Psychological Sense of Community: A New Construct for the Field of Management

This article introduces a new construct to the field of management called Psychological Sense of Community (PSOC). This is important because management scholars are calling for the creation of communities in organizations in an environment that lacks appropriate construct development. The aims of this article are threefold: (a) develop a working definition of PSOC via a review of the extant literature on PSOC from other disciplines with the goal of translating it into the domain of management, (b) synthesize findings from parallel literatures on the outcomes of PSOC with an eye toward exploring the relevance of such outcomes in management contexts, and (c) assess the value of PSOC as it relates to its uniqueness in relation to other prominent management constructs and its scope of applicability in a variety of management inquiry areas.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Studying Effects of Primary Care Physicians and Patients on the Trade-Off Between Charges for Primary Care and Specialty Care Using a Hierarchical Multivariate Two-Part Model

Objective. To examine effects of primary care physicians (PCPs) and patients on the association between charges for primary care and specialty care in a point-of-service (POS) health plan. Data Source. Claims from 1996 for 3,308 adult male POS plan members, each of whom was assigned to one of the 50 family practitioner-PCPs with the largest POS plan member-loads. Study Design. A hierarchical multivariate two-part model was fitted using a Gibbs sampler to estimate PCPs' effects on patients' annual charges for two types of services, primary care and specialty care, the associations among PCPs' effects, and within-patient associations between charges for the two services. Adjusted Clinical Groups (ACGs) were used to adjust for case-mix. Principal Findings. PCPs with higher case-mix adjusted rates of specialist use were less likely to see their patients at least once during the year (estimated correlation: –.40; 95% CI: –.71, –.008) and provided fewer services to patients that they saw (estimated correlation: –.53; 95% CI: –.77, –.21). Ten of 11 PCPs whose case-mix adjusted effects on primary care charges were significantly less than or greater than zero (p < .05) had estimated, case-mix adjusted effects on specialty care charges that were of opposite sign (but not significantly different than zero). After adjustment for ACG and PCP effects, the within-patient, estimated odds ratio for any use of primary care given any use of specialty care was .57 (95% CI: .45, .73). Conclusions. PCPs and patients contributed independently to a trade-off between utilization of primary care and specialty care. The trade-off appeared to partially offset significant differences in the amount of care provided by PCPs. These findings were possible because we employed a hierarchical multivariate model rather than separate univariate models.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

Reactivation of rheumatoid arthritis after pregnancy: increased phagocyte and recurring lymphocyte gene activity

OBJECTIVE: Pregnancy is associated with reduced disease activity in rheumatoid arthritis (RA) and frequently with disease exacerbation after delivery. This study was undertaken to generate a systematic overview of the molecular mechanisms related to disease remission and postpartum reactivation. METHODS: Transcriptomes of peripheral blood mononuclear cells (PBMCs) were generated from RA patients and healthy women by transcription profiling during the third trimester and 24 weeks after delivery. For functional interpretation, signatures of highly purified immune cells as well as Kyoto Encyclopedia of Genes and Genomes pathway annotations were used as a reference. RESULTS: Only minor differences in gene expression in PBMCs during pregnancy were found between RA patients and controls. In contrast, RA postpartum profiles presented the most dominant changes. Systematic comparison with expression signatures of monocytes, T cells, and B cells in healthy donors revealed reduced lymphocyte and elevated monocyte gene activity during pregnancy in patients with RA and in controls. Monocyte activity decreased after delivery in controls but persisted in RA patients. Furthermore, analysis of 32 immunologically relevant cellular pathways demonstrated a significant additional activation of genes related to adhesion, migration, defense of pathogens, and cell activation, including Notch, phosphatidylinositol, mTOR, Wnt, and MAPK signaling, in RA patients postpartum. CONCLUSION: Our findings indicate that innate immune functions play an important role in postpartum reactivation of arthritis. However, this may depend not only on the monocyte itself, but also on the recurrence of lymphocyte functions postpartum and thus on a critical interaction between both arms of the immune system.

Electron microscopy of high pressure frozen samples: bridging the gap between cellular ultrastructure and atomic resolution

Transmission electron microscopy has provided most of what is known about the ultrastructural organization of tissues, cells, and organelles. Due to tremendous advances in crystallography and magnetic resonance imaging, almost any protein can now be modeled at atomic resolution. To fully understand the workings of biological "nanomachines" it is necessary to obtain images of intact macromolecular assemblies in situ. Although the resolution power of electron microscopes is on the atomic scale, in biological samples artifacts introduced by aldehyde fixation, dehydration and staining, but also section thickness reduces it to some nanometers. Cryofixation by high pressure freezing circumvents many of the artifacts since it allows vitrifying biological samples of about 200 mum in thickness and immobilizes complex macromolecular assemblies in their native state in situ. To exploit the perfect structural preservation of frozen hydrated sections, sophisticated instruments are needed, e.g., high voltage electron microscopes equipped with precise goniometers that work at low temperature and digital cameras of high sensitivity and pixel number. With them, it is possible to generate high resolution tomograms, i.e., 3D views of subcellular structures. This review describes theory and applications of the high pressure cryofixation methodology and compares its results with those of conventional procedures. Moreover, recent findings will be discussed showing that molecular models of proteins can be fitted into depicted organellar ultrastructure of images of frozen hydrated sections. High pressure freezing of tissue is the base which may lead to precise models of macromolecular assemblies in situ, and thus to a better understanding of the function of complex cellular structures.

The Concept of Developmental-Tasks and its Significance for Education and Social Work

The term "developmental-task" was introduced by Robert Havighurst in the 1950's. According to R. Harvighurst, the term refers to tasks which arise in a social context during an individual lifetime. Since the 1950's the concept of developmental-tasks has become an important theoretical approach in educational science and in theories of growth and development - but not in social work and social pedagogy. In the following article I aim to show that this approach is very important to theory and practice of social pedagogy and social work.

A fuzzy risk attitude classification based on prospect theory

Traditional methods do not actually measure peoples’ risk attitude naturally and precisely. Therefore, a fuzzy risk attitude classification method is developed. Since the prospect theory is usually considered as an effective model of decision making, the personalized parameters in prospect theory are firstly fuzzified to distinguish people with different risk attitudes, and then a fuzzy classification database schema is applied to calculate the exact value of risk value attitude and risk be- havior attitude. Finally, by applying a two-hierarchical clas- sification model, the precise value of synthetical risk attitude can be acquired.