Z世代の視点から見る緊急事態管理：修正版DPETツールの活用
2026 年 48 巻 2 号 p. 97-111
詳細
2026 年 48 巻 2 号 p. 97-111
Indonesia ranks second globally in natural disaster risk, underscoring the urgency of strengthening emergency preparedness. Generation Z, representing 28% of the population, plays a strategic role due to its digital fluency and entry into the workforce. This study assessed the disaster preparedness of Generation Z students using a modified Disaster Preparedness Evaluation Tool (DPET). A cross-sectional survey was conducted among 445 respondents aged 21–25 years. Data were collected through an online questionnaire covering demographics, knowledge, skills, and preparedness. Descriptive statistics, independent t-tests, one-way ANOVA, Pearson correlation, and multiple linear regression were used for analysis. Knowledge (M = 4.87), skills (M = 4.74), and preparedness (M = 4.65) were in the moderate range (scale 1–6). Prior disaster training, university region, and frequency of social media use significantly influenced preparedness (p < 0.05). Strong positive correlations were found between knowledge, skills, and preparedness (r = 0.77–0.82). Regression analysis identified skills, prior training, and knowledge as significant predictors, with skills being the most influential. The findings highlight the need to integrate structured disaster education, simulations, and digital interventions into higher education curricula. Enhancing experiential learning is critical to bridging the gap between digital awareness and real-world emergency response among youth in disaster-prone regions.
Natural disasters are among the most critical challenges for human societies, often overwhelming local capacities and necessitating external assistance. In 2023 alone, 399 natural hazard-related disasters affected more than 93 million people and caused over 86,000 deaths worldwide [1]. There have been several disasters in countries all over the world. Asia is the most prone region, with 152 disasters occurring in 2023, an increase compared to the annual average in the previous 30 years [2]. The World Risk Report affirmed in 2024 that Indonesia ranks second globally in disaster risk with a World Risk Index score of 41.13, just behind the Philippines. This ranking reflects Indonesia’s high exposure to natural hazards like earthquakes, tsunamis, and floods, combined with significant vulnerability and limited capacity to respond effectively [3]. This vulnerability is driven by Indonesia’s unique geological setting along the Pacific Ring of Fire, with 127 active volcanoes, frequent earthquakes, and recurrent hydrometeorological hazards [4]. A study conducted by Faradiba et al identified five clusters based on the level of vulnerability at the sub-district/village level, stating that the top five provinces with the highest disaster-prone areas were Aceh, North Sumatra, West Java, East Java, and Central Sulawesi [5]. The findings indicate that sub-districts and villages in Indonesia can be categorized according to their vulnerability levels.
Sumatra has repeatedly faced severe geological and hydrometeorological disasters over the past two decades, underlining its extreme vulnerability. In May 2024, monsoon rains triggered flash floods and lahars in West Sumatra, particularly in Agam and Tanah Datar, killing more than 55 people, damaging hundreds of structures, and disrupting the Padang–Bukittinggi national road [6]. Earlier, in 2010, a 7.7-magnitude earthquake off the western coast of Sumatra in 2010 generated a tsunami that struck the Mentawai Islands, killing 448 people and damaging public facilities [6]. In 2005, an 8.6-magnitude earthquake in Nias and Simeulue caused over 1,300 deaths and hundreds of injuries, while the 2004 Indian Ocean tsunami resulted in 227,898 deaths across 14 countries, with Aceh being the hardest hit [7]. These recurring disasters clearly demonstrate the urgent need for sustained disaster risk reduction and mitigation strategies across Sumatra.
Indonesia has faced frequent and deadly disasters in recent years. In November 2022, a 5.6-magnitude earthquake struck Cianjur, West Java, killing 635 people and injuring over 7,000 [8]. More recently, Meteorology, Climatology, and Geophysical Agency (BMKG in Indonesia) reported intense seismic activity in January 2025: 254 aftershocks in Kolaka Timur, Southeast Sulawesi (largest M 5.1, up to V MMI) [9]. 106 earthquakes in West Java (strongest M 4.7), and 142 incidents in East Java within one week (largest M 4.3) [10]. Alongside seismic hazards, BMKG also recorded 1,891 extreme weather events floods, landslides, fallen trees, and infrastructure damage between January and mid-March 2025, reflecting the growing influence of climate change on hydrometeorological disaster [11].
Emergency management is essential to anticipate and respond to disasters, enabling communities to identify risks, assess potential impacts, and strengthen their capacity to prevent, prepare, respond, and recover [12]. Despite Indonesia being among the countries with the highest disaster frequency, research indicates that disaster management efforts have not yet been fully felt by communities [13]. A key demographic to be empowered is Generation Z (Gen Z; born late 1990s–2012), who are known for their strong digital orientation [14]. Gen Z now forms the largest population group in Indonesia, comprising 27.94% and surpassing the millennials [15]. A national survey further shows their wide geographic distribution across Java (60%), Sumatra (15%), Kalimantan (10%), Sulawesi (10%), and other islands (5%), reflecting their strategic importance in disaster preparedness initiatives [16].
Generation Z is highly proficient with digital technology, social media, and internet-based communication, often replacing face-to-face interaction with online engagement [17]. For instance, 79% of Turkish university students report checking their smartphones constantly [18], while in Indonesia 79.5% of the population has internet access, with 34% belonging to Gen Z [19]. This generation is digitally inclined, multitasking, creative, and values inclusivity, with strong interest in social and environmental issues. These traits carry important implications for education, highlighting the need for adaptive teaching methods that integrate technology and interactive learning [19]. Compared to earlier generations, Gen Z students also demonstrate greater self-confidence, competitiveness, curiosity, independence, and individuality [20].
A study by Seemiller and Grace, found that Generation Z generally leans moderate to liberal on social issues [21]. Along with Feinman, this perspective can positively influence emergency management by promoting a more inclusive approach to preparedness, response, and recovery [22]. In a study on Knowledge, Attitude, and Practice of Fire Safety Systems and Preparedness Among Students at Higher Learning Institutions conducted by Zul et al, the results showed that more than half of the students who were respondents had good knowledge, positive attitudes and good practices towards fire safety preparedness [23]. A statistically significant relationship was found between age and fire safety knowledge; those under 20 showed the highest proportion of excellent knowledge (58.2%), followed by the level of knowledge in the 21–25 age group (34.4%). This study concluded that age, gender, and education level appear to influence attitudes and understanding of fire safety. Younger individuals showed higher awareness, likely due to targeted educational programs. However, no significant link was found between education level and fire safety knowledge overall, implying that factors like hands-on training may play a more important role.
Limited research hampers understanding of how Gen Z confronts emergencies. A study during COVID-19 emphasized the need for Gen Z to recognize risks, respond effectively, and build resilience [24]. Most emergency management tools were designed with older generations in mind, yet Gen Z’s distinct digital behaviors may offer new perspectives for crisis management. Given Indonesia’s high disaster ranking and the large proportion of Gen Z within its productive population, assessing their preparedness is essential to strengthen skills and knowledge for emergency response.
This study therefore examines how Gen Z in Indonesia views emergency management, focusing on students in their final college years and recent graduates, a group transitioning into the workforce and increasingly exposed to real-world risks. They are likely to have participated in formal or informal preparedness programs, making them valuable informants for understanding Gen Z readiness. Sampling was concentrated in higher education institutions in Sumatra and Java, two disaster-prone regions frequently affected by earthquakes, floods, landslides, tsunamis, and volcanic eruptions. While previous studies mainly targeted health workers or youth in general, research specifically on Gen Z remains limited. Moreover, standardized instruments such as the Disaster Preparedness Evaluation Tool (DPET) are rarely adapted for this demographic. Therefore, this study aims to assess the level of disaster preparedness among Generation Z students in Indonesia and to identify key factors: knowledge, skills, and prior disaster training, that influence their readiness for emergencies. The findings are expected to inform the development of structured disaster education, simulation-based training, and digital preparedness initiatives within higher education settings.
Research Planning
This study adopts a semi-quantitative methodological approach that integrates both a quantitative survey, conducted through the use of a structured questionnaire, and an extensive literature review aimed at supporting the development of a robust conceptual framework. Within the context of emergency management research, a descriptive-correlational and cross-sectional research design was employed to explore and analyze the relationship between knowledge, skills, and preparedness among Generation Z. This design facilitates a comprehensive understanding of how cognitive and practical dimensions of disaster preparedness interact within this demographic group, proposing insights that can inform both policy and educational interventions.
Sampling Framework and Population
The target population for this study comprises members of Generation Z, defined as individuals born between 1998 and 2012, residing in Indonesia. The research employs a purposive sampling strategy to ensure feasibility and relevance, focusing on the following groups:
1. Third and fourth year undergraduate students
2. Fresh graduates
3. Individuals who are either undertaking post-graduation internships or have recently commenced employment
These cohorts are at a pivotal stage in their professional development, where heightened awareness of emergency preparedness is critically important. It is also likely that they possess prior experience with both formal preparedness training and informal training. Regarding the geographic and institutional scope of the sampling frame, the study targets polytechnic colleges and universities located in Java and Sumatra Island. These regions were selected based on the following criteria:
1. High exposure to natural disasters
2. Large populations of Generation Z students
3. Academic programs that include internships and active student organizations
The study strategically selects representative Indonesian higher education institutions to enhance the generalizability of its findings across diverse geographic, socio-cultural, and academic contexts. Each institution reflects unique aspects of disaster resilience and community engagement, consistent with the study’s objectives.
Universitas Indonesia (UI), situated in the capital city of Jakarta, exemplifies urban disaster exposure and serves as a focal point for policy development due to its proximity to governmental institutions. Universitas Gadjah Mada (UGM) in Yogyakarta is notable for its strong emphasis on community engagement in disaster response, particularly through its Disaster Response Unit (DERU) and the mandatory Student Community Service Program (KKN-PPM), which actively involve students in disaster management initiatives nationwide. Politeknik Negeri Bandung (POLBAN) highlights the role of technical and vocational education in disaster resilience, integrating practical skills training with community service to ensure graduates are well-prepared for disaster preparedness and response. Universitas Sumatera Utara (USU) and Universitas Sriwijaya (UNSRI) represent the regional context of Sumatra, which is characterized by significant exposure to natural disasters. The inclusion of additional colleges and universities from Java and Sumatra further broadens the study’s coverage, capturing a wider range of regional disaster resilience strategies and responses.
By selecting these institutions, the research aims to provide a comprehensive analysis of disaster resilience within Indonesia’s diverse educational landscape.
Sample Size and Sampling Methodologies
The sample size was calculated with Cochran’s formula for unknown population proportion. This calculation incorporates a 15% buffer to mitigate non-response effects, a common practice in survey research to maintain statistical power and reliability. To ensure a robust representation of the target population and account for potential non-responses, a final sample size of 445 respondents was determined. Data collection was facilitated through online surveys, utilizing purposive sampling methods to target specific groups relevant to the study’s objectives. The primary channels for participant recruitment included:
1. College Student Organizations: Engaging with student bodies to distribute surveys among active members
2. Networks of Alumni and Career Centers: Leveraging established networks to reach a diverse pool of respondents
3. Online Communities and Social Media Platforms: Utilizing digital platforms to access a broader audience
Data Gathering Tool
The questionnaire was adapted from the Disaster Preparedness Evaluation Tool (DPET) developed by Setyawati et al and was adjusted to suit the characteristics of Generation Z [25]. The survey consists of 25 items and was distributed Online through Google Forms. Some questions were modified to fit the target samples, as the origin questionnaire was focused on the characterization of nurses. On the modified questionnaire, questions from the original questionnaire that were related to patient care were removed because they specifically fit the nurse characteristics, and some questions from the original questionnaire were modified to fit the sample’s characteristics, which is Gen Z; for example, questions related to social media and linked to the place where they studied or worked. The modification was only subjected to what Gen Z knows using the generic terms. It comprises Likert-scale questions arranged into Knowledge (11 items), Skills (6 items), Preparedness (8 items). Responses were collected on a six point Likert scale from strongly disagree (1) to strongly agree (6), with higher numeric values denoting more advanced knowledge, stronger skills, and greater disaster preparedness. The modified questionnaire has been tested for its validity and reliability. The result for the validity test was >0.2869 (∝=0.005) and the reliability test was 0.790 (Preparedness), 0.866 (Knowledge), and 0.838 (Skills), form which it can be concluded that the modified questionnaire was valid and reliable to be used for Gen Z preparedness level assessment. There were be further demographic questions covering age, educational level, disaster management preparedness training, university region origin, and social media usage frequency.
Data Analysis Planning
The data collected from the questionnaire were evaluated employing both descriptive and inferential statistical methods. Descriptive statistics were be used to capture the demographic attributes of the respondents and calculate the mean scores for each primary variable: knowledge, skills, and preparedness. Since there were some modifications in the questionnaires to adapt to the target respondents, Cronbach’s Alpha coefficient was undertaken to evaluate the internal consistency and reliability of each DPET construct.
| Origin | Modified |
|---|---|
| Preparedness | |
| 1. I participate in 1 of the following educational activities on regular basis: continuing education classes, seminars, or conferences dealing with disaster preparedness (knowledge) | I have participated in training/seminar/on boarding related to disaster preparedness management |
| 2. I participate in peer evaluation of skills on disaster preparedness and response | I have been evaluated or was given a role in emergency preparedness training. Example: as a floor warden |
| 3. I am able to describe my role in the response phase of a disaster in the context of my workplace, the general public, media, and personal contact | I have explained my role in my workplace if an emergency situation happens |
| 4. I participate in disaster drills or exercises at my workplace (clinic, hospital, etc) on a regular basis (knowledge) | I have participated in training or emergency drills in the workplace |
| 5. Additional (new) | I am initiative in sharing or proceeding disaster-related information for other people if emergency warnings happen |
| 6. I have personal/family emergency plans in place for disaster situations (skill) | I have a personal or group plan in dealing with disaster situations |
| 7. I have an agreement with loved ones and family members on how to execute our personal/family emergency plans (skill) | I have agreement with group members about the implementation of emergency plans |
| 8. I am familiar with the organizational logistics and roles among local, state, and federal agencies in disaster response situations | I understand the role of local or national foundations in emergency situations |
| Knowledge | |
| 1. I find that the research literature on disaster preparedness in understandable | I feel information according to emergency preparedness and management is easy to be access and understand |
| 2. I know where to find relevant research or information related to disaster preparedness and management to fill in gaps in my knowledge | I know reliable information resources in increasing my knowledge about disaster management |
| 3. I know who to contact (chains of command) in disaster situations in my community | I know who to contact in emergency situations at my college or workplace |
| 4. Additional (new) | I understand the differences between emergency response and post-disaster recovery phase |
| 5. Additional (new) | I know the location of and how to use safety equipment such as fire extinguisher and evacuation routes |
| 6. I am aware of what the potential vulnerabilities in my community are (eg, earthquake, floods, terror, etc) (skill) | I am aware of the types of disasters that might happen at my college or workplace |
| 7. I am familiar with the local emergency response system for disasters (skill) | I understand the early warning system that being used in my region |
| 8. In case of a bioterrorism/biological attack, I know how to use personal protective equipment (skill) | I know what to do when bioterrorism or biology attack happens |
| 9. I am familiar with accepted triage principles used in disaster situations (skill) | I understand the principles of triage in emergency situations |
| 10. I read journal articles related to disaster preparedness | I have watched education or promotion of disaster and post-disaster recovery on social media |
| 11. Additional (new) | I got information about disaster |
| Skill | |
| 1. I consider myself prepared for the management of disasters | I understand what to do in facing a disaster |
| 2. Additional (new) | I have basic skills in providing first aid in emergency situations |
| 3. As an RN, I would feel confident in my abilities as a direct care provider and first responder in disaster situations (preparedness) | I am confident to be first responder in emergency situation |
| 4. I would feel confident implementing emergency plans, evacuation procedures, and similar functions (preparedness) | I am confident about implementing emergency plans and evacuation procedures |
| 5. I know the limits of my knowledge, skills, and authority as an RN to act in disaster situations, and I would know when I exceed them | I know the limits of my authority and ability about what to do during a disaster |
| 6. Additional (new) |
Independent T-Tests and One-Way ANOVA were used to analyze the associations between the demographic characteristics of respondents and their perception of disaster preparedness. Additionally, correlation analysis, utilizing Pearson’s correlation based on data distribution, was performed to discover the correlations among the three primary variables: knowledge, skills, and preparedness. Where relevant, supplementary subgroup analyses were conducted to investigate disparities in preparedness according to variables such as age, educational level, disaster management training, university region of origin, and frequency of social media usage. This analysis aimed to identify contextual elements that may affect emergency preparedness levels among the Gen Z population. Furthermore, multiple linear regression tests were performed to determine the magnitude of the simultaneous and partial influence of dependent variables on disaster preparedness. This analysis was used to determine the proportion of variation in Gen Z preparedness that the regression model can explain through the coefficient of determination value (R2).
Ethical Clearance
This study received ethical approval from the Research Ethics Committee, Faculty of Medicine, Universitas Andalas, Indonesia (No. 501/UN.16.2/KEP-FK/2025), following a thorough review to ensure the protection of the rights and welfare of all research participants.
Demographic Characteristic of Participants
| Demographic Factors | n (Percentage/%) |
|---|---|
| Age | |
| ≤ 20 | 28 (6.3) |
| 21–25 | 410 (92.1) |
| > 25 | 7 (1.6) |
| Education Level | |
| College Student | 366 (82.2) |
| Worker | 79 (17.8) |
| Disaster Preparedness Management Training | |
| Yes | 399 (89.7) |
| No | 46 (10.3) |
| University Region Origin | |
| Jawa | 382 (85.8) |
| Sumatera | 63 (14.2) |
| Social Media Usage Frequency | |
| 1–2 days | 22 (4.9) |
| 3–4 days | 68 (15.3) |
| Every day | 355 (79.8) |
Table 2 presents the demographic characteristics of the participants, based on data from 445 respondents who completed an online questionnaire via Google Forms, Most of the respondents were between 21 and 25 years old, which aligns with the Generation Z cohort born between 1997 and 2012. Eighty-five point eight percent of the Gen Z respondents resided in Java Island, reflecting the island’s status as the most populous in Indonesia. Furthermore, around 82.2% of the Gen Z respondents were currently engaged in university, which indicates that most of them were still pursuing their education. Meanwhile, the rest of the Gen Z were already engaged in the workplace, where they already experienced the work environment. Additionally, about 89.7% of the respondents had participated in disaster preparedness management training through formal education or informal education, such as community programs, seminars, onboarding sessions, or online campaigns. In this study, Disaster Preparedness Management Training refers to any structured activity designed to enhance awareness, knowledge, and response capability in emergency situations. This high participation rate highlights the growing awareness and proactive engagement of Gen Z in disaster resilience initiatives.
Disaster Knowledge, Skills, and Preparedness
The Disaster Preparedness Evaluation Tool (DPET) questionnaires were analyzed to determine mean scores (SD), as shown in Tables 3–5. The highest mean score in Table 5 is on items about understanding local or national foundations’ role in emergency situations (mean 5.04), which means participants are well aware of the role of local or national foundations in emergency situations. The participants also took the initiative to share disaster-related information with others, which is proven by a mean score of 5.02 (strong).
| Items | Mean (SD) |
|---|---|
| I feel information according to emergency preparedness and management is easy to be accessed and understood | 4.85 (1.01) |
| I know reliable information resources in increasing my knowledge about disaster management | 4.99 (0.94) |
| I know whom to contact in emergency situation at my college or workplace | 4.95 (1.04) |
| I understand the differences between emergency response and post-disaster recovery phase | 4.74 (1.13) |
| I know the location and how to use safety equipment such as fire extinguisher and evacuation route | 4.80 (1.19) |
| I am aware the types of disasters that might happen at my college or workplace | 5.01 (0.94) |
| I understand early warning system that being used in my region | 4.84 (1.15) |
| I know what to do when bioterrorism or biology attack happen | 4.55 (1.33) |
| I understand the principles of triage in emergency situation | 4.52 (1.35) |
| I have watched education or promotion of disaster and post-disaster recovery in social media | 5.11 (0.88) |
| I got information about disaster | 5.17 (0.86) |
| Total | 4.87 (0.66) |
Table 3 shows that three items in knowledge of disaster management are included in the strong category. Most participants got information about disaster (mean 5.17) and had watched education or promotion about disasters and post-disaster recovery on social media (mean 5.11). Participants were also aware that the mean score of the knowledge scale was 4.87, which means that participants’ knowledge of disaster management is categorized as moderate. It can be interpreted that most of the respondents have a good enough understanding of disaster management.
| Items | Mean (SD) |
|---|---|
| I understand what to do in facing a disaster | 4.86 (0.99) |
| I have basic skills in providing first aid in emergency situations | 4.52 (1.28) |
| I’m confident to be first responder in an emergency situation | 4.56 (1.22) |
| I’m confident in implementing emergency plans and evacuation procedures | 4.59 (1.25) |
| I know the limits of my authority and ability during a disaster | 4.92 (1.04) |
| I understand how fundraising for disaster victims works in social media | 5.00 (0.98) |
| Total | 4.74 (0.81) |
Based on Table 4, one item has a strong category: the participant’s understanding of how fundraising for disaster victims works in social media (mean 5.00). The participant’s disaster management skill is categorized as moderate, which can be interpreted as meaning that most of the participants feel skilled enough in disaster management (mean 4.74).
| Items | Mean (SD) |
|---|---|
| I have participated in training/seminar/on boarding related to disaster preparedness management | 4.87 (1.13) |
| I have been evaluated or was given a role in emergency preparedness training. ex: as floor warden | 4.40 (1.46) |
| I have explained my role in my workplace if an emergency situation happens | 4.30 (1.46) |
| I have participated in training or emergency drill in the workplace | 4.69 (1.33) |
| I am initiative in sharing or proceeding disaster-related information for other people if emergency or warnings happen | 5.02 (0.95) |
| I have a personal or group plan in dealing with disaster situations | 4.48 (1.30) |
| I have agreement with group members according to how to implement emergency plans | 4.42 (1.36) |
| I understand the role of local or national foundation in emergency situations | 5.04 (0.89) |
| Total | 4.65 (0.85) |
Preparedness levels for disaster management were categorized as weak (mean 1.00–2.99), moderate (mean 3.00–4.99), and strong (mean 5.00–6.00). The mean score for the preparedness subscale was 4.65 (SD = 0.85), the knowledge subscale was 4.87 (0.66), and the skill subscale was 4.74 (0.81). Table 5 shows that the mean score on the preparedness scale was 4.65, which means that the participants’ preparedness for disaster management is categorized as moderate.
Factors Related to Disaster Preparedness
| Variables | n | Mean (SD) | t/F | P-value |
|---|---|---|---|---|
| Age | ||||
| ≤ 20 | 28 | 39.50 (5.78) | 1.81 | 0.165 |
| 21–25 | 410 | 37.05 (6.83) | ||
| > 25 | 7 | 38.43 (8.32) | ||
| Education Level | ||||
| College Student | 366 | 37.01 (6.88) | –1.46 | 0.145 |
| Worker | 79 | 38.24 (6.42) | ||
| Disaster Preparedness Management Training | ||||
| Yes | 399 | 38.63 (5.32) | –16.06 | 0.001 |
| No | 46 | 25.07 (6.22) | ||
| University Region Origin | ||||
| Java | 382 | 36.76 (7.12) | –3.59 | 0.001 |
| Sumatra | 63 | 40.05 (3.38) | ||
| Social Media Usage Frequency | ||||
| 1–2 days | 22 | 40.27 (2.95) | 7.43 | 0.001 |
| 3–4 days | 68 | 39.44 (3.91) | ||
| Everyday | 355 | 36.61 (7.27) |
The mean comparison test was conducted using the Independent T-Test and One-Way ANOVA to discover the difference in disaster preparedness levels based on the participants’ demographic characteristics. The Disaster Preparedness score was derived from the total of the participants’ responses on the preparedness domain of the modified DPET, measured on a six-point Likert scale, where higher scores indicate greater preparedness. A t-test was used for demographic variables that only consisted of two group categories (disaster management training, education level, and university origin). In comparison, the ANOVA test was used for demographic variables that consisted of more than two group categories (such as age and social media usage frequency). These tests were used to test whether there was a significant statistical difference in disaster preparedness mean level between groups in each characteristic.
Based on the analysis result of univariate the average of disaster preparedness towards demographic variables, it was found that three among five variables showed a statistically significant difference: disaster preparedness management training, university region origin, and social media usage frequency (P-value <0.05). An ANOVA comparing disaster preparedness across three age groups (≤20, 21–25, >25 years) revealed no statistically significant differences (F = 1.81, P = 0.165), despite the ≤20 group having the highest mean preparedness score. Likewise, an independent-samples t-test showed no significant difference in preparedness between students and those employed (t = –1.46, P = 0.145), indicating that education or employment status does not substantially affect preparedness. In contrast, respondents who had completed disaster management training scored significantly higher (38.63 vs. 25.07; P < 0.001) than those without training, underscoring the importance of formal training in enhancing readiness. Geographic differences emerged as well: a t-test showed respondents from Sumatra were significantly more prepared than those from Java (t = –3.59, P = 0.001), possibly reflecting differential exposure to disasters. Finally, preparedness also varied according to frequency of social media use (ANOVA: F = 7.43, P = 0.001), with those accessing social media 1–2 days per week showing higher preparedness than daily users, suggesting that moderate usage may be more beneficial than constant exposure. This result indicates that those three variables significantly influence the participants’ preparedness in facing a disaster. Participants who have participated in disaster preparedness training, have a university origin in Sumatra and access social media less frequently tend to have higher levels of disaster preparedness. Meanwhile, age and education level did not show significant differences, which indicates that those two variables do not significantly influence disaster preparedness in the context of the participant population in this study.
The bivariate analysis was used to discover the correlation between knowledge, skills, and preparedness for disaster. Pearson Correlation Test was used to do the bivariate analysis because all variables are interval scaled, and this test was used to determine the strength and direction of the linear correlation between two variables.
| N=445 | ||||
|---|---|---|---|---|
| Variables | Mean (SD), average per item | Variables | R value | P-value |
| Knowledge | 4.87 (0.66) | Knowledge vs Skills | 0.82 | <0.001 |
| Skills | 4.74 (0.81) | Knowledge vs Preparedness | 0.77 | <0.001 |
| Preparedness | 4.65 (0.85) | Skills vs Preparedness | 0.80 | <0.001 |
Table 7 presents the result of the Pearson Correlation test between the three main variables in this study: knowledge, skills, and preparedness. A significant, positive, and strong correlation was found between knowledge and skills (P-value < 0.001, r value = 0.82), by which it can be interpreted that the higher an individual’s knowledge about disasters, the better an individual’s skills in facing a disaster. The knowledge and preparedness variables also showed a significant, positive, and strong correlation (P-value <0.001, r value = 0.77), where the higher an individual’s knowledge about disasters, the better the individual’s preparedness for a disaster. The correlation between skills and preparedness variables also showed a significant, positive, and strong correlation (P-value <0.001, r value = 0.80), which means the better an individual’s skills in a disaster, the better the individual’s preparedness in facing it. This result implies that preparedness enhancement strategies should focus on skills-based training and be integrated with conceptual knowledge enhancement.
A linear regression analysis was carried out to determine the magnitude of the influence of the dependent variables simultaneously and partially on disaster preparedness.
| N=445 | |||
|---|---|---|---|
| Variables | B | Standard Error | P-value |
| Age | –0.22 | 0.61 | 0.722 |
| Disaster Preparedness Management Training | 5.59 | 0.64 | 0.001 |
| University Region Origin | 0.43 | 0.49 | 0.381 |
| Social Media Usage Frequency | –0.39 | 0.32 | 0.221 |
| Knowledge | 0.29 | 0.04 | 0.001 |
| Skills | 0.58 | 0.06 | 0.001 |
| R2=73.6%, F=203.98 | |||
Table 8 shows that disaster preparedness management training, knowledge, and skills variables significantly influence disaster preparedness (P-value < 0.05). Meanwhile, age, university region origin, and frequency of social media usage did not significantly influence disaster preparedness. Skills are the most numerically dominant variable in enhancing preparedness, followed by disaster preparedness management training and knowledge variables. Based on this result, practical interventions can be conducted by training and programs to improve skills and knowledge as a primary strategy in building community preparedness for disasters.
This study utilized the modified Disaster Preparedness Evaluation Tool (DPET) to evaluate the level of emergency management capabilities of Gen Z in Java and Sumatra, and found that scores for skill, knowledge, and preparedness were consistently in the moderate category. These findings are consistent with previous research using the same tool among nurses in Indonesia, which found that most respondents reported a moderate level of disaster preparedness despite receiving basic disaster management [25]. The questionnaire item on the skill section ‘I understand how to conduct fundraising via social media for disaster victims’ scored strongly, indicating that most respondents felt capable of using social platforms for this purpose. This aligns with Chugh, who found that within two days of the 2015 Nepal earthquake, the Nepalese diaspora in Australia raised over USD 500,000 through Facebook via a community-led page [26]. Similarly, a 2023 study by Lynn-Sze, Nazielah and Fathi showed that Indonesian social media influencers effectively used Instagram, leveraging trust and engagement, to mobilize substantial donations.
The level of knowledge of Gen Z for disaster management scored moderate, and one of the lowest scores was the triage principle. This indicates a lack of understanding of the victim prioritization process in emergency situations. This finding is in line with the research of Ferianto et al on adolescents in Tuban, who reported that the ability to identify flood victims before triage training was still low [27]. However, after being given a triage-based Tabletop Disaster Exercise (TDE), there was a significant increase (P <0.001) in this ability. A similar thing was reported by Addiarto and Wahyusari, who through a quasi-experiment using TDE showed a significant increase in both triage skills and victim referral flow (P = 0.001) [28]. This confirms that in addition to basic theoretical education, simulation-based training such as TDE is crucial to closing the gap in understanding related to triage among Gen Z.
The disaster preparedness level among the Gen Z cohort in this study was assessed as moderate with especially low confidence in articulating their roles during emergency response situations (e.g., at work or during internships), indicating inadequate exposure to real-world disaster management contexts. This suggests that many Gen Z individuals may not yet clearly understand their functional roles during emergency situations. This aligns with findings from (2024), who reported that Gen Z’s digital literacy in disaster contexts is limited to basic navigation and lacks critical evaluation skills, reflecting insufficient preparedness. Additionally, research focusing on university students highlighted that although students may possess theoretical disaster risk awareness, they often lack practical preparedness, stemming from minimal engagement with disaster simulations, defined roles, or structured campus-based initiatives [30].
In this study, disaster preparedness among Gen Z respondents was found to be significantly correlated with previous disaster management training, the geographic origin of their university, and social media usage frequency.
Disaster Training Has a Positive Impact on Disaster Preparedness Management
Participants who had undergone prior disaster training exhibited higher levels of preparedness. This observation aligns with the broader literature: a study integrating disaster nursing into the university curriculum in Turkiye found that structured education with practical components significantly increased students’ disaster literacy and preparedness, implying that without such exposure, students remain underprepared [31]. The significant effect of disaster management training on preparedness can be understood through the lens of self-efficacy theory. In a randomized trial, Psychological First Aid training for nurses over six weeks not only improved their perception of preparedness across all disaster phases but also significantly increased their general self-efficacy underprepared [31]. This suggests that training functions as a psychological intervention beyond skill acquisition, by enhancing participants’ confidence and belief in their ability to act effectively during emergencies. Consequently, higher self-efficacy mediates the relationship between training and actual disaster preparedness, underscoring its importance in developing robust Gen-Z emergency response capabilities.
Gen Z Participants from Sumatra Displayed Notably Higher Levels of Disaster Preparedness
The finding that Gen Z participants from Sumatra exhibited significantly higher levels of disaster preparedness is likely linked to the region’s geographic vulnerability and the corresponding educational initiatives targeted toward disaster-prone areas. For example, a study conducted in the outer islands of West Sumatra revealed that the introduction of a locally tailored physics e-booklet on tsunami mitigation significantly improved students’ preparedness levels, shifting them into the high category [32]. This supports the argument that region-specific and culturally contextual learning tools are effective in enhancing disaster resilience among youth populations. Moreover, this outcome can be further explained through the lens of Protection Motivation Theory (PMT), which posits that individuals’ self-protective actions are primarily motivated by perceived threat severity, vulnerability, and their self-efficacy in coping with risks. A study by Tang & Feng, in post-earthquake Taiwan demonstrated that self-efficacy had the strongest direct and total effect on actual disaster preparedness behavior, with behavior significantly mediated by intention [33]. This suggests that Gen Z students in Sumatra, who are more exposed to disaster-prone environments, may have developed stronger self-efficacy through community-led or school-based preparedness programs, leading to greater readiness. Thus, these findings imply that place-based vulnerability combined with exposure to structured, relevant educational interventions may foster not only higher risk perception but also empowerment through self-efficacy, translating into tangible preparedness actions among Gen Z populations.
Frequency of Social Media Use for Preparedness
Our finding that Gen Z respondents who used social media less frequently exhibited higher levels of disaster preparedness aligns with previous research suggesting that frequency alone is insufficient to improve readiness [34]. Wukich, found that routine social media usage does not enhance household or community disaster preparedness, “particularly when content lacks engagement or relevance [34].” In our context, this implies that purpose-driven, high quality digital engagement, especially when integrated with structured disaster training, is more effective than passive consumption of frequent social media content. This observation is supported theoretically by critiques of the information-deficit model: Web- and mobile-based technologies facilitate information flow, but do not automatically spur behavior change unless they encourage active engagement and interaction [35]. Further, evidence from Australia indicates that social media channels with images, maps, and real-time situational awareness messaging generate higher community engagement levels [36]. This suggests that quality and interactive content, rather than mere presence on social platforms, drives meaningful preparedness actions among Gen Z. However, this finding may also reflect what scholars have termed a “social media paradox”, where increased exposure to information does not necessarily translate into higher preparedness. One possible mechanism is information fatigue, as Gen Z users are constantly exposed to disaster content, alerts, and other stimuli on multiple platforms. This overload can cause cognitive saturation, reducing motivation to engage in concrete preparedness actions. Another explanation is exposure to misinformation, since unverified or sensational disaster posts may distort perceptions of risk or foster distrust toward official sources. Lastly, the paradox may stem from a disconnect between passive information consumption and active behavioral preparation. Many young users may scroll through or share disaster-related content without transforming awareness into tangible readiness behaviors such as joining simulations, preparing emergency kits, or learning first aid. Recognizing these underlying dynamics is essential to design effective risk communication strategies that go beyond information dissemination and emphasize experiential, interactive engagement.
Although this study provides valuable insights into the disaster preparedness of Gen Z populations in Indonesia, the interpretation of these findings should consider the sample’s demographic concentration. The participants were primarily university students and graduates from the Java and Sumatra regions that are generally more urbanized and have greater access to education, technology, and institutional disaster programs. Consequently, the results may overrepresent the perspectives of a more educated and digitally connected subset of Gen Z, whose disaster literacy and preparedness behaviors could differ from those in less urban or resource-limited settings. Therefore, caution is warranted when generalizing these findings to the broader national population. Future research should aim to include participants from other islands and rural contexts to provide a more comprehensive understanding of Gen Z disaster preparedness across Indonesia.
This study employed a cross-sectional design and collected data via an online questionnaire survey. Consequently, the findings cannot be used to establish causal relationships. The participants were Gen Z, which means individuals born between late 1990s-2012, from Java and Sumatra, regions selected due to their vulnerability to disasters, so the results may not be generalizable to the broader Indonesian population. Additionally, the outcomes were based solely on self-reported survey responses and were not validated through objective assessments. Furthermore, both the knowledge and skills constructs were measured through self-report items, which may lead to conceptual overlap and reflect perceived self-efficacy rather than entirely distinct cognitive and behavioral domains. This overlap may have contributed to the strong positive correlation observed between these two variables. Future studies are encouraged to employ mixed or performance-based assessments to better differentiate these dimensions and provide a more objective evaluation of preparedness capacity.
Implications for Gen Z
Indonesia is situated along the Pacific Ring of Fire, where the convergence of the Pacific, Eurasian, and Indo-Australian tectonic plates has resulted in the country having 127 active volcanoes [4]. A study by Faradiba et al using a weighted index method to assess regional vulnerability, identified Aceh, North Sumatra, West Java, East Java, and Central Sulawesi as the provinces with the highest number of disaster-prone sub-districts or villages [5]. The results of this study show that Gen Z respondents with prior disaster training, a Sumatra-based university origin, and a lower frequency of social media use exhibited significantly higher disaster preparedness, carrying several practical implications for disaster-prone Indonesia. Collectively, these findings underscore the importance of incorporating structured role clarification and practical training within Gen Z disaster education programs to enhance their readiness for real-world emergency responses. By combining immersive training, regional relevance, and curated digital practices, Gen Z across Indonesia, especially in disaster-prone areas, can cultivate actionable resilience and readiness for future emergencies.
Future Research
Future studies should further explore the specific characteristics and effectiveness of disaster preparedness training. In this study, the “training” variable encompassed diverse formats such as seminars, online campaigns, and awareness programs, without distinguishing between practical and theoretical modalities. To strengthen the applicability of future findings, subsequent research should differentiate between experiential, skill-based training such as simulation drills, field exercises, and first-aid practice, and passive, knowledge-based activities like online lectures or seminars. Understanding these distinctions will clarify how different forms of training contribute to the development of preparedness skills and behavioral competence among young adults. In addition, future research could benefit from employing longitudinal or experimental designs to examine how improvements in training quality, digital engagement, and skill acquisition interact over time to influence overall disaster preparedness. Such approaches would provide stronger causal evidence and practical guidance for educational and emergency management institutions aiming to strengthen resilience within the Gen Z population.
This study evaluated disaster preparedness in Generation Z students on the islands of Java and Sumatra using a modified tool from the DPET. The results show that although Gen Z has a moderate level of knowledge, skills, and preparedness, there are several factors that significantly affect the level of preparedness, namely previous disaster training, geographical location (Sumatra), and lower frequency of social media use. While initial analyses suggested a paradoxical association between higher social media exposure and lower practical preparedness, this relationship was not statistically significant in the multiple regression model after accounting for training, knowledge, and skills. The apparent paradox therefore likely reflects the confounding influence of stronger predictors rather than a direct causal effect. These findings emphasize the importance of integrating experiential disaster education, such as simulation training and role clarification into the college curriculum, especially in disaster-prone areas. Strategically designed digital interventions can also improve preparedness when combined with a skills-based approach and local relevance. By understanding Gen Z’s typical behavior patterns, stakeholders can design more effective emergency management strategies to shape young people to be resilient and responsive to future disasters.
The author would like to express sincere gratitude to Universitas Indonesia for the support and guidance provided throughout the course of this research. Such support has been instrumental in the successful completion of this study.
Conceptualization, A.P.P. and F.L.; methodology, B.; software, D.E.; validation, F.L., D.E., and B.; formal analysis, A.P.P.; investigation, D.E.; resources, A.P.P.; data curation, B.; writing-original draft preparation, A.P.P.; writing-review and editing, F.L.; visualization, A.P.P.; supervision, F.L.; project administration, E.E.; funding acquisition, A.P.P.
This research received no external funding.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Medicine, Universitas Andalas, Indonesia (No. 501/UN.16.2/KEP-FK/2025).
Informed consent was obtained from all subjects involved in the study.
The authors declare no conflict of interest.
The datasets generated during and/or analyzed during the current study are not publicly available due to privacy, but are available from the corresponding author upon reasonable request.
