Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data

The benchmark dose (BMD) approach has gained acceptance as a valuable risk assessment tool, but risk assessors still face significant challenges associated with selecting an appropriate BMD/BMDL estimate from the results of a set of acceptable dose‐response models. Current approaches do not explicitly address model uncertainty, and there is an existing need to more fully inform health risk assessors in this regard. In this study, a Bayesian model averaging (BMA) BMD estimation method taking model uncertainty into account is proposed as an alternative to current BMD estimation approaches for continuous data. Using the “hybrid” method proposed by Crump, two strategies of BMA, including both “maximum likelihood estimation based” and “Markov Chain Monte Carlo based” methods, are first applied as a demonstration to calculate model averaged BMD estimates from real continuous dose‐response data. The outcomes from the example data sets examined suggest that the BMA BMD estimates have higher reliability than the estimates from the individual models with highest posterior weight in terms of higher BMDL and smaller 90th percentile intervals. In addition, a simulation study is performed to evaluate the accuracy of the BMA BMD estimator. The results from the simulation study recommend that the BMA BMD estimates have smaller bias than the BMDs selected using other criteria. To further validate the BMA method, some technical issues, including the selection of models and the use of bootstrap methods for BMDL derivation, need further investigation over a more extensive, representative set of dose‐response data.     

State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems

The objective of this article is to discuss a needed paradigm shift in disaster risk analysis to emphasize the role of the workforce in managing the recovery of interdependent infrastructure and economic systems. Much of the work that has been done on disaster risk analysis has focused primarily on preparedness and recovery strategies for disrupted infrastructure systems. The reliability of systems such as transportation, electric power, and telecommunications is crucial in sustaining business processes, supply chains, and regional livelihoods, as well as ensuring the availability of vital services in the aftermath of disasters. There has been a growing momentum in recognizing workforce criticality in the aftermath of disasters; nevertheless, significant gaps still remain in modeling, assessing, and managing workforce disruptions and their associated ripple effects to other interdependent systems. The workforce plays a pivotal role in ensuring that a disrupted region continues to function and subsequently recover from the adverse effects of disasters. With this in mind, this article presents a review of recent studies that have underscored the criticality of workforce sectors in formulating synergistic preparedness and recovery policies for interdependent infrastructure and regional economic systems.     

Anti-N-methyl-D-aspartate receptor antibody encephalitis: An important cause of encephalitis in young adults. A report of two cases

Encephalitis is a clinical syndrome which can include altered mental status, motor and sensory deficits, altered behavior including personality changes, speech and movement disorders and seizures. While the overall incidence of encephalitis is not known, it is common enough that most pediatric and adolescent medicine physicians will have seen at least one case. Peak times of risk include the newborn period and middle-to-late adolescence.¹ Dalmau J, Tüzün E, Wu HY, et al. Paraneoplastic anti-N-methyl-D-aspartate receptor encephalitis associated with ovarian teratoma. Ann Neurol. 2007 Jan;61(1):25–36. doi:10.1002/ana.21050. PMID: 17262855.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] It is important for clinicians to have a working knowledge of the broad range of encephalitis etiologies: viral, post-viral, toxic, auto-immune, and paraneoplastic. We discuss two cases of encephalitis in young adult women with ovarian teratoma and production of anti-N-methyl-D-aspartate receptor (NMDAR) antibodies.     

Integrating self-care into clinical practice with trauma clients

ABSTRACT

Self-care is recognized as an important aspect of social work practice. Beginning in educational settings, developing social workers are encouraged to learn about and practice self-care. However, self-care is typically promoted through strategies and approaches outside of the practice context. Social workers are oftentimes encouraged to use individualized self-care plans, which often feature a variety of relaxation and secondary techniques; focus on self-awareness and self-reflection; and have proper use of supervision. Although these strategies are invaluable, they do little to directly benefit the social worker during direct practice or while in session with a client which is a time period when clinicians are particularly vulnerable to distress or burnout. The importance of real-time self-care strategies is particularly critical for clinicians, especially those who engage in trauma work, given the sensitivity of topics that clients may have endured or benefit from assistance in processing. Further, little information has been published on the use of self-care techniques during a session with a client or in a clinical context. The purpose of the present paper is to discuss self-care strategies that can be useful both outside of and within a clinical setting and present a model of such strategies that focus on integrating self-care in clinical practice particularly for those engaging in trauma work. The paper will conclude by discussing the relevancy of the developed model in practice.     

Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy

Abstract

With a shift to more automation technology, social acceptance of technology plays an important role in the manufacturing sector. To what extent this occurs, and affects the adoption of technology, has been less researched, but is important in deciding how such technology is introduced, and the nature of the shift from labour-intensive manufacturing to automation. This research applies the revised technology acceptance model (TAM) to examine the impact of social and individual antecedents on the acceptance of automation manufacturing technology. Survey data are collected from 258 Chinese manufacturers. Results suggest that perceived norms significantly affect organizational intention to use automation manufacturing technology both directly and via perceived usefulness; organizational efficacy explains the intention to use via mediating effect of perceived usefulness and perceived ease of use. This research is one of the first extending and applying TAM from individuals to organizations.     

Academic Entrepreneurship: Time for a Rethink?

Academic entrepreneurship, which refers to efforts undertaken by universities to promote commercialization on campus and in surrounding regions of the university, has changed dramatically in recent years. Two key consequences of this change are that more stakeholders have become involved in academic entrepreneurship and that universities have become more ‘strategic’ in their approach to this activity. The authors assert that the time is ripe to rethink academic entrepreneurship. Specifically, theoretical and empirical research on academic entrepreneurship needs to take account of these changes, so as to improve the rigour and relevance of future studies on this topic. We outline such a framework and provide examples of key research questions that need to be addressed to broaden understanding of academic entrepreneurship.     

No Mind Reading Necessary: Conducting Evidence-Based Electronic Resource Marketing and Outreach Using Marketing Research Assessment

Abstract

In her presentation entitled “No Mind Reading Necessary: Conducting Evidence-Based Electronic Resource Marketing and Outreach” at the North Carolina Serials Conference April 2019, Kate Hill discussed marketing research strategies and outreach tools used to increase online users’ access to electronic resources and primary resources. In an effort to connect users to seldom-used resources, Jackson Library collaborated with university partners to develop surveys to identify the information-seeking behavior of its users and apply the gathered marketing research to strategically plan outreach activities.     

The distinct role of group-central and group-peripheral norms in taxpaying behaviour

In recent years, a social identity approach has been used to help understand why people do or do not pay tax [see Taylor, 2003; Wenzel, M., 2002. The impact of outcome orientation and justice concerns on tax compliance: the role of taxpayers’ identity. Journal of Applied Psychology 87, 629–645; Wenzel, M., 2004. An analysis of norm processes in tax compliance. Journal of Economic Psychology 25, 213–228; Wenzel, M., 2005. Misperception of social norms about tax compliance: from theory to intervention. Journal of Economic Psychology 26, 862–883; Wenzel, M., 2007. The multiplicity of taxpayer identities and their implications for tax ethics. Law & Policy 29, 31–50]. This research, which has focused almost exclusively on national identity, indicates that the more people identify with a group, the more likely they are to adhere to its tax norms and values. However, conformity to group norms may be more nuanced than this, and depend on (a) the meaning or content of the identity in question [e.g., Turner, J.C., 1999. Some current themes in research on social identity and self-categorization theories. In: Ellemers, N., Spears, R., Doojse, B. (Eds.), Social Identity: Context, Commitment, Content. Blackwell, Oxford, pp. 6–34] and (b) whether the norms and values are central or peripheral to the content of that identity. In line with this idea, two studies explored whether the concept and act of taxpaying are more central to what it means to be a member of one's nation than of one's occupational group. Both studies confirm this expectation. Importantly, the findings also suggest that although occupational groups have different norms and values in relation to pre-tax behaviours (e.g., how to deal with extra income), these too can be peripheral to what it means to a group member. If norms are peripheral to identity content, conformity to such norms may be independent of group identification.     

Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35 years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two‐stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly–Seber estimates based on single capture methods.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.