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dc.contributorSchool of Nursing-
dc.creatorMao, X-
dc.creatorChen, K-
dc.creatorHu, X-
dc.creatorWen, X-
dc.creatorLoke, AY-
dc.rights© The Author(s) 2021en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
dc.rightsThe following publication Mao, X., Chen, K., Hu, X. et al. Establishment of the Psychometric Properties of a Disaster Resilience Measuring Tool for Healthcare Rescuers in China: A Cross-Sectional Study. Int J Disaster Risk Sci 12, 381–393 (2021) is available at
dc.subjectDisaster resilience measuring toolen_US
dc.subjectFactor analysisen_US
dc.subjectHealthcare rescuersen_US
dc.titleEstablishment of the psychometric properties of a disaster resilience measuring tool for healthcare rescuers in China : a cross-sectional studyen_US
dc.typeJournal/Magazine Articleen_US
dcterms.abstractThe aim of this study was to test the validity and reliability of a tool for measuring the disaster resilience of healthcare disaster rescuers. A cross-sectional study involving 936 healthcare disaster rescuers of the Sichuan Disaster Response Team was conducted to establish the psychometric properties of the disaster resilience measuring tool (DRMT). Item analysis, exploratory factor analysis, confirmatory factor analysis, and correlation analysis were adopted to analyze the data. Item analysis showed that all but three items had the critical ratio over 3, which indicates adequate discriminability for inclusion in the measuring tool. The exploratory factor analysis showed that 65.93% of the total variance was explained by four factors—self-efficacy, social support, positive growth, and altruism. The confirmatory factor analysis showed goodness of fit for the four-factor model: CMIN/DF (2.846), GFI (0.916 ≥ 0.90), CFI (0.949 ≥ 0.90), AGFI (0.891 ≥ 0.80), and RMSEA (0.063 ≤ 0.08). Criterion validity demonstrated significant associations of the DRMT and the Connor-Davidson Resilience Scale (P < 0.01, r = 0.566). Convergent validity was established by correlation with stress (P < 0.05, r = − 0.095), depression (P < 0.01, r = − 0.127), posttraumatic stress disorder-PCL-C (P < 0.05, r = − 0.100), compassion satisfaction (P < 0.01, r = 0.536), and burnout (P < 0.01, r = − 0.330). The DRMT demonstrated adequate internal consistency (Cronbach’s alpha > 0.84) and stability over the two-week study period (intraclass correlation coefficient > 0.85), and a cut-off point of 61 was suggested. The disaster resilience measuring tool has satisfactory psychometric properties and is a valid, reliable, and valuable instrument for assessing disaster resilience in healthcare rescue workers. The scale needs to be tested further among other populations and those from other cultures.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of disaster risk science, June 2021, v. 12, no. 3, p. 381-393-
dcterms.isPartOfInternational journal of disaster risk science-
dc.description.validate202109 bcvc-
dc.description.oaVersion of Recorden_US
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