Predictors of RNs’ intent to work and work decisions 1 year later in a U.S. national sample

BackgroundMany 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.ObjectivesTo 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?DesignPanel study using Dillman's design method.Settings and participantsRandomly selected national cluster sample from 40 urban geographic regions (MSAs) in 29 states of the United States.MethodsFour 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).ResultsThe 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.ConclusionsRegional 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.