Latent profiles of job embeddedness and their predictors among specialist nurses in China

Abstract

Objective: The aim of this study is to identify potential categories of job embeddedness among specialist nurses using latent profile analysis, explore the demographic characteristics of each subgroup, and examine the relationship between these profiles and their sense of professional mission.

Methods: From March to April 2024, 492 specialist nurses from six general hospitals in Sichuan Province, China, were selected in this study using convenience sampling. A socio-demographic characteristic questionnaire, job embeddedness scale, and professional mission scale were used. Mplus 8.3 was used to explore the potential subgroups of job embeddedness among specialist nurses by latent profile analysis. IBM SPSS 26.0 was used to analyze the factors influencing the job embeddedness of specialist nurses in each category using univariate and Multinomial logistic regression analyses.

Results: 484 specialist nurses were finally included. Specialist nurses' job embeddedness score was (27.63 ± 4.89). Specialist nurses' job embeddedness could be categorized into three potential profiles: low embedded-alienation group (n = 113, 23.4%), medium job-embedded group (n = 199, 41.1%), and high embedded-identity group (n = 172, 35.5%). The results of the multivariate logistic regression showed that unmarried (OR = 0.087, p = 0.045), ≤3 years of specialty nursing experience (OR = 0.093, p = 0.029), choosing a nursing specialty based on personal interest (OR = 4.854, p = 0.013), and good and fair self-assessed health (OR = 10.211, p = 0.002 OR = 9.682, p = 0.002; OR = 10.656, p = 0.028; OR = 9.269, p = 0.037), low and moderate work intensity (OR = 5.719, p = 0.046; OR = 4.002, p = 0.017), and sense of professional mission (OR = 1.559, p < 0.001; OR = 2.542, p < 0.001) were the main factors influencing the job embeddedness potential profile of specialist nurses (all p < 0.05).

Conclusion: There is significant heterogeneity in job embeddedness among specialist nurses, with medium job-embedded group and high embedded-identity groups dominating. Nursing managers should develop targeted intervention strategies based on the characteristics of different job embeddedness types of specialist nurses, such as optimizing human resource allocation and strengthening positive publicity for specialist nurses to stimulate a sense of professional mission among specialist nurses, which will enhance job embeddedness and reduce the turnover rate of specialist nurses.

Keywords: influencing factors; job embeddedness; latent profile analysis; professional mission; specialist nurses.

Figure 1

Latent profile overview of job embeddedness among specialist nurses.