The Society for Social Work and Research

2013 Annual Conference

January 16-20, 2013 I Sheraton San Diego Hotel and Marina I San Diego, CA

How Well Does An Intent to Leave Proxy Predict Child Welfare Workers' Actual Turnover?

Saturday, January 19, 2013
Grande Ballroom A, B, and C (Sheraton San Diego Hotel & Marina)
* noted as presenting author
Charles Auerbach, PhD, Professor, Yeshiva University, New York, NY
Wendy Schudrich, MSW, Doctoral Student, Yeshiva University, New York, NY
Catherine K. Lawrence, PhD, CSW, Assistant Research Professor, State University of New York at Albany, Albany, NY
Nancy Claiborne, PhD, Associate Professor, State University of New York at Albany, Albany, NY
Background and Purpose: National studies of public and private child welfare agencies report annual turnover rates ranging between 20 and 40 percent, with length of employment averaging less than two years (American Public Human Services Association [APHSA], 2001, 2005; GAO, 2003).  This is problematic because it takes approximately two years to acquire the skills and knowledge necessary to become an effective and independent child welfare practitioner (Louisiana Job Task Force, 2000).  As a result, there has been a growing literature on research of the child welfare workforce to better understand and curb undesired turnover.  Many of these studies use intent to stay/leave as a proxy for actual retention or turnover.  Other studies utilize a series of items to determine the likelihood of leaving.  It is possible that more workers express their intent to leave than actually do leave.  Thus, it is important to determine how well proxies predict actual attrition.

Methods:  Data for this study was obtained from a sample of 77 child welfare workers employed at a voluntary child welfare agency in a large northeastern city.  Voluntary agencies in this locale are private agencies that are under contract with the city and provide preventive services.  Workers in the sample represent various roles within the agency and included administrators, supervisors, social workers, caseworkers, and case planners. The workers filled out an extensive survey that contained items on their intention to leave including, “Have you considered looking for a new job within the past year?”  The researchers returned to the agency 12 months later to obtain data on who actually left. Binary logistic regression was utilized to test how well the proxy “intention to leave” predicted actual turnover.  Stata 12.1 was used to conduct the analysis.

Results:  There were several factors that differentiated those who left from those who remained. For example, 43%  (n = 33) of the workers actually left the agency within a year.  Workers who left had a significantly (t = 3.0; p <. 001) lower mean number of years at the agency (2.3 years) compared to those who remained (6.5 years).  A majority of workers with a social work degree (80%) left compared to 30% of those without a degree (X2=15.2; p < .001).   Almost 70% of those who considered looking for a new job actually left the agency.  Workers who indicated that they did intend to leave had a 2.5 times greater likelihood of actually leaving than those who did not. (OR = 2.5, p = < .05). 

Conclusions and Implications:  The results of this study indicate that the proxy “have you considered looking for a new job within the past year?” is a strong predictor of actual turnover.  Personal characteristics including years employed and having a social work degree were also strong predictors. Although the results of this study need to be replicated, using a proxy for attrition provides a method for administrators to predict planned turnover at their agencies.