Measurement Invariance and Latent Mean Differences in the Nurses' Emotional Labour Scale

Abstract

BackgroundThe measurement invariance and latent mean differences in emotional labor across different hospital and monthly salary levels among registered nurses have never been confirmed for the Emotional Labour Scale. These issues may influence the application and efficacy of this scale in practice.PurposeThis study was developed to evaluate the factor structure of the nurses' Emotional Labour Scale and to examine the measurement invariance and latent mean differences for this scale across different hospital and monthly salary levels.MethodsData were collected from 461 registered nurses working in four general hospitals and 12 long-term care hospitals. Confirmatory factor analysis and a multigroup confirmatory factor analysis were performed to determine the internal structure and measurement invariance of the Emotional Labour Scale.ResultsThe results of the confirmatory factor analysis indicate that the factor structure model proposed by the original scale fits well with our data as well as configural invariance, factor loading invariance, intercept invariance, and uniqueness invariance. Moreover, factor variance/covariance invariance across two hospital levels as well as configural invariance, factor loading invariance, and intercept invariance across two monthly salary levels were supported. The mean score for emotional control effort in the profession of general hospital nurses was lower than that for long-term care hospital nurses. No statistically significant latent mean differences were found across monthly salary levels.Conclusions/Implications for PracticeThe findings show the Emotional Labour Scale to be a valid and reliable tool for assessing registered nurses and also comparing the mean score for emotional labor across hospital and monthly salary levels to be feasible. The scale may contribute to the development of human resource strategies.

Exploring the Accuracy and Consistency of a School Readiness Assessment Tool for Preschoolers: Reliability, Validity and Measurement Invariance Analysis

“…The fit of each model is evaluated by using goodness-of-fit indices, such as the ratio of Chi-square by degrees of freedom, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR) (Li et al 2019). If the factor structure is the same across groups or time points, the model should fit the data well, indicating configural invariance (Gygi et al 2016;Kim et al 2022).…”

“…If the configural invariance, factor loading invariance, and intercept invariance were established, the latent mean differences across two groups can be examined in a model in which the factor loadings and intercepts were constrained to be equal (Teo et al 2022). Latent mean difference refers to the difference in the means of the latent variables (i.e., unobserved variables) between two or more groups in MG-CFA (Kim et al 2022). Assessing the latent mean difference for MI typically involves a series of steps, including testing for configural invariance (i.e., the same factor structure across groups), followed by testing for metric invariance (i.e., the same factor loadings across groups), scalar invariance (i.e., the same intercepts across groups), and, finally, latent mean invariance (i.e., the same latent means across groups) (Kang and Leung 2022).…”

Deductive Reasoning Skills in Children Aged 4–8 Years Old

“…Despite the lack of residual invariance at the age level, the deductive reasoning test has invariances of configural, metric, and scalar models. Therefore, the deductive reasoning test demonstrates a valid and acceptable measurement invariance across age groups in the study (Goñi et al 2020;Kim et al 2022).…”

“…After establishing full scalar measurement invariances of the deductive reasoning test for country, gender, and age groups, the group mean differences of latent variables were explored ( Chiu et al 2015 ; Goñi et al 2020 ; Kim et al 2022 ). Slovakia served as the reference group in the country-level comparison, while boys were used as the reference in the gender-level analysis.…”

Reliability, Validity and Measurement Invariance of the Difer Tests

“…If the configural invariance, factor loading invariance, and intercept invariance were established, the latent mean differences across two groups can be examined in a model in which the factor loadings and intercepts were constrained to be equal (Teo et al, 2022). Latent mean difference refers to the difference in the means of the latent variables (i.e., unobserved variables) between two or more groups in MG-CFA (Kim et al, 2022). Assessing the latent mean difference for MI typically involves a series of steps, including testing for configural invariance (i.e., the same factor structure across groups), followed by testing for metric invariance (i.e., the same factor loadings across groups), scalar invariance (i.e., the same intercepts across groups), and, finally, latent mean invariance (i.e., the same latent means across groups) (Kang & Leung 2022).…”