Adaptive and Maladaptive Correlates of Repetitive Behavior and Restricted Interests in Persons with Down Syndrome and Developmentally-Matched Typical Children: A Two-Year Longitudinal Sequential Design

We examined the course of repetitive behavior and restricted interests (RBRI) in children with and without Down syndrome (DS) over a two-year time period. Forty-two typically-developing children and 43 persons with DS represented two mental age (MA) levels: `` younger'' 2-4 years; `` older'' 5-11 years. For typically developing younger children some aspects of RBRI increased from Time 1 to Time 2. In older children, these aspects remained stable or decreased over the two-year period. For participants with DS, RBRI remained stable or increased over time. Time 1 RBRI predicted Time 2 adaptive behavior (measured by the Vineland Scales) in typically developing children, whereas for participants with DS, Time 1 RBRI predicted poor adaptive outcome (Child Behavior Checklist) at Time 2. The results add to the body of literature examining the adaptive and maladaptive nature of repetitive behavior.

'Security Here is Not Safe': Violence, Punishment, & Space in the Contemporary U.S. Penitentiary

The US penitentiary at Lewisburg, Pennsylvania, was retrofitted in 2008 to offer the country’s first federal Special Management Unit (SMU) program of its kind. This model SMU is designed for federal inmates from around the country identified as the most intractably troublesome, and features double-celling of inmates in tiny spaces, in 23-hour or 24-hour a day lockdown, requiring them to pass through a two-year program of readjustment. These spatial tactics, and the philosophy of punishment underlying them, contrast with the modern reform ideals upon which the prison was designed and built in 1932. The SMU represents the latest punitive phase in American penology, one that neither simply eliminates men as in the premodern spectacle, nor creates the docile, rehabilitated bodies of the modern panopticon; rather, it is a late-modern structure that produces only fear, terror, violence, and death. This SMU represents the latest of the late-modern prisons, similar to other supermax facilities in the US but offering its own unique system of punishment as well. While the prison exists within the system of American law and jurisprudence, it also manifests features of Agamben’s lawless, camp-like space that emerges during a state of exception, exempt from outside scrutiny with inmate treatment typically beyond the scope of the law.

"Security Here is Not Safe": Violence, Punishment, and Space in the Contemporary US Penitentiary

The US penitentiary at Lewisburg, Pennsylvania, was retrofitted in 2008 to offer the country's first federal Special Management Unit (SMU) program of its kind. This model SMU is designed for federal inmates from around the country identified as the most intractably troublesome, and features double-celling of inmates in tiny spaces, in 23-hour or 24-hour a day lockdown, requiring them to pass through a two-year program of readjustment. These spatial tactics, and the philosophy of punishment underlying them, contrast with the modern reform ideals upon which the prison was designed and built in 1932. The SMU represents the latest punitive phase in American penology, one that neither simply eliminates men as in the premodern spectacle, nor creates the docile, rehabilitated bodies of the modern panopticon; rather, it is a late-modern structure that produces only fear, terror, violence, and death. This SMU represents the latest of the late-modern prisons, similar to other supermax facilities in the US but offering its own unique system of punishment as well. While the prison exists within the system of American law and jurisprudence, it also manifests features of Agamben's lawless, camp-like space that emerges during a state of exception, exempt from outside scrutiny with inmate treatment typically beyond the scope of the law

Quality Control in the Healthcare Industry: An Analysis of Surgery Turnover Times

For virtually all hospitals, utilization rates are a critical managerial indicator of efficiency and are determined in part by turnover time. Turnover time is defined as the time elapsed between surgeries, during which the operating room is cleaned and preparedfor the next surgery. Lengthier turnover times result in lower utilization rates, thereby hindering hospitals’ ability to maximize the numbers of patients that can be attended to. In this thesis, we analyze operating room data from a two year period provided byEvangelical Community Hospital in Lewisburg, Pennsylvania, to understand the variability of the turnover process. From the recorded data provided, we derive our best estimation of turnover time. Recognizing the importance of being able to properly modelturnover times in order to improve the accuracy of scheduling, we seek to fit distributions to the set of turnover times. We find that log-normal and log-logistic distributions are well-suited to turnover times, although further research must validate this finding. Wepropose that the choice of distribution depends on the hospital and, as a result, a hospital must choose whether to use the log-normal or the log-logistic distribution. Next, we use statistical tests to identify variables that may potentially influence turnover time. We find that there does not appear to be a correlation between surgerytime and turnover time across doctors. However, there are statistically significant differences between the mean turnover times across doctors. The final component of our research entails analyzing and explaining the benefits of introducing control charts as a quality control mechanism for monitoring turnover times in hospitals. Although widely instituted in other industries, control charts are notwidely adopted in healthcare environments, despite their potential benefits. A major component of our work is the development of control charts to monitor the stability of turnover times. These charts can be easily instituted in hospitals to reduce the variabilityof turnover times. Overall, our analysis uses operations research techniques to analyze turnover times and identify manners for improvement in lowering the mean turnover time and thevariability in turnover times. We provide valuable insight into a component of the surgery process that has received little attention, but can significantly affect utilization rates in hospitals. Most critically, an ability to more accurately predict turnover timesand a better understanding of the sources of variability can result in improved scheduling and heightened hospital staff and patient satisfaction. We hope that our findings can apply to many other hospital settings.