral Matching Effects. SOC PSYCHOL PERS SCI 2021, 12(6):946-954.http://doi.org/10.1177/1948550620947853 Kim J, Nan X: Temporal Framing Effects Differ for Narrative Versus Non-Narrative Messages: The Case of Promoting HPV Vaccination. COMMUN RES 2019, 46:401-417. http://doi.org/10.1177/0093650215626980 Batson CD, Batson JG, Slingsby JK, Harrell KL, Peekna HM, Todd RM: Empathic joy and the empathy-altruism hypothesis. J PERS SOC PSYCHOL 1991, 61(3):413-426. http://doi.org/10.1037/0022-3514.61.3.413 Liu BF, Austin L, Lee Y, Jin Y, Kim S: Telling the tale: the role of narratives in helping people respond to crises. J APPL COMMUN RES 2020, 48(3):328-349. http://doi.org/10.1080/00909882.2020.1756377 Kim Y, Jung J: SNS dependency and interpersonal storytelling: An extension of media system dependency theory. NEW MEDIA SOC 2017, 19(9):1458-1475. http://doi.org/10.1177/1461444816636611 Morton T, Duck J: Communication and health beliefs - Mass and interpersonal influences on perceptions of risk to self and others. COMMUN RES 2001, 28(5):602-626. http://doi.org/10.1177/009365001028005002 Seo M: Amplifying panic and facilitating prevention: Multifaceted effects of traditional and social media use during the 2015 MERS crisis in South Korea. Journalism & Mass Communication Quarterly 2021, 1(98):221-240. https://doi.org/10.1177/1077699019857693 Jones AM, Omer SB, Bednarczyk RA, Halsey NA, Moulton LH, Salmon DA: Parents' source of vaccine information and impact on vaccine attitudes, beliefs, and nonmedical exemptions. Advances in preventive medicine 2012, 2012:932741. http://doi.org/10.1155/2012/932741 Tummers L, Bekkers V, Vink E, Musheno M: Coping During Public Service Delivery: A Conceptualization and Systematic Review of the Literature. J PUBL ADM RES THEOR 2015, 25(4):1099-1126.http://doi.org/10.1093/jopart/muu056 Kazi A, Jafri L: The use of mobile phones in polio eradication. B WORLD HEALTH ORGAN 2016, 94(2):153-154. http://doi.org/10.2471/BLT.15.163683 Wang L, Graddy E: Social Capital, Volunteering, and Charitable Giving. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations 2008, 19(1):23-42. http://doi.org/10.1007/s11266-008-9055-y Zavyalova A, Pfarrer M, Reger R, Shapiro D: MANAGING THE MESSAGE: THE EFFECTS OF FIRM ACTIONS AND INDUSTRY SPILLOVERS ON MEDIA COVERAGE FOLLOWING WRONGDOING. ACAD MANAGE J 2012, 55(5):1079-1101.http://doi.org/10.5465/amj.2010.0608 Valente T, Saba W: Campaign exposure and interpersonal communication as factors in contraceptive use in Bolivia. J HEALTH COMMUN 2001, 6(4):303-322. http://doi.org/10.1080/108107301317140805 Spitale G, Germani F, Biller-Andorno N: The PHERCC Matrix. An Ethical Framework for Planning, Governing, and Evaluating Risk and Crisis Communication in the Context of Public Health Emergencies. AM J BIOETHICS 2024, 24(4):67-82. http://doi.org/10.1080/15265161.2023.2201191 Ickert J, Stewart I: Earthquake risk communication as dialogue - insights from a workshop in Istanbul's urban renewal neighbourhoods. NAT HAZARD EARTH SYS 2016, 16(5):1157-1173. http://doi.org/10.5194/nhess-16-1157-2016 Williams L, Rasmussen S, Kleczkowski A, Maharaj S, Cairns N: Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic. Psychology, Health & Medicine 2015, 20(7):832-837. http://doi.org/10.1080/13548506.2015.1028946 Ye Y, Wang R, Feng D, Wu R, Li Z, Long C, Feng Z, Tang S: The Recommended and Excessive Preventive Behaviors during the COVID-19 Pandemic: A Community-Based Online Survey in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020, 17(19):6953.http://doi.org/10.3390/ijerph17196953 Hong W, Liu R, Ding Y, Hwang J, Wang J, Yang Y: Cross-Country Differences in Stay-at-Home Behaviors during Peaks in the COVID-19 Pandemic in China and the United States: The Roles of Health Beliefs and Behavioral Intention. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021, 18(4):2104. http://doi.org/10.3390/ijerph18042104 Liu Z, Huang X: Evaluating the credibility of scholarly information on the web: A cross cultural study. The International Information & Library Review 2005, 37(2):99-106. http://doi.org/https://doi.org/10.1016/j.iilr.2005.05.004 Zhang H, Yang C, Deng X, Luo C: How Authoritative Media and Personal Social Media Influence Policy Compliance Through Trust in Government and Risk Perception: Quantitative Cross-Sectional Survey Study. J MED INTERNET RES 2025, 27.http://doi.org/10.2196/64940 Cutilli C: Seeking Health Information What Sources Do Your Patients Use? ORTHOP NURS 2010, 29(3):214-219.http://doi.org/10.1097/NOR.0b013e3181db5471 Siegrist M, Gutscher H, Earle TC: Perception of risk: the influence of general trust, and general confidence. J RISK RES 2005, 8(2):145-156.http://doi.org/10.1080/1366987032000105315 Siegrist M, Cvetkovich G, Roth C: Salient value similarity, social trust, and risk/benefit perception. RISK ANAL 2000, 20(3):353-362. http://doi.org/10.1111/0272-4332.203034 Vaughan E, Tinker T: Effective Health Risk Communication About Pandemic Influenza for Vulnerable Populations. AM J PUBLIC HEALTH 2009, 99:S324-S332. http://doi.org/10.2105/AJPH.2009.162537 Yang S, Kang M, Johnson P: Effects of Narratives, Openness to Dialogic Communication, and Credibility on Engagement in Crisis Communication Through Organizational Blogs. COMMUN RES 2010, 37(4):473-497.http://doi.org/10.1177/0093650210362682 Westerman D, Spence P, Van der Heide B: Social Media as Information Source: Recency of Updates and Credibility of Information. J COMPUT-MEDIAT COMM 2014, 19(2):171-183. http://doi.org/10.1111/jcc4.12041 Chae J, Lee C: The Psychological Mechanism Underlying Communication Effects on Behavioral Intention: Focusing on Affect and Cognition in the Cancer Context. COMMUN RES 2019, 46(5):597-618.http://doi.org/10.1177/0093650216644021 Paek H, Oh S, Hove T: How Fear-Arousing News Messages Affect Risk Perceptions and Intention to Talk About Risk. HEALTH COMMUN 2016, 31(9):1051-1062. http://doi.org/10.1080/10410236.2015.1037419 Oh S, Lee S, Han C: The Effects of Social Media Use on Preventive Behaviors during Infectious Disease Outbreaks: The Mediating Role of Self-relevant Emotions and Public Risk Perception. HEALTH COMMUN 2021, 36(8):972-981.http://doi.org/10.1080/10410236.2020.1724639 Carlo G, Randall BA: The Development of a Measure of Prosocial Behaviors for Late Adolescents. J YOUTH ADOLESCENCE 2002, 31(1):31-44.http://doi.org/10.1023/A:1014033032440 Rutsaert P, Pieniak Z, Regan Á, McConnon Á, Kuttschreuter M, Lores M, Lozano N, Guzzon A, Santare D, Verbeke W: Social media as a useful tool in food risk and benefit communication? A strategic orientation approach. FOOD POLICY 2014, 46:84-93. https://doi.org/10.1016/j.foodpol.2014.02.003 Gammage K, Klentrou P: Predicting Osteoporosis Prevention Behaviors: Health Beliefs and Knowledge. AM J HEALTH BEHAV 2011, 35(3):371-382.http://doi.org/10.5993/AJHB.35.3.10 Kahlor L: PRISM: A Planned Risk Information Seeking Model. HEALTH COMMUN 2010, 25(4):345-356.http://doi.org/10.1080/10410231003775172 Yang S: Effects of Government Dialogic Competency: The MERS Outbreak and Implications for Public Health Crises and Political Legitimacy. J MASS COMMUN Q 2018, 95:582383804.http://doi.org/10.1177/1077699017750360 Green M, Brock T: The role of transportation in the persuasiveness of public narratives. J PERS SOC PSYCHOL 2000, 79(5):701-721.http://doi.org/10.1037/0022-3514.79.5.701 Kreuter M, Green M, Cappella J, Slater M, Wise M, Storey D, Clark E, O'Keefe D, Erwin D, Holmes K et al : Narrative communication in cancer prevention and control: A framework to guide research and application. ANN BEHAV MED 2007, 33(3):221-235. http://doi.org/10.1007/BF02879904 Ho S: The Knowledge Gap Hypothesis in Singapore: The Roles of Socioeconomic Status, Mass Media, and Interpersonal Discussion on Public Knowledge of the H1N1 Flu Pandemic. MASS COMMUN SOC 2012, 15(5):695-717.http://doi.org/10.1080/15205436.2011.616275 Yoo W, Choi D, Park K: The effects of SNS communication: How expressing and receiving information predict MERS-preventive behavioral intentions in South Korea. COMPUT HUM BEHAV 2016, 62:34-43.http://doi.org/https://doi.org/10.1016/j.chb.2016.03.058 Besalú R, Pont-Sorribes C: Credibility of Digital Political News in Spain: Comparison between Traditional Media and Social Media. SOC SCI-BASEL 2021, 10(5):170. http://doi.org/10.3390/socsci10050170 Additional Declarations No competing interests reported. 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06:49:38\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":33898,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eResearch framework\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7506021/v1/52d25d2d5235e5dec5218a83.png\"},{\"id\":106415006,\"identity\":\"f9e4f9c6-42d3-43ce-ad90-3e65aa224f2a\",\"added_by\":\"auto\",\"created_at\":\"2026-04-08 10:31:53\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1897815,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7506021/v1/2079baf7-3c16-466a-a143-686f3e002344.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Influence Mechanisms of Multidimensional Risk Communication Strategies on Public Altruistic Protective Behavior: Evidence from Public Health Emergencies\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eIn the \\\"VUCA era\\\", when public health emergencies occur frequently, governments face tension between limited resources and complex risks, making it difficult to address systemic challenges through unilateral efforts. Stimulating proactive public participation and achieving multiactor cogovernance has become a crucial pathway for managing public crises. As the ultimate bearer of risk policies, the public's response behaviors have great impacts on the effectiveness of risk governance. Whether government policies can achieve the expected goals hinges on effective risk communication that provides timely information and guidelines that stimulate accurate risk perceptions and corresponding protective behaviors in the public [1].\\u003c/p\\u003e\\u003cp\\u003eRisk has the dual attributes of objective reality and a subjective construct. Owing to differences in cognitive foundation, social experience and cultural background, the public often constructs subjective judgments on the basis of limited information that is not entirely consistent with the actual risk, thus affecting their behavioral responses. Therefore, in public health emergencies, high-quality risk communication between the government and the public is not only a technical issue of information transfer but also the core element in fostering correct perceptions and guiding behavioral choices. Multidimensional, perceptible, and situationally adapted risk communication strategies can effectively bridge the information gap between the government and society, stimulate altruistic protective behaviors, and promote a shift toward collaborative governance in risk management [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eAlthough risk communication research has yielded substantial theoretical insights, most studies have focused primarily on the accuracy of information and the choice of communication channels, with limited attention given to how different communication strategies shape prosocial protective behaviors under conditions of high uncertainty [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Public responses to risk are not driven solely by individual rationality but are deeply embedded in cultural norms, collectivist values, and institutional trust, particularly in the Chinese context [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Under such influences, individuals are more likely to engage in altruistic protective behaviors, which willingly incur personal costs without direct benefits to enhance the safety of others and the broader community, thereby contributing to greater social resilience[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. However, during public health emergencies, individuals often exhibit bounded rationality in risk decision-making, making their behavioral responses highly susceptible to external information cues. In this context, government-led risk communication strategies are pivotal in shaping public risk perception, trust in information, and subsequent protective behavior [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. While some studies have noted the impact of risk communication on protective behavior, these studies are mostly confined to theoretical deductions and case analyses. They tend to provide macrolevel descriptions and overlook the differential effects of specific risk communication elements\\u0026mdash;such as communication content, narrative style, and information source\\u0026mdash;on public protective behavior, especially given the lack of dedicated research on altruistic protective behavior. Therefore, investigating the underlying mechanisms through which multidimensional risk communication strategies influence prosocial protective behaviors is imperative.\\u003c/p\\u003e\\u003cp\\u003eWe use the COVID-19 pandemic as a canonical public health emergency because it combines extreme uncertainty, frequent policy shifts, and an \\u0026ldquo;infodemic\\u0026rdquo; of competing messages\\u0026mdash;conditions that foreground the role of risk communication. Many COVID-19 protective actions (e.g., mask wearing, vaccination, and self-isolation) carry strong positive externalities, making altruistic protection both salient and observable. The event also produced abundant, time-stamped communication and behavior data, enabling rigorous empirical assessment of messaging effects. This study aims to investigate how multidimensional governmental risk communication strategies affect public altruistic protective behavior. Key findings will provide empirical support for designing public-oriented, precise, and effective risk communication and emergency mobilization.\\u003c/p\\u003e\"},{\"header\":\"Method\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eTheoretical background\\u003c/h2\\u003e\\u003cp\\u003eThe protective action decision model (PADM) is a classic model for analyzing how individuals or groups make decisions about protective behaviors in unexpected risk situations [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. The PADM emphasizes that public behavior in a risk context is jointly influenced by three types of external information: environmental cues, social cues, and risk warnings [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Environmental cues include physical phenomena at the time of a risk event, such as disaster sights or sounds. Social cues refer to information that individuals obtain by observing and imitating others\\u0026rsquo; behaviors. Risk warnings consist of risk information released by official or authoritative sources. This information, moderated by individual characteristics (e.g., cognitive level, social network, and resource endowment), triggers the public's three core perceptions of risk, i.e., threat perception, protective behavior perception, and stakeholder perception, which in turn affect protective behavior decisions.\\u003c/p\\u003e\\u003cp\\u003eHowever, the original PADM model has a complex structure containing multiple psychological processes and behavioral pathways, and in reality, the public often does not go through all stages in full [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. For example, in highly urgent situations, an authoritative and credible source of information may prompt individuals to act quickly, skipping many stages of information processing[\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Therefore, this study simplifies and reconstructs the theory based on the PADM to present a clearer picture of the mechanism of risk communication strategies on altruistic protective behaviors.\\u003c/p\\u003e\\u003cp\\u003eFrom the perspective of communication, risk communication is essentially an information dissemination activity that covers five elements: the communication source, communication content, communication media, audience and communication effect [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. The source of communication refers to the provider of risk information, such as the government, media and surrounding people, which directly affects the level of public trust in the information. The communication content includes aspects such as the nature of the risk event, its severity, and protective measures, which determine the effectiveness and relevance of the information. In addition, information is presented in different ways, which affects the public's understanding and emotional response to the information. The communication media, as a channel of information diffusion, influences the coverage and immediacy of risk information. Finally, the communication effect is reflected in the audience's (i.e., the public's) understanding, attitudes, and protective behavioral responses to risk information [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eIn the context of public health emergencies, this study divides the above elements into four dimensions of risk communication strategies: the information source strategy, the communication content strategy, the narrative style strategy, and the communication media strategy. These strategies aim to influence the public's risk perception and thereby guide their decisions to engage in altruistic protective behavior. Additionally, considering the special circumstances of public health emergencies\\u0026mdash;for example, home quarantine\\u0026mdash;can impede interpersonal information sources, and the Chinese government, through strong scrutiny and control of other information sources during emergencies, usually possesses more timely first-hand information about crisis events, giving authoritative information sources a marked advantage over others[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Therefore, this study introduces the public's trust in authoritative information sources to explore how trust affects the relationship between risk communication strategies and risk perception.\\u003c/p\\u003e\\u003cp\\u003eIn summary, by integrating communication and behavioral theories, this study developed the causal pathway of \\u0026ldquo;risk communication strategies \\u0026rarr; risk perception \\u0026rarr; altruistic protective behavior\\u0026rdquo; in stimulating collective behaviors, taking into consideration the moderating role of \\u0026ldquo;trust in authoritative information sources\\u0026rdquo;. We systematically analyze how different communication strategies, through the interactive effects of public risk perception and trust levels, influence the public\\u0026rsquo;s choices of altruistic protective behavior in a public health crisis context. The theoretical analytical framework is depicted in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eFor information sources, this study draws upon the classification framework proposed by [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e] and categorizes risk information sources in public health emergencies into three types on the basis of their authority, accessibility, and degree of personalization: Authoritative information sources (AIS), mass media information sources (MMIS), and interpersonal information sources (IIS). For communication content, guided by the typology of [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e], this study identifies three key categories of risk-related content: epidemic information (EI), institutional response information (IRI), and preventive information (PI). With respect to the narrative strategy dimension, following narrative transportation theory [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e] and prior empirical classifications [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e], risk messages are classified into two types: story-based styles (SS) and data-based styles (DS). Finally, for the communication media dimension, using the typology of [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e] and established survey instruments such as the China General Social Survey (CGSS), this study categorizes communication media into internet (IT), television (TV), telephone calls and SMS (TCSMS), radio broadcasts (RB), newspapers and printed materials (NPM), and face-to-face communication with public officials (F2F). For the purpose of clarity and conciseness in subsequent tables and models, all variables are abbreviated using their initial letters.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eResearch hypotheses\\u003c/h3\\u003e\\n\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eRisk communication and public altruistic protective behavior\\u003c/h2\\u003e\\u003cp\\u003eThe core function of risk communication lies in reshaping the internal structure of risk events through strategic information delivery [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. In the context of public health emergencies, this process is often constrained by asymmetrical bidirectional communication dynamics between governments and the public [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Effective risk communication not only mitigates coordination failures between political and societal actors but also enhances individual threat perceptions and the sense of social responsibility. More importantly, it facilitates a synergistic interaction between information provision and trust, thereby stimulating prosocial motivation and fostering the transformation of citizens into active agents of altruistic protective behavior, a critical determinant of effective pandemic response[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. By integrating the PADM with the structural components of risk communication, this study identifies four key dimensions\\u0026mdash;the information source, communication media, message content, and narrative style\\u0026mdash;as observable variables. These dimensions are used to examine how multidimensional risk communication strategies influence public altruistic protective behaviors, forming the basis for the formulation of corresponding research hypotheses.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003e(1) Information sources and altruistic public protective behavior\\u003c/h3\\u003e\\n\\u003cp\\u003ePublic exposure to diverse sources of information during public health emergencies stimulates differential protective behaviors. Studies have shown that the public exhibits varying degrees of attention to information: they first pay attention to who provides the information and judge its credibility before focusing on the content[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. In other words, who presents the information is more important than the specific content of the information. Scholars have found that authoritative information sources backed by high-quality information and government endorsement are favored by citizens and significantly influence citizens\\u0026rsquo; compliance behaviors [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. However, because communications from authoritative sources must undergo strict vetting and are not driven by \\u0026ldquo;click-rate\\u0026rdquo; incentives, they often respond slower and with relatively limited content during public health emergencies. The public thus turns to mass media sources to obtain information and adjust their protective behaviors accordingly[\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. Moreover, studies indicate that interpersonal information sources, which are often overlooked by scholars, can sometimes have a stronger influence on changing public behavior than traditional authoritative sources do, significantly enhancing health-protective behaviors[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. Therefore, we propose the following hypotheses and research questions:\\u003c/p\\u003e\\u003cp\\u003eH1: Information sources have a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH1a: Authoritative information sources have a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH1b: Mass media information sources have a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH1c: Interpersonal information sources have a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eR1: Which information source has the greatest impact on public altruistic protective behavior during public health emergencies?\\u003c/p\\u003e\\n\\u003ch3\\u003e(2) Communication content and public altruistic protective behavior\\u003c/h3\\u003e\\n\\u003cp\\u003eRisk messages with well-designed content and appropriate communication can increase the likelihood that the public will adopt protective behaviors[\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. Risk communicators should disseminate information that the public feels they need to know, including but not limited to, descriptions of the risk, consequences, likelihood of exposure, and knowledge of protection [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. Friedman noted that simple and easy-to-use instructional prevention messages are more likely to promote public behavior change [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Research has shown that crisis information released by public health organizations, as well as organizations\\u0026rsquo; own risk response information, can positively influence public protective behaviors [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. Decisive and timely information from the government in the early stages of an outbreak can enhance public trust and sense of security, thereby increasing altruistic protective behavior[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. Additionally, epidemic information released by government departments often involves both self-interested and altruistic elements, which can stimulate public altruistic protective intentions [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. Therefore, we propose the following hypotheses and research question:\\u003c/p\\u003e\\u003cp\\u003eH2: Communication content has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH2a: Epidemic information has a significant positive effect on public protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH2b: Institutional response information has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH2c: Preventive information has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eR2: Which communication content has the greatest influence on public altruistic protective behavior during a public health emergency?\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e(3) Narrative style and public altruistic protective behavior\\u003c/h2\\u003e\\u003cp\\u003eNarrative transportation theory posits that the essence of crisis communication is narration and that citizens' attitudes and behaviors in response to a crisis are strongly influenced by narrative styles. An effective narrative of a crisis event can help the public comprehend the issue (Yang et al., 2010), shape civic identification, influence information acceptance, and alter perceptual attitudes[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. This, in turn, encourages citizens to undertake protective behaviors and altruistic actions [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. People draw lessons from stories; a narrative (story-based) style helps the public comprehend and contextualize real-world problems, enhances their sense of immersion, and evokes resonance. Witnessing others\\u0026rsquo; painful experiences can arouse sympathy and empathy, prompting actions that benefit others[\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. During the COVID-19 pandemic, narrative storytelling was able to communicate the attribution of crisis responsibility and promote public protective behaviors[\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. However, other research suggests that, compared with a storytelling style, a statistical (data-driven) style\\u0026mdash;owing to its concreteness and verifiability\\u0026mdash;can be more persuasive; when information is presented in a data-centric manner, it is more likely to strengthen public altruistic protective behavior [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Accordingly, the research hypotheses and questions are formulated as follows:\\u003c/p\\u003e\\u003cp\\u003eH3: Narrative style has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH3a: Story-based style has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH3b: Data-based style has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eR3: Which narrative style has a greater influence on public altruistic protective behavior in public health emergencies?\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003e(4) Communication media and public altruistic protective behavior\\u003c/h3\\u003e\\n\\u003cp\\u003eThe media influences public attitudes and behaviors through information dissemination [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e], and different media vary in terms of the richness of the information conveyed and their communication effects. Traditional media, with their high authority and broad reach, play a leading role in guiding public opinion and public behavioral compliance [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. However, with the diversification of communication media, social media, which allows information exchange across time and space, has \\u0026ldquo;decentralized\\u0026rdquo; the discourse power of traditional media, profoundly affecting public prosocial behaviors [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]; however, the internet has a \\u0026ldquo;double-edged sword\\u0026rdquo; effect\\u0026mdash;information distortion and emotionalization tendencies\\u0026mdash;that can undermine the effectiveness of protective behaviors [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. In addition, the role of face-to-face communication between street-level bureaucrats and citizens, as well as the telephone and SMS, has been underestimated in research. On the one hand, street-level bureaucrats (grassroots public officials) act as transmitters, interpreters, and implementers of information; their role, credibility, and communication style significantly influence citizen behavior [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. On the other hand, telephone calls and text messages, characterized by high coverage and immediacy, allow citizens to proactively seek advice or report relevant crisis information and enable them to receive prompts from government agencies and adjust their behavior accordingly [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. The use of multiple communication media promotes mutual connection, trust, and reciprocity among the public, provides more opportunities to understand others\\u0026rsquo; needs, and can significantly enhance altruistic behaviors such as donations and contributions [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. We therefore propose the following hypotheses and research questions:\\u003c/p\\u003e\\u003cp\\u003eH4: Communication media has a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4a: The internet has a significantly positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4b: Telephones and SMS have a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4c: Television has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4d: Radio broadcasts have a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4e: Newspapers and other printed materials have a significant positive influence on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH4f: Face-to-face communication with public officials has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eR4: Which communication media has the greatest influence on public protective behavior during public health emergencies?\\u003c/p\\u003e\\u003cp\\u003eIn this study, risk communication is divided into four core dimensions, namely, the information source, communication content, narrative style, and communication media, and corresponding hypotheses are proposed for each. Therefore, we employ an entropy method (EM) and the CRITIC method to assign combined weights to these four dimensions, derive an overall risk communication index, and propose the following hypothesis:\\u003c/p\\u003e\\u003cp\\u003eH5: Overall, risk communication has a significant positive effect on public altruistic protective behavior.\\u003c/p\\u003e\\n\\u003ch3\\u003eThe mediating role of risk perception\\u003c/h3\\u003e\\n\\u003cp\\u003eThe core mechanism of risk communication lies in influencing public risk cognition through information dissemination, thereby driving protective behaviors. Different dimensions of risk communication strategies can have differential effects on individual risk perceptions [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. First, the authority, professionalism, and intimacy of the information source influence the public's judgment of information credibility, which shapes risk perception [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Second, the completeness and relevance of the communication content directly shape individuals' threat assessment and perceived controllability. Third, narrative style, as a form of information expression, can induce different effects depending on its presentation. A contextualized, concrete story-based style can enhance emotional immersion and resonance [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e], whereas a clearly structured, quantifiable data-based style reinforces the public\\u0026rsquo;s rational judgment of risk [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Finally, the communication media, as a vehicle for transmitting risk information, has attributes such as accessibility, interactivity, and social recognition that influence how deeply the public engages with information and how they process it, thereby affecting their risk perception [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]. Both protection motivation theory and the health belief model suggest that an individual's perception of health risks, including their susceptibility, severity, and coping efficacy, is a key psychological variable that predicts their protective behavior [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. In public health emergencies, increased public risk perception can stimulate both personal and altruistic protective intentions[\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. In summary, risk perception is expected to mediate the relationship between risk communication and public altruistic behavior. Accordingly, we propose the following hypothesis:\\u003c/p\\u003e\\u003cp\\u003eH6: Risk perception plays a mediating role between risk communication and public altruistic protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH6a: Risk perception plays a positive mediating role between information sources and public protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH6b: Risk perception positively mediates the relationship between communication content and public protective behavior.\\u003c/p\\u003e\\u003cp\\u003eH6c: Risk perception positively mediates the relationship between narrative style and public protective behavior\\u003c/p\\u003e\\u003cp\\u003eH6d: Risk perception positively mediates the relationship between the communication media and public protective behavior.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eModerating role of trust in authoritative information sources\\u003c/h2\\u003e\\u003cp\\u003eThe degree of public trust in information sources usually depends on the source's authority, professionalism, transparency, and historical reliability [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Differences in trust manifest in two ways: On the one hand, within the same population, there are varying levels of trust in different information sources. Studies have shown that digital natives have significantly greater trust in information released by authoritative entities such as the government and experts than in information from commercial and social media [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e]. Although conventional wisdom holds that medical professionals are the most trusted health information source for the public, in reality, when facing health issues, the public often first turns to mass media sources such as the internet[\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. A lack of trust in authoritative information sources heightens the public\\u0026rsquo;s uncertainty and anxiety, thereby amplifying their risk perception [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]. On the other hand, different groups exhibit structural differences in their levels of trust in the same information source. This primarily stems from individual traits, information literacy, and experiential differences, leading to cognitive disparities in processing and accepting the same risk information and thus yielding different risk perceptions [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. Trust functions as a heuristic, implicit mode of information processing that helps reduce cognitive complexity and processing costs. In the context of a pandemic, individuals with higher levels of trust are more inclined to accept risk communication recommendations, whereas low levels of trust may reinforce anxiety and risk perception[\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e]. Therefore, the following research hypothesis is proposed:\\u003c/p\\u003e\\u003cp\\u003eH7: Trust in authoritative information sources has a significant negative moderating effect on the relationship between information sources and risk perception.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eProcedure and participants\\u003c/h2\\u003e\\u003cp\\u003eThis study was conducted between October and December 2023 via the Credamo platform via questionnaires, and all participants were informed and participated voluntarily. To maximize sample coverage and enhance representativeness and external validity, we adopted a stratified site-selection strategy that balanced Chinese economic zones (east/central/west) and latitudinal regions (north/central/south). Within 11 provincial-level administrative units\\u0026mdash;including Beijing Municipality, Shandong Province, Hubei Province, and the Guangxi Zhuang Autonomous Region\\u0026mdash;we selected two cities in each. One was economically developed, and the other was comparatively less developed. These served as the primary sampling sites. In total, 1,491 questionnaires were collected; after excluding invalid responses, 1,417 valid cases remained (validity rate\\u0026thinsp;=\\u0026thinsp;95.04%). Among the samples, women accounted for 51.7%, and in terms of age distribution, middle-aged and young people were predominant, accounting for 32.1% of the 18\\u0026ndash;26-year group, 42.6% of the 27\\u0026ndash;39-year group, and 19% of the 40\\u0026ndash;60-year group. The proportion of nonagricultural Hukous was 51.5%, and 80.4% of the respondents assessed themselves as being healthy.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eMeasures\\u003c/h2\\u003e\\u003cp\\u003eThe measurement scales used in this study were all established internationally and adapted with appropriate semantic localization to fit the Chinese sociocultural context while adhering to the structure of the original scales. The means, standard deviations, reliability coefficients, and measurement items for each variable are presented in Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eMeasurement Items of the Variable\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eDimension\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eItem\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eReference\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eInformation Source\\u003c/p\\u003e\\u003cp\\u003e(IS)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you get information about public health emergencies from government departments or experts?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMMIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you obtain information related to public health emergencies from mass media such as television, the internet, or various social media influencers?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eIIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you get information related to public health emergencies from your family and friends?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eCommunication Content\\u003c/p\\u003e\\u003cp\\u003e(CC)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eEI\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you focus on the source of the epidemic, the hazards, the number of deaths and injuries, etc.?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eIRI\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you focus on information about how relevant government departments are preventing and handling the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePI\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you focus on knowledge and information about the prevention and treatment of the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eNarrative Style\\u003c/p\\u003e\\u003cp\\u003e(NS)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you prefer to learn about the epidemic through specific people and stories?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eDS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you prefer graphical data to learn information about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003ecommunication media\\u003c/p\\u003e\\u003cp\\u003e(CM)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eIT\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on the internet to search for and receive information related to the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eTCSMS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on telephone calls or SMS to receive epidemic-related information?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eTV\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on television to search for and watch epidemic-related information?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eRB\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on radio to listen to information about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNPM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on newspapers or printed materials to search and read information about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eF2F\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you rely on face-to-face communication from government officials to get information about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eTrust in Authoritative Information Source\\u003c/p\\u003e\\u003cp\\u003e(TIAIS)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel that the information released by government and healthcare professionals is professional and accurate?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel that the information released by government and healthcare professionals is transparent and credible?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel that the information released by government and healthcare professionals is complete and unbiased?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003eRisk Perceived\\u003c/p\\u003e\\u003cp\\u003e(RP)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you believe the epidemic poses a serious threat to you and your family's physical and mental health?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you think it is likely that you and your family will get infected or be infected?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you think it would have a significant negative impact on your and your family's life and work?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel worry about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel anxious about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eDo you feel fearful about the epidemic?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003eAltruistic Protective Behavior\\u003c/p\\u003e\\u003cp\\u003e(APB)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eWill you cease work and production as required by the government?\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e[\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e] [\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e]\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eWill you actively donate money or materials?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eWill you participate in online epidemic prevention volunteer services,?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eWill you participate in offline epidemic prevention volunteer services?\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eProperties of the main variables\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eCronbach's α\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eMean\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eSD\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eDimension\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e0.677\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.08\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.03\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eAIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.18\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.948\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eMMIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.056\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eIIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eCC\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e0.842\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.826\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eEI\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.31\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.809\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eIRI\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.76\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003ePI\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eNS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e0.496\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.016\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eSS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.04\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.933\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eDS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003eCM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e0.852\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.27\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.869\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eIT\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.228\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eTCSMS\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.42\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.153\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eTV\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.306\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eRB\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e2.84\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.301\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eNPM\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.209\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eF2F\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTIAIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.901\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.977\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRP\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.833\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.67\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAPB\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.892\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.87\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.901\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStatistical analyses\\u003c/h2\\u003e\\u003cp\\u003eTo test for common method bias, we conducted Harman\\u0026rsquo;s single-factor test. The results showed that in an unrotated principal component analysis, there were 14 factors with eigenvalues greater than 1, and the first factor accounted for 18.59% of the variance, which was well below the 40% threshold. This suggests that serious common method bias was not present. Considering that the four constituent dimensions of risk communication may have different importance in public cognition, we applied a weighting approach that combines the entropy and CRITIC methods to assign weights to the four dimensions (information source, communication content, narrative style, and communication media) and constructed a composite measurement index. The weighted composite score reflects the overall frequency of public exposure and reliance on each type of communication strategy in the context of a public health emergency. The weighting results are shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e. In addition, for the measurements of risk perception, trust in authoritative information sources, and altruistic protective behavior, we used the arithmetic mean of the item scores on each scale as the overall score; higher scores indicated a higher level of the corresponding variable. All scale items were scored on a five-point Likert scale (1\\u0026thinsp;=\\u0026thinsp;strongly disagree, 5\\u0026thinsp;=\\u0026thinsp;strongly agree), with higher scores indicating a greater degree of agreement with that dimension.\\u003c/p\\u003e\\u003cp\\u003eSPSS 26.0 was used to conduct multiple linear regression analysis of the effect of risk communication on altruistic protective behavior. Stepwise regression analyses were conducted to test the mediating effect of risk perception. The PROCESS macro (Model 1) was used to test the moderating effect of trust in authoritative information sources (5,000 bootstrap samples, 95% confidence interval).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eRisk Communication Dimensional Profiles\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"9\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariable\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eDimension\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eEM\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCRITIC\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eCW\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eDimension\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003eEM\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003eCRITIC\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003eCW\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"13\\\" rowspan=\\\"14\\\"\\u003e\\u003cp\\u003eRC\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003eIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e22.20%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e25.99%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e24.095%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eAIS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e33.05%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e35.94%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" 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colname=\\\"c8\\\"\\u003e\\u003cp\\u003e33.59%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e35.19%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eIRI\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e34.51%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e32.53%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e33.52%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003ePI\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e28.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e33.88%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e31.29%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eNS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e23.20%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e24.49%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e23.845%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eSS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e58.41%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e50%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e54.21%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eDS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e41.59%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e50%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e45.80%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003eCM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e39.49\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e35.57%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e36.53%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eTCSMS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e18.36%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e14.75%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e16.56%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eTV\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e12.76%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e14.97%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e13.87%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eRB\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e23.19%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e13.89%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e18.54%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003ePM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e27.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e13.84%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e20.47%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eF2F\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e14.61%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e15.55%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e15.08%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eITS\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.98%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e27%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e15.49%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eRelationship between risk communication and public altruistic protective behavior\\u003c/h2\\u003e\\n \\u003cp\\u003eRisk communication had a significant positive effect on public altruistic protective behavior (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.648, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), supporting H5 (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). With respect to the control variables, gender and health status had consistently significant effects on altruistic protective behavior. Specifically, women were more willing than men to take protective actions, and individuals with better self-rated health were more willing to take protective actions. Age and education level also had significant positive effects on altruistic protective behavior: older and more highly educated members of the public were more willing to engage in altruistic protective behavior. This may be because higher education and older age correspond to having undergone more socialization and education processes, leading to a stronger sense of responsibility and greater appreciation\\u0026mdash;from life experience and knowledge\\u0026mdash;of the importance of epidemic prevention, thereby increasing the willingness to act altruistically. Interestingly, Hukou registration type had a significant negative effect on altruistic protective behavior: compared with those with nonagricultural (urban) Hukou, individuals with agricultural (rural) Hukou were more willing to take altruistic protective actions. This could be influenced by the \\u0026ldquo;acquaintance society\\u0026rdquo; social context of rural areas, where people tend to rely more on social capital and maintain closer ties with each other, forming strong social networks that foster higher levels of mutual aid, cooperation, and altruistic spirit.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eEffects of Risk Communication and Information Sources on Public Altruistic Protective Behavior\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"7\\\"\\u003e\\n \\u003cp\\u003eAltruistic protective behavior\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.951\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.315\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.639\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.84\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.896\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.136\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.498\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.167\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.074\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.108\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.102\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.074\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.082\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.069\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.088\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.119\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.101\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.121\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.127\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.108\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.034*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.025\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.027\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.034\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.026\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.061\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.182*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.238\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.241\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.235\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.244\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.241\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.061\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.029\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.093\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.098\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.092\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.086\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.127\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.06\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.111\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.121\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.118\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.1\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.648\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.216\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.172\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMMIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.182\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.089\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.135\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.255\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.078\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.137\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.114\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.102\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.149\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e12.867\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e60.152\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e16.987\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e28.017\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e22.568\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e19.933\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e24.69\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eInfluence of information sources on public altruistic protective behavior\\u003c/h2\\u003e\\n \\u003cp\\u003eAs shown by Models 4, 5, and 6 in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, authoritative information sources (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.216, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), mass media information sources (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.182, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and interpersonal information sources (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.135, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) all had significant positive effects on public altruistic protective behavior. This supports H1, H1a, H1b, and H1c.\\u003c/p\\u003e\\n \\u003cp\\u003eThe results indicate that, in terms of influence on altruistic protective behavior, the sources rank as follows: authoritative information source\\u0026thinsp;\\u0026gt;\\u0026thinsp;mass media information source\\u0026thinsp;\\u0026gt;\\u0026thinsp;interpersonal information source. This finding highlights that authoritative information sources consistently play a pivotal role in driving citizens\\u0026rsquo; protective behavior, addressing R1. Moreover, considering the diverse nature of public risk information sources during a public health crisis, we included all three types of information sources in a single regression model (Model 7 in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e) for further analysis. The results show that mass media sources (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.089, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) and authoritative sources (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.172, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) still significantly influence public altruistic protective behavior when considered together, but the influence of interpersonal information sources is no longer significant when they are considered simultaneously.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eInfluence of communication content on public altruistic protective behavior\\u003c/h2\\u003e\\n \\u003cp\\u003eAs shown in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e, epidemic information (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.276, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), institutional response information (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.352, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and preventive information (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.317, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) all had significant positive effects on public altruistic protective behavior. This supports H2, H2a, H2b, and H2c.\\u003c/p\\u003e\\n \\u003cp\\u003eThe results indicate that the strength of influence on altruistic protective behavior is in the following order: institutional response information\\u0026thinsp;\\u0026gt;\\u0026thinsp;preventive information\\u0026thinsp;\\u0026gt;\\u0026thinsp;epidemic information, which answers R2. These three types of content often appear together during a public health crisis, for example, when government departments publicly release outbreak handling procedures alongside personal protective policies. We included all three content types in a single regression model for a comparative analysis. The results show that institutional response information (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.247, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) and preventive information (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.113, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) still have significant impacts on public altruistic protective behavior, whereas the effect of epidemic information is no longer significant when all content types are considered simultaneously.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eEffects of Communication Content Dimensions on Public Altruistic Protective Behavior\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003eAltruistic protective behavior\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.639\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.684\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.363\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.423\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.116\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.108\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.096\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.068\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.077\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.067\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.119\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.096\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.092\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.09\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.085\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.027\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.027\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.023\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.025\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.238\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.26\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.267\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.266\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.273\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.115\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.107\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.11\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.11\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.09\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.109 \\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.087\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.276\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.056\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIRI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.352\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.247\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.317\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.113\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.078\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.174\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.147\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e0.183\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e16.987\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e28.704\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e37.134\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30.433\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e31.485\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eInfluence of narrative style on public altruistic protective behavior\\u003c/h2\\u003e\\n \\u003cp\\u003eAs shown in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e, both the story-based style (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.287, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) and the data-based style (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.205, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) had significant positive effects on public altruistic protective behavior, supporting H3, H3a, and H3b. When comparing the effects of the two narrative styles, we found that the story-based style had a stronger influence on altruistic protective behavior than the data-based style. Furthermore, when both narrative styles are included in the same regression model, both remain significant, and the standardized regression coefficient for the story-based style remains higher than that for the data-based style, indicating that narrative storytelling has a more pronounced guiding effect on public behavior.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eEffects of Narrative Style Dimensions on Public Altruistic Protective Behavior\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\"\\u003e\\n \\u003cp\\u003eAltruistic protective behavior\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstants\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.639\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.455\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.968\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.23\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.108\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.063\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.09\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.062\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.119\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.097\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.116\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.098\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.028\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.038\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.033\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.238\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.183\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.241\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.192\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.063\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.114\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.072\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.122\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.102\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.287 \\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.25\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eDS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.205\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.116\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.078\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.174\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.122\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.186\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e16.987\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.99\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e24.5\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e35.791\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eInfluence of communication media on public altruistic protective behavior\\u003c/h2\\u003e\\n \\u003cp\\u003eTable \\u003cspan class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e shows that the Internet (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.219, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), telephone and SMS (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.224, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), television (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.248, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), radio broadcasts (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.242, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), newspapers (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.208, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and face-to-face communication with public officials (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.231, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) all had significant positive effects on altruistic protective behavior. This finding supports H4 ,H4a, H4b, H4c, H4d, H4e, and H4f. Considering the individual impact coefficients of each medium, the influence ranks are as follows: Television\\u0026thinsp;\\u0026gt;\\u0026thinsp;Radio\\u0026thinsp;\\u0026gt;\\u0026thinsp;Face-to-face (officials)\\u0026thinsp;\\u0026gt;\\u0026thinsp;Telephone \\u0026amp; SMS\\u0026thinsp;\\u0026gt;\\u0026thinsp;Internet\\u0026thinsp;\\u0026gt;\\u0026thinsp;Newspapers, which answers research question R4. When we entered multiple communication media into a single regression model, we found that the Internet, television, radio, telephone and SMS, and face-to-face communication with officials still significantly influenced public altruistic protective behavior, whereas the influence of newspapers was no longer significant in the full model. In Model 8, traditional media, such as television and radio, had a strong positive influence, indicating that they have significant guiding power for public protective behavior in a single context. However, in the full model that included multiple media, the Internet had the highest coefficient of influence, suggesting that the Internet holds a dominant position in dissemination and enjoys a higher frequency of use and degree of reliance in the information environment. This difference may stem from the overlapping usage of different media and differences in cognitive primacy. In other words, the Internet is not only a platform for initially issuing and receiving information but also serves as a channel for reprocessing and verifying information from other media. As a result, in a communication environment where multiple information sources coexist, the Internet wields a stronger influence on guiding behavior.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab7\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 7\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eEffects of Communication Media Dimensions on Public Altruistic Protective Behavior\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariables\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"8\\\"\\u003e\\n \\u003cp\\u003eAltruistic protective behavior\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 5\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 6\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 7\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 8\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.639\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.795***\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.843\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.717\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.692\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.893\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.62\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.81\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.108\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.068\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.134\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.099\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.121\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.144\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.111\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.09\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.119\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.133\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.104\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.098\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.086\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.096\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.101\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.096\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.028\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.033\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.036\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.037\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.027*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.238\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.246\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.185\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.204\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.14\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.194\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.178\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.152\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.121\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.056\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.057\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.028\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.041\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.028\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.124\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.104\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.102\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.107\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.113\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.118\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.083\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eInternet\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.219\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTCSMS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.224\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.055\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.248\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.079\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.242\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.118\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNPM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.208\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF2F\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.231\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.085\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.078\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.121\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.161\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.169\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.179\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.154\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.163\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.232\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e16.987\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e24.266\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e33.888\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e35.849\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e38.471\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e32.155\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e34.346\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e32.603\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003eMediating effect of risk perception\\u003c/h2\\u003e\\n \\u003cp\\u003eAs shown in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e, risk communication had a significant positive effect on risk perception (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.477, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and risk perception had a significantly positive effect on public altruistic protective behavior (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.168, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01). This finding indicates that risk perception plays a significantly positive mediating role in the pathway by which risk communication affects public altruistic protective behavior, supporting H6. Specifically, information source (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.249, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), communication content (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.546, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), narrative style (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.272, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and communication media (\\u0026beta;\\u0026thinsp;=\\u0026thinsp;0.267, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) each had a significant positive effect on risk perception, which in turn had a significant positive effect on public altruistic protective behavior. These findings suggest that H6a, H6b, H6c, and H6d are supported.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab8\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 8\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eRisk Perception Mediation Between Risk Communication and Altruistic Protective Behavior\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003eRisk perception\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003eAltruistic protective behavior\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 5\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 6\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 7\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 8\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 9\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 10\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.451\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.211\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.835\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.145\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.138\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.149\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.989\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.749\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.807\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1.745\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.069\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.066\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.056\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.063\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.102\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.069\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.065\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.058\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.057\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.109\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.064\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.042\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.071\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.054\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.061\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.092\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.125\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.093\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.109\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.097\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.006\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.014\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.006\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.034\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.026\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.036\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.035\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.042\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.069\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.182\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.236\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.265\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.200\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.156\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.008\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.045\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.066\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.047\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.028\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.076\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.100\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.075\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.062\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.047\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.038\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.064\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.104\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.095\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.106\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.091\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.477\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.616\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.068\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.167\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.126\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.139\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.115\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.249\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.250\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.546\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.006\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.272\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.336\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.267\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.370\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.135\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.072\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.111\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.084\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.094\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.255\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.156\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.191\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.196\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.228\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e27.565\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e13.728\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e21.886\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e16.191\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e18.181\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e60.152\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e30.097\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.858\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e38.194\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e46.299\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eModerating effect of trust in authoritative information sources.\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eTable \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003e presents the results of the moderation analyses. The results indicate that trust in authoritative information sources has a significant negative moderating effect on the \\u0026ldquo;information source \\u0026rarr; risk perception\\u0026rdquo; path (interaction term \\u0026beta;=-0.060, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). In other words, when the public\\u0026rsquo;s level of trust in authoritative sources is high, the positive impact of information sources on risk perception is weakened. This finding suggests that trust does not always amplify the effectiveness of information; its role is context dependent and complex. Further subgroup (interaction) analysis revealed that the moderating effect of authoritative source trust on the \\u0026ldquo;authoritative source \\u0026rarr; risk perception\\u0026rdquo; path was not significant (\\u0026beta;=-0.029, p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05). However, for the paths of \\u0026ldquo;mass media source \\u0026rarr; risk perception\\u0026rdquo; and \\u0026ldquo;interpersonal source \\u0026rarr; risk perception,\\u0026rdquo; trust in authoritative sources exhibited significant negative moderation (interaction terms \\u0026beta;= -0.058 and \\u0026beta;= -0.048, respectively, both p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Therefore, H7 is supported. This result indicates that when the public has high trust in authoritative information sources, information from nonauthoritative sources (such as social media and interpersonal networks) has a reduced marginal effect on their risk perception. In this context, trust exhibits an \\u0026ldquo;information selectivity suppression effect,\\u0026rdquo; meaning that high-trust functions as a filter that diminishes the uptake of information from other sources. This phenomenon aligns with the heuristic information-processing pathway: under conditions of high trust, individuals tend to make quick judgments on the basis of their existing trust, thereby reducing deep processing of external information. This also explains why, when authoritative institutions are highly trusted, nonauthoritative information sources find it difficult to further increase the public\\u0026rsquo;s risk perception.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab9\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 9\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eModerating effect test of trust in authoritative information sources on the influence of information sources and risk perception\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"4\\\"\\u003e\\n \\u003cp\\u003eRisk perception\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 3\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eModel 4\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConstant\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.369\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3.260\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.488\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2.837\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGender\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.066\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.087\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.063\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.076\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAge\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.041\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.052\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.042\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.036\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOccupation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHukou\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.050\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.038\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.040\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.049\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEducation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.049\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.059\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.056\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.047\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eHealth status\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.031\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.024\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.034\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.462\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.220\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMMIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.378\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.322\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTIAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.238\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.134\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.283\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.220\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIS* TIAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.060\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAIS* TIAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.029\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMMIS* TIAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.058\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eIIS*TIAIS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e-0.048\\u003csup\\u003e**\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eR\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.077\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.081\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.065\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0.059\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11.756\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e12.444\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9.809\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8.766\\u003csup\\u003e***\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec23\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eDirect effects of risk communication on public altruistic protective behavior\\u003c/h2\\u003e\\u003cp\\u003eThe findings show that information sources can exert a significant positive effect on public altruistic protective behavior, with authoritative information sources consistently playing a central role; their influence is significantly greater than that of mass media or interpersonal sources. Through an institutional trust anchoring effect, authoritative sources act as the core drivers of behavior [\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e], whereas mass media maintain a secondary influence due to their agenda-setting power. In an environment where multiple information sources coexist, mass media sources retain a robust influence (β\\u0026thinsp;=\\u0026thinsp;0.089, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), reflecting that in the modern digital era, the agenda-setting capacity of social media has become deeply embedded in the risk communication network[\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e]. In contrast, the marginal utility of interpersonal communication has been structurally compressed by changes in the media ecosystem, rendering its effect insignificant and weakening its supplementary role. These results not only reveal a gradient of influence \\u0026mdash; authoritative\\u0026thinsp;\\u0026gt;\\u0026thinsp;mass media\\u0026thinsp;\\u0026gt;\\u0026thinsp;interpersonal \\u0026mdash; but also highlight that in pandemic crisis contexts, the public prioritizes information sources that strike a balance between credibility and accessibility when processing information and making decisions [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. This finding indicates that authoritative sources remain the critical trust foundation for eliciting altruistic behavior, whereas mass media need to strike a balance between expanding reach and maintaining content professionalism.\\u003c/p\\u003e\\u003cp\\u003eEpidemic information, institutional response information, and preventive information all have significant positive effects on public altruistic protective behavior. However, when all three types of content are included together in the regression model, the effect of epidemic information is no longer significant. This result suggests that different types of information interact and carry different relative weights in influencing public protective behavior. From a social cognition theory perspective, the formation of individual behavior is influenced not only by objective information stimuli but also by the personal subjective interpretation of the context and cognitive processing of the information[\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. In public health emergencies, information released by authoritative institutions not only serves the functional role of communicating epidemic risk but also symbolizes the state\\u0026rsquo;s governance capacity. The clarity and transparency of such institutional response information can enhance public identification with and compliance with government directives, thereby increasing the likelihood of engaging in altruistic protective behaviors [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e]. Moreover, altruistic protective behavior\\u0026mdash;as a morally driven form of public action\\u0026mdash;typically requires individuals to exhibit a heightened sense of responsibility and collective consciousness. In this process, compared with the objective description of epidemic information, the government's demonstrated competence in crisis management through risk communication more effectively triggers prosocial behavioral responses among the public.\\u003c/p\\u003e\\u003cp\\u003eBoth narrative styles and data-based narrative styles can significantly and positively influence public altruistic protective behavior, with the effect of narrative style being more prominent. To some extent, this result echoes the basic judgment of narrative transportation theory on the effectiveness of crisis information dissemination; that is, narratives are not only a medium for transmitting facts but also an important path for stimulating emotional resonance and guiding the public's attitudes and behaviors [\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e]. Although some studies have emphasized that data-based information is more persuasive because of its objectivity, verifiability, and intuition [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e], in highly uncertain situations such as public health emergencies, narratives are more effective in evoking emotional recognition and risk empathy through the construction of figurative scenarios and characters, thus stimulating altruistic behavior.\\u003c/p\\u003e\\u003cp\\u003eMultiple communication media outlets each have a significant positive effect on public altruistic protective behavior, but in the multivariate regression model, the influence of newspapers becomes nonsignificant. This result can be interpreted in two ways. First, a collinearity diagnosis indicates that there is no severe multicollinearity among the communication media variables (all VIFs\\u0026thinsp;\\u0026lt;\\u0026thinsp;5, with VIF_max\\u0026thinsp;=\\u0026thinsp;3.319), ruling out statistical interference from high overlap between predictors. Second, from the perspective of media development trends, the influence of traditional media on public behavior is gradually waning in the digital environment. Compared with print media, television and radio\\u0026mdash;due to their regulated content and censorship mechanisms\\u0026mdash;are more readily accepted by the public and are more likely to gain their identification[\\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e]. In contrast, the Internet and other digital media grant the public greater agency, enabling people to filter and acquire information according to their own needs, and have become the dominant media form influencing public protective behavior[\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e] (Yoo, 2016). Therefore, the impact of media choice on public altruistic protective behavior is undergoing a structural shift characterized by digital media at the core and a differentiation of traditional media functions.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec24\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eIndirect effects of risk communication on public altruistic protective behavior\\u003c/h2\\u003e\\u003cp\\u003eThe results of the mediation analysis demonstrate that risk perception plays a significant positive mediating role in the pathway through which risk communication affects public altruistic protective behavior. This finding corroborates the classic \\u0026ldquo;cognitive\\u0026ndash;attitude\\u0026ndash;behavior\\u0026rdquo; sequence in behavior change mechanisms, indicating that public risk perception serves as a bridge between information reception and behavioral conversion. The strong consistency and coherence observed between risk perception and protective behavior suggest that citizens are more likely to engage in socially responsible altruistic actions when they perceive higher levels of risk. Therefore, when designing crisis communication strategies, governments should emphasize appropriately stimulating the public\\u0026rsquo;s level of risk perception, thereby promoting the occurrence of altruistic behavior.\\u003c/p\\u003e\\u003cp\\u003eTrust in authoritative information sources has a significant negative moderating effect on the relationship between information sources and risk perception. Further detailed analysis indicates that this moderating effect is present mainly in the pathways for \\u0026ldquo;mass media information sources\\u0026rdquo; and \\u0026ldquo;interpersonal information sources\\u0026rdquo; but is not significant in the \\u0026ldquo;authoritative information source\\u0026rdquo; pathway. This suggests that trust in authoritative sources has an exclusive reinforcement effect: under conditions of high trust, the public tends to rely more on authoritative channels, thereby reducing their sensitivity to and acceptance of information from nonauthoritative sources, which weakens the influence of mass media and interpersonal communication on risk perception [\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. This finding offers a nuanced amendment to existing risk communication theory. Traditional views tend to emphasize that trust enhances the effectiveness of information dissemination. Our study, however, further reveals that trust not only is an \\u0026ldquo;additive factor\\u0026rdquo; for information adoption but can also act as an \\u0026ldquo;interfering variable\\u0026rdquo; for other information pathways. Through a cognitive filtering mechanism, trust influences the public\\u0026rsquo;s willingness to accept and deeply process diverse information. This mechanism can be regarded as an \\u0026ldquo;information focus effect\\u0026rdquo;, stemming from the dual factors of the limited nature of risk cognition resources and the path dependence of trust.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eOn the basis of the PADM and risk communication theory, this study systematically explored the path and mechanism of the influence of multidimensional risk communication strategies on public altruistic protective behaviors during public health emergencies. The findings show that risk communication strategies across all dimensions\\u0026mdash;information sources, communication content, narrative styles, and communication media\\u0026mdash;have significant impacts on public altruistic protective behavior, with risk perception serving as a mediating bridge. Moreover, trust in authoritative information sources significantly moderates the relationship between information sources and risk perception, resulting in a \\u0026lsquo;high-trust attenuation effect\\u0026rsquo;, meaning that at high levels of trust, the marginal impact of information sources on risk perception is weakened. These insights enrich the theoretical understanding of the structure and mechanisms of risk communication in crisis contexts, extend the applicability of the PADM to the domain of altruistic behavior, and underscore the pivotal role of information trust as an intervention point in the digital era.\\u003c/p\\u003e\\u003cp\\u003eFrom a practical perspective, this study offers the following policy recommendations for government and public health authorities to enhance communication strategies during public health emergencies. First, establish a diversified and interactive structure of information sources. Governments should actively integrate authoritative media, mass media platforms, and interpersonal communication networks to improve the efficiency and reach of information dissemination, thereby reducing dependence on any single source. Second, differentiated content delivery and tailored messaging of risk information should be promoted. Communication materials should be adapted to the informational preferences and psychological profiles of different target groups to enhance message persuasiveness and actionability, thereby bridging the gap between risk perception and behavioral response. Third, the strategic combination of narrative styles should be optimized. Integrating the credibility of data-based messaging with the emotional appeal of narrative storytelling can enhance audience identification, foster a sense of personal responsibility, and increase behavioral intention. Fourth, media synergy and cross-platform coordination should be strengthened. Greater alignment between traditional media and digital platforms should be encouraged to generate a multichannel amplification effect, increasing both the reach and retention of risk-related messages in critical moments.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec26\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003elimitations\\u003c/h2\\u003e\\u003cp\\u003eThis study has several limitations. First, we collected data through a questionnaire survey; although the sample covers a wide range and is representative, self-reported data can contain subjective bias. Second, while we examined the relationship between risk communication strategies and altruistic behavior, the causal chain linking the two requires more complex experimental designs or longitudinal studies for validation. Future research can be expanded in the following directions: (1) incorporate behavior tracking or experimental methods to strengthen causal inferences; (2) include additional psychosocial factors such as emotional variables and social norms to broaden the theoretical boundaries and empirical depth of altruistic protective behavior research.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003ePADM \\u0026nbsp; \\u0026nbsp;Protective Action Decision Model\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eEM \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Entropy Method\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eCW \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Combined Weight.\\u003c/p\\u003e\\n\\u003cp\\u003eIS \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Information Source\\u003c/p\\u003e\\n\\u003cp\\u003eAIS \\u0026nbsp; \\u0026nbsp; Authoritative information sources\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eMMIS \\u0026nbsp; Mass Media Information Sources\\u003c/p\\u003e\\n\\u003cp\\u003eIIS \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Interpersonal Information Sources\\u003c/p\\u003e\\n\\u003cp\\u003eCC \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Communication Content\\u003c/p\\u003e\\n\\u003cp\\u003eEI \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Epidemic Information\\u003c/p\\u003e\\n\\u003cp\\u003eIRI \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Institutional Response Information\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003ePI \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Preventive Information\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eNS \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Narrative Style\\u003c/p\\u003e\\n\\u003cp\\u003eDS \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Data-based Styles\\u003c/p\\u003e\\n\\u003cp\\u003eSS \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Story-based Styles\\u003c/p\\u003e\\n\\u003cp\\u003eCM \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Communication Media\\u003c/p\\u003e\\n\\u003cp\\u003eIT \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Internet\\u003c/p\\u003e\\n\\u003cp\\u003eTCSMS \\u0026nbsp;Telephone Calls and SMS\\u003c/p\\u003e\\n\\u003cp\\u003eTV \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Television\\u003c/p\\u003e\\n\\u003cp\\u003eRB \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Radio Broadcasts\\u003c/p\\u003e\\n\\u003cp\\u003eNPM \\u0026nbsp; \\u0026nbsp;Newspapers and Printed Materials\\u003c/p\\u003e\\n\\u003cp\\u003eF2F \\u0026nbsp; \\u0026nbsp; Face-to-Face Communication with Public Officials\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eEthics approval and consent to participate\\u0026nbsp;\\u003c/h2\\u003e\\n\\u003cp\\u003eThis study was performed in line with the principles of the Declaration of Helsinki and has received ethical approval from theMedical Ethics Committee of Guangxi University (No:GXU-2025-089) . Informed consent was obtained from all individual participants included in the study.\\u003c/p\\u003e\\n\\u003ch2\\u003eConsent for publication\\u0026nbsp;\\u003c/h2\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003ch2\\u003eData availability\\u003c/h2\\u003e\\n\\u003cp\\u003eThe dataset generated and analyzed during the current study is available from the corresponding author upon reasonable request.\\u003c/p\\u003e\\n\\u003ch2\\u003eCompeting interests\\u003c/h2\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003ch2\\u003eFunding\\u003c/h2\\u003e\\n\\u003cp\\u003eThis work was supported by the Education Department of Guangxi Zhuang Autonomous Region under Grant No. 2025KY0003; and by the Key Research Base of Humanities and Social Sciences of Universities in Guangxi Zhuang Autonomous Region：Regional Social Governance Innovation Research Center under Grant No. 202501100.\\u003c/p\\u003e\\n\\u003ch2\\u003eAuthors' contributions\\u003c/h2\\u003e\\n\\u003cp\\u003eYunpeng Xu and Shuning Wang designed this work. Linxiu Jiang collected the data. YunpengXu, Shuanglei Wwang and \\u0026nbsp;Shuning Wangperformed the statistical analysis and wrote the draft manuscript.YunpengXu edited the manuscript. All authors approved the final version of the manuscript.\\u003c/p\\u003e\\n\\u003ch2\\u003eAcknowledgements\\u003c/h2\\u003e\\n\\u003cp\\u003eWe would like to thank Shuai Li for his statistical support.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eHearit KM, Courtright JL: A social constructionist approach to crisis management: Allegations of sudden acceleration in the Audi 5000. \\u003cem\\u003eCOMMUN STUD\\u003c/em\\u003e 2003, 54(1):79-95. http://doi.org/10.1080/10510970309363267\\u003c/li\\u003e\\n\\u003cli\\u003eEiser J, Bostrom A, Burton I, Johnston D, McClure J, Paton D, van der Pligt J, White M: Risk interpretation and action: A conceptual framework for responses to natural hazards. \\u003cem\\u003eINT J DISAST RISK RE\\u003c/em\\u003e 2012, 1:5-16.http://doi.org/10.1016/j.ijdrr.2012.05.002\\u003c/li\\u003e\\n\\u003cli\\u003eRenn O: The role of risk perception for risk management. \\u003cem\\u003eRELIAB ENG SYST SAFE\\u003c/em\\u003e 1998, 59(1):49-62.https://doi.org/10.1016/S0951-8320(97)00119-1\\u003c/li\\u003e\\n\\u003cli\\u003eVan Bavel J, Baicker K, Boggio P, Capraro V, Cichocka A, Cikara M, Crockett M, Crum A, Douglas K, Druckman J\\u003cem\\u003e et al\\u003c/em\\u003e: Using social and behavioural science to support COVID-19 pandemic response. \\u003cem\\u003eNAT HUM BEHAV\\u003c/em\\u003e 2020, 4(5):460-471.http://doi.org/10.1038/s41562-020-0884-z\\u003c/li\\u003e\\n\\u003cli\\u003eJordan J, Yoeli E, Rand D: Don\\u0026apos;t get it or don\\u0026apos;t spread it: comparing self-interested versus prosocial motivations for COVID-19 prevention behaviors. \\u003cem\\u003eSCI REP-UK\\u003c/em\\u003e 2021, 11(1):20222. http://doi.org/10.1038/s41598-021-97617-5\\u003c/li\\u003e\\n\\u003cli\\u003eHabib M, Kaur P, Sharma V, Talwar S: Analyzing the food waste reduction intentions of UK households. A Value-Attitude-Behavior (VAB) theory perspective. \\u003cem\\u003eJ RETAIL CONSUM SERV\\u003c/em\\u003e 2023, 75.http://doi.org/10.1016/j.jretconser.2023.103486\\u003c/li\\u003e\\n\\u003cli\\u003eHeydari S, Zarei L, Sadati A, Moradi N, Akbari M, Mehralian G, Lankarani K: The effect of risk communication on preventive and protective Behaviours during the COVID-19 outbreak: mediating role of risk perception. \\u003cem\\u003eBMC PUBLIC HEALTH\\u003c/em\\u003e 2021, 21(1):54. http://doi.org/10.1186/s12889-020-10125-5\\u003c/li\\u003e\\n\\u003cli\\u003eLindell M, Mumpower J, Huang S, Wu H, Samuelson C, Wei H: Perceptions of protective actions for a water contamination emergency. \\u003cem\\u003eJ RISK RES\\u003c/em\\u003e 2017, 20(7):887-908. http://doi.org/10.1080/13669877.2015.1121906\\u003c/li\\u003e\\n\\u003cli\\u003eTerpstra T, Lindell M: Citizens\\u0026rsquo; Perceptions of Flood Hazard Adjustments An Application of the Protective Action Decision Model. \\u003cem\\u003eENVIRON BEHAV\\u003c/em\\u003e 2013, 45:993-1018. http://doi.org/10.1177/0013916512452427\\u003c/li\\u003e\\n\\u003cli\\u003eGladwin C, Gladwin H, Peacock W: Modelling Hurricane Evacuation Decisions With Ethnographic Method. \\u003cem\\u003eInternational journal of mass emergencies and disasters\\u003c/em\\u003e 2001, 19:117-143. http://doi.org/10.1177/028072700101900201\\u003c/li\\u003e\\n\\u003cli\\u003eLasswell HD: \\u003cem\\u003eThe structure and function of communication in society. In L. Bryson (Ed.), The communication of ideas\\u003c/em\\u003e. New York: Harper and Row.; 1948.\\u003c/li\\u003e\\n\\u003cli\\u003eRimal R, Real K: Perceived risk and efficacy beliefs as motivators of change: Use of the risk perception attitude (RPA) framework to understand health behaviors. \\u003cem\\u003eHUM COMMUN RES\\u003c/em\\u003e 2003, 29(3):370-399.http://doi.org/10.1111/j.1468-2958.2003.tb00844.x\\u003c/li\\u003e\\n\\u003cli\\u003eWojcieszak M, Kim N: How to Improve Attitudes Toward Disliked Groups. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2016, 43:785-809.http://doi.org/10.1177/0093650215618480\\u003c/li\\u003e\\n\\u003cli\\u003eGriffin R, Dunwoody S, Zabala F: Public reliance on risk communication channels in the wake of a Cryptosporidium outbreak. \\u003cem\\u003eRISK ANAL\\u003c/em\\u003e 1998, 18(4):367-375. http://doi.org/10.1111/j.1539-6924.1998.tb00350.x\\u003c/li\\u003e\\n\\u003cli\\u003eDeYoung SE, Sutton JN, Farmer AK, Neal D, Nichols KA: \\u0026ldquo;Death was not in the agenda for the day\\u0026rdquo;: Emotions, behavioral reactions, and perceptions in response to the 2018 Hawaii Wireless Emergency Alert. \\u003cem\\u003eINT J DISAST RISK RE\\u003c/em\\u003e 2019, 36:101078. http://doi.org/https://doi.org/10.1016/j.ijdrr.2019.101078\\u003c/li\\u003e\\n\\u003cli\\u003eYang S, Kang M, Johnson P: Effects of Narratives, Openness to Dialogic Communication, and Credibility on Engagement in Crisis Communication Through Organizational Blogs. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2010, 37(4):473-497.http://doi.org/10.1177/1077699017750360\\u003c/li\\u003e\\n\\u003cli\\u003eZebregs S, van den Putte B, Neijens P, de Graaf A: The Differential Impact of Statistical and Narrative Evidence on Beliefs, Attitude, and Intention: A Meta-Analysis. \\u003cem\\u003eHEALTH COMMUN\\u003c/em\\u003e 2015, 30(3):282-289.http://doi.org/10.1080/10410236.2013.842528\\u003c/li\\u003e\\n\\u003cli\\u003eChan MS, Winneg K, Hawkins L, Farhadloo M, Jamieson KH, Albarrac\\u0026iacute;n D: Legacy and social media respectively influence risk perceptions and protective behaviors during emerging health threats: A multi-wave analysis of communications on Zika virus cases. \\u003cem\\u003eSOC SCI MED\\u003c/em\\u003e 2018, 212:50-59. https://doi.org/10.1016/j.socscimed.2018.07.007\\u003c/li\\u003e\\n\\u003cli\\u003eHerovic E, Sellnow TL, Sellnow DD: Challenges and opportunities for pre-crisis emergency risk communication: lessons learned from the earthquake community. \\u003cem\\u003eJ RISK RES\\u003c/em\\u003e 2020, 23(3):349-364.http://doi.org/10.1080/13669877.2019.1569097\\u003c/li\\u003e\\n\\u003cli\\u003eCamaj L: The Consequences of Attribute Agenda-Setting Effects for Political Trust, Participation, and Protest Behavior. \\u003cem\\u003eJ BROADCAST ELECTRON\\u003c/em\\u003e 2014, 58(4):634-654. http://doi.org/10.1080/08838151.2014.966363\\u003c/li\\u003e\\n\\u003cli\\u003eMiao Q, Schwarz S, Schwarz G: Responding to COVID-19: Community volunteerism and coproduction in China. \\u003cem\\u003eWORLD DEV\\u003c/em\\u003e 2021, 137:105128. http://doi.org/https://doi.org/10.1016/j.worlddev.2020.105128\\u003c/li\\u003e\\n\\u003cli\\u003eCandelario DM, Vazquez V, Jackson W, Reilly T: Completeness, accuracy, and readability of Wikipedia as a reference for patient medication information. \\u003cem\\u003eJ AM PHARM ASSOC\\u003c/em\\u003e 2017, 57(2):197-200.http://doi.org/https://doi.org/10.1016/j.japh.2016.12.063\\u003c/li\\u003e\\n\\u003cli\\u003eFreberg K: Intention to comply with crisis messages communicated via social media. \\u003cem\\u003ePUBLIC RELAT REV\\u003c/em\\u003e 2012, 38(3):416-421.https://doi.org/10.1016/j.pubrev.2012.01.008\\u003c/li\\u003e\\n\\u003cli\\u003eTai Z STJ: Media dependencies in a changing media environment: The case of the 2003 SARS epidemic in China. \\u003cem\\u003eNEW MEDIA SOC\\u003c/em\\u003e 2007, 6(9):987-1009. http://doi.org/https://doi.org/10.1177/1461444807082691\\u003c/li\\u003e\\n\\u003cli\\u003eLee C: The Interplay Between Media Use and Interpersonal Communication in the Context of Healthy Lifestyle Behaviors: Reinforcing or Substituting? \\u003cem\\u003eMASS COMMUN SOC\\u003c/em\\u003e 2010, 13(1):48-66. http://doi.org/10.1080/15205430802694869\\u003c/li\\u003e\\n\\u003cli\\u003eLindell MK, Prater CS, Gregg CE, Apatu EJI, Huang S, Wu HC: Households\\u0026apos; immediate Responses to the 2009 American Samoa Earthquake and Tsunami. \\u003cem\\u003eINT J DISAST RISK RE\\u003c/em\\u003e 2015, 12:328-340.http://doi.org/https://doi.org/10.1016/j.ijdrr.2015.03.003\\u003c/li\\u003e\\n\\u003cli\\u003eKahlor L, Dunwoody S, Griffin R, Neuwirth K, Giese J: Studying heuristic-systematic processing of risk communication. \\u003cem\\u003eRISK ANAL\\u003c/em\\u003e 2003, 23(2):355-368. http://doi.org/10.1111/1539-6924.00314\\u003c/li\\u003e\\n\\u003cli\\u003eSinghal A: Effective health risk messages: A step-by-step guide. \\u003cem\\u003eJ HEALTH COMMUN\\u003c/em\\u003e 2004, 9(5):485-486.http://doi.org/10.1080/10810730490504350\\u003c/li\\u003e\\n\\u003cli\\u003eJin Y: Making Sense Sensibly in Crisis Communication: How Publics\\u0026apos; Crisis Appraisals Influence Their Negative Emotions, Coping Strategy Preferences, and Crisis Response Acceptance. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2010, 37(4):522-552.http://doi.org/10.1177/0093650210368256\\u003c/li\\u003e\\n\\u003cli\\u003eWong L, AbuBakar S: Health Beliefs and Practices Related to Dengue Fever: A Focus Group Study. \\u003cem\\u003ePLOS NEGLECT TROP D\\u003c/em\\u003e 2013, 7(7):e2310.http://doi.org/10.1371/journal.pntd.0002310\\u003c/li\\u003e\\n\\u003cli\\u003eLuttrell A, Petty R: Evaluations of Self-Focused Versus Other-Focused Arguments for Social Distancing: An Extension of Moral Matching Effects. \\u003cem\\u003eSOC PSYCHOL PERS SCI\\u003c/em\\u003e 2021, 12(6):946-954.http://doi.org/10.1177/1948550620947853\\u003c/li\\u003e\\n\\u003cli\\u003eKim J, Nan X: Temporal Framing Effects Differ for Narrative Versus Non-Narrative Messages: The Case of Promoting HPV Vaccination. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2019, 46:401-417. http://doi.org/10.1177/0093650215626980\\u003c/li\\u003e\\n\\u003cli\\u003eBatson CD, Batson JG, Slingsby JK, Harrell KL, Peekna HM, Todd RM: Empathic joy and the empathy-altruism hypothesis. \\u003cem\\u003eJ PERS SOC PSYCHOL\\u003c/em\\u003e 1991, 61(3):413-426. http://doi.org/10.1037/0022-3514.61.3.413\\u003c/li\\u003e\\n\\u003cli\\u003eLiu BF, Austin L, Lee Y, Jin Y, Kim S: Telling the tale: the role of narratives in helping people respond to crises. \\u003cem\\u003eJ APPL COMMUN RES\\u003c/em\\u003e 2020, 48(3):328-349. http://doi.org/10.1080/00909882.2020.1756377\\u003c/li\\u003e\\n\\u003cli\\u003eKim Y, Jung J: SNS dependency and interpersonal storytelling: An extension of media system dependency theory. \\u003cem\\u003eNEW MEDIA SOC\\u003c/em\\u003e 2017, 19(9):1458-1475. http://doi.org/10.1177/1461444816636611\\u003c/li\\u003e\\n\\u003cli\\u003eMorton T, Duck J: Communication and health beliefs - Mass and interpersonal influences on perceptions of risk to self and others. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2001, 28(5):602-626. http://doi.org/10.1177/009365001028005002\\u003c/li\\u003e\\n\\u003cli\\u003eSeo M: Amplifying panic and facilitating prevention: Multifaceted effects of traditional and social media use during the 2015 MERS crisis in South Korea. \\u003cem\\u003eJournalism \\u0026amp; Mass Communication Quarterly\\u003c/em\\u003e 2021, 1(98):221-240.\\u0026ensp;https://doi.org/10.1177/1077699019857693\\u003c/li\\u003e\\n\\u003cli\\u003eJones AM, Omer SB, Bednarczyk RA, Halsey NA, Moulton LH, Salmon DA: Parents\\u0026apos; source of vaccine information and impact on vaccine attitudes, beliefs, and nonmedical exemptions. \\u003cem\\u003eAdvances in preventive medicine\\u003c/em\\u003e 2012, 2012:932741. http://doi.org/10.1155/2012/932741\\u003c/li\\u003e\\n\\u003cli\\u003eTummers L, Bekkers V, Vink E, Musheno M: Coping During Public Service Delivery: A Conceptualization and Systematic Review of the Literature. \\u003cem\\u003eJ PUBL ADM RES THEOR\\u003c/em\\u003e 2015, 25(4):1099-1126.http://doi.org/10.1093/jopart/muu056\\u003c/li\\u003e\\n\\u003cli\\u003eKazi A, Jafri L: The use of mobile phones in polio eradication. \\u003cem\\u003eB WORLD HEALTH ORGAN\\u003c/em\\u003e 2016, 94(2):153-154. http://doi.org/10.2471/BLT.15.163683\\u003c/li\\u003e\\n\\u003cli\\u003eWang L, Graddy E: Social Capital, Volunteering, and Charitable Giving. \\u003cem\\u003eVOLUNTAS: International Journal of Voluntary and Nonprofit Organizations\\u003c/em\\u003e 2008, 19(1):23-42. http://doi.org/10.1007/s11266-008-9055-y\\u003c/li\\u003e\\n\\u003cli\\u003eZavyalova A, Pfarrer M, Reger R, Shapiro D: MANAGING THE MESSAGE: THE EFFECTS OF FIRM ACTIONS AND INDUSTRY SPILLOVERS ON MEDIA COVERAGE FOLLOWING WRONGDOING. \\u003cem\\u003eACAD MANAGE J\\u003c/em\\u003e 2012, 55(5):1079-1101.http://doi.org/10.5465/amj.2010.0608\\u003c/li\\u003e\\n\\u003cli\\u003eValente T, Saba W: Campaign exposure and interpersonal communication as factors in contraceptive use in Bolivia. \\u003cem\\u003eJ HEALTH COMMUN\\u003c/em\\u003e 2001, 6(4):303-322. http://doi.org/10.1080/108107301317140805\\u003c/li\\u003e\\n\\u003cli\\u003eSpitale G, Germani F, Biller-Andorno N: The PHERCC Matrix. An Ethical Framework for Planning, Governing, and Evaluating Risk and Crisis Communication in the Context of Public Health Emergencies. \\u003cem\\u003eAM J BIOETHICS\\u003c/em\\u003e 2024, 24(4):67-82. http://doi.org/10.1080/15265161.2023.2201191\\u003c/li\\u003e\\n\\u003cli\\u003eIckert J, Stewart I: Earthquake risk communication as dialogue - insights from a workshop in Istanbul\\u0026apos;s urban renewal neighbourhoods. \\u003cem\\u003eNAT HAZARD EARTH SYS\\u003c/em\\u003e 2016, 16(5):1157-1173. http://doi.org/10.5194/nhess-16-1157-2016\\u003c/li\\u003e\\n\\u003cli\\u003eWilliams L, Rasmussen S, Kleczkowski A, Maharaj S, Cairns N: Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic. \\u003cem\\u003ePsychology, Health \\u0026amp; Medicine\\u003c/em\\u003e 2015, 20(7):832-837. http://doi.org/10.1080/13548506.2015.1028946\\u003c/li\\u003e\\n\\u003cli\\u003eYe Y, Wang R, Feng D, Wu R, Li Z, Long C, Feng Z, Tang S: The Recommended and Excessive Preventive Behaviors during the COVID-19 Pandemic: A Community-Based Online Survey in China. \\u003cem\\u003eINTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH\\u003c/em\\u003e 2020, 17(19):6953.http://doi.org/10.3390/ijerph17196953\\u003c/li\\u003e\\n\\u003cli\\u003eHong W, Liu R, Ding Y, Hwang J, Wang J, Yang Y: Cross-Country Differences in Stay-at-Home Behaviors during Peaks in the COVID-19 Pandemic in China and the United States: The Roles of Health Beliefs and Behavioral Intention. \\u003cem\\u003eINTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH\\u003c/em\\u003e 2021, 18(4):2104. http://doi.org/10.3390/ijerph18042104\\u003c/li\\u003e\\n\\u003cli\\u003eLiu Z, Huang X: Evaluating the credibility of scholarly information on the web: A cross cultural study. \\u003cem\\u003eThe International Information \\u0026amp; Library Review\\u003c/em\\u003e 2005, 37(2):99-106. http://doi.org/https://doi.org/10.1016/j.iilr.2005.05.004\\u003c/li\\u003e\\n\\u003cli\\u003eZhang H, Yang C, Deng X, Luo C: How Authoritative Media and Personal Social Media Influence Policy Compliance Through Trust in Government and Risk Perception: Quantitative Cross-Sectional Survey Study. \\u003cem\\u003eJ MED INTERNET RES\\u003c/em\\u003e 2025, 27.http://doi.org/10.2196/64940\\u003c/li\\u003e\\n\\u003cli\\u003eCutilli C: Seeking Health Information What Sources Do Your Patients Use? \\u003cem\\u003eORTHOP NURS\\u003c/em\\u003e 2010, 29(3):214-219.http://doi.org/10.1097/NOR.0b013e3181db5471\\u003c/li\\u003e\\n\\u003cli\\u003eSiegrist M, Gutscher H, Earle TC: Perception of risk: the influence of general trust, and general confidence. \\u003cem\\u003eJ RISK RES\\u003c/em\\u003e 2005, 8(2):145-156.http://doi.org/10.1080/1366987032000105315\\u003c/li\\u003e\\n\\u003cli\\u003eSiegrist M, Cvetkovich G, Roth C: Salient value similarity, social trust, and risk/benefit perception. \\u003cem\\u003eRISK ANAL\\u003c/em\\u003e 2000, 20(3):353-362. http://doi.org/10.1111/0272-4332.203034\\u003c/li\\u003e\\n\\u003cli\\u003eVaughan E, Tinker T: Effective Health Risk Communication About Pandemic Influenza for Vulnerable Populations. \\u003cem\\u003eAM J PUBLIC HEALTH\\u003c/em\\u003e 2009, 99:S324-S332. http://doi.org/10.2105/AJPH.2009.162537\\u003c/li\\u003e\\n\\u003cli\\u003eYang S, Kang M, Johnson P: Effects of Narratives, Openness to Dialogic Communication, and Credibility on Engagement in Crisis Communication Through Organizational Blogs. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2010, 37(4):473-497.http://doi.org/10.1177/0093650210362682\\u003c/li\\u003e\\n\\u003cli\\u003eWesterman D, Spence P, Van der Heide B: Social Media as Information Source: Recency of Updates and Credibility of Information. \\u003cem\\u003eJ COMPUT-MEDIAT COMM\\u003c/em\\u003e 2014, 19(2):171-183. http://doi.org/10.1111/jcc4.12041\\u003c/li\\u003e\\n\\u003cli\\u003eChae J, Lee C: The Psychological Mechanism Underlying Communication Effects on Behavioral Intention: Focusing on Affect and Cognition in the Cancer Context. \\u003cem\\u003eCOMMUN RES\\u003c/em\\u003e 2019, 46(5):597-618.http://doi.org/10.1177/0093650216644021\\u003c/li\\u003e\\n\\u003cli\\u003ePaek H, Oh S, Hove T: How Fear-Arousing News Messages Affect Risk Perceptions and Intention to Talk About Risk. \\u003cem\\u003eHEALTH COMMUN\\u003c/em\\u003e 2016, 31(9):1051-1062. http://doi.org/10.1080/10410236.2015.1037419\\u003c/li\\u003e\\n\\u003cli\\u003eOh S, Lee S, Han C: The Effects of Social Media Use on Preventive Behaviors during Infectious Disease Outbreaks: The Mediating Role of Self-relevant Emotions and Public Risk Perception. \\u003cem\\u003eHEALTH COMMUN\\u003c/em\\u003e 2021, 36(8):972-981.http://doi.org/10.1080/10410236.2020.1724639\\u003c/li\\u003e\\n\\u003cli\\u003eCarlo G, Randall BA: The Development of a Measure of Prosocial Behaviors for Late Adolescents. \\u003cem\\u003eJ YOUTH ADOLESCENCE\\u003c/em\\u003e 2002, 31(1):31-44.http://doi.org/10.1023/A:1014033032440\\u003c/li\\u003e\\n\\u003cli\\u003eRutsaert P, Pieniak Z, Regan \\u0026Aacute;, McConnon \\u0026Aacute;, Kuttschreuter M, Lores M, Lozano N, Guzzon A, Santare D, Verbeke W: Social media as a useful tool in food risk and benefit communication? A strategic orientation approach. \\u003cem\\u003eFOOD POLICY\\u003c/em\\u003e 2014, 46:84-93. https://doi.org/10.1016/j.foodpol.2014.02.003\\u003c/li\\u003e\\n\\u003cli\\u003eGammage K, Klentrou P: Predicting Osteoporosis Prevention Behaviors: Health Beliefs and Knowledge. \\u003cem\\u003eAM J HEALTH BEHAV\\u003c/em\\u003e 2011, 35(3):371-382.http://doi.org/10.5993/AJHB.35.3.10\\u003c/li\\u003e\\n\\u003cli\\u003eKahlor L: PRISM: A Planned Risk Information Seeking Model. \\u003cem\\u003eHEALTH COMMUN\\u003c/em\\u003e 2010, 25(4):345-356.http://doi.org/10.1080/10410231003775172\\u003c/li\\u003e\\n\\u003cli\\u003eYang S: Effects of Government Dialogic Competency: The MERS Outbreak and Implications for Public Health Crises and Political Legitimacy. \\u003cem\\u003eJ MASS COMMUN Q\\u003c/em\\u003e 2018, 95:582383804.http://doi.org/10.1177/1077699017750360\\u003c/li\\u003e\\n\\u003cli\\u003eGreen M, Brock T: The role of transportation in the persuasiveness of public narratives. \\u003cem\\u003eJ PERS SOC PSYCHOL\\u003c/em\\u003e 2000, 79(5):701-721.http://doi.org/10.1037/0022-3514.79.5.701\\u003c/li\\u003e\\n\\u003cli\\u003eKreuter M, Green M, Cappella J, Slater M, Wise M, Storey D, Clark E, O\\u0026apos;Keefe D, Erwin D, Holmes K\\u003cem\\u003e et al\\u003c/em\\u003e: Narrative communication in cancer prevention and control: A framework to guide research and application. \\u003cem\\u003eANN BEHAV MED\\u003c/em\\u003e 2007, 33(3):221-235. http://doi.org/10.1007/BF02879904\\u003c/li\\u003e\\n\\u003cli\\u003eHo S: The Knowledge Gap Hypothesis in Singapore: The Roles of Socioeconomic Status, Mass Media, and Interpersonal Discussion on Public Knowledge of the H1N1 Flu Pandemic. \\u003cem\\u003eMASS COMMUN SOC\\u003c/em\\u003e 2012, 15(5):695-717.http://doi.org/10.1080/15205436.2011.616275\\u003c/li\\u003e\\n\\u003cli\\u003eYoo W, Choi D, Park K: The effects of SNS communication: How expressing and receiving information predict MERS-preventive behavioral intentions in South Korea. \\u003cem\\u003eCOMPUT HUM BEHAV\\u003c/em\\u003e 2016, 62:34-43.http://doi.org/https://doi.org/10.1016/j.chb.2016.03.058\\u003c/li\\u003e\\n\\u003cli\\u003eBesal\\u0026uacute; R, Pont-Sorribes C: Credibility of Digital Political News in Spain: Comparison between Traditional Media and Social Media. \\u003cem\\u003eSOC SCI-BASEL\\u003c/em\\u003e 2021, 10(5):170. http://doi.org/10.3390/socsci10050170\\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\":\"info@researchsquare.com\",\"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\":\"Risk Communication Strategies, Public Altruistic Protective Behavior, Risk Perception, Trust in Authoritative Information Sources, Public Health Emergencies\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7506021/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7506021/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eAltruistic protective behavior is pivotal to community resilience during public health emergencies, yet prior research has rarely integrated how multidimensional risk communication strategies shape such behavior. Drawing on the protective action decision model and risk communication theory, we examine how information sources, communication content, narrative style, and communication media influence public altruistic protective behavior through risk perception, and whether trust in authoritative information sources conditions these effects.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eWe conducted a cross-sectional online survey in mainland China (October\\u0026ndash;December 2023) using stratified site selection across 11 provincial-level regions. After data cleaning, 1,417 valid responses were retained. Validated multi-item scales were adapted to the Chinese context. Analyses included hierarchical ordinary least squares regressions, mediation tests with bias-corrected bootstrapping (PROCESS Model 4; 5,000 resamples), and moderation tests (PROCESS Model 1; 5,000 resamples). Multicollinearity and common-method bias were assessed (VIFs\\u0026thinsp;\\u0026lt;\\u0026thinsp;5; Harman single-factor test).\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eEach communication dimension\\u0026mdash;information sources, communication content, narrative style, and communication media\\u0026mdash;was positively associated with altruistic protective behavior,albeit with heterogeneous effect sizes across dimensions. Risk perception exerted a significant positive mediating effect between risk communication and public altruistic protective behavior. Trust in authoritative information sources negatively moderated the path from information sources to risk perception, indicating a \\u0026ldquo;high-trust attenuation\\u0026rdquo; pattern whereby strong trust in authoritative sources reduces the incremental impact of non-authoritative sources on perceived risk.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e\\u003cp\\u003eFindings extend PADM to the collective-action domain by specifying how multidimensional risk communication promotes altruistic protection via risk perception and how trust calibrates source effects. Practice implications include building coordinated, multi-source messaging matrices; tailoring high-precision content to audience segments; combining story-based and data-based narratives; and orchestrating cross-media delivery.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Influence Mechanisms of Multidimensional Risk Communication Strategies on Public Altruistic Protective Behavior: Evidence from Public Health Emergencies\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-10-20 06:49:33\",\"doi\":\"10.21203/rs.3.rs-7506021/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"e9130a79-63ee-48de-8df7-ee6c738b4786\",\"owner\":[],\"postedDate\":\"October 20th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-03-30T18:40:08+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-10-20 06:49:33\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7506021\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7506021\",\"identity\":\"rs-7506021\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}