Development and psychometric evaluation of the emergency nurses’ professional resilience tool

Abstract

Background There is no specific tool for measuring the professional resilience of emergency nurses. Therefore, the present study aimed to design and psychometrically evaluate a new tool named the emergency nurses’ professional resilience tool. Method This mixed-method sequential exploratory study was conducted in two phases: (1) item generation using literature review and evaluation of the results of a qualitative study and (2) psychometric evaluation of the developed scale. The face, content, and construct validity (exploratory and confirmatory factor analysis), reliability (internal consistency, relative, and absolute), and accountability were assessed in the population of Iranian nurses (N = 465) during March 2019-June 2020. Results The tool designed for assessing the professional resilience of Iranian nurses included 37 items. The average scale content validity index (S-CVI/Ave) was equal to 0.94. The exploratory factor analysis revealed five factors, including professional competencies, emotional-cognitive characteristics, external support, in addition to behavioral and cognitive strategies, and explained 75.59% of the whole variance. Cronbach’s alpha and intraclass correlation were 0.915 and 0.888, respectively. Construct validity for five factors was established with acceptable model fit indices [Chi–square/df = 1336.56/619, p < .001]; [Comparative Fit Index [CFI] = 0.96]; [Non-Normed Fit Index [NNFI] = 0.96]; [Root Mean Square Error of Approximation (RMSEA) = 0.074 and 90 Percent Confidence Interval = (0.069; 0.080)]; and [SRMR = 0.095]. Conclusions According to the findings of the current study, the emergency nurses’ professional resilience tool can be used by healthcare managers as a valid and reliable scale to evaluate the professional resilience of nurses to designate them as nurses working in emergency and disaster situations.

Development and initial validation of the career resilience instrument for CDC emergency responders in China within the context of public health emergencies: based on a survey conducted in Shanghai

“…Further, we compiled the instrument revised by experts into a questionnaire and randomly sampled 1,286 CDC emergency responders in Shanghai, using the questionnaires they filled in for reliability and validity analyses. Additional, reliability and structural validity were examined using Cronbach’s α coefficient and exploratory factor analysis, respectively, which are widely used in the development and validation of instruments ( 9 , 28 ). The results of this study showed that all the Cronbach’s α coefficients were above 0.85, and the factor loadings in exploratory factor analysis were above 0.65, and there were no double loadings, indicating good results for reliability and validity validation.…”

“…Therefore, considering the limitations of the trait and outcome perspectives, in this study, we developed the career resilience measurement instrument from a process perspective, describing protective individual characteristics, internal and external interactions and self-regulatory processes, and adaptive outcomes and employing a variable-centered approach to reveal the dynamic process of an individual’s breakdown from equilibrium to reintegration into equilibrium. In addition, career resilience in the healthcare field has mostly been studied with nurses, and primary healthcare professionals ( 28 , 33–37 ), while basically, no studies are available regarding CDC emergency responders. This study introduces career resilience to the group of CDC emergency responders in hopes of focusing on the mental health and work status of this group, so that they can better respond to public health emergencies and protect public health.…”

“…Third, for the career resilience instrument, as revised by the expert consultations, we used Cronbach’s α coefficient to test its reliability and exploratory factor analysis to determine its structural validity. A Cronbach’s α coefficient greater than 0.7 indicates good reliability, and in exploratory factor analysis, a Kaiser-Meyer-Olkin (KMO) value greater than 0.7 and a p -value less than 0.05 indicate that it is suitable for factor analysis ( 28 ). In this study, the principal component method was used for factor extraction, the maximum variance method was used for factor rotation, and the number of factors was determined based on the eigenvalue being greater than 1.…”