Engaging fathers : examining social service agency father-friendliness and its relationships with father involvement

Social scientists have become increasingly interested over the past 30 years in the role fathers play in child development. As a result, a large bank of research has been accumulated; however, one area in this literature which remains understudied is the relationships between agency father friendliness and father involvement. This paper is one attempt to understand the intricacies of the interchange point between fathers and agencies by using longitudinal data collected by the Supporting Father Involvement study, specifically examining the associations between father involvement and father friendliness, as well as the relationships among the various components of agency father friendliness over time. Based on the results of the analysis, recommendations are made about how agencies can increase their level of father friendliness and increase father involvement among their clients

Scaling-up Child and Youth Mental Health Services: Assessing Coverage of a County-wide Initiative

Over 7 million children and youth have a diagnosable mental illness any given year. There are evidence-based treatments (EBTs) to effectively treat these conditions, but these EBTs reach a very small percentage of their target population with treatment rates between 1-3%.1 We know very little about what influences these coverage rates. Beginning in 2009, the Los Angeles County Mental Health Department (LACDMH) began an ambitious agenda to scale-up the provision of EBTs in child/youth mental health care. The present study seeks to contribute to the scale-up literature by examining three questions based on LACDMH’s initiative: 1) To what extent have the county’s selected EBTs reached their target population?; 2) Are there differences in coverage rates within the county?; and 3) What factors are associated with the coverage rates? To answer these questions, the author used small area variation analysis and geospatial methods to create coverage scores at the county, service planning area, and clinic service area levels. The author aggregated community and clinic characteristics to the clinic service area level (n=254) to assess factors related to coverage. The author used LACDMH administrative claims data for FY 2013-2014 with population data from the American Community Survey 2014 5-yr estimates (ACS). The county reached 17% of its target population during FY 2013-2014. Coverage varied throughout the county. OLS regression results indicated that the proportion of ethnic minorities, immigrants and adults with a college degree were negatively associated with clinic service area coverage scores