The impact of religiousness, spirituality, and social support on psychological well-being among older adults in rural areas

This paper presents the results of a study on the impact of spirituality, religiousness, and social support on the psychological well-being among rural elderly. With a rural community sample of 215 older adults, hierarchical regression analyses found significant associations between dimensions of spirituality/religiousness, social support, and psychological well-being, with spirituality/religiousness inversely related to depression and social support, positively related to life satisfaction. Findings of this study suggest that practitioners need to develop programs or services that are congruent with religious/spiritual beliefs and practices in order to better enhance the psychosocial well-being and improve the quality of life among older persons in rural areas.     

Editorial

Journal of Nonverbal Behavior -     

Developing From Tranditional Microscale Chemistry to Microscale Green Chemistry

Microscale chemistry is appealing to all levels of education.In contrast to conventional macroscale chemistry,only minute amount of chemicals are required to undertaking a chemical investigation.     

Complementary Relationships Between Traditional Media and Health Apps Among American College Students

Abstract

Objective: This study explored the potential relationships between existing media and health apps for health information among college students. Participants: This study collected and analyzed a total of 408 surveys from students of 7 universities across the United States. Methods: In order to explore the research questions and test the hypotheses, quantitative data from the online survey were analyzed through hierarchical regression analyses. Results: Results from the hierarchical regression analyses indicated that the perceived credibility of health information from traditional mass media was positively and significantly associated with college students' perception of health apps. However, there was no significant effect in regards to online media. Conclusions: This study's consideration of the relationships between existing media and health apps may guide health practitioners in their strategic approaches to improve the well-being of college students.     

Two ways of modelling overdispersion in non-normal data

For non-normal data assumed to have distributions, such as the Poisson distribution, which have an a priori dispersion parameter, there are two ways of modelling overdispersion: by a quasi-likelihood approach or with a random-effect model. The two approaches yield different variance functions for the response, which may be distinguishable if adequate data are available. The epilepsy data of Thall and Vail and the fabric data of Bissell are used to exemplify the ideas.     

The robustness of the quasilikelihood estimator

The quasilikelihood estimator is widely used in data analysis where a likelihood is not available. We illustrate that with a given variance function it is not only conservative, in minimizing a maximum risk, but also robust against a possible misspecification of either the likelihood or cumulants of the model. In examples it is compared with estimators based on maximum likelihood and quadratic estimating functions.     

CONVERGENCE AND PREDICTION OF PRINCIPAL COMPONENT SCORES IN HIGH-DIMENSIONAL SETTINGS

A number of settings arise in which it is of interest to predict Principal Component (PC) scores for new observations using data from an initial sample. In this paper, we demonstrate that naive approaches to PC score prediction can be substantially biased towards 0 in the analysis of large matrices. This phenomenon is largely related to known inconsistency results for sample eigenvalues and eigenvectors as both dimensions of the matrix increase. For the spiked eigenvalue model for random matrices, we expand the generality of these results, and propose bias-adjusted PC score prediction. In addition, we compute the asymptotic correlation coefficient between PC scores from sample and population eigenvectors. Simulation and real data examples from the genetics literature show the improved bias and numerical properties of our estimators.     

Mad, Bad, or Reasonable? Newspaper Portrayals of the Battered Woman Who Kills

A heated debate about battered women who kill abusive male partners started in the 1970s. In this study, we tracked the public discourse on battered women who kill by coding 250 newspaper articles published between 1978 and 2002. Using four typifying models, we found that leading explanations for why battered women kill medicalized then criminalized their actions; they were mad then bad. We also found that reporters used quotes from claims makers supporting conventional or medical typifications of battered women to a much greater degree than statements from alternative, feminist sources. In conclusion, simplified, sensational and conventional understandings of crime causation drove the social construction of “the battered woman who kills”. She may be mad or bad, but rarely has she been portrayed as reasonable. Suggestions for promoting feminist narrative in the media are also provided.     

Recovery of inter-block information: extensions in a two variance component model

For a two variance component mixed linear model, it is shown that under suitable conditions there exists a nonlinear unbiased estimator that is better than a best linear unbiased estimator defined with respect to a given singular covariance matrix. It is also shown how this result applies to improving on intra-block estimators and on estimators like the unweighted means estimator in a random one-way model.