Usability in product design--the importance and need for systematic assessment models in product development--Usa-Design Model (U-D) ©

In product design, human factors are considered as an element of differentiation given that today's consumer demands are increasing. Safety, wellbeing, satisfaction, health, effectiveness, efficiency, and other aspects must be effectively incorporated into the product development process. This work proposes a usability assessment model that can be incorporated as an assessment tool. The methodological approach is settled in two stages. First a literature review focus specifically on usability and developing user-centred products. After this, a model of usability named Usa-Design (U-D?) is presented. Consisted of four phases: understanding the use context, pre-preliminary usability assessment (efficiency/effectiveness/satisfaction); assessment of usability principles and results, U-D? features are modular and flexible, allowing principles used in Phase 3 to be changed according to the needs and scenario of each situation. With qualitative/quantitative measurement scales of easy understanding and application, the model results are viable and applicable throughout all the product development process.     

100 key research questions for the post‐2015 development agenda

The Sustainable Development Goals (SDGs) herald a new phase for international development. This article presents the results of a consultative exercise to collaboratively identify 100 research questions of critical importance for the post‐2015 international development agenda. The final shortlist is grouped into nine thematic areas and was selected by 21 representatives of international and non‐governmental organisations and consultancies, and 14 academics with diverse disciplinary expertise from an initial pool of 704 questions submitted by 110 organisations based in 34 countries. The shortlist includes questions addressing long‐standing problems, new challenges and broader issues related to development policies, practices and institutions. Collectively, these questions are relevant for future development‐related research priorities of governmental and non‐governmental organisations worldwide and could act as focal points for transdisciplinary research collaborations.     

Framing in Legislation: The Case of Population Policy in the Philippines

This paper investigates the political framing of population in policy discourse through an analysis of legislative documents. Semantic network analysis was conducted and results were interpreted through discourse analysis of the typical arguments identified. Policy texts were classified into three sets: population management, reproductive health and family planning, and anti-abortion and anti-FP. While the “population management” frame focuses on social and economic consequences of population growth, the “reproductive health” frame defines the problem from a health perspective. Both policies propose aggressive FP programs but each frame uses distinct political rhetoric and semantic approach in its arguments. The “anti-abortion and anti-FP” frame identifies two problems: rise in incidence of abortion and existing policy that prohibit health professionals from refusing patients information on contraception. By invoking a moral argument and anchoring on rights, these policies challenge the problem and solutions identified by the first two frames.     

Realistic Major Previews in the School‐to‐College Transition of Italian High School Students

Industrial/organizational researchers have reported that realistic job previews diminish prospective workers' expectations but promote the satisfaction and persistence of those who ultimately accept a job assignment. The authors applied this strategy to the context of school‐to‐college transition; 354 Italian high school students were provided with a 2‐hour lecture designed to simulate exposure to a college major of their choice. Students showed moderate pre‐post increases in subject matter knowledge but reported small decreases in interests and outcome expectations (but not self‐efficacy) related to the academic major to which they were exposed.     

Inflated beta distributions

This paper considers the issue of modeling fractional data observed on [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model since its density can have quite different shapes depending on the values of the two parameters that index the distribution. Properties of the proposed distributions are examined. Also, estimation based on maximum likelihood and conditional moments is discussed. Finally, practical applications that employ real data are presented.     

Benefits and costs associated with mutual-help community-based recovery homes: The Oxford House model

We used data from a randomized controlled study of Oxford House (OH), a self-run, self-supporting recovery home, to conduct a cost-benefit analysis of the program. Following substance abuse treatment, individuals that were assigned to an OH condition (n = 68) were compared to individuals assigned to a usual care condition (n = 61). Economic cost measures were derived from length of stay at an Oxford House residence, and derived from self-reported measures of inpatient and outpatient treatment utilization. Economic benefit measures were derived from self-reported information on monthly income, days participating in illegal activities, binary responses of alcohol and drug use, and incarceration. Results suggest that OH compared quite favorably to usual care: the net benefit of an OH stay was estimated to be roughly $29,000 per person on average. Bootstrapped standard errors suggested that the net benefit was statistically significant. Costs were incrementally higher under OH, but the benefits in terms of reduced illegal activity, incarceration and substance use substantially outweighed the costs. The positive net benefit for Oxford House is primarily driven by a large difference in illegal activity between OH and usual care participants. Using sensitivity analyses, under more conservative assumptions we still arrived at a net benefit favorable to OH of $17,830 per person.     

Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy): spatial special issue

To improve the quality of prediction of radioactive contamination, geostatistical methods, and in particular multivariate geostatistical models, are increasingly being used. These methods, however, are optimal only in the case in which the data may be assumed Gaussian and do not properly cope with data measurements that are discrete, nonnegative or show some degree of skewness. To deal with these situations, here we consider a hierarchical model in which non-Gaussian variables of different kind are handled simultaneously. We show that when observations are assumed to be conditionally distributed as Poisson and Gamma, variograms and cross-variograms have convenient simple forms, and estimation of the parameters of the model can be carried out by Monte Carlo EM. This work was inspired by radioactive contamination data from the Maddalena Archipelago (Sardinia, Italy).     

Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed

In this paper we examine maximum likelihood estimation procedures in multilevel models for two level nesting structures. Usually, for fixed effects and variance components estimation, level-one error terms and random effects are assumed to be normally distributed. Nevertheless, in some circumstances this assumption might not be realistic, especially as concerns random effects. Thus we assume for random effects the family of multivariate exponential power distributions (MEP); subsequently, by means of Monte Carlo simulation procedures, we study robustness of maximum likelihood estimators under normal assumption when, actually, random effects are MEP distributed.