Risk Communication,Values Clarification,and Vaccination Decisions

Many health‐related decisions require choosing between two options, each with risks and benefits. When presented with such tradeoffs, people often make choices that fail to align with scientific evidence or with their own values. This study tested whether risk communication and values clarification methods could help parents and guardians make evidence‐based, values‐congruent decisions about children's influenza vaccinations. In 2013–2014 we conducted an online 2×2 factorial experiment in which a diverse sample of U.S. parents and guardians (n = 407) were randomly assigned to view either standard information about influenza vaccines or risk communication using absolute and incremental risk formats. Participants were then either presented or not presented with an interactive values clarification interface with constrained sliders and dynamic visual feedback. Participants randomized to the risk communication condition combined with the values clarification interface were more likely to indicate intentions to vaccinate (β = 2.10, t(399) = 2.63, p < 0.01). The effect was particularly notable among participants who had previously demonstrated less interest in having their children vaccinated against influenza (β = –2.14, t(399) = –2.06, p < 0.05). When assessing vaccination status reported by participants who agreed to participate in a follow‐up study six months later (n = 116), vaccination intentions significantly predicted vaccination status (OR = 1.66, 95%CI (1.13, 2.44), p < 0.05) and rates of informed choice (OR = 1.51, 95%CI (1.07, 2.13), p < 0.012), although there were no direct effects of experimental factors on vaccination rates. Qualitative analysis suggested that logistical barriers impeded immunization rates. Risk communication and values clarification methods may contribute to increased vaccination intentions, which may, in turn, predict vaccination status if logistical barriers are also addressed.     

Social Work Practice in Mental Health: An Introduction

The results of empirical research suggest that the ability to assess, regulate, and utilize emotions is important to the performance of health professionals. Nevertheless, few professional programs adequately address this matter in their curricula. The main objective of the present research was to examine whether emotional intelligence and empathy could be improved in the traditional classroom, employing experiential teaching modes. Pre- and post-questionnaires were used to assess the emotional competencies of 165 social work undergraduate students. The results indicated an increase in emotional intelligence at the end of a course for advanced-year students. Overall empathy had not increased for both first- and advanced-year students. Further findings indicated significant correlation between empathy and emotional intelligence at the end of a course for advanced-year students compared with an insignificant correlation at the beginning of the course, whereas for first-year students, findings were in the opposite direction. Future research should focus on strategies for the teaching and professional training of social workers that promote emotional competencies.     

Partial groups ranked set sampling and mean estimation

Ranked set sampling (RSS) is an advanced sampling method which is very effective for estimating mean of the population when exact measurement of observation is difficult and/or expensive. Balanced Groups RSS (BGRSS) is one of the modification of RSS where only the lowest, the median and the largest ranked units are taken into account. Although BGRSS is advantageous and useful for some specific cases, it has strict restrictions regarding the set size which could be problematic for sampling plans. In this study, we make an improvement on BGRSS and propose a new design called Partial Groups RSS which offers a more flexible sampling plan providing the independence of the set size and sample size. Partial Groups RSS also has a cost advantage over BGRSS. We construct a Monte Carlo simulation study comparing the performance of the mean estimators of the proposed sampling design and BGRSS according to their sampling costs and mean squared errors for various type of distributions. In addition, we give a biometric data application for investigating the efficiency of Partial Groups RSS in real life applications.     

Transnational Families: Memories and Narratives

This introduction to a special issue of the journal explores not only the role of memory and narratives in understanding gender and transnational families, but suggests how such families use and understand their memories to construct coherent narratives of the self and kin. In common with renewed thinking about the multifaceted nature of migration, the complexities of the process, and the continuing dialogue that migration establishes between the old and the new, the past and the present, those who engage with oral history/life story methods are increasingly aware that such data provide a ‘value added’ to rich empirical detail. These methods reveal the use of memory and its role in the continuing emotional adjustments in which most transnational experience is embroiled. They show how the multi‐layering of memory, language and narratives are indicators of the ways in which culture shapes recall and recounting. Families themselves become sites of belonging, part of the imaginary unity through which a transnational family may seek its identity. Equally, oral histories can tease out ways in which gender differences impact on, or are impacted by, transnational lives. The introduction situates the subsequent articles within a brief overview of oral history and migration.     

Robust two parameter ridge M-estimator for linear regression

The problem of multicollinearity and outliers in the data set produce undesirable effects on the ordinary least squares estimator. Therefore, robust two parameter ridge estimation based on M-estimator (ME) is introduced to deal with multicollinearity and outliers in the y-direction. The proposed estimator outperforms ME, two parameter ridge estimator and robust ridge M-estimator according to mean square error criterion. Moreover, a numerical example and a Monte Carlo simulation experiment are presented.