Predicting Burnout and Leave Intentions in Child Welfare: Case, Provider, and Organizational Factors.

Abstract

Child welfare caseloads are frequently higher than optimal, leading to provider burnout and turnover. This study aims to identify which case, provider, and organizational factors differentiate providers with higher versus lower burnout and leave intentions. Participants were 26 Family Advocacy Program providers and 17 supervisors at 11 U.S. Department of the Air Force installations who provided data for seven months. We used linear mixed-effects model tree algorithms to determine the factors that distinguish favorable and unfavorable outcomes. The model predicting burnout yielded three significant partitioning variables: (a) number of cases on the high risk for violence and child sexual maltreatment response team lists, (b) command support, and (c) years since licensure. The model predicting leave intentions yielded five significant partitioning variables: (a) client challenge, (b) number of cases, (c) ease of reaching commanders of on-base tenant units, (d) percentage of clients receiving substance abuse treatment services, and (e) command support. This study is a first step toward developing dynamic caseload management tools.