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.
Is the Self-Evaluation of Resilience a Valid Assessment to Measure Resilience in Healthcare? A Confirmatory validation Study in Italian Healthcare Settings / A. Pennini, R. Caruso, G. Conte, M. De Maria, L. Nirta, A. Magon, G. Armellin. - In: EVALUATION & THE HEALTH PROFESSIONS. - ISSN 0163-2787. - (2023), pp. 1632787231170236.1-1632787231170236.9. [Epub ahead of print] [10.1177/01632787231170236]
Is the Self-Evaluation of Resilience a Valid Assessment to Measure Resilience in Healthcare? A Confirmatory validation Study in Italian Healthcare Settings
R. Caruso
Secondo
Writing – Review & Editing
;
2023
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.File | Dimensione | Formato | |
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