A simulation study of methods for selecting subgroup‐specific doses in phase 1 trials

Patient heterogeneity may complicate dose‐finding in phase 1 clinical trials if the dose‐toxicity curves differ between subgroups. Conducting separate trials within subgroups may lead to infeasibly small sample sizes in subgroups having low prevalence. Alternatively,it is not obvious how to conduct a single trial while accounting for heterogeneity. To address this problem,we consider a generalization of the continual reassessment method on the basis of a hierarchical Bayesian dose‐toxicity model that borrows strength between subgroups under the assumption that the subgroups are exchangeable. We evaluate a design using this model that includes subgroup‐specific dose selection and safety rules. A simulation study is presented that includes comparison of this method to 3 alternative approaches,on the basis of nonhierarchical models,that make different types of assumptions about within‐subgroup dose‐toxicity curves. The simulations show that the hierarchical model‐based method is recommended in settings where the dose‐toxicity curves are exchangeable between subgroups. We present practical guidelines for application and provide computer programs for trial simulation and conduct.     

The Aging Semantic Differential in Mandarin Chinese: Measuring Attitudes toward Older Adults in China

ABSTRACT

The Aging Semantic Differential (ASD) is the most widely used instrument to measure young people’s attitudes towards older adults. This study translated the ASD to Mandarin and examined its psychometric properties. The Mandarin-ASD contains three latent factors (Personality and Mental Health, Societal Participation, and Physical) that have high internal reliability and reasonable discriminate validity. Social work researchers, practitioners and allied professionals may utilize the ASD-Mandarin instrument to measure young people’s attitudes towards older adults in China. We issue a call for a universal-ASD that can be applied across different cultural contexts.     

‘I want to be better than you:’ lived experiences of intergenerational child maltreatment prevention among teenage mothers in and beyond foster care

The growing body of research on teenage motherhood in foster care has largely focused on the risks involved for both mother and child, yet these mothers depict a much more complex picture of their own experience of becoming and being mothers. The current study employed interpretative phenomenological analysis to explore 18 in‐depth, qualitative interviews from six participants on the meaning and experience of motherhood among teenage mothers in foster care and in the years immediately after ageing out. This study focused on a particular dimension of motherhood: participants' efforts to break the cycle of child abuse and neglect with their own children. Two themes emerged as characteristic of these experiences: (i) treating children well/parenting differently and avoiding the system; and (ii) reducing isolation and enhancing support. Given the increased likelihood of the children of teen mothers – particularly those who have been maltreated – becoming involved with the child welfare system, study findings suggest possible strategies for disrupting cycles of intergenerational child welfare involvement generated by young mothers themselves. Practice implications for addressing possible substance abuse, mental health and relational and parenting needs are discussed.     

Racial/Ethnic Minority Vocational Research Trends: An 11‐Year Update

This study extends Flores et al.'s ( 2006 ) 36‐year analysis of racial/ethnic minority (REM) career research to identify recent trends in choice of topics and leading individual and institutional contributors. The authors identified 166 articles on REM career research published from 2005 to 2015 in the Journal of Vocational Behavior, The Career Development Quarterly, the Journal of Career Assessment, and the Journal of Career Development. Of these studies, 92% were empirical, with more than three quarters of these using quantitative rather than qualitative methodology. Most frequently, the empirical studies (n = 153) were based on samples of high school (30.7%) or undergraduate (34.6%) students. The authors discuss the implications of their findings and suggest ways to expand REM career research in the future.     

iConstruct: virtual disabilities in online settings

The present study focused on cultural constructions of disability in virtual settings, examining specifically how cultural constructions of disability were mediated through the use of online technology. This was accomplished by identifying and analyzing Greek Cypriot online news media articles and online readers’ posts in response to these articles. Findings indicated that disability in these online settings mainly reproduced traditional models of disability, with the charity model being more prevalent. However, there were instances in which dominant discourses of disability were ruptured through the introduction of counter-narratives in users’ posts which echoed the human rights model of disability. Implications for the fields of media, education and disability studies are discussed in relation to the possibility of using digital media to contribute to the challenge of critical media literacy to address issues of diversity and disability.     

Do Mission Statements Matter for Nonprofit Performance?

In this exploratory study, we examine whether organizational mission statement attributes make a difference to the performance of nonprofit performing arts organizations. We use text analysis to measure two semantic attributes—activity and commonality—of mission statements. We examine whether these attributes are associated with improved performance for the instrumental and expressive functions of nonprofit performing arts organizations. Our findings indicate that the mission statement attribute activity is associated with improved performance for both instrumental and expressive functions. Our analysis of nonfindings for the mission statement attribute commonality suggests that there is a need to develop and use content analysis tools tailored to nonprofit contexts.     

Sociolinguistic interaction and identity construction: The view from game‐theoretic pragmatics

Understanding the dynamics that characterize interaction between conversational participants is a fundamental goal of most theories of socially conditioned language use and identity construction through language. In this paper, I outline a class of formal tools that, I suggest, can be helpful in making progress towards this goal. More precisely, this paper explores how Bayesian signalling game models can be used to formalize key aspects of current sociolinguistic theories, and, in doing so, contribute to our knowledge of how speakers use their linguistic resources to communicate information and carve out their place in the social world. The Bayesian framework has become increasingly popular for the analysis of pragmatic phenomena of many different types, and, more generally, these models have become a dominant paradigm for the explanation of non‐linguistic cognitive processes. As such, I argue that this approach has the potential to yield a formalized theory of personal and social identity construction and to situate the study of sociolinguistic interaction within a broader theory of rationalistic cognition.     

Birds of a feather petition together? Characterizing e-petitioning through the lens of platform data

E-petitioning platforms are increasingly popular in Western democracies and considered by some lawmakers and scholars to enhance citizen participation in political decision-making. In addition to social media and other channels for informal political communication, online petitioning is regarded as both a useful instrument to afford citizens a more important role in the political process and allow them to express support for issues which they find relevant. Building on existing pre-internet systems, e-petitioning websites are increasingly implemented to make it easier and faster to set up and sign petitions. However, little attention has so far been given to the relationship between different styles of usage and the causes supported by different groups of users. The functional difference between signing paper-based petitions vs. doing so online is especially notable with regard to users who sign large numbers of petitions. To characterize this relationship, we examine the intensity of user participation in the German Bundestag’s online petitioning platform through the lens of platform data collected over a period of five years, and conduct an analysis of highly active users and their political preferences. We find that users who sign just a single petition favor different policy areas than those who sign many petitions on a variety of issues. We conclude our analysis with observations on the potential of behavioral data for assessing the dynamics of online participation, and suggest that quantity (the number of signed petitions) and quality (favored policy areas) need more systematic joint assessment.     

What is gained and what is left to be done when content analysis is added to network analysis in the study of a social movement: Twitter use during Gezi Park

As social movements relying on the weak ties found in social networks have spread around the world, researchers have taken several approaches to understanding how networks function in such instances as the Arab Spring. While social scientists have primarily relied on survey or content analysis methodology, network scientists have used social network analysis. This research combines content analysis with the automated techniques of network analysis to determine the roles played by those using Twitter to communicate during the Turkish Gezi Park uprising. Based on a network analysis of nearly 2.4 million tweets and a content analysis of a subset of 5126 of those tweets, we found that information sharing was by far the most common use of the tweets and retweets, while tweets that indicated leadership of the movement constituted a small percentage of the overall number of tweets. Using automated techniques, we experimented with coded variables from content analysis to compute the most discriminative tokens and to predict values for each variable using only textual information. We achieved 0.61 precision on identifying types of shared information. Our results on detecting the position of user in the protest and purpose of the tweets achieved 0.42 and 0.33 precision, respectively, illustrating the necessity of user cooperation and the shortcomings of automated techniques. Based on annotated values of user tweets, we computed similarities between users considering their information production and consumption. User similarities are used to compute clusters of individuals with similar behaviors, and we interpreted average activities for those groups.     

A transnational networked public sphere of air pollution: analysis of a Twitter network of PM2.5 from the risk society perspective

ABSTRACT

Drawing on digitaltrace data, publicly accessible government documents, and journalistic reports, this research integrates Beck’s risk society theory with digital media theories to examine the mediated process of risk definition and assessment of PM2.5 (particulate matters with a diameter less than 2.5 micrometers) in a networked public sphere. Network and content analysis of a PM2.5 Twitter network shows that political and professional elite remained the most powerful producers of risk definition. Established media played a key role, yet faced challenges from a variety of actors who disseminated and filtered information. Laypersons, while peripheral, actively interacted with elite and established media. The blurring geographic boundary in the PM2.5 Twitter network revealed an emerging transnational public sphere, which, however, was segregated by language. This research advances a layered understanding of the contingent, paradoxical media impact for social changes in a risk society.