Child Welfare Workers' Turnover Intentions: A Multi-Level Approach

Background:

High employee turnover is a continuing problem in American child welfare systems. Instability in the child welfare workforce not only has a financial impact on these systems, but also has a very real impact on the lives of the youth and families served by them. Prior attempts to predict factors that lead to worker turnover have yielded mixed results and gaps in our understanding remain. Specifically, prior research has given scant attention to the influence of job function beyond basic comparisons of supervisory versus non-supervisory personnel. Thus, the aim of the present study is to model turnover intentions both at the individual worker level and the job function level.

Methods:

Data were obtained from a survey of child welfare workers in a large public agency in the southern US. Respondents (n=906) were nested within 25 different job functions and had the following characteristics: 66% urban, 85% female, 19% held master of social work degrees, 44% white, 32% supervisors, 6% executives, mean age 39.84 (SD=10.52), mean duration of agency employment 8.50 years (SD=6.99). Multi-level regression (hierarchical linear modeling) was used to assess which worker and job function characteristics predicted respondents’ intent to remain in child welfare until retirement, which is a proxy for turnover intent.

Results:

Approximately 85% of the total variability in turnover intent occurred at the worker level with 15% at the job function level. The final model accounted for nearly 35% of variance at the individual level and 14% of variance at the job function level. At the individual level, worker age, rural location, duration of employment in child welfare, satisfaction with salary, job satisfaction, work unit cohesiveness, satisfaction with university preparation to work in child welfare, and self-assessment of skill working with special needs clients all positively predicted intent to remain until retirement. Possessing a master of social work degree and being non-white negatively predicted intent to remain. Interestingly, respect from coworkers and self-assessment of skills working with diverse populations were no longer significant predictors after controlling for the nesting of workers within job functions. At the job function level, supervisors and executives expressed higher intent to remain than frontline workers.

Implications:

The most important findings from the present study are: (a) a significant portion of variance in turnover intentions occurs at the job function rather than individual level; (b) a significant portion of variance at the job function level remains even after controlling for supervisor status; and (c) individual-level predictors may become non-significant after controlling for the nesting of workers into job functions. Future research should include job function characteristics as well as individual worker characteristics when exploring factors influencing child welfare workers’ turnover intentions. Insights from this line of inquiry could help agencies target retention efforts to job functions with higher turnover risk as well as clarify individual worker-level characteristics that predict turnover.