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.     

How Samsung organized for innovation

This study examines a Korean firm, the Samsung Corporation, to find out: What are the characteristics of the organizational innovations in the era of globalization? What are the consequences of the organizational innovations? What problems does the company face in implementing them? And what are the remedies to overcome those problems? The company has made efforts in three ways: 1. operating teams; 2. flattening of hierarchy; and 3. networking. These three innovations were interrelated and can be often observed in a single organization which is labelled a “Clustered Web” organization. The innovations faced problems and required time to be implemented. Remedies for those problems and implications are discussed.     

A Weighting Approach for GEE Analysis with Missing Data

We propose a new weighting (WT) method to handle missing categorical outcomes in longitudinal data analysis using generalized estimating equations (GEE). The proposed WT provides a valid GEE estimator when the data are missing at random (MAR), and has more stable weights and shows advantage in efficiency compared to the inverse probability weighing method in the presence of small observation probabilities. The WT estimator is similar to the stabilized weighting (SWT) estimator under mild conditions, but it is more stable and efficient than SWT when the associations of the outcome with the observation probabilities and the covariate are strong.     

A mixture of beta–Dirichlet processes prior for Bayesian analysis of event history data

In this paper, we propose a mixture of beta–Dirichlet processes as a nonparametric prior for the cumulative intensity functions of a Markov process. This family of priors is a natural extension of a mixture of Dirichlet processes or a mixture of beta processes which are devised to compromise advantages of parametric and nonparametric approaches. They give most of their prior mass to the small neighborhood of a specific parametric model. We show that a mixture of beta–Dirichlet processes prior is conjugate with Markov processes. Formulas for computing the posterior distribution are derived. Finally, results of analyzing credit history data are given.     

Multivariate Control Charts Based on Hybrid Novelty Scores

We propose a new nonparametric multivariate control chart that integrates a novelty score. The proposed control chart uses as its monitoring statistic a hybrid novelty score, calculated based on the distance to local observations as well as on the distance to the convex hull constructed by its neighbors. The control limits of the proposed control chart were established based on a bootstrap method. A rigorous simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compare it with existing multivariate control charts in terms of average run length (ARL) performance. The simulation results showed that the proposed control chart outperformed both the parametric and nonparametric Hotelling's T ² control charts, especially in nonnormal situations. Moreover, experimental results with real semiconductor data demonstrated the applicability and effectiveness of the proposed control chart. To increase the capability to detect small mean shift, we propose an exponentially weighted hybrid novelty score control chart. Simulation results indicated that exponentially weighted hybrid score charts outperformed the hybrid novelty score based control charts.     

Adaptive and repeated cumulative meta‐analyses of safety data during a new drug development process

During a new drug development process, it is desirable to timely detect potential safety signals. For this purpose, repeated meta‐analyses may be performed sequentially on accumulating safety data. Moreover, if the amount of safety data from the originally planned program is not enough to ensure adequate power to test a specific hypothesis (e.g., the noninferiority hypothesis of an event of interest), the total sample size may be increased by adding new studies to the program. Without appropriate adjustment, it is well known that the type I error rate will be inflated because of repeated analyses and sample size adjustment. In this paper, we discuss potential issues associated with adaptive and repeated cumulative meta‐analyses of safety data conducted during a drug development process. We consider both frequentist and Bayesian approaches. A new drug development example is used to demonstrate the application of the methods. Copyright © 2015 John Wiley & Sons, Ltd.     

Part-time employment and worker health in the United States

A growing body of research has highlighted the consequences of part-time employment for workers’ health and well-being. However, these studies have yielded inconsistent results and relied on cross-sectional data. In addition, relatively little empirical research has explored whether the effect of working part-time on health varies by gender, particularly in the United States. Using longitudinal data from three waves of the General Social Survey panel (2010–2012–2014), our study examined the association between part-time employment and perceived health among U.S employees, and whether this association varied by gender. The results showed that part-time workers were less likely to report poor self-rated health than full-time workers, especially among males. The pattern of results was consistent across empirical approaches—including generalized estimating equations and random effects models, with an extensive set of covariates. Taken together, these findings suggest that for U.S. employees, working part-time appears to be beneficial or at least not detrimental to perceived health, which warrants further investigation.     

Postretirement work and volunteering by poverty groups informed by role theory

This study uses role theory to examine the association between postretirement work and volunteering among retirees and to determine whether this association varies across poverty status. Data came from the 2012 wave of the Health and Retirement Study (HRS). The sample was restricted to respondents of older retirees (N = 6,619). We found that postretirement work positively influenced volunteering. However, poverty can be a risk factor of volunteering among older retirees. The positive effect of post-retirement work was found to be more significant in the near-poverty group. We provide an empirical foundation to help inform volunteer programs for retirees.