On the Distribution of the Inverted Linear Compound of Dependent F-Variates and its Application to the Combination of Forecasts

This paper establishes a sampling theory for an inverted linear combination of two dependent F-variates. It is found that the random variable is approximately expressible in terms of a mixture of weighted beta distributions. Operational results, including rth-order raw moments and critical values of the density are subsequently obtained by using the Pearson Type I approximation technique. As a contribution to the probability theory, our findings extend Lee & Hu's (1996) recent investigation on the distribution of the linear compound of two independent F-variates. In terms of relevant applied works, our results refine Dickinson's (1973) inquiry on the distribution of the optimal combining weights estimates based on combining two independent rival forecasts, and provide a further advancement to the general case of combining three independent competing forecasts. Accordingly, our conclusions give a new perception of constructing the confidence intervals for the optimal combining weights estimates studied in the literature of the linear combination of forecasts.     

Opportunities for public relations research in public health

While communication researchers have developed a solid body of knowledge in the health field, we know little about the activities of public relations practitioners in public health bodies. This is unfortunate, because public health bodies at the federal, state, and local level have faced considerable criticism for what amounts to poor public relations. Public relations scholarship and practice have much to offer the field of public health in helping public health bodies meet their challenges. In order for public relations scholars to assist public health bodies, however, scholars first must fill a void in the research by investigating the public relations functions of public health bodies. The author suggests six avenues of public relations research in the field of public health.     

Reexamining the Nurse Scheduling Problem: Staffing Ratios and Nursing Shortages*

Legislators at the state and national levels are addressing renewed concerns over the adequacy of hospital nurse staffing to provide quality care and ensure patient safety. At the same time, the well‐known nursing shortage remains an ongoing problem. To address these issues, we reexamine the nurse scheduling problem and consider how recent health care legislation impacts nursing workforce management decisions. Specifically, we develop a scheduling model and perform computational experiments to evaluate how mandatory nurse‐to‐patient ratios and other policies impact schedule cost and schedule desirability (from the nurses' perspective). Our primary findings include the following: (i) nurse wage costs can be highly nonlinear with respect to changes in mandatory nurse‐to‐patient ratios of the type being considered by legislators; (ii) the number of undesirable shifts can be substantially reduced without incurring additional wage cost; (iii) more desirable scheduling policies, such as assigning fewer weekends to each nurse, have only a small impact on wage cost; and (iv) complex policy statements involving both single‐period and multiperiod service levels can sometimes be relaxed while still obtaining good schedules that satisfy the nurse‐to‐patient ratio requirements. The findings in this article suggest that new directions for future nurse scheduling models, as it is likely that nurse‐to‐patient ratios and nursing shortages will remain a challenge for health care organizations for some time.     

Methodologic challenges of e-health research

In this article, research-based strategies used in a web-based study to assess the impact of participation in cancer-related mailing lists on cancer survivors and caregivers are highlighted. The paper presents alternative methods of measuring response rates in Internet surveys. Response rate estimation, based on American Association for Public Opinion Research guidelines, ranged between 15% and 24.9% for the study. Several strategies were implemented to increase survey participation and reduce item nonresponse. Few participants opted for a telephone survey as an alternative to a web-administered design (mixed-mode administration). Using time-stamp data to diagnose places in the questionnaire where respondents prematurely exited or broke off survey participation, we were able to decrease premature break offs. A lottery was also implemented to increase response rates. The experience of obtaining institutional review board approval for the lottery is also described. Preliminary data indicate slight increases in response rates subsequent to implementing the lottery.     

Recidivism and resilience in juvenile sexual offenders: an analysis of the literature

The majority of research that exists studying juvenile sex offenders (JSOs) is dominated by the predilection that identifying risk factors associated with recidivism will benefit both the JSOs and treatment providers. Further, the majority of existing treatments are guided by research that has identified what makes JSOs more likely to reoffend. Absent from the majority of the literature is an examination of the strengths and positive characteristics demonstrated by JSOs that may prove useful in both reducing recidivism and increasing the likelihood of achieving positive outcomes (i.e., demonstrating resilience). Research examining known risk factors for sexual and nonsexual recidivism is described. Next, literature on resilience is reviewed, followed by a discussion of this literature in the context of treatment for JSOs. Finally, future directions of research are presented.