Abstract

Disaster-risk perception (DRP) plays a critical role in disaster risk management (DRM) by enhancing community preparedness through protective actions and intervention measures before, during, and after disasters. This study investigated variations in DRP among hospital employees based on socio-demographic characteristics. A cross-sectional study was conducted with 2145 hospital employees (933 males and 1212 females) aged 20 to 65 from multiple hospitals in Tehran, Iran. DRP was assessed using six factors: exposure, knowledge, familiarity, preventability, worry, and dread. Data were collected via a valid and reliable questionnaire, and the overall DRP score was calculated using an index-based approach. Structural Equation Modeling (SEM), incorporating confirmatory factor analysis (CFA) and path analysis, was employed to evaluate relationships among the DRP factors. The mean DRP score for hospital employees was 2.878 ± 1.0236, with “familiarity” receiving the highest score (3.101 ± 0.9793) and “dread” the lowest (2.457 ± 0.9506). DRP significantly differed by gender, age, education level, and occupation (p < 0.01). Females, employees aged 40–49, and those with MSc. or Ph.D. degrees demonstrated higher DRP scores. Managers exhibited the highest DRP, while cleaning workers had the lowest. SEM analysis revealed significant relationships among DRP factors, including a positive association between exposure and knowledge (β = 0.61, p = 0.000) and a negative association between preventability and dread (β= -0.35, p = 0.000). These findings highlight the importance of designing targeted disaster training programs that address socio-demographic differences. Enhancing preparedness among healthcare workers through tailored education and interventions is essential for strengthening DRM. Future research should explore the weighting of DRP factors to refine disaster preparedness strategies further.

Introduction

Disasters, both natural and human-made, are defined as events of great magnitude that disrupt the functioning of society and have adverse impacts on the environment, economy, and public health

Study area.

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Participants and sampling

The cross-sectional study was conducted on 2,145 hospital employees (993 males and 1,212 females) aged 20 to 65 from various hospitals in the major metropolitan city of Tehran, Iran. A three-stage sampling method was employed to ensure a representative and diverse sample, enhancing the generalizability of the findings.

In the first stage, five clusters were identified using stratified sampling based on geographical distribution of people and hospital type (e.g., private or public). This approach ensured that the sample represented different sectors within Tehran’s healthcare system, which vary in workforce composition and healthcare infrastructure. In the second stage, a list of hospitals within the selected clusters was obtained, and a systematic random sampling method was applied to select hospitals. This involved choosing every nth hospital from the list, ensuring that each hospital had an equal chance of selection, thereby reducing any bias related to hospital characteristics. Figure 2 illustrates the sampling locations, with the base map sourced from OpenStreetMap (Accessed January 2025) and processed in QGIS 3.28. According to the formula provided below, a minimum of 332 subjects per cluster (83 per hospital) was required as the sample size39.

n = (Z1-α/2+Z1-β)2s2/d2,

Where Z1−α/2 =1.96 (the value of normal deviate at 0.05 level of confidence), Z1−β = 0.85 (the value of normal deviate at the study power of 0.8), d = 2.5 (the expected absolute allowable error in the mean), and s = expected standard deviation of 16.2 according to the study conducted by Xu et al. (2019)

(Source: https://www.qgis.org, https://www.openstreetmap.org).

Sampling locations. The base map was obtained from OpenStreetMap (Accessed on January 2025), and further processing, including markers and data visualization, was performed using QGIS 3.28.

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Questionnaire development

At first, we extracted keywords related to study and finally conducted a search in Scopus, PubMed, and Google Scholar using search syntax. PubMed search syntax: ((perception [TIAB] OR [TIAB] OR understanding [TIAB]) AND (disaster* [TIAB] OR earthquake*[TIAB] OR landslide*[MH] OR landslide*[TIAB] OR flood*[TIAB] “extreme weather“[TIAB] OR hurricane*[TIAB] OR storm*[TIAB] OR wildfire*[TIAB] OR terrorist[TIAB] OR fire[TIAB] OR epidemi* [TIAB])). Then, a rigorous and in-depth literature review was carried out. Finally, the criteria, methods, models, and approaches used in the studies determining disaster-risk perception were investigated. Following studies scrutiny, no suitable questionnaire was found to measure hospital employees’ disaster-risk perception; therefore, the researchers decided to develop indicators to evaluate hospital workers’ disaster-risk perception. Disaster-risk perception indicators related to each of the six factors affecting risk perception (Exposure: E1, E2, E3; Knowledge: K1, K2, K3, K4; Familiarity: F1, F2, F3, F4; Preventability: P1, P2; Worry: W1, W2; Dread: D1, D2, D3, D4) were extracted from academic studies conducted on risk perception (Table 1). The definition of disaster-risk perception indicators is as follows:

  • Exposure (actual quantitative risk level)44;

  • Familiarity (personal experience of the hazardous events)44;

  • Preventability (the degree to which the hazard is perceived as controllable or its effects preventable) [52];

  • Dread (afraid of future events and knowing the risks posed by hazards)45;

  • Knowledge (the depth of an individual’s understanding of the hazard)46;

  • Worry (people’s psychological and emotional feelings about disasters)12.

Ong et al. (2021) measured participants′ feelings whenever they thought about a major earthquake with the statement: “I feel stressed whenever I think about the big one happening in the country”47. Inspired by this approach, one of the dread indicators in our study was created with the statement: “I feel afraid when I think about disasters in my workplace”.

Content and face validity of the questionnaire

To evaluate the face validity of the disaster-risk perception questionnaire, a pilot group of 10 employed staff members was recruited, using the same method as in the test-retest phase of the study. This group included employees working in various hospital positions. The respondents were asked to complete the questionnaire and provide feedback, either written or oral, regarding the items and scales. Face validity was confirmed by the pilot group: all participants agreed on the relevance of the questions related to disaster-risk perception, and the items were generally found to be easy to answer.

Content validity was evaluated through rational analysis by competent experts, who assessed the items on the instrument in terms of construction, relevance, and clarity. According to Haynes et al. (1995), content validity refers to the extent to which the elements in a measuring instrument are relevant and represent a construct that aligns with the measurement objectives48. In our study, this assessment involved experts from various fields: three psychometrics experts, two social science experts, and two disaster science experts, totaling 7 expert judgments. Each expert was given a validation sheet containing 19 statement items, which they assessed based on construction (1 = poor, 2 = fair, 3 = average, 4 = good, and 5 = very good), relevance (1 = not relevant, 2 = item needs revision, 3 = item needs some revision, 4 = relevant but need minor revision, and 5 = very relevant), and clarity (1 = not clear, 2 = item needs revision, 3 = item needs some revision, 4 = clear but need minor revision, and 5 = very clear) using a five-point scale. To assess consistency between experts, the content validity index (CVI) was calculated using Aiken’s formula (V)49. Aiken’s Formula (V) is formulated as follows:

$$:text{V}=frac{sum:text{s}}{text{n}:(text{c}-1)}:,:text{s}hspace{0.17em}=hspace{0.17em}text{r}-{text{l}}_{0}$$

Where V is the value of Aiken′s validity coefficient, s is the value of the rating scale (r) minus the lowest validity rating score ((:{text{l}}_{0})), n is the number of experts used in the validation, and c is the highest score in the rating scale. Aiken’s index (V) ranges from 0 to 1, indicating the level of agreement among experts in evaluating items and their statistical significance. To be statistically significant, an item content validity analysis using the Aiken index with seven experts must produce a V index greater than or equal to 0.75. This threshold is derived from the table right-tail probabilities for selected values of the validity coefficient, as established by Aiken50. If the Aiken′s (V) index is ≥ 0.75, it indicates agreement among experts stating that the item is relevant to the specific content. Conversely, if Aiken’s index (V) < 0.75, it suggests that the item is not considered relevant by the experts.

Our analysis results showed that the developed questionnaire for measuring disaster-risk perception has strong content validity, with all items being relevant to the construct. Based on the validation results, Aiken′s index was ≥ 0.75 for all items, indicating that the construction, relevance, and clarity of all 19 statement items met the required threshold.

Table 1 Indicators selected for disaster-risk perception.

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Using a 5-point Likert scale anchored with 1 = strongly disagree and 5 = strongly agree, the extracted risk perception indicators were evaluated. The average score for indicators of each factor (exposure, knowledge, familiarity, preventability, worry, and dread) was calculated using Eq. 1. Based on these values, the overall disaster-risk perception was calculated using Eq. 2.

$$F = ~frac{{~left( {IA1 + ~IA2 + ~IA3 + … + ~IA~n} right)}}{n}$$

(1)

$$Overall{text{ }}disaster – risk{text{ }}perception{text{ }} = frac{{F1 + F2 + F3 + F4 + F5 + F6}}{6}$$

(2)

F1: Exposure, F2: Knowledge, F3: Preventability, F4: Dread, F5: Worry, F6: Familiarity.

Data analysis

Statistical analysis was performed by SPSS 23 (IBM Corporation, New York, NY, United States). One-sample Kolmogorov-Smirnov test and Mardia’s coefficient were used to assess univariate and multivariate normality, respectively. Statistical outliers were checked using Grubb′s test, which is based on the difference between the sample mean and the most extreme data point, considering the standard deviation

Perceived possibility of disasters.

Structural equation model (SEM). Chi-square = 149.23, df = 2145, CFI = 0.958, GFI = 0.925, AGFI = 0.992, CMIN/DF = 3.979, RMSEA = 0.06.

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Discussion

This study provides valuable insights into the status and importance of disaster-risk perception among hospital employees and examine the socio-demographic factors influencing their perception levels in Tehran, Iran. It also underscores the broader implications of these perceptions for hospital disaster preparedness and response. In high-risk environments like hospitals, accurate and comprehensive disaster-risk perception plays a crucial role in enhancing both individual safety and institutional readiness during emergencies70,71,72.

To evaluate disaster-risk perception, we developed and validated a novel, theory-based questionnaire grounded in cognitive theory. The questionnaire assessed six key factors affecting risk perception: exposure, knowledge, familiarity, preventability, worry, and dread. Its factor structure and model fit were confirmed through confirmatory factor analysis, ensuring its reliability and applicability.

Hospital employees’ disaster-risk perception

Our findings showed that many of the hospital employees state earthquakes as the most common disaster in their workplace because there are active faults in the city of Tehran73. On the other hand, there are many training programs related to the earthquake on community-based disaster management in Iran, which is considered as prominent community-based disaster health management approach in increasing the level of people awareness74,75,76. The hospital’s employees have considered epidemic second priority regarding the disaster-risk perception score. This finding may be due to increased hospital employees’ awareness through training programs and social media, especially after the coronavirus (COVID-19) outbreak throughout the world77,78. The findings of this study revealed that only 178 (8.3%) of participants ranked fire disaster as the primary disaster in hospitals, while according to previous studies assessing the risks of hospitals, fire is one of the top five high-importance hazards in Iran79. This study indicates that the fire risk perception of hospital employees is low despite its importance in hospitals, probably due to the incompatibility of the training programs of hospitals with the actual training needs of hospital employees80. The landslide was the least essential hazard mentioned by the respondents, which is consistent with the results of the study on disaster risk assessments of the hospitals in Tehran81.

In line with previous studies52,82, the present study found a positive association between disaster-risk perception and personal experience of a hazard (familiarity). This may be because individuals cannot fully perceive the impact of a disaster until they experience it firsthand. Similarly, Heydari et al. (2022) demonstrated that knowledge significantly and positively predicts disaster-risk perception33. Accurate knowledge of a hazard, combined with scientific and epidemiological information, can enhance awareness of potential risks in one′s living area, thereby increasing sensitivity and disaster-risk perception. Furthermore, previous studies have identified exposure to a hazard as a significant positive predictor of disaster-risk perception33,52. Being exposed to hazards often raises public awareness through media coverage and contributes to a deeper understanding of nature and its effects83. The results of the present study also revealed that preventability had the weakest association with disaster-risk perception compared to other components. However, consistent with Sullivan-Wiley et al. (2017)84 and Bosschaart et al. (2013)46, dread and worry positively predicted disaster-risk perception. This could be because fear and worry about hazards motivate individuals to seek more information about potential impacts, thereby enhancing their awareness and perception of disaster risks.

Socio-demographic factors influencing individuals′ disaster-risk perception

In this study, females exhibited a higher disaster-risk perception than males. This difference can be attributed to several factors. First, women are often more likely to express emotional concerns and anxiety, which may heighten their perception of threats during global health crises85. Second, as primary caregivers within families, women typically bear greater responsibility for the well-being of their loved ones, potentially their sensitivity to risks86. Furthermore, socio-cultural norms and expectations may predispose women to greater awareness and concern regarding health-related risks. These findings align with previous research indicating that women generally exhibit higher levels of health-related anxiety and fear during public health emergencies87,88. However, contrary to our findings, Heydari et al. (2022) found that female hospital employees reported lower flood disaster-risk perception than their male colleagues. The authors attributed this discrepancy to men′s lower expectations of loss and women′s lack of awareness about flood-related factors and response strategies, which could influence their risk perception33.

The present study revealed that age had a significant and varied influence on disaster-risk perception. Specifically, males and females over the age of 40 exhibited a higher disaster-risk perception compared to their younger counterparts. This could be attributed to the fact that as individuals age, they are more likely to have experienced a range of disasters, which may heighten their awareness and sensitivity to potential risks89. Similarly, Kellens et al. (2011) found a positive correlation between age and risk perception due to their greater life experience with various hazards90. Interestingly, although older adults typically exhibit higher disaster–risk perceptions due to their accumulated life experiences, some studies indicate that younger individuals, particularly those well-versed inmodern mitigation strategies, may also report higher risk perceptions. This apparent paradox highlights the complexity of disaster-risk perception and underscores the importance of developing tailored risk communication strategies that address generational differences in disaster preparedness and readiness91.

This study also revealed that the disaster-risk perception level of participants with higher educational qualifications is higher than those with lower educational qualifications. Similarly, Wang et al. (2022) addressed education level as a significant predictor of disaster-risk perception among workforces. They stated that education in both direct and indirect formats can increase individuals’ awareness, attitudes, critical thinking, and even problem-solving capacities92. In this way, education can play a vital role in reducing the severity of human vulnerability when a disaster occurs. Heydari et al. (2022) found a statistically significant relationship between the hospital staff’s educational level and their perception of flood outcomes, where people with higher education levels mentioned more environmentally friendly solutions for flood damage mitigation and were aware of their self-responsibilities more33. Wize et al. (2020) similarly found that individuals with graduate levels of education perceived a higher risk perception of COVID-19 pandemic93.

Consistent with the literature review33, there was no relationship between work experience and disaster-risk perception level. It could be because there is no fixed pattern for recruiting graduates. In the present study, some employees were younger than 30 years old and had more than seven years of work experience, but some were older than 30 and had only two years of work experience. In addition, participants may have different disaster exposure levels in their life; some may have more disaster experience with limited job experience, and some have no disaster experience with more job experience.

Our findings also indicated a significant relationship between disaster-risk perception levels and the occupation roles of hospital employees, with managers perceiving higher disaster risks compared to other occupations. This may be attributed to their participation in disaster risk management meetings held by various organizations focused on disaster relief efforts. A study by Woyessa et al. (2020) on disaster preparedness and risk perceptions among managers found that hospital authorities exhibited moderate to high levels of disaster-risk perception94, aligning with the present study findings. Additionally, security staff demonstrated the second-highest disaster-risk perception after managers. This could be due to their extensive training for handling emergencies such as fires, quarrels, and potential terrorist attacks. Conversely, cleaning workers exhibited the lowest disaster-risk perception levels, followed closely by office employees. This disparity is likely due to their limited participation in disaster-related training programs. These findings emphasize the need for targeted training initiatives for non-managerial staff, particularly cleaning personnel, to enhance their preparedness and response effectiveness during disasters. Consistent with Heydari et al. (2022), our study also found that nurses had a higher level of disaster-risk perception compared to administrative staff, likely because of their direct and frequent interactions with patients during emergencies33.

This study has several strengths. First, it used the Structural Equation Modeling (SEM), a robust method that not only provides clarity on the relationships between socio-demographic factors and disaster-risk perception but also enables the development of a theory-based framework that can inform disaster management strategies across various healthcare settings. Second, the different occupational groups in hospitals were included in the study and was not focused on a specific group. Another strength of this study is the high number of selected participants based on population distribution in the metropolitan city. However, the current investigation has a few limitations to note. The study is a cross-sectional analysis, which may potentially limit the generalizability of the results in other areas such as industries. Additionally, the lack of a control group and several variables affecting the individuals’ disaster-risk perception such as nutritional status, personality traits, and physical activity can be regarded as reasonable limitations due to the potential for misinterpretation. Another limitation of the present study was that only two items were designed for the components of preventability and worry, which can reduce the validity of the results of these components. Hence, longitudinal studies are necessary to assess how disaster-risk perceptions evolve over time, particularly in response to changes in hospital training programs or real-world disaster experiences. Furthermore, future research should address other socio-psychological factors, such as personality traits and stress resilience, which could influence disaster-risk perception but were not captured in this study. Hence, it is necessary to conduct future studies in various sectors of organizations and industries with an emphasis on various subjects, including disaster prevention, disaster preparedness, and local community resilience to verify and prioritize the actions affecting them and reduce injuries and fatalities. The future studies could also consider changes in disaster-risk perception dimensions while performing uncontrolled multitasks by health workers (e.g., working in crowded wards, heavy workload, and talking to patients). Although the number of subjects participating in the present study is good enough, however, more study is required to confirm these findings on a larger and multi-centric database among health workers.

Conclusions

This study highlights the development and validation of a comprehensive disaster-risk perception questionnaire specifically designed for hospital employees, demonstrating strong content and face validity. The tool′s utility extends beyond healthcare settings, offering significant potential for broader disaster risk management applications.

Our findings revealed notable differences in disaster-risk perception based on socio-demographic factors such as education level, occupation, age, and gender, while job experience did not show a significant impact. These results underscore the importance of tailoring disaster-risk training programs to address the diverse profiles of hospital employees. Such customized training can enhance preparedness, improve response measures, and ultimately contribute to better outcomes in disaster situations. Hospital managers are strongly encouraged to use disaster-risk assessment results to design inclusive and effective training programs and control measures for all personnel, irrespective of their job roles.

To transition from theory to practice, this study’s findings can serve as a basis for future research on risk behavior, risk psychology, and disaster risk management (DRM). Strengthening theoretical frameworks, prioritizing practical applications, and developing comprehensive paradigms for disaster-risk perception are crucial steps in addressing the growing frequency of disasters. Future research should expand on the theoretical underpinnings of disaster-risk perception and focus on translating these insights into actionable preparedness strategies. Such efforts will better equip healthcare systems to effectively respond to the dynamic and evolving nature of disaster risks.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported by the Iran University of Medical Sciences, Tehran, Iran (No. IR.IUMS.REC.1401.869). The University had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. The authors would like to express special thanks to all the experts and subjects for giving up their time for this research.

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Authors and Affiliations

  1. Department of Health in Disasters and Emergencies, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

    Saeid Bahramzadeh Gendeshmin

  2. Department of Ergonomics, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Sajjad Rostamzadeh

  3. Department of Health in Disasters and Emergencies, Health Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

    Mohsen Dowlati

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  1. Saeid Bahramzadeh Gendeshmin

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Contributions

S.B.G: Conceptualization, Investigation, Validation, Methodology, Writing-original draft, Writing-review & editing. S.R.: Investigation, Validation, Data curation, Formal analysis, Writing-original draft, Writing-review & editing. M.D.: Conceptualization, Investigation, Validation.

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Mohsen Dowlati.

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Gendeshmin, S.B., Rostamzadeh, S. & Dowlati, M. Evaluation of disaster risk perception and influencing factors among hospital personnel using structural equation modeling.
Sci Rep 15, 12780 (2025). https://doi.org/10.1038/s41598-025-97747-0

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  • Received: 31 August 2024

  • Accepted: 07 April 2025

  • Published: 14 April 2025

  • DOI: https://doi.org/10.1038/s41598-025-97747-0

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Keywords

  • Disaster risk management (DRM)
  • Structural equation modeling (SEM)
  • Healthcare
  • Disaster risk perception (DRP)
  • Preparedness
  • Hospital

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