Should I stay or should I go? Career change and labor force separation among registered nurses in the U.S.
Efforts to retain nurses within the profession are critical for resolving the global nursing shortage, but very little research explores the phenomenon of nursing workforce attrition in the U.S. This study is the first to simultaneously investigate the timing of attrition through survival analysis, the exit path taken (career change vs. labor force separation), and the major socioeconomic, family structure, and demographic variables predicting attrition in this country. Using nationally representative U.S. data from the 2004 National Sample Survey of Registered Nurses (N=29,472), we find that the rate of labor force separation is highest after the age of 60, a typical pattern for retirement. However, a non-trivial proportion of career change also occurs at older ages (50+ years old), and the rate of labor force separation begins to climb at relatively young ages (30-40 years old). Particularly strong predictors of early labor force separation include being married and providing care to dependents in the home (young children or elderly parents). Career change is predicted strongly by higher levels of education, male gender, and current enrollment in a non-nursing degree program. Having an Advanced Practice credential reduced the hazards of attrition for both exit paths. The results suggest a fruitful path for future research and a number of policy approaches to curbing nurse workforce attrition.
Nooney
Jennifer G
JG
University of Central Florida, Florida Center for Nursing, 12424 Research Parkway, Ste. 220, Orlando, FL 32826, USA. Electronic address: jnooney@mail.ucf.edu.
Unruh
Lynn
L
University of Central Florida, Department of Health Management and Informatics, Orlando, FL, USA.
Yore
Michelle M
MM
University of Central Florida, Florida Center for Nursing, 12424 Research Parkway, Ste. 220, Orlando, FL 32826, USA.
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002322:Career Mobility; D004651:Employment / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009726:Nurses / Q000706:statistics & numerical data* / Q000600:supply & distribution; D012179:Retirement; D012737:Sex Factors; D012959:Socioeconomic Factors; D014481:United States; D055815:Young Adult