Description:
Background and aims: Oppositional Defiant Disorder (ODD) is a common childhood disorder (American Psychiatric Association [APA], 2000; APA, 2013). The aim of the present study was to ascertain the optimal structure for the ODD symptoms by identifying whether ODD is a qualitatively distinct entity (categorical) or is a continuum, with high levels on this continuum reflecting ODD (quantitative or dimensional view). Methods: Mothers' ratings of the ODD symptoms of 457 children, aged 3 to 15 years, as presented in the disruptive behavior rating scale were obtained. Confirmatory factor analysis (CFA), latent class analysis (LCA), and factor mixture modelling (FMM) were applied to determine the best model for oppositional defiant disorder (ODD) symptoms in children. Results: The findings provided most support for a FMM with 3 classes (unaffected odd class, at risk class, and affected class) and 3 factors (oppositional, antagonistic, and negative affect). Conclusion: The findings are discussed in relation to dimensional, categorical, and hybrid (categorical/dimensional) models of ODD symptoms.
Description:
In this paper, we present some inverse function theorems and implicit function theorems for set-valued mappings between Fréchet spaces. The proof relies on Lebesgue's Dominated Convergence Theorem and on Ekeland's variational principle. An application to the existence of solutions of differential equations in Fréchet spaces with non-smooth data is given.
Description:
Although the importance of customer orientation (CO) has been recognized, its relationship with firm performance is far from clear. This lack of clarity is partly because the impact of CO on firm performance may depend on certain internal or external factors. Based on social learning theory and an interactional perspective, this study concurrently explores the separate and joint moderating effects of ethical leadership and competitive intensity. Survey data from 264 Chinese firms was collected to test the hypotheses. The results show that humane leadership and moderation leadership help firms to better leverage CO for enhancing their performance. The absence of moderation leadership may be particularly harmful for firms operating in a less competitive environment while the moderating effect is not influenced by competitive intensity. In addition, justice leadership has a positive impact for firms operating in a more competitive environment, which assists firms to better realize the benefits of CO.
Description:
Simulation-based education has become a ubiquitous teaching approach in nursing. However, ensuring the quality of simulation research is critical. We reviewed the methodological quality of 26 quantitative studies published in Clinical Simulation in Nursing, 2017. The Medical Education Research Study Quality Instrument and Simulation Research Evaluation Rubric showed that nearly all studies were of moderate to high quality (rated ≥50%). Correlation coefficients showed that interrater agreement was high overall (≥0.94). In conclusion, this was a valid approach for examining simulation study quality. Although most included studies were of high quality, some elements of study reporting can be improved upon.
Description:
Simulation-based education has become a ubiquitous teaching approach in nursing. However, ensuring the quality of simulation research is critical. We reviewed the methodological quality of 26 quantitative studies published in Clinical Simulation in Nursing, 2017. The Medical Education Research Study Quality Instrument and Simulation Research Evaluation Rubric showed that nearly all studies were of moderate to high quality (rated ≥50%). Correlation coefficients showed that interrater agreement was high overall (≥0.94). In conclusion, this was a valid approach for examining simulation study quality. Although most included studies were of high quality, some elements of study reporting can be improved upon.
Description:
Clinical simulation is an essential component of health professional education. Digital technologies can provide students with near-reality, interactive virtual simulation learning experiences on static and mobile appliances. Clarification is needed, however, regarding the various types of virtual simulation and the different program components. We drew on published literature to define virtual simulation modalities and to offer definitive terminology to clarify the nomenclature and composition of virtual simulation. Reporting should include description of ‘Fidelity’ ‘Immersion’ and ‘Patient’ to add clarity and utility to research in the field.
Description:
This paper presents a canonical d.c. (difference of canonical and convex functions) programming problem, which can be used to model general global optimization problems in complex systems. It shows that by using the canonical duality theory, a large class of nonconvex minimization problems can be equivalently converted to a unified concave maximization problem over a convex domain, which can be solved easily under certain conditions. Additionally, a detailed proof for triality theory is provided, which can be used to identify local extremal solutions. Applications are illustrated and open problems are presented.
Description:
This paper presents a canonical d.c. (difference of canonical and convex functions) programming problem, which can be used to model general global optimization problems in complex systems. It shows that by using the canonical duality theory, a large class of nonconvex minimization problems can be equivalently converted to a unified concave maximization problem over a convex domain, which can be solved easily under certain conditions. Additionally, a detailed proof for triality theory is provided, which can be used to identify local extremal solutions. Applications are illustrated and open problems are presented.
Description:
Predictive coding schemes, proposed in the literature, essentially model the residuals with discrete distributions. However, real-valued residuals can arise in predictive coding, for example, from the usage of an r order linear predictor specified by r real-valued coefficients. In this paper, we propose a symbol-by-symbol coding scheme for the Laplace distribution, which closely models the distribution of real-valued residuals in practice. To efficiently exploit the real-valued predictions at a given precision, the proposed scheme essentially combines the process of residual computation and coding, in contrast to conventional schemes that separate these two processes. In the context of adaptive predictive coding framework, where the source statistics must be learnt from the data, the proposed scheme has the advantage of lower 'model cost' as it involves learning only one parameter. In this paper, we also analyze the proposed parametric coding scheme to establish the relationship between the optimal value of the coding parameter and the scale parameter of the Laplace distribution. Our experimental results demonstrated the compression efficiency and computational simplicity of the proposed scheme in adaptive coding of residuals against the widely used arithmetic coding, Rice-Golomb coding, and the Merhav-Seroussi-Weinberger scheme adopted in JPEG-LS.