Abstract
Although the Self-Evaluation of Resilience (SEOR) scale is a promising tool for assessing resilience in healthcare, its psychometric structure has not yet been confirmed. This study aimed to assess and validate the four-factor psychometric structure of the SEOR. Between September 2020 and January 2021, cross-sectional data were collected from randomly selected healthcare workers, managers, and administrators from a predefined network of 70 healthcare facilities in 12 Italian regions. The sample size was based on a Monte Carlo simulation using estimates from the SEOR developmental study. Two confirmatory factor models (first-order and second-order) were predefined. The responders (n = 199, response rate, 81%) were healthcare workers (n = 99; 49.7%), managers (n = 86; 43.2%), and administrators (n = 14; 7%). The two confirmatory factor models each showed a good fit in explaining sample statistics, corroborating the capacity of the scale to provide a total score of resilience and sub-scores for organizational resilience, network-based resilience, skill-based resilience, and individual-based resilience. The Molenaar-Sijtsma coefficients (internal consistency) ranged between 0.889 and 0.927. The SEOR enables managers and policy-makers to comprehensively screen resilience in healthcare from an epidemiological perspective.
Keywords
Get full access to this article
View all access options for this article.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
