Quality of life among lifetime victimized men

Quality of life was compared for lifetime victimized (n = 353) and nonvictimized men (n = 167) for demographic and quality of life variables by a cross-sectional design. The univariate analyses showed that victims compared to nonvictims had a lower quality of life, were younger, more often had upper secondary school education, and were more often blue-collar/low white-collar workers, on student allowances, on unemployment, financially strained, and smokers. The regressions revealed that unemployment, financial strain, smoking, depression, and home/public abuse were associated with reduced quality of life among victimized men. Being a blue-collar/low/intermediate white-collar worker and social support were related to increased quality of life. This study may have provided new insights into the experiences of quality of life of victimized men.     

Pearls and pitfalls in evaluating a Student Assistance Program: a five-year case study

This article presents data from a five-year evaluation-research case study of a large urban schools district's internal Student Assistance Program (SAP). The district employed specially trained and licensed school-based counselors to implement an internal SAP expanded to include tertiary prevention, and modeled after an employee assistance program established for adults. From the population of more than 10,000 students who received some type of program assistance for at-risk behaviors, a stratified random sample of 2,238 cases, over a five year period, were reviewed. Results indicate a statistically significant decline (p < .05) in students' drug use and a significant improvement in internal locus of control occurred each year. While not statistically significant, the average number of student discipline referrals was less than the year prior to program admission; however, there was no significant change in academic performance. A significant correlation between students' drug use and the amount of time in program, the type of assistance received, and the student's custody status was also found.     

Relationships among nutrients,chloride and biological indices in urban Maryland streams

Using a spatially extensive urban database constructed from the Maryland Biological Stream Survey (MBSS), we describe the relationships of nutrients in small-order streams to eight defined categories of percent catchment urbanization, correlations between chloride and conductivity in urban streams, and relationships between nutrients and chloride with two Maryland-specific indices of biotic integrity for benthic macroinvertebrates and fish assemblages. Stream nutrients become elevated with increasing percent catchment urbanization, followed by increases in all four measured nitrogen species and total phosphorus at catchment urbanization levels greater than 10%. There was a strong collinear relationship (r ² = 0.90) between chloride and conductivity (trimeans) across all eight urbanization classes, where Cl (mg/L) = −0.397 + 0.188*conductivity (μS/cm). Critical values for all water quality parameters with the two Maryland biological indices were derived using quantile regression, with significant regressions developed for 11 of 16 water quality parameters and the two biotic indices. For nitrate (NO₃-N), the critical thresholds between fair and poor stream quality for the two Maryland biological indices were 0.83 mg/L (benthic macroinvertebrate assemblages) and 0.86 mg/L (fish assemblages). Increasing stream nutrient and chloride levels, associated with widespread catchment urbanization intensity, now affect many small streams in Maryland, with implications for decreasing water quality in major tributaries and the Chesapeake Bay.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

FORECAST EVALUATION OF LIVINGSTON DATA ON INFLATION RATES AND INFLATION UNCERTAINTY*

Livingston data on expected inflation rates have been used extensively in the financial literature, especially in investgating the relationship between nominal interest rates and expected inflation rates; however, the data have not been subjected to a thorough analysis of forecast accuracy. The objective of this paper is to analyze the forecast properties of Livingston data using a wide variety of time and frequency domain methods over an extended sample period and for selected subperiods.     

The Predicament of Population Aging: A Review Essay*

Ken Dychtwald, Age Power: How the 21st Century Will Be Ruled by the New Old Richard Leete (ed.), Dynamics of Values in Fertility Change Donald T. Critchlow, Intended Consequences: Birth Control, Abortion, and the Federal Government in Modern America Bernard Jeune and James W. Vaupel (eds.), Validation of Exceptional Longevity     

Assessing attitude toward same-sex marriage: scale development and validation

This paper reports the results of three studies conducted to develop, refine, and validate a scale which assessed heterosexual adults' attitudes toward same-sex marriage, the Attitude Toward Same-Sex Marriage Scale (ASSMS). The need for such a scale is evidenced in the increasing importance of same-sex marriage in the political arena of the United States and other nations, as well as the growing body of empirical research examining same-sex marriage and related issues (e.g., Lannutti, 2005; Solomon, Rothblum, & Balsam, 2004). The results demonstrate strong reliability, convergent validity, and predictive validity for the ASSMS and suggest that the ASSMS may be adapted to measure attitudes toward civil unions and other forms of relational recognition for same-sex couples. Gender comparisons using the validated scale showed that in college and non-college samples, women had a significantly more positive attitude toward same-sex marriage than did men.     

The exponentiated power exponential regression model with different regression structures: application in nursing data

We define the exponentiated power exponential distribution and propose a regression model with different systematic structures based on the new distribution. We show that the new regression model can be applied to dispersion data since it represents a parametric family of models that includes as sub-models some widely-known regression models. It then can be used more effectively in the analysis of real data. We use maximum likelihood estimation and derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. Some global-influence measurements are also investigated and simulation studies are performed to evaluate the accuracy of the estimates. We provide an application of the regression model with four systematic structures to nursing activities score data in the Unit of the Medical Clinic of University of São Paulo (USP) Hospital.