Disaster preparedness and its correlates among nurses in border areas of Southwest China: A multicenter cross-sectional survey

Aoli Li; Lihan Chen; Maosong Li; Qiu Ma; Qilian He; Lorna Kwai Ping Suen; Aoli Li; Lihan Chen; Maosong Li; Qiu Ma; Qilian He; Lorna Kwai Ping Suen

doi:10.3934/publichealth.2026039

AIMS Public Health

2026, Volume 13, Issue 3: 725-740. doi: 10.3934/publichealth.2026039

Previous Article Next Article

Research article

Disaster preparedness and its correlates among nurses in border areas of Southwest China: A multicenter cross-sectional survey

1.
School of Nursing, Dali University, Dali 671000, China
2.
Department of Nursing, Xianyang Central Hospital, Xianyang 712000, China
3.
Bureau of Science and Technology of Dali Bai Autonomous Prefecture, Dali 671000, China
4.
School of Nursing, Tung Wah College, Hong Kong Special Administrative Region, China
These two authors contributed equally.

Received: 24 January 2026 Revised: 04 May 2026 Accepted: 07 May 2026 Published: 07 July 2026

Background
Nurses play a critical role in disaster preparedness and response, particularly in disaster-prone border areas where health systems may face compounded challenges related to natural hazards, population mobility, and resource constraints. However, empirical evidence on nurses' disaster preparedness in such settings remains limited.
Objective
We aimed to examine disaster preparedness among nurses working in disaster-prone border areas of Southwest China and to identify priority correlates to inform workforce development and training strategies.
Methods
We conducted a multicenter cross-sectional survey of 1366 nurses using multistage stratified cluster sampling in a representative disaster-prone border area of Southwest China (Yunnan Province, China, bordering Myanmar). Data were collected using a general information questionnaire, the Chinese version of the Disaster Preparedness Evaluation Tool, the Resilience Scale of Medical Staff, and the Sense of Professional Mission Scale. Data were analyzed using descriptive statistics, univariate analysis, Pearson correlation analysis, LASSO regression, multivariable linear regression, and random forest analysis.
Results
The mean total disaster preparedness score was 182.32 ± 43.51, indicating a moderate level of preparedness. Random forest analysis identified resilience, gender, and sense of professional mission as the most prominent correlates. In the multivariable linear regression model, resilience, sense of professional mission, gender, and disaster-related training remained significant predictors of disaster preparedness.
Conclusions
Disaster preparedness among nurses working in disaster-prone border areas of Southwest China was moderate. Resilience and sense of professional mission were identified as important correlates of preparedness, highlighting potential priorities for workforce training and public health capacity building in border-area contexts.
- disaster preparedness,
- nurses,
- border areas,
- resilience,
- random forest
Citation: Aoli Li, Lihan Chen, Maosong Li, Qiu Ma, Qilian He, Lorna Kwai Ping Suen. Disaster preparedness and its correlates among nurses in border areas of Southwest China: A multicenter cross-sectional survey[J]. AIMS Public Health, 2026, 13(3): 725-740. doi: 10.3934/publichealth.2026039

Related Papers:

Abstract

Background

Nurses play a critical role in disaster preparedness and response, particularly in disaster-prone border areas where health systems may face compounded challenges related to natural hazards, population mobility, and resource constraints. However, empirical evidence on nurses' disaster preparedness in such settings remains limited.

Objective

We aimed to examine disaster preparedness among nurses working in disaster-prone border areas of Southwest China and to identify priority correlates to inform workforce development and training strategies.

Methods

We conducted a multicenter cross-sectional survey of 1366 nurses using multistage stratified cluster sampling in a representative disaster-prone border area of Southwest China (Yunnan Province, China, bordering Myanmar). Data were collected using a general information questionnaire, the Chinese version of the Disaster Preparedness Evaluation Tool, the Resilience Scale of Medical Staff, and the Sense of Professional Mission Scale. Data were analyzed using descriptive statistics, univariate analysis, Pearson correlation analysis, LASSO regression, multivariable linear regression, and random forest analysis.

Results

The mean total disaster preparedness score was 182.32 ± 43.51, indicating a moderate level of preparedness. Random forest analysis identified resilience, gender, and sense of professional mission as the most prominent correlates. In the multivariable linear regression model, resilience, sense of professional mission, gender, and disaster-related training remained significant predictors of disaster preparedness.

Conclusions

Disaster preparedness among nurses working in disaster-prone border areas of Southwest China was moderate. Resilience and sense of professional mission were identified as important correlates of preparedness, highlighting potential priorities for workforce training and public health capacity building in border-area contexts.

Acknowledgments

The research was supported by the Project of National Social Science Foundation of China (21BMZ018).

Authors' contributions

AL and LC contributed equally to this work and share first authorship. AL and QH conceived and designed the study. AL and LC collected, analyzed the data and drafted the manuscript. ML and QM assisted with participant recruitment and coordination. LKS provided methodological guidance and critically revised the manuscript. QH supervised the study and critically revised the manuscript. All authors read and approved the final manuscript.

Conflict of interest

Lorna Kwai Ping Suen is an editorial board member for AIMS Public Health and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

References

[1]	Giugale M (2017) Time to Insure Developing Countries Against Natural Disasters. HuffPost . [cited 2024 September 16]. Available from: https://www.huffpost.com/entry/time-to-insure-developing-countries-against-natural_b_59de7a0ee4b069e5b833b1f8
[2]	Thacker PG, Menaker R, Kolbe AB, et al. (2021) Preparing for the next pandemic: It is more than just about numbers. Clin Imaging 79: 179-182. https://doi.org/10.1016/j.clinimag.2021.05.017
[3]	Bai J (2023) There are more than 5.2 million registered nurses in the country. People's Daily . [cited 2024 September 16]. Available from: http://paper.people.com.cn/rmrb/html/2023-05/12/nw.D110000renmrb_20230512_1-06.htm
[4]	Hugelius K, Adolfsson A (2019) The HOPE model for disaster nursing–A systematic literature review. Int Emerg Nurs 45: 1-9. https://doi.org/10.1016/j.ienj.2019.03.007
[5]	Al Thobaity A, Williams B, Plummer V (2016) A new scale for disaster nursing core competencies: Development and psychometric testing. Australas Emerg Nurs J 19: 11-19. https://doi.org/10.1016/j.aenj.2015.12.001
[6]	Wang J, Li C, Zou S, et al. (2020) Psychometric evaluation of undergraduate student nurses' learning perceived needs in disaster nursing: Two cross-sectional studies. Nurse Educ Today 84: 104208. https://doi.org/10.1016/j.nedt.2019.104208
[7]	Said NB, Chiang VCL (2020) The knowledge, skill competencies, and psychological preparedness of nurses for disasters: A systematic review. Int Emerg Nurs 48: 100806. https://doi.org/10.1016/j.ienj.2019.100806
[8]	Parker N (2013) Nursing in disaster events. Australas Emerg Nurs J 16: 1-2. https://doi.org/10.1016/j.aenj.2013.01.001
[9]	Baack S, Alfred D (2013) Nurses' preparedness and perceived competence in managing disasters. J Nurs Scholarsh 45: 281-287. https://doi.org/10.1111/jnu.12029
[10]	Mohamed NA, Abdel-Aziz HR, Elsehrawy MG (2023) Nursing students' knowledge, attitude, and practice regarding disaster preparedness: A cross-sectional study. Risk Manag Healthc Policy 16: 2427-2437. https://doi.org/10.2147/RMHP.S435131
[11]	Zang X, Li C, Chen C (2021) Investigation and analysis of the current status of disaster preparedness among male nurses. Contemp Nurse (China) 28: 9-13. https://doi.org/10.19791/j.cnki.1006-6411.2021.16.003
[12]	Breiman L (2001) Random forests. Mach Learn 45: 5-32. https://doi.org/10.1023/A:1010933404324
[13]	Labrague LJ, Hammad K (2024) Disaster preparedness among nurses in disaster-prone countries: A systematic review. Australas Emerg Care 27: 88-96. https://doi.org/10.1016/j.auec.2023.09.002
[14]	Ediz Ç, Yanik D (2024) Disaster preparedness perception, psychological resiliences and empathy levels of nurses after 2023 Great Turkiye earthquake: Are nurses prepared for disasters: A risk management study. Public Health Nurs 41: 164-174. https://doi.org/10.1111/phn.13267
[15]	Zhang D, Zhang LY, Zhang X, et al. (2024) Improve disaster literacy in nurses: A qualitative descriptive study. BMC Nurs 23: 730. https://doi.org/10.1186/s12912-024-02381-2
[16]	Rahimi B, Yari A, Rafiei F, et al. (2024) Assessment of nursing managers' awareness and hospital preparedness for disasters: A cross-sectional study. BMC Emerg Med 24: 203. https://doi.org/10.1186/s12873-024-01122-7
[17]	Farhadian M, Torkaman S, Mojarad F (2020) Random forest algorithm to identify factors associated with sports-related dental injuries in 6 to 13-year-old athlete children in Hamadan, Iran-2018: A cross-sectional study. BMC Sports Sci Med Rehabil 12: 69. https://doi.org/10.1186/s13102-020-00217-5
[18]	Yunnan Provincial Bureau of StatisticsYunnan Statistical Yearbook 2022 (2022). [cited 2024 September 16]. Available from: https://www.yn.gov.cn/sjfb/tjnj_2/202302/t20230215_254980.html
[19]	Wang Y, Liu Y, Yu M, et al. (2023) Disaster preparedness amongst nurses in China: A cross-sectional study. J Nurs Res 31: e255. https://doi.org/10.1097/JNR.0000000000000537
[20]	Tichy M, Bond AE, Beckstrand RL, et al. (2009) Nurse practitioners' perception of disaster preparedness education. Am J Nurse Pract 13: 10-22.
[21]	Li Z, Sheng Y (2014) An investigation of emergency nurses' preparedness for disasters in China. Chinese J Nurs 49: 699-703.
[22]	Zhu HQ, Wan J, Shi K, et al. (2016) Scale design and research on composition of resilience of medical staff. J Stat Info forum 31: 107-112.
[23]	Zhang C (2015) A study of career as a calling in China: Structure, assessment, and its relation to well-being [dissertation]. [China]: Southwest University.
[24]	Dobrow SR, Tosti-Kharas J (2011) Calling: The development of a scale measure. Pers Psychol 64: 1001-1049. https://doi.org/10.1111/j.1744-6570.2011.01234.x
[25]	Grömping U (2009) Variable importance assessment in regression: Linear regression versus random forest. Am Stat 63: 308-319. https://doi.org/10.1198/tast.2009.08199
[26]	Lu J, Wu Y, Xu R, et al. (2015) Disaster preparedness amongst community nurses and its influencing factors. J Nurs Sci 30: 101-103.
[27]	Duan Y, He J, Zheng R, et al. (2022) The relationship between disaster preparedness, psychological capital, and coping style amongst nurses: A cross-sectional study from China. Perspect Psychiatr Care 58: 2577-2584. https://doi.org/10.1111/ppc.13097
[28]	Zhang D, Zhang L, Gong A (2021) Development of disaster nursing in China: From the spirit of Nightingale to COVID-19. Disaster Med Public Health Prep 15: e32-e35. https://doi.org/10.1017/dmp.2020.468
[29]	Alan H, Eskici GT, Sen HT, et al. (2022) Nurses' disaster core competencies and resilience during the COVID-19 pandemic: A cross-sectional study from Turkey. J Nurs Manag 30: 622-632. https://doi.org/10.1111/jonm.13552
[30]	Jin R, Ji Y (2020) Current status of disaster readiness of junior nurses and its influence factors: A 376-case study. J Nurs (China) 27: 38-41.
[31]	Jin T, Zhou Y, Zhang L (2021) The mediating effects of job embeddedness and career identity on the relationship between perceived empowering leadership and career calling amongst nurses. Chin J Nurs Educ 18: 87-91.

Reader Comments

Your name:*

Email:*
© 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)