Shape analysis for automated sulcal classification and parcellation of MRI data

We describe geometric invariants that characterize the shape of curves and surfaces in 3D space: curvature, Gauss integrals and moments. We apply these invariants to neuroimaging data to determine if they have application for automatically classifying and parcellating cortical data. The curves of sulci and gyri on the cortical surface can be obtained by reconstructing cortical surface representations of the human brain from magnetic resonance imaging (MRI) data. We reconstructed gray matter surfaces for 15 subjects, traced 10 sulcal curves on each surface and computed geometric invariants for each curve. These geometric features were used classify the curves into sulcal and hemispheric classes. The best classification results were obtained when moment-based features were computed on the sulcal curves in native space. Gauss integral measures showed that they were useful for differentiating the hemispheric location of a single sulcus. These promising results may indicate that moment invariants are useful for characterizing shape on a global scale. Gauss integral invariants are potentially useful measures for characterizing cortical shape on a local, rather than global scale. Gauss integrals have found biological significance in characterizing proteins so it is worthwhile to consider their possible application to neuroscientific data.     

Mixing Apples and Oranges and Other Methodological Problems with a Meta-Analysis of Long Term Psychodynamic Psychotherapy

Current trends in mental health practice indicate that mental health practitioners, including clinical social workers, are tending to move away from psychodynamic approaches and are favoring short-term empirically supported approaches such as cognitive-behavioral therapy (CBT). Recently, the presumption that long-term psychodynamic psychotherapy (LTPP) approaches lack empirical support has been challenged, however, with the publication in major peer reviewed journals of meta-analyses that are claimed to demonstrate its equality to or superiority over empirically supported short-term therapies for some conditions. The present article examines the methodology employed in one particular meta-analysis which compared LTPP to short term therapies and the studies upon which the analysis was based. We found that major methodological and statistical flaws with the meta-analysis and with the individual studies preclude drawing any conclusions regarding the efficacy of LTPP.     

Using the Delphi method to engage stakeholders: A comparison of two studies

Involving stakeholders can greatly impact evaluation results. The Delphi method, a consensus-building tool, is a promising process to promote and encourage involvement from all stakeholders during the evaluation framing process. The Delphi method removes geographic challenges and time boundaries allowing all stakeholders to participate. The Delphi method uses a series of surveys interspersed with controlled feedback designed to gather information and build consensus without requiring face-to-face meetings. Two different formats of the Delphi method, a paper-and-pencil, postal-mail version and a web-based, real-time computer version are compared in this study. Both versions of the Delphi were administered to a non-profit community based organization as part of framing an evaluation. Participation rates were better with the paper–pencil version. The quantity and quality of data collected were comparable in both versions.     

Bayesian modeling of temporal properties of infectious disease in a college student population

A Bayesian statistical model is developed for analysis of the time-evolving properties of infectious disease, with a particular focus on viruses. The model employs a latent semi-Markovian state process, and the state-transition statistics are driven by three terms: (i) a general time-evolving trend of the overall population, (ii) a semi-periodic term that accounts for effects caused by the days of the week, and (iii) a regression term that relates the probability of infection to covariates (here, specifically, to the Google Flu Trends data). Computations are performed using Markov Chain Monte Carlo sampling. Results are presented using a novel data set: daily self-reported symptom scores from hundreds of Duke University undergraduate students, collected over three academic years. The illnesses associated with these students are (imperfectly) labeled using real-time (RT) polymerase chain reaction (PCR) testing for several viruses, and gene-expression data were also analyzed. The statistical analysis is performed on the daily, self-reported symptom scores, and the RT PCR and gene-expression data are employed for analysis and interpretation of the model results.     

Local stationarity in small area estimation models

Small area estimators are often based on linear mixed models under the assumption that relationships among variables are stationary across the area of interest (Fay–Herriot models). This hypothesis is patently violated when the population is divided into heterogeneous latent subgroups. In this paper we propose a local Fay–Herriot model assisted by a Simulated Annealing algorithm to identify the latent subgroups of small areas. The value minimized through the Simulated Annealing algorithm is the sum of the estimated mean squared error (MSE) of the small area estimates. The technique is employed for small area estimates of erosion on agricultural land within the Rathbun Lake Watershed (IA, USA). The results are promising and show that introducing local stationarity in a small area model may lead to useful improvements in the performance of the estimators.     

Support networks and social support for persons with psychiatric disabilities—a Swedish mixed-methods study

The aim of this study was to explore the structure, interaction, and function of the support networks of women and men with psychiatric disabilities. The study took a mixed-methods approach, using quantitative (n=181) and qualitative (n=42) data from a region in southern Sweden. The quantitative results showed that the respondents received widespread support of different types and from many different sources. However, the qualitative interviews revealed that many of the interviewees did not perceive the received support as supportive. The respondents’ internal resources influenced both their ability to receive support and their perception of the support. The informal and formal support sources formed the external resources of the respondents. Our interviewees often experienced formal support as conditional support, while informal support from the family was experienced as unconditional. There was thus a gap between the structure and function of the social support. This article contributes important knowledge from the perspective of persons with psychiatric disabilities.     

Multilevel Social Dynamics Considerations for Project Management Decision Makers: Antecedents and Implications of Group Member Tie Development

Successful projects represent the effective culmination of management skills, planning, and individual project member strengths. In operations management, such strengths are often viewed predominantly from the perspective of skill base. However, it has become increasingly evident that behavioral traits associated with individuals play a very significant, if not ultimately dominating, role in the effectiveness of certain group projects. Our aim in this study is to look into how certain individual attributes viewed as relevant to these project contexts may lead to social networking decisions that have impacts spanning multiple levels of analysis. Such insights are likely to prove valuable to decision makers managing project teams as well. We employ a controlled 4‐month investigation of multiple projects, for which we are able to consider both objective, and subjective pre‐, in situ, and postproject data. Our results demonstrate that the issues of perceived control, confidence, and conscientiousness are relevant not only in driving individual perceptions of the value of within‐group interactions, and hence the development of associated ties, but are also ultimately relevant in helping to drive higher levels of group performance.     

Improving quality at the point of service

The authors provide a research-based construct of youth program quality that differentiates safety, support, interaction, and engagement, four important issues for practitioners working with youth in the middle years. They describe two tools that have helped direct staff to be intentional about creating offerings that are appropriate for early adolescents: the focusing idea of point-of-service quality and the technology of observational assessment. They describe how these tools can be used to create cultures of accountability and intentionality that extend across program levels.     

Business Performance Analytics: exploring the potential for Performance Management Systems

Business Performance Analytics (BPA) entails the systematic use of data and analytical methods (mathematical, econometric and statistical) for performance measurement and management. Although potentially overcoming some traditional diagnostic issues related to Performance Management Systems (PMS), such as information overload, absence of cause-effect relationships, lack of a holistic view of the organisation, research in the field is still in its infancy. A comprehensive model for operationalising analytics for diagnostic and interactive PMS is still lacking. Adopting an action research approach, this paper addresses this gap and develops a five-step framework applied to a company operating in the construction industry. The results show that in addition to encouraging dialogue, BPA can contribute to identifying critical performance variables, potential sources of risk and related interdependencies. A number of critical issues in implementing data-based approaches are also highlighted, including data quality, organisational competences and cultural shifts.