Enhancing Emergency Cognitive Ability in College Students Under Emergencies: A Study of Influencing Factors and Hierarchical Relationships

Abstract

This study addresses the need to enhance college students’ emergency cognitive ability by identifying key influencing factors and analyzing their hierarchical structure. To fill the gap in understanding these relationships, we used grounded theory to identify 12 influencing factors through a literature review, case analysis, and interviews. The interpretive structural modeling (ISM) method categorized these factors into three levels: direct, key, and root factors. Root factors such as risk awareness, crisis perception, and responsibility are core to the cognitive ability framework and have a profound impact on students’ responses to emergencies. Further, the matrix of cross-impact multiplications applied to classification (MICMAC) analysis categorized the factors based on driving force and dependency, showing strong interrelationships. The integration of ISM-MICMAC methods offers a novel approach to understanding the hierarchical influence among factors, enabling educational institutions and policymakers to design targeted emergency training programs. By incorporating information technology into the educational process, this research provides practical guidance for enhancing students’ preparedness and resilience in emergencies. The findings support policy development and the design of effective educational interventions, offering valuable insights for administrators, policymakers, and emergency management professionals in creating safer, more resilient educational environments.

1. Introduction

China’s development is facing the daunting challenge of many overlapping contradictions and a confluence of risks and hidden dangers. With the rapid economic development and the acceleration of human social processes, emergencies have become increasingly common in people’s lives. The lack of emergency cognition ability is an important cause of casualties in emergencies [1]. Xi Jinping stressed the need to strengthen China’s emergency management system and capacity building during the nineteenth collective study session of the Political Bureau of the Central Committee. In the new normal of frequent emergencies, emergency management should focus more on advancing checkpoints and promoting the broad participation of basic forces. Qi et al. [2], using CiteSpace 5.3.R4 (64-bit) literature analysis software, conducted a knowledge map analysis of recent research hotspots and development trends in China’s emergency management. This analysis indicates that China’s future emergency management system and mechanisms will become more refined. During the 2020 National People’s Congress and Chinese People’s Political Consultative Conference, Zheng Hong, a member of the National Committee of the CPPCC and Vice President of Xihua University, stated that as society’s understanding of emergency management deepens, the demand for emergency management professionals is continuously increasing. Therefore, the discipline of emergency management should be scientifically positioned, and education for emergency management talent in colleges and universities should be strengthened [3]. The country’s emphasis on education has made college students a group that cannot be ignored. However, in recent years, the frequent emergencies in colleges and universities in China have attracted widespread attention from all sectors of society. For example, the Wenchuan earthquake in May 2008 caused the collapse of a three-story dormitory building in a secondary school, burying most of the students. In October 2010, a student at a school in Xi’an was sentenced to death for killing a person in a car crash. In April 2013, a postgraduate student at a university in Shanghai was tragically poisoned to death by his housemate. In March 2014, a fire broke out in a laboratory of a university in Beijing. In 2015, a university laboratory explosion occurred. In the first half of 2017, there were consecutive cases of missing students studying in the United States, tourists visiting Japan, and school-related personnel. The June 2019 Changning earthquake led to the phenomenon of emergency escape difficulties for students in the dormitory building of a university in Chongqing. In December 2020, a student dormitory at a university in Hunan caught fire. In March 2022, a student from Shanxi University of Finance and Economics died suddenly while running, and so on. Due to the lack of emergency cognition, self-rescue knowledge, and related skills among college students, tragedies can easily occur when facing emergencies [4]. Schools shoulder the responsibility of cultivating talent for society, and frequent emergencies have hurt both colleges and universities and society, especially causing physical and mental harm to college students. Behind these emergencies lies an urgent need to cultivate and enhance college students’ emergency cognitive ability, which has become an important issue to address.

With the frequent occurrence of emergencies in colleges and universities, strengthening students’ emergency cognitive ability has become one of the core objectives of emergency education in these institutions. However, the current emergency education in colleges and universities generally has issues such as an incomplete system, superficial content, and insufficient training, which fail to genuinely improve students’ emergency cognitive level [5]. Research has found that college students often exhibit a lack of risk awareness, self-rescue knowledge, and essential emergency skills when facing emergencies [6]. These deficiencies are not only related to the design of educational content but are also closely tied to the development of cognitive ability under the influence of multiple factors, such as psychological traits, family background, and school educational resources. Frequent emergencies have a significant impact on college students. Whether natural disasters, social incidents, or political conflicts, these events pose significant challenges to college students’ lives and studies [7]. The emergency cognition of college students in the face of emergencies has become particularly important, making it essential to seriously consider how to enhance their emergency cognitive ability. The cultivation and formation of emergency cognitive ability among college students are influenced by various factors. For example, physiological factors (sensory organs, nervous system, etc.) [8,9], psychological factors (personality, emotions, etc.) [10], school emergency education, family safety education [11,12], etc. The relationships between these factors are complex and diverse, intertwining to form a multi-layered structure. Therefore, analyzing a single factor alone is insufficient to reveal the full picture of emergency cognitive ability. A systematic approach is needed to clarify the hierarchical relationships and interactions among these factors, enabling it to serve as a tool for measuring college students’ emergency cognition. In light of this, conducting an in-depth study of the key factors influencing college students’ emergency cognitive ability and systematically analyzing their interrelationships hold significant theoretical and practical value. Clarifying the hierarchical structure and mechanisms of these factors is essential for providing a scientific basis for designing more effective and systematic emergency education programs in colleges and universities, thereby genuinely enhancing students’ emergency response capability. This study primarily addresses the following two questions:

Question 1: What is the hierarchical structure of factors influencing college students’ emergency cognitive ability?

Question 2: How do these influencing factors interact with each other to affect college students’ emergency cognitive ability?

Therefore, this study introduces a combined approach of interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC) method to identify and analyze the main factors influencing college students’ emergency cognitive ability and their interrelationships, thereby constructing a systematic analytical framework.

This study will commence with an extensive literature review, gather data through on-site interviews and accident statistics, and employ grounded theory analysis to identify and select key indicators. Subsequently, data and expert opinions related to these indicators will be collected through survey methods. Afterward, the ISM method will be employed to determine the interdependencies among the selected variables. Finally, the MICMAC method will be used to categorize the variables based on their driving force and dependency. Through the comprehensive application of the ISM-MICMAC model, this study not only systematically reveals the hierarchical structure of complex factors influencing college students’ emergency cognitive ability but also provides a theoretical basis for constructing a scientifically sound and effective emergency education framework in colleges and universities. This innovative approach addresses the limitations of traditional single-factor analysis in current research, offering a new perspective and empirical support for the improvement and optimization of emergency education in colleges and universities, as well as for enhancing emergency cognitive ability.

2. Literature Review

The occurrence of emergencies not only results in significant casualties and property damage but also causes psychological harm to individuals [13]. Developing high-quality emergency plans in the face of emergencies is a fundamental task for emergency departments at all levels [14]. Before the occurrence of emergencies, it is necessary to establish emergency response plans, comprehensively consider various factors, train emergency rescue personnel, and disseminate emergency knowledge and provide education to the public. Students are not only the future of the country and the nation but also their health is closely related to the happiness of many families. Therefore, colleges and universities need to enhance students’ emergency cognitive ability, enabling them to remain calm and effectively respond to emergencies when they occur.

According to reports, from 2000 to 2020, a total of 110 incidents occurred in Chinese colleges and universities [15]. These accidents may have direct impacts on the lives and studies of college students, such as school closures, emergency evacuations, negative effects on their psychological well-being, and so on. College students are often defined as a vulnerable group, especially during the critical phase of a disaster. Research has shown that college students often underestimate risks, lack sufficient attention to disasters, have inadequate knowledge of emergency response in their studies, and rarely participate in any preparedness activities [16]. Fishbein and Ajzen, from the perspective of cognitive psychology and decision making research, explained how individuals decide to take measures to protect themselves from the harm of disasters [17]. Cognitive factors in risk perception include risk cognition, personal judgments of the likelihood of an event occurring, judgments of the potential impact of the event, risk salience, and personal consideration of the frequency of risks. Learning from historical disaster experiences has been demonstrated to influence risk cognition. Research has found that individuals who have experienced danger are more likely to worry about future events, indicating that risk awareness influences crisis perception ability [18]. Ho et al. found that individuals who have experienced disasters are more likely to anticipate the occurrence of disasters compared to those with limited experience. This finding is related to the level of mastery in emergency response and crisis perception of disasters [19]. Cui and Han found that, compared to people who have never experienced an earthquake, people who have experienced an earthquake perceive a higher risk of earthquakes [20]. Paton et al. argued that learning from disaster experiences has a positive impact on risk emergency cognition [21]. Greer et al. studied earthquake risk perception and risk adjustment among college students, suggesting that risk perception is more likely to be related to post-disaster adjustment measures. Pre-disaster attention and insufficient risk perception are not sufficient to motivate individuals to adjust their risk response [22].

Accident investigations have indicated that improper handling behavior is the most significant influencing factor. This behavior is influenced by the level of attention to disasters and the learning and application of disaster knowledge. Both students and teachers demonstrate a low level of attention to disasters and a lack of safety awareness and safety culture [23]. Human intervention is highly significant in reducing the occurrence of accidents. Teaching students safety knowledge and instilling safety awareness can enhance their emergency cognitive ability. Walters et al. investigated the current state of safety awareness, attitudes, and practices among university students in Trinidad regarding chemical laboratories. The findings indicated that while students had high awareness, there were significant gaps in hazard recognition and emergency response. More education and training were needed to improve students’ emergency cognition [24]. Papadopoli et al. explored the knowledge, attitudes, and behaviors of research lab personnel in Italy concerning chemical hazards in research activities. The results showed that individuals who frequently handled high-risk chemicals and conducted experiments had higher hazard cognition and had also received sufficient training in emergency response to accidents [25]. Assessing the severity of disaster threats can effectively reduce the impact of negative consequences of risks. Rainear and Lin studied the trust and perceptions of college students regarding risk information dissemination. Lower trust in information sources can predict higher risk perception, while greater trust in information sources can lead to stronger response efficacy and improved emergency cognition in disaster situations [26]. Current emergency distance teaching can enable teachers to appropriately review and assess the students’ state. Saputra and Rusmana conducted a questionnaire survey on 60 college students and found that students exhibited a positive attitude toward emergency distance teaching. This teaching method can also enhance students’ learning engagement in emergency cognition, behavior, and emotional participation [27]. Collecting information and data before and after a disaster can provide key insights into how individuals and organizations respond to emergencies [28].

Many scholars have conducted in-depth studies on individual factors influencing emergency cognitive ability. For example, research has focused on disaster attention, crisis perception, disaster knowledge acquisition and application, and safety awareness, revealing the specific impact mechanisms of these factors on cognitive ability. However, emergency cognitive ability in emergencies is influenced by multiple factors acting together, and analyzing a single factor may not fully reveal its complex influencing relationships. To address this, a growing number of studies have begun using systematic analysis methods, such as ISM, to construct hierarchical relationships among factors, identify key influencing factors, and understand their interactions. ISM is a systematic analysis tool that uses theoretical, conceptual, and computational frameworks to effectively construct directed graphs or network representations of complex relationships among elements [29]. ISM has unique advantages in analyzing the influencing factors of emergencies and revealing the hierarchical relationships between them, helping to integrate expert knowledge from a systems perspective for emergency management research. Huang and Chen used an ISM model to study the hierarchical structure of factors influencing risk perception of public health emergencies among the public in urban–rural fringe areas, categorizing 24 influencing factors into direct, indirect, and fundamental levels [30]. Zhao et al. used the multiple student death incidents at a university in Yunnan in 2015 as a case study, applying ISM to analyze the structural characteristics of effective influencing factors in the emergency response to university incidents. They also provided recommendations for improving emergency response procedures in colleges and universities [31]. Li et al. analyzed 11 influencing factors of the emergency industry from economic, social, and environmental perspectives and constructed an ISM model for the industry. The results indicated that investment in the emergency industry, input–output efficiency, and technological innovation are key factors directly impacting its development, while public safety awareness is a fundamental factor influencing the industry’s growth [32].

While ISM can effectively reveal the hierarchical relationships between factors, it has limitations in identifying the driving and dependency aspects of factors. To better understand the interactions among factors, MICMAC analysis can be combined with ISM to further clarify key drivers and dependencies, enhancing the model’s explanatory power. To date, the combined ISM-MICMAC approach has been widely applied across various research fields. Jin, using socio-technical theory, ISM, and MICMAC, studied the influencing factors of emergency management for college and university incidents from four subsystems: personnel, technology, organization, and environment. The results indicated that the organizational management subsystem is the most essential factor, and standardizing organizational structures and strengthening regulations are necessary to ensure effective emergency management from the ground up [33]. Luo et al. summarized and integrated risk factors for large sports events and then applied the ISM model to explore the hierarchical and logical relationships between these factors. Using MICMAC, they created a driver-dependence diagram for verification analysis, supporting risk management at large sports events [34]. Li et al., based on the context of fires and other emergencies in escape room venues, studied 26 factors affecting the evacuation of people from such spaces across four dimensions: personnel, building structure, environment, and fire management. Using Antagonistic ISM, MICMAC, and Network Hierarchy Analysis, they categorized these factors by importance, highlighting the need for stakeholders to address the deeper root causes to prevent the impact of emergencies at the source [35]. Li et al. developed a safety grading index system for emergency responders in building collapse scenarios and constructed an improved Grey-DEMATEL-ISM-MICMAC model to assess risk levels. The results indicated that addressing safety education should be considered the top priority, contributing to the improvement of emergency response levels in China [36]. Parizi et al. used ISM, MICMAC, and DEMATEL to study the key characteristics of urban physical resilience in emergencies and their interactions. The results indicated that “redundancy” and “robustness”, as two essential features supporting urban physical resilience, can inform resilience-based urban and spatial planning to bridge the gap between the theory and practice of urban physical resilience [37].

In summary, although previous studies have explored factors influencing emergency cognitive ability from single perspectives, such as disaster attention and crisis perception, there is a relative lack of systematic research on college students’ emergency cognitive ability. In existing emergency management research, methods like ISM and MICMAC are widely applied to analyze interactions among multiple factors, but their application to the college student population is limited. Additionally, these studies often have methodological gaps and fail to fully reveal the hierarchical structure and driving relationships among factors. Based on this, the present study proposes a combined ISM-MICMAC model to systematically analyze the factors influencing college students’ emergency cognitive ability, clarifying the hierarchical relationships and interdependencies. This approach aims to provide a theoretical framework and practical recommendations for emergency education and management in colleges and universities, addressing a gap in the field.

3. Methodology

This study on college students’ emergency cognitive ability employed a mix of qualitative and quantitative triangulation methods to evaluate the key factors influencing their emergency cognitive ability, thereby improving reliability and effectiveness [38]. The study was conducted in three stages. In the first stage, literature analysis and data collection were used, employing grounded theory to identify the influencing factors of college students’ emergency cognitive ability. This led to the construction of an indicator system for these factors. In the second stage, the ISM method was utilized to investigate the hierarchical structure and underlying mechanisms of the influencing factors of college students’ emergency cognitive ability, building an Interpretive Structural Equation Model. In the third stage, using the MICMAC method, the driving force and dependency of each influencing factor were calculated, categorizing the factors that impact college students’ emergency cognitive ability. This served to validate the reasonableness and feasibility of the ISM model. The overall research design framework is depicted in Figure 1.

Prior to conducting the study, our research plan was reviewed by multiple experts. Experts were selected based on their extensive experience and knowledge in fields relevant to emergency management, cognitive psychology, and educational strategies related to emergency preparedness. The selected experts included university faculty with a background in cognitive science, emergency management professionals with practical experience in crisis response, and educational psychologists specializing in cognitive development in high-stress situations. This diverse range of expertise ensured a comprehensive understanding of emergency cognitive capacity and contributed valuable insights into the factors influencing college students’ emergency cognition. In their view, conducting on-site interviews and soliciting opinions would not cause any psychological harm to participants, nor would it have any adverse social impact on them. Consequently, they agreed that the research plan was scientifically robust, feasible, and compliant with Chinese laws and regulations. Informed written consent was obtained from each participant prior to enrollment. All participants provided written informed consent before monitoring began. They were informed that the survey results would be used solely for academic research and would have no negative impact on them. Any follow-up research would only proceed with their permission. The study was conducted on a voluntary and anonymous basis.

3.1. Grounded Theory

Grounded theory is a qualitative research method based on empirical data, aimed at deriving new concepts and ideas from the data. It focuses on exploring logical relationships rather than verifying existing hypotheses [39]. The grounded theory method is a qualitative research approach suitable for theory construction, enhancing the contextual and practical relevance of research. Its methodological guidelines help to avoid limitations from procedural constraints and preset assumptions, allowing data collection and conclusions to remain free from empirical restrictions [40]. This method derives theory by gradually analyzing and summarizing empirical data, following a bottom–up, exploratory approach that results in more natural and objective concepts and categories.

The steps of grounded theory mainly include defining the research question, identifying data sources, data collection and organization, open coding, axial coding, selective coding, initial theory construction, and testing for theoretical saturation [41,42].

Step 1: It is essential to clarify the core research theme to allow flexible exploration during the study.

Step 2: Identify data sources, including interviews, case studies, and other diverse information sources, to ensure data richness.

Step 3: Proceed with data collection and organization to lay the foundation for subsequent analysis.

Step 4: Based on this, conduct open coding to break down data into various concepts and categories, discovering new themes and patterns.

Step 5: This is followed by axial coding, where relationships among categories are analyzed to form a higher-level framework.

Step 6: Selective coding then focuses on the core category, linking the main concepts to the core category and refining the theoretical framework.

Step 7: Afterward, an initial theory is constructed by deriving a model or framework that explains the data phenomena based on coding results.

Step 8: Theoretical saturation testing is conducted, with continuous data collection and analysis until no new concepts or relationships emerge, indicating that the theory has reached saturation.

In this study, the research question was first clarified to determine the core focus, centering on key factors influencing college students’ emergency cognitive ability. Data were primarily collected through typical incident cases and on-site interviews. Using grounded theory’s steps of open coding, axial coding, and selective coding, interview content, event types, and causes in accident cases are analyzed and factors extracted, ultimately constructing an index system of factors affecting college students’ emergency cognitive ability.

3.2. Interpretive Structural Modeling

The various influencing factors of college students’ emergency cognitive ability in emergencies can be viewed as a complex system, and these factors are interrelated. Interpretive structural modeling (ISM) is a structured approach developed by Warfield to represent a set of factors that influence the achievement of a single system [43]. Malone introduced the foundational concept, definition, and methodology of ISM and explained its utility from a complex systems perspective [44]. In recent research, ISM has been employed as an analytical tool that can explore the interrelationships between different decision objectives, breaking down complex, ambiguous, and fuzzy systems into graphical networks [45,46]. ISM aids in understanding both direct and indirect relationships among the factors impacting the system under consideration [47]. It leverages the practical understanding and consciousness of experts to break down complex systems into logical and hierarchical relationships among numerous components, forming structural models for a clear and insightful analysis of complex real-world problems [48]. The working principle of ISM involves breaking down the system to be analyzed into the individual factors that influence the system. It then analyzes the interrelationships among these individual factors and represents these relationships in the form of a matrix. Subsequently, through Boolean logic operations, the individual factors are layered, and the results are presented using a directed topological graph. ISM is suitable for the analysis of systems with numerous factors and complex interrelationships, and it provides an intuitive and effective way to depict causal relationships among factors. The specific steps are as follows [38]:

Step 1: Establish contextual relationships between factors. First, identify the key influencing factors to be analyzed and determine their contextual relationships. This step is typically completed through expert interviews and a literature review to clarify the interactions and dependencies among factors.

Step 2: Identify the system’s set of factors, denoted as $C=\left\{C_1,C_2,\cdots ,C_n\right\}$. Where $C_i(i=1,2,\cdots ,n)$ represents the i-th factor, and n is the total number of factors.

Step 3: Create the adjacency matrix I. Based on whether there is a direct influencing relationship between factor C_i and C_j, establish the adjacency matrix $I={(a_{ij})}_{n\times n}$. Where a_ij satisfies:

$$a_{ij}=\{\begin{array}{cc}1\hfill & C_i \mathrm{has} \mathrm{a} \mathrm{direct} \mathrm{impact} \mathrm{on} C_j.\hfill \\ 0\hfill & C_i \mathrm{has} \mathrm{no} \mathrm{direct} \mathrm{impact} \mathrm{on} C_j.\hfill \end{array}$$

(1)

In this formula, a_ij represents an element in matrix I, and if i = j, then a_ij = 0.

Step 4: Calculate the reachability matrix M. According to the rules of Boolean matrix operations, the reachability matrix M can be determined when the adjacency matrix I satisfies the following formula:

$$M={(I+E)}^{k+1}={(I+E)}^k\ne {(I+E)}^{k-1} k\ge 2$$

(2)

where M is the reachability matrix, I is the adjacency matrix, and E is the identity matrix.

Step 5: Establish hierarchical relationships. Based on the reachability matrix M, determine the reachable set P(C_i), precedent set Q(C_i), and intersection set U(C_i) for each factor. Here, P(C_i) represents the set of column factors in M with a value of 1 in the i-th row; Q(C_i) is the set of row factors in M with a value of 1 in the i-th column; and U(C_i) is the intersection of P(C_i) and Q(C_i). The first-level factors can be identified when U(C_i) satisfies the condition P(C_i)∩Q(C_i) = P(C_i). Remove the corresponding rows and columns in the reachability matrix M for the first-level factors to obtain a new reachability matrix. Repeat the above steps to identify the second-level factors, and so on, until all hierarchical factors are determined.

Step 6: Construct the interpretive structural model. Based on the calculations and analyses conducted as described above, construct a multi-level interpretive structural model of the system factors.

3.3. Matrix of Cross-Impact Multiplications Applied to Classification

The matrix of cross-impact multiplications applied to classification (MICMAC) is a matrix multiplication system developed by Duperrin and Godet, who introduced an operational method for ranking the elements of a system [49]. The main purpose of MICMAC is to evaluate the significance of the dimensions impacting the system and categorize them based on their influence and dependency within digital dimensions [50]. Gupta et al. emphasized that the MICMAC framework is used to explore the main drivers and dependencies of research system dimensions, based on the interaction between rows and columns [51]. Based on their characteristics, these variables are categorized into four classes.

➢

Cluster I (Linkage variables): Variables with both high influence and high dependence, playing a central role in system interactions.

➢

Cluster II (Independent variables): Variables that strongly influence others but are minimally affected by them.

➢

Cluster III (Autonomous variables): Variables with low influence and low dependence, having limited interaction within the system.

➢

Cluster IV (Dependent variables): Variables highly influenced by others but with low ability to influence in return.

To address the limitations of the ISM method and to better understand the interactions between factors, further analysis is conducted using MICMAC. This method helps to simplify and standardize the often prevalent unstable behavior in the process [52]. The specific steps are as follows:

Step 1: Calculate the driving force D_i and dependency R_j using the sum of the values in the rows and columns of the initial reachability matrix.

$$D_i={\displaystyle \sum _{j=1}^n{M}_{ij}} (i=1,2,\cdots ,n)$$

(3)

$$R_i={\displaystyle \sum _{i=1}^n{M}_{ij}} (i=1,2,\cdots ,n)$$

(4)

In this formula, M_ij represents an element in the reachability matrix M, where i is the row of the element, and j is the column of the element. D_i reflects the extent to which the resolution of factor C_i can drive the resolution of other factors, while R_j reflects the extent to which the resolution of factor C_j depends on the resolution of other factors.

Step 2: Create a four-quadrant matrix with x–y axes, where the x-axis represents the dependency of each influencing factor, and the y-axis represents the driving force of each influencing factor.

Step 3: Allocate each influencing factor to different categories.

Step 4: Interpret and apply the results. Based on the classification of each factor, analyze their roles and significance within the system. MICMAC analysis helps to identify key drivers and dependent factors in the system, providing a basis for further decision making and strategy development.

4. Results

4.1. Constructing the Indicator System of the Influencing Factors of College Students’ Emergency Cognitive Ability

4.1.1. Data Collection

Grounded theory guides the collection of data by studying the research problem. Researchers purposefully select data sources that are deemed relevant to the research and can provide rich information. Data can be in the form of text, including the perspectives of research subjects, experiences, or historical events. Data for this study were gathered from on-site interviews and typical accident cases, which complement and enhance each other.

Relevant topics for on-site interviews were selected through a literature review. Before conducting the main set of 20 interviews, a preliminary round of interviews was conducted with a small group of individuals to validate the interview questions. This preliminary stage helped to assess the clarity, relevance, and appropriateness of each question. Feedback from these preliminary interviews was used to refine and adjust the questions, ensuring they were effective in capturing insights related to emergency cognitive capacity. This validation process enhanced the reliability of the data collected during the main interviews. Building upon previous research and results from a small-scale preliminary interview, this study finalized the interview outline and specific questions, as shown in

Table 1. Interview outline.

Outline Numbers	Interview Topic
1	How much attention do you pay to natural disasters or emergencies that occur in society?
2	How do you typically obtain information about disasters and emergencies?
3	How well do you understand basic safety knowledge, such as the use of fire extinguishers and emergency first aid?
4	Do you enhance your emergency awareness by studying historical disaster cases?
5	Do you proactively pay attention to potential safety hazards in your daily life?
6	Are you able to recognize the risks you may face and take appropriate preventive measures?
7	Can you make quick and calm decisions and take action to protect yourself in emergencies?
8	Are you able to promptly perceive potential crises?
9	Are you willing to actively participate in activities promoting safety awareness and emergency drills?

. The outline covers three main aspects: “How to obtain disaster information?”, “Whether the corresponding emergency knowledge is acquired?”, and “How to respond to disasters?”. The interviewees in this study mainly included college students, members of the school emergency department, and relevant leaders. These individuals possessed knowledge of the daily behaviors of college students, were capable of making timely emergency responses when facing disasters, and could provide a wealth of information. To ensure the obtained information was sufficiently representative, the participants in this study were purposively selected based on their familiarity with emergency response and their specific roles within university emergency management. The selection criteria focused on individuals with relevant emergency knowledge and experience in handling or overseeing emergency situations. Specifically, the interviewees included two leaders in charge of safety in colleges and universities, four safety officers, and fourteen college students, for a total of twenty people. This combination ensured a diverse range of perspectives, providing a comprehensive understanding of factors influencing college students’ emergency cognitive ability. The average interview duration for each participant was approximately 30 min. Beyond the questions in the interview outline, participants were invited to share their perspectives on factors affecting college students’ emergency cognitive ability, drawing from their professional knowledge and work experience, to gather additional data. Before the interviews, the purpose and general content of the interviews were explained to the participants. With their consent, the interviews were recorded. Following the interviews, the content was compiled into Word documents for further analysis. Additionally, 50 typical cases from the past 10 years were selected as primary data. These data include detailed accident processes and causal analyses, making them suitable for foundational theoretical analysis.

4.1.2. Open Coding

The answers obtained from the on-site interviews were subjected to conceptualization to form concepts and categories. Concepts were refined and analyzed, with similar ones grouped together to form categories [53]. Meanwhile, 70% of the selected 50 accident cases were subjected to open coding, and some of the results are shown in

Table 2. Open coding (partial excerpt).

Number	Interview Answers or Typical Cases	Conceptualization	Categorization
1	I pay a low level of attention to disasters and typically obtain disaster information through social media.	The level of attention to disasters is low, and the information is obtained through social media.	Disaster information acquisition channel Level of media attention
2	I have some basic safety knowledge, but my understanding of specific safety knowledge is limited.	There is a high level of basic safety knowledge but a limited understanding of safety knowledge in specific fields.	Level of mastery of basic safety knowledge Level of mastery of safety knowledge in specific fields
3	I am aware of some safety-related laws and regulations, such as the Fire Safety Law and Emergency Management Law.	Awareness of safety laws and regulations.	Degree of understanding of relevant laws and regulations
4	I enhance my emergency awareness by studying historical disaster cases.	Enhancement of emergency awareness through studying historical disaster cases.	Learning from historical disaster experiences
5	I proactively pay attention to potential safety hazards in my daily life.	Possessing risk awareness and proactively paying attention to potential safety hazards.	Risk awareness Self-protection awareness
6	I can make quick and calm decisions and take action to protect myself in emergencies.	Having self-protection awareness and the ability to take action.	Self-protection awareness
7	In 2012, a formaldehyde leakage accident occurred in the 6th-floor laboratory of the Chemistry Building at Nanjing University’s Gulou Campus. The cause of the accident was that a student left the experiment midway, resulting in the formaldehyde leakage.	Lack of safety awareness and a weak sense of responsibility	Risk awareness Sense of responsibility
8	On 10 January 2016, a refrigerator caught fire in a laboratory at a university in Beijing’s Science and Technology Building. The cause of the fire was a short circuit in the refrigerator’s circuit, leading to self-ignition.	Low-risk awareness and inadequate safety inspections	Risk awareness
9	In 2016, a traffic accident occurred at Suzhou University, resulting in one fatality. The cause of the accident was that the driver did not drive according to regulations, and the road was covered in snow due to rain and snow on the day of the accident.	Insufficient attention to disasters, lack of crisis perception, and inadequate emergency measures and skills	Disaster information acquisition channel Crisis perception Level of emergency measures and skills mastery
10	In 2017, a landslide accident occurred at a university campus, resulting in the internal roads being buried and causing casualties and property damage. The geological conditions during the rainfall, mountain stability issues, and lack of relevant warning measures contributed to the landslide.	Failure to timely disseminate disaster information, inadequate emergency response measures and skills	Dissemination channels for disaster information Level of emergency measures and skills mastery
11	In 2020, a serious traffic accident occurred at Dalian University of Technology, resulting in the death of one student.	Insufficient self-protection awareness and a weak sense of responsibility	Self-protection awareness Sense of responsibility
12	In 2021, a laboratory explosion occurred at Nanjing University of Aeronautics and Astronautics, resulting in the death of two people and injury to nine others.	Inadequate knowledge and skills in laboratory safety, and lack of a sense of responsibility	Level of mastery of safety knowledge in specific fields Sense of responsibility

.

4.1.3. Axial Coding

Axial coding involves clustering and analyzing relationships among concepts and categories to establish core categories [54]. Through in-depth interviews and case accident analysis, the categories created during open coding were refined, allowing for the extraction and classification of key concepts. Ultimately, axial coding was obtained, as shown in

Table 3. Axial coding.

Number	Main Category	Corresponding Connotation
1	Disaster information acquisition channel	A way to help students gain a full understanding of the disaster situation and take timely countermeasures.
2	Dissemination channels for disaster information	It is used to achieve all-round and multi-angle information transmission and to improve public awareness of and response to disasters.
3	Learning from historical disaster experiences	Valuable experiences and lessons can be extracted to provide a scientific basis and guidance for disaster management and response work.
4	Level of media attention	Covering the importance, news value, influence, and hot topics of events.
5	Level of mastery of basic safety knowledge	Includes content related to safety concepts, safety skills, safety regulations, and standards, as well as information security and cybersecurity.
6	Level of mastery of safety knowledge in specific fields	Understanding and mastery of safety skills, safety measures and standards, and emergency plans in specific fields.
7	Degree of understanding of relevant laws and regulations	Ability to understand, update, and learn the content of laws and regulations.
8	Level of emergency measures and skills mastery	Mastery, learning, and updating of emergency measures and emergency skills.
9	Risk awareness	The ability to recognize, evaluate, and predict potential risks.
10	Self-protection awareness	Awareness and importance of personal safety, risk identification, and prevention ability, and mastery of self-protection and self-defense skills.
11	Crisis perception	Sensitivity to potential crises and risks, information collection and analysis ability, risk assessment and prediction ability.
12	Sense of responsibility	Sense of responsibility for personal behavior and decision making, social responsibility, cooperation, and team responsibility, as well as attitude towards continuous learning and self-improvement.

.

4.1.4. Selective Coding

Using axial coding, categories and main categories with specific associations were systematically generalized to identify the core categories that unified all categories [55]. Finally, they were identified as three core categories: disaster attention, safety knowledge, and safety awareness.

4.1.5. Theoretical Saturation Test

Theoretical saturation is the process of testing established categories with new data until no additional codes or categories appear, serving as the stopping criterion for sampling in grounded theory [56]. By re-coding the remaining 30% of typical accident cases, it was found that the newly obtained categories did not influence the already established main categories and core categories. Therefore, the theoretical categories reached saturation, and the core categories were considered relatively accurate, indicating successful theoretical saturation testing.

4.1.6. Index System for Influencing Factors of College Students’ Emergency Cognitive Ability

Through open coding, axial coding, selective coding, and theoretical saturation testing, three core categories and twelve main categories were identified, resulting in the construction of an index system for factors influencing college students’ emergency cognitive ability, as shown in

Table 4. Index system for influencing factors of college students’ emergency cognitive ability.

	Core Category	Main Categories
Index system for influencing factors of college students’ emergency cognitive ability A	Disaster attention B1	Channels for disaster information acquisition C1
		Pathways for disaster information dissemination C2
		Disaster history experience learning C3
		Media attention C4
	Safety knowledge B2	Degree of basic safety knowledge mastery C5
		Degree of mastery of security knowledge in specific fields C6
		Degree of understanding of relevant laws and regulations C7
		Degree of emergency measures and skill C8
	Safety awareness B3	Self-protection awareness C9
		Risk awareness C10
		Crisis perception C11
		Sense of responsibility C12

.

4.2. Analysis of the Hierarchy of the Influencing Factors of College Students’ Emergency Cognitive Ability

4.2.1. Construction of the Adjacency Matrix

From the results of grounded theory coding in Section 4.1, a list of 12 factors influencing college students’ emergency cognitive ability was compiled. Then, we sought the opinions of 15 experts in the fields of safety and emergency management as well as higher education on the logical relationships between these 12 influencing factors. If more than half of the experts agreed that C_i has a direct impact on C_j, then a_ij in the adjacency matrix I was set to 1. Otherwise, a_ij was set to 0. The resulting adjacency matrix is presented in

Table 5. Adjacency matrix I.

Factors	C1	C2	C3	C4	C5	C6	C7	C8	C9	C10	C11	C12
C1	0	0	0	0	0	0	0	0	0	0	0	0
C2	0	0	0	0	0	0	0	0	0	0	0	0
C3	0	0	0	0	1	0	1	0	0	0	0	0
C4	0	0	0	0	0	0	0	0	0	0	0	0
C5	0	0	0	0	0	0	1	0	1	0	0	0
C6	0	0	0	0	1	0	0	0	0	0	0	0
C7	0	0	0	0	0	0	0	1	0	0	0	0
C8	0	0	0	0	1	0	1	0	0	0	0	0
C9	1	0	1	1	1	1	1	1	0	0	0	0
C10	0	0	0	0	1	0	0	0	0	0	0	0
C11	1	0	1	0	1	1	0	1	0	0	0	0
C12	0	0	0	1	1	0	0	0	0	0	0	0

.

4.2.2. Construction of the Reachability Matrix

To further illustrate the indirect relationships between factors, constructing a reachability matrix based on the adjacency matrix is essential. Using Equation (2) and MATLAB tools, the reachability matrix M was calculated, as shown in

Table 6. Reachability Matrix M.

Factors	C1	C2	C3	C4	C5	C6	C7	C8	C9	C10	C11	C12	Driver Power
C1	1	0	0	0	0	0	0	0	0	0	0	0	1
C2	0	1	0	0	0	0	0	0	0	0	0	0	1
C3	1	1	1	1	1	1	1	1	1	0	0	0	9
C4	0	1	0	1	0	0	0	0	0	0	0	0	2
C5	1	0	1	1	1	1	1	1	1	0	0	0	8
C6	1	0	1	1	1	1	1	1	1	0	0	0	8
C7	1	1	1	1	1	1	1	1	1	0	0	0	9
C8	1	0	1	1	1	1	1	1	1	0	0	0	8
C9	1	1	1	1	1	1	1	1	1	0	0	0	9
C10	1	1	1	1	1	1	1	1	1	1	0	0	10
C11	1	0	1	1	1	1	1	1	1	0	1	0	9
C12	1	1	1	1	1	1	1	1	1	0	0	1	10
Dependence power	10	7	9	10	9	9	9	9	9	1	1	1

.

4.2.3. Hierarchical Relationship Division

Referring to the reachability matrix, the factors were divided into various levels, as shown in

Table 7. Layer relationship.

i	P(Ci)	Q(Ci)	U(Ci)	Lever
1	1	1, 3, 5, 6, 7, 8, 9, 10, 11, 12	1	1
2	2	2	2	1
3	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
4	4	3, 4, 5, 6, 7, 8, 9, 10, 11, 12	4	1
5	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
6	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
7	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
8	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
9	1, 3, 4, 5, 6, 7, 8, 9	3, 5, 6, 7, 8, 9, 10, 11, 12	3, 5, 6, 7, 8, 9	2
10	1, 3, 4, 5, 6, 7, 8, 9, 10	10	10	3
11	1, 3, 4, 5, 6, 7, 8, 9, 11	11	11	3
12	1, 3, 4, 5, 6, 7, 8, 9, 12	12	12	3

.

4.2.4. Construction of the Interpretive Structural Model

Using the hierarchical decomposition results, an ISM model for the factors influencing college students’ emergency cognitive ability was constructed, as shown in Figure 2. The influencing factors of college students’ emergency cognitive ability could be divided into three levels, namely, the direct factors layer, the critical factors layer, and the fundamental factors layer. The direct factors include channels for disaster information acquisition (C₁), pathways for disaster information dissemination (C₂), and media attention (C₄). The critical factors include disaster history experience learning (C₃), degree of basic safety knowledge mastery (C₅), degree of mastery of security knowledge in specific fields (C₆), degree of understanding of relevant laws and regulations (C₇), degree of emergency measures and skill (C₈), and self-protection awareness (C₉). The fundamental factors include risk awareness (C₁₀), crisis perception (C₁₁), and a sense of responsibility (C₁₂).

4.3. Analysis of the Influencing Factors of College Students’ Emergency Cognitive Ability Using MICMAC

Using the reachability matrix M, the driving and dependence values for each factor were calculated with Equations (3) and (4), as displayed in Table 6. The driving and dependence values revealed each factor’s role within the system, helping to identify which factors had a stronger influence on college students’ emergency cognitive ability. Factors with high driving force typically have significant influence over others, making them key drivers in the system, while factors with high dependence are more influenced by others and require additional support or improvement. To further analyze the relationships between these factors, we used the average values of driving and dependence as boundaries to create a quadrant classification chart for the 12 influencing factors, as shown in Figure 3. The 12 influencing factors were divided into four different quadrants: the first quadrant was linkage, the second quadrant was independent, the third quadrant was autonomous, and the fourth quadrant was dependent.

5. Discussion

5.1. Results Analysis

Although multiple methods exist in the literature to examine relationships between factors, this study employed ISM and MICMAC to establish hierarchical relationships and calculate the driving forces and dependencies of the factors. This approach offers a more comprehensive and systematic advantage in studying the relationships between factors compared to traditional methods [57].

Figure 2 provides a clear hierarchical structure of the influencing factors of college students’ emergency cognitive ability, demonstrating strong interrelationships among these 12 factors. It effectively conveys these relationships to emergency management personnel in an easily understandable manner, aiding managers in devising measures to enhance college students’ emergency cognitive ability [58]. ISM, grounded in the practical experience and knowledge of on-site experts, deduced both direct and indirect relationships among the influencing factors of college students’ emergency cognitive ability, providing deeper insights for managers to address specific requirements during emergencies.

In the current ISM model, factors related to disaster attention are at the top level of the model, factors related to safety knowledge are in the middle, and factors related to safety awareness are at the bottom of the ISM model (Figure 2). From Figure 2, it can be seen that disaster information acquisition (C₁), pathways for disaster information dissemination (C₂), and media attention (C₄) are located at the top level of the ISM model, belonging to the direct factor layer. These factors at the direct level influence college students’ emergency cognitive ability directly because they are directly related to information acquisition and attention allocation. The sources of information, methods of dissemination, and media attention all directly shape students’ level of cognition of potential risks. Different information channels can provide different types of information. Diverse sources of information can increase students’ comprehensive cognition of potential risks, including various types of disasters and emergencies [59]. Reliable information dissemination channels ensure accurate communication of information. For example, official emergency notification channels and trustworthy news media can provide timely and credible information, helping students to better understand the current situation. High media attention means that students are exposed to information related to disasters and emergencies more frequently [60]. This can increase their level of attention to potential risks and make it easier for them to understand current events. Their relationships are shown in Figure 4.

Figure 4 clearly illustrates the entire process from information acquisition to dissemination and enhanced attention. College students acquire information through diverse channels (C₁), which expands coverage via rapid dissemination pathways (C₂). High media attention (C₄) further increases the frequency of exposure, helping to strengthen students’ risk awareness and emergency cognitive ability.

Factors such as disaster history experience learning (C₃), degree of basic safety knowledge mastery (C₅), degree of mastery of security knowledge in specific fields (C₆), degree of understanding of relevant laws and regulations (C₇), degree of emergency measures and skill (C₈), and self-protection awareness (C₉) are positioned in the middle layer of the ISM model, belonging to the critical factors layer. These factors in the critical factors layer influence college students’ emergency cognitive ability because they involve specific knowledge, experience, and skills [61]. They can enhance students’ recognition of risks, their ability to take appropriate measures, and their self-protection awareness. Through personal experience or learning from others’ experiences, students can better understand the characteristics and consequences of disasters and emergencies. This can help them to respond more effectively to similar situations, improving their emergency cognition. The level of knowledge students possess directly affects their recognition of potential risks and their ability to take emergency measures [62]. Specific domain knowledge can help students better understand the risks and needs in specific areas, making them more specialized. Understanding relevant laws and regulations can guide students to take legal action, ensuring their actions are compliant. Self-protection awareness means that students are more willing to take proactive measures to protect themselves, improve their safety, and be capable of helping others in emergencies. Their relationships are shown in Figure 5.

Figure 5 illustrates the influence of key factors on college students’ emergency cognitive ability. In this diagram, learning from disaster history (C₃), mastery of basic safety knowledge (C₅), and expertise in specific safety fields (C₆) provide students with knowledge support and practical experience, enhancing their ability to respond to disasters by strengthening their mastery of emergency measures and skills (C₈). Awareness of relevant laws and regulations (C₇) helps students to maintain compliance in emergency situations. Ultimately, the improvement of emergency skills directly strengthens students’ self-protection awareness (C₉), thereby enhancing their emergency cognitive ability in critical incidents. This figure visually represents the interactions among key factors, highlighting the synergistic role of knowledge, skills, and legal compliance in enhancing emergency cognition.

Risk awareness (C₁₀), crisis perception (C₁₁), and a sense of responsibility (C₁₂) are in the bottom layer of the ISM model, belonging to the fundamental factor layer. These factors influence the emergency cognitive ability of college students at the fundamental level because they involve deeper thinking, perception, and a sense of responsibility [63]. They provide crucial qualities for dealing with emergencies and risks, forming a solid foundation for college students’ emergency cognitive ability. These factors can influence students’ risk perception, crisis recognition, and their sense of responsibility toward society and others. This means that they play a crucial role in encouraging college students to actively engage in the development of their emergency cognitive ability. These factors motivate individuals to actively seek information about potential risks and crises, be more proactive in problem detection, and take appropriate actions. At the same time, they can help students to quickly identify emergencies, enhance their willingness to participate in emergency actions, and take steps to protect themselves and others. Their relationships are shown in Figure 6.

In Figure 6, risk awareness (C₁₀) and crisis perception (C₁₁) work together to strengthen students’ sense of responsibility (C₁₂). Risk awareness helps students to identify potential crises, while crisis perception enables them to understand and respond to crisis situations. On this foundation, responsibility drives students to take action to protect themselves and others. This diagram illustrates how fundamental factors interact to provide essential support for college students’ emergency cognitive ability, building their foundational emergency awareness and proactive response capability.

The second aim of this study was to establish the relationship between the factors influencing college students’ emergency cognitive ability and their driving forces and dependencies through MICMAC analysis. As shown in Figure 3, MICMAC analysis classifies the factors into four types: linkage factors, independent factors, autonomous factors, and dependent factors. The linkage factors in the first quadrant (e.g., C₃, C₅, C₆, C₇, C₈, and C₉) exhibit strong driving and dependence forces. These factors are primarily situated in the middle of the ISM model, where they are influenced by driving factors and also impact dependent factors, acting as essential connectors in the system. They transmit the influence of driving factors to dependent factors, playing a crucial role in enhancing students’ knowledge levels and self-protection awareness. Through the intermediary role of these linkage factors, the influence of driving factors can be extended to a broader area of emergency cognition. The independent factors in the second quadrant (e.g., C₁₀, C₁₁, and C₁₂) have strong driving forces but low dependence. These factors have a significant positive impact on other system elements and operate relatively independently, unaffected by other factors. As root factors influencing college students’ emergency cognitive ability, they provide fundamental risk awareness and a sense of responsibility, enhancing students’ motivation and awareness in emergencies. These driving factors impact other elements directly or indirectly through intermediary effects. Prioritizing these factors in strategies to improve emergency cognitive ability would positively influence other system components. The third quadrant includes factors with weak driving forces and weak dependencies. Factors in this quadrant are typically irrelevant to the system. In this study, there are no factors belonging to this quadrant, indicating that the 12 factors considered in this research that influence college students’ emergency cognitive ability are all interrelated. The dependent factors in the fourth quadrant (e.g., C₁, C₂, and C₄) have weak driving forces but high dependence on other factors. Positioned at the top level of the ISM model, they primarily rely on the support of driving and linkage factors. Improving the driving and linkage factors can indirectly enhance the effectiveness of these dependent factors, thereby strengthening students’ rapid response capability in emergencies. Enhancing these dependent factors ultimately contributes to building a more comprehensive emergency cognition system.

These factors interact at different levels to collectively influence college students’ emergency cognitive ability. Driving factors provide foundational motivation, linkage factors transmit influence within the system, and dependent factors serve as the output of emergency cognitive ability, supported by other system elements. This hierarchical structure and the interrelationships indicate that enhancing college students’ emergency cognitive ability requires starting with core driving factors and progressively strengthening each level to achieve comprehensive improvement within the system.

In summary, this study used ISM-MICMAC analysis to identify key factors influencing college students’ emergency cognitive ability and revealed the interactions among these factors. Direct and key factors, as surface and intermediate influences on cognitive ability, provide specific knowledge and skill support, while fundamental factors supply core motivation, forming the foundation for building emergency cognition. Through a multi-level system analysis, this study effectively addresses both research questions, illustrating each factor’s role and interconnections in shaping college students’ emergency cognitive ability.

5.2. Countermeasures and Suggestions

Based on the ISM and MICMAC analyses, it is evident that there are complex interactions among the influencing factors of college students’ emergency cognitive ability, and each factor holds a different position and impact. In light of these findings, specific measures can be proposed to enhance and improve college students’ emergency cognitive ability.

5.2.1. Government Level

(1) Formulate comprehensive emergency education policies. The government should develop and promote comprehensive emergency education policies that encompass the school education system. These policies can include integrating emergency courses into the school curriculum, teacher training, emergency drills, and student support programs during emergencies. This will provide clear guidance to schools and ensure students receive comprehensive emergency education.

(2) Support research and information dissemination. The government can fund research projects aimed at understanding the influencing factors of college students’ emergency cognitive ability and effective educational strategies. The government could also establish online platforms or information centers to disseminate emergency and disaster information, converting available knowledge resources into formats tailored to local contexts in order to foster a “culture of safety” within communities [64].

(3) Establish emergency support systems. The government can support the establishment of emergency support systems on university campuses, including providing mental health support, volunteer organizations, and reserves of emergency resources. This will help students to access support and resources more effectively during emergencies.

5.2.2. University Administrators

(1) Integrate emergency education programs. Thahomina et al. examined the current trends in disaster preparedness courses for construction projects and other disciplines, highlighting the lack of sufficient emergency plans in educational institutions to adequately prepare students for a disaster response [65]. Therefore, university administrators should integrate emergency education programs into the academic curriculum, ensuring that all students receive basic emergency training. The Emergency Response Law also mandates that schools at all levels incorporate emergency knowledge into their teaching, including courses on disaster history, basic safety, and crisis awareness.

(2) Establish emergency response strategies. School administrators need to formulate clear emergency response strategies, including emergency notification systems, emergency drills, student support during emergencies, and safety resources. These strategies will help to enhance campus safety.

(3) Promote a culture of self-protection. University administrators can actively promote a culture of self-protection by encouraging students to participate in self-protection activities and volunteer work. When students learn disaster risk reduction through socially-based activities, their emergency cognitive ability is significantly enhanced [66]. This teaching approach often combines suitable learning theories and innovative tools to enhance students’ awareness of self-protection.

5.2.3. Student Self-Level

(1) Actively learn emergency knowledge. Students should proactively learn about emergency knowledge, including basic safety knowledge, disaster history, and regulations. They can improve their knowledge by participating in training, studying relevant materials, and engaging in volunteer work.

(2) Participate in emergency drills. Students can actively participate in campus emergency drills to learn how to respond to different types of emergencies. This will enhance their emergency awareness and response ability.

(3) Build community cooperation. Students can actively participate in campus and community emergency support organizations and volunteer activities, collaborating with others to enhance overall emergency preparedness.

5.3. Future Research

Through a literature review, on-site interviews, and accident case analysis, 12 factors influencing college students’ emergency cognitive ability were identified, and an ISM model was constructed along with MICMAC analysis. However, this study has some limitations. The formation of emergency cognitive ability in college students is a complex issue influenced by multiple factors, and it is not feasible to include all influencing factors in the model. Additionally, this study used grounded theory to identify these factors and employed ISM and MICMAC to analyze their relationships, providing a useful analytical framework. Future research will build on this study to further explore and expand pathways for developing college students’ emergency cognitive ability.

(1) Expanding sample diversity. Future research could broaden the scope from current limited samples to a national or even cross-cultural scale, incorporating participants from different ages, academic backgrounds, and regions to increase the generalizability of findings. Collaborating with multiple universities or educational institutions would help access a more diverse sample.

(2) Integrating smart educational tools. Future research could explore the application of big data and AI technologies in emergency cognitive education to enhance precision and effectiveness. For example, learning management systems (LMS) could track students’ learning progress and, combined with intelligent analysis tools, provide personalized feedback. Methods might include developing smart learning systems or mobile applications to monitor learning progress in real time and offer instant feedback and resources. Experimental studies could further assess the effectiveness of these technologies in improving emergency cognitive ability.

(3) Expanded application of the ISM-MICMAC model. Through this study, we have validated the effectiveness and advantages of the ISM-MICMAC model in analyzing the factors influencing college students’ emergency cognitive ability. In future research, this model can be further applied, particularly to improve other educational strategies in higher education. For instance, beyond cognitive ability, the model could be used to analyze factors affecting students’ disaster preparedness, health management, and crisis response capability. By incorporating real-world case studies and teaching practices, future studies could explore how the ISM-MICMAC model can enhance frameworks for disaster preparedness and health education, ultimately improving students’ overall crisis response skills.

6. Conclusions

This paper provides important guidelines for policymakers, university administrators, and scholars, aiming to enhance university students’ emergency cognitive ability through the integration of mathematical techniques and educational tools. By conducting a comprehensive literature review and accident case analysis, 12 key factors influencing college students’ emergency cognitive ability were identified. The ISM method was used to hierarchically categorize these factors into direct, key, and root factors, clarifying the structural relationships between the levels. Through MICMAC analysis, these factors were further classified based on their driving and dependency relationships into autonomous, dependent, linkage, and driving factors, determining their impact on the system and their attributes. This comprehensive model categorizes the influencing factors effectively, revealing the driving and dependency roles of each factor in the formation of students’ emergency cognitive ability. The paper offers new perspectives and frameworks for theoretical research, and in practice, it provides valuable guidance for designing and implementing data-driven educational plans and training programs. The strategies and recommendations proposed based on the model’s results promote the application of educational and information technologies in emergency management. This has significant implications for enhancing safety and resilience in educational environments.