Improving Community Adaptation Outcomes for Youth Graduating from Residential Mental Health Programs: A Synthesis Review (FULL REPORT)

The focus of this synthesis review was to understand the capacity of systems of care and integrated program models to foster successful community adaptation for children and youth graduating from children\u27s residential mental health treatment

Pathways to Economic Outcomes and the Impact of Health: Comparing Hispanic and Non-Hispanic Adults after Foster Care

Abstract This study examines the financial outcomes in adulthood of Hispanics (N = 87) and White (Non-Hispanic, N = 498) persons placed in foster care during childhood. It uses the Casey Family Programs National Alumni Study (CFPNAS) database. Path models including predictors such as gender, education, having a partner, preparation for leaving care, and problem characteristics yielded predominantly similar effects for Hispanic and White Non-Hispanic respondents. The direct effect of physical and mental health conditions such as physical or learning disability, visual or hearing impairments, or DSM disorders more strongly predicted negative outcomes for White (Non-Hispanic) respondents than for Hispanic ones

Strategic Predictors of Successful Enterprise Systems Deployment

Purpose The delivered wisdom to date has enterprise system purchase and implementation as one of the most hazardous projects any organization can undertake. The aim was to reduce this risk by both theoretically and empirically finding those key predictors of a successful enterprise system deployment. Design/methodology/approach A representative sample of 60 firms drawn from the Fortune 1000 that had recently (1999-2000) adopted enterprise resource planning (ERP) systems was used to test a model of adoption performance with significant results. Findings Leadership (social learning theory), business process re-engineering (change the company not the technology) and acquisition strategy (buy, do not make) were found to be significant predictors of adoption performance (final model R 2=43 percent, F=5.5, pp Originality/value The “four factor” model we validate is a robust predictor of ERP adoption success and can be used by any organization to audit plans and progress for this undertaking

Strategic Predictors of Successful Enterprise Systems Deployment

Purpose The delivered wisdom to date has enterprise system purchase and implementation as one of the most hazardous projects any organization can undertake. The aim was to reduce this risk by both theoretically and empirically finding those key predictors of a successful enterprise system deployment. Design/methodology/approach A representative sample of 60 firms drawn from the Fortune 1000 that had recently (1999-2000) adopted enterprise resource planning (ERP) systems was used to test a model of adoption performance with significant results. Findings Leadership (social learning theory), business process re-engineering (change the company not the technology) and acquisition strategy (buy, do not make) were found to be significant predictors of adoption performance (final model R 2=43 percent, F=5.5, pp Originality/value The “four factor” model we validate is a robust predictor of ERP adoption success and can be used by any organization to audit plans and progress for this undertaking

Family Dependency Drug Courts: An Empirical Test Of Therapeutic Jurisprudence

The rise in cases of child abuse and neglect over the past two decades has overwhelmed the nation’s dependency court and child welfare agencies. While multiple factors are associated with child abuse and neglect, it is indisputable that substance abuse plays a significant role. The families that come into the dependency system with substance abuse issues are substantially more difficult and challenging to serve. Consequently, the families experience low levels of reunification and high levels of child welfare recidivism. In response to the increase in dependency cases involving substance abuse and the inability of the traditional dependency courts (TDC) to handle these cases, Family Dependency Drug Courts (FDDC) were created. The study utilized Therapeutic Jurisprudence Theory to examine differences in child welfare outcomes between substance abusing individuals served in a traditional dependency court system versus the therapeutic jurisprudence driven Family Dependency Drug Court system. Logistic regression, ANOVA and Chi-square were performed on a non-random sample derived from court systems in two Central Florida counties to examine two child welfare outcomes, specifically reunification rates and child welfare recidivism. The findings indicate that substance using participants in the FDDC have much higher rates of reunification than comparable substance using participants processed through the traditional dependency court. Also, of the individuals who attended FDDC, iv those who graduated were reunified at a significantly higher rate than those that didn’t graduate. In regards to child welfare recidivism within a one year time period, there was not a statistically significant difference when comparing the FDDC participants and the TDC participants. When comparing the FDDC participants who completed the program versus those that failed to complete the program, while the child welfare recidivism rates were not significantly different, there is some evidence that the participants that completed the FDDC program experience less child welfare recidivism than those that don’t have the full experience of therapeutic jurisprudence. This research lends some support for both the FDDC program and the explanatory power of Therapeutic Jurisprudence Theory. Theoretical and policy implications, as well as further research, are proposed and discusse

Building Combined Classifiers

This chapter covers different approaches that may be taken when building an ensemble method, through studying specific examples of each approach from research conducted by the authors. A method called Negative Correlation Learning illustrates a decision level combination approach with individual classifiers trained co-operatively. The Model level combination paradigm is illustrated via a tree combination method. Finally, another variant of the decision level paradigm, with individuals trained independently instead of co-operatively, is discussed as applied to churn prediction in the telecommunications industry