BACKGROUND: Many studies have examined predictors of nurses' intention to work in their job, including desire to quit. Intent has been a good predictor of actual turnover. Few longitudinal studies exist that consider regional variables. OBJECTIVES: To extend the conceptual framework of turnover research to the whole nursing workforce and determine: (1) how do demographics, region (metropolitan statistical area: MSA), movement opportunities, and work setting variables affect registered nurses' (RNs) intent to work and desire to quit; and (2) how do demographics, MSA variables, movement opportunities, and work setting variables affect RNs' work behavior at time 2? DESIGN: Panel study using Dillman's design method. SETTINGS AND PARTICIPANTS: Randomly selected national cluster sample from 40 urban geographic regions (MSAs) in 29 states of the United States. METHODS: Four thousand surveys were sent. There were 1907 female RNs under 65 (48% response rate) from year 1 of which 1348 responded at year 2 (70% response rate). RESULTS: The first analyses used desire to quit (explained 65% of the variance) and intent to work from year 1 as dependent variables. Satisfaction and organizational commitment were significant negative predictors of desire to quit. In the logistic regression on intent to work, the work motivation and work-family conflict were positive and significant as well as wages (negative) and three benefit variables. In year 2, the dependent variable was working or not and if working, full-time or not. For this bivariate probit regression no attitudes influenced the work/not work decision, but MSA level variables, wages (positive) and benefits (positive) did. Organizational commitment and higher workload increased the probability of working FT. CONCLUSIONS: Regional differences across markets need to be controlled and their influence investigated. In addition, attitudes as well as wages and benefits were important in certain decisions: these factors are clearly under the influence of employers.
BACKGROUND: Many studies have examined predictors of nurses' intention to work in their job, including desire to quit. Intent has been a good predictor of actual turnover. Few longitudinal studies exist that consider regional variables. OBJECTIVES: To extend the conceptual framework of turnover research to the whole nursing workforce and determine: (1) how do demographics, region (metropolitan statistical area: MSA), movement opportunities, and work setting variables affect registered nurses' (RNs) intent to work and desire to quit; and (2) how do demographics, MSA variables, movement opportunities, and work setting variables affect RNs' work behavior at time 2? DESIGN: Panel study using Dillman's design method. SETTINGS AND PARTICIPANTS: Randomly selected national cluster sample from 40 urban geographic regions (MSAs) in 29 states of the United States. METHODS: Four thousand surveys were sent. There were 1907 female RNs under 65 (48% response rate) from year 1 of which 1348 responded at year 2 (70% response rate). RESULTS: The first analyses used desire to quit (explained 65% of the variance) and intent to work from year 1 as dependent variables. Satisfaction and organizational commitment were significant negative predictors of desire to quit. In the logistic regression on intent to work, the work motivation and work-family conflict were positive and significant as well as wages (negative) and three benefit variables. In year 2, the dependent variable was working or not and if working, full-time or not. For this bivariate probit regression no attitudes influenced the work/not work decision, but MSA level variables, wages (positive) and benefits (positive) did. Organizational commitment and higher workload increased the probability of working FT. CONCLUSIONS: Regional differences across markets need to be controlled and their influence investigated. In addition, attitudes as well as wages and benefits were important in certain decisions: these factors are clearly under the influence of employers.
Authors: Behdin Nowrouzi; Emilia Giddens; Basem Gohar; Sandrine Schoenenberger; Mary Christine Bautista; Jennifer Casole Journal: Int J Occup Environ Health Date: 2016-10-13
Authors: Eva Smokrović; Tomislav Kizivat; Antun Bajan; Krešimir Šolić; Zvjezdana Gvozdanović; Nikolina Farčić; Boštjan Žvanut Journal: Int J Environ Res Public Health Date: 2022-07-05 Impact factor: 4.614