Models of burnout: Implications for interventions

Three process models of burnout are discussed, Cherniss' process model, Golembiewski's phase model and Leiter's process model. Empirical support for each model is reported. The models make different contributions to the problem of burnout and its development, and the kind of interventions that follow from each model seem to represent different targets. The strengths and weaknesses of the three models are assessed, and the relative merits of individual versus organizational level interventions are addressed. More model-driven research is necessary to reduce the problem of burnout for individuals and organizations.     

创造性思维计算模型研究综述

本文综述了已有的创造性思维计算模型,根据其采用的计算方法进行分类,分析这些方法的优缺点,对创造性思维的计算模拟方法进行了展望。     

Models for Counterparts

Lewis proposed to test the validity of a modal thesis by checking whether its possible-world translation is a theorem of counterpart theory. However, that criterion fails to validate many standard modal laws, thus raising doubts about the logical adequacy of the Lewisian framework. The present paper considers systems of counterpart theory of increasing strength and shows how each can be motivated by exhibiting a suitable intended model. In particular, perfect counterpart theory validates all the desired modal laws and therefore provides a way out of the logical objection. Finally, a weakening of perfect counterpart theory is put forward as a response to some metaphysical objections.     

Models for Hylomorphism

Journal of Philosophical Logic - In a series of papers (Fine et al., 1982; Fine, Noûs28(2), 137–158; 1994, Midwest Studies in Philosophy, 23, 61–74, 1999) Fine develops his...     

Art and life: Models for understanding music

Book Information Science, Truth, and Democracy. By Philip Kitcher. Oxford. New York. 2001. Pp. xiii + 219. US$27.50.     

Hierarchical Diagnostic Classification Models: A Family of Models for Estimating and Testing Attribute Hierarchies

Although latent attributes that follow a hierarchical structure are anticipated in many areas of educational and psychological assessment, current psychometric models are limited in their capacity to objectively evaluate the presence of such attribute hierarchies. This paper introduces the Hierarchical Diagnostic Classification Model (HDCM), which adapts the Log-linear Cognitive Diagnosis Model to cases where attribute hierarchies are present. The utility of the HDCM is demonstrated through simulation and by an empirical example. Simulation study results show the HDCM is efficiently estimated and can accurately test for the presence of an attribute hierarchy statistically, a feature not possible when using more commonly used DCMs. Empirically, the HDCM is used to test for the presence of a suspected attribute hierarchy in a test of English grammar, confirming the data is more adequately represented by hierarchical attribute structure when compared to a crossed, or nonhierarchical structure.     

Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential

Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components—ability, capacity, and availability—where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study–Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.     

Inconsistent Models of Arithmetic Part I: Finite Models

The paper concerns interpretations of the paraconsistent logic LP which model theories properly containing all the sentences of first order arithmetic. The paper demonstrates the existence of such models and provides a complete taxonomy of the finite ones.     

MMPI-Rorschach Interrelationships: Proposed Criteria for Evaluating Explanatory Models

An extensive empirical literature, spanning 50 years and 45 published investigations, leads to the conclusion that the Rorschach and the Minnesota Multiphasic Personality Inventory (MMPI) bear little or no meaningful relationship to each other. An inherent tension exists between these empirical findings and the widespread clinical practice of integrating MMPI and Rorschach results. At least three perspectives have been advanced concerning the relationship between these two instruments. One view holds that variables from the two measures will demonstrate significant patterns of convergence only in carefully designed research studies that involve specific, well-constructed and theoretically derived predictions. A second view postulates that although variables from the Rorschach and MMPI do not bear a high intercorrelation with each other, these variables may be combined to contribute significantly to the prediction of outcome variance. In this view, the combined use of the two instruments yields clinically useful increases in incremental validity not achievable by the use of either instrument in isolation. A third approach is reflected in the proposition that although the MMPI and Rorschach do not produce significant interrelationships under general conditions, meaningful relationships may be yielded under specific psychometric conditions, for example, under conditions in which the response styles are consistently displayed across those two instruments. This article will review research evidence related to each of these perspectives, with particular emphasis on the importance of clearly specifying the criteria to be applied in evaluating these models. The concepts of parsimony and heuristic value are proposed for these evaluation purposes.     

Models of Psychotherapy: Implications for Pastoral Care Practice

Pastoral care givers are called to provide care and counseling to parishioners that are suffering in many ways. A core question is what does a pastor rely on to provide this care? Pastors usually call on models of psychotherapy to inform their care giving. A framework of theological anthropology, cosmology, soteriology and harmatiology is developed for analyzing the worldviews inherent in models of psychotherapy. The specific models of Adler’s Individual Psychology, Narrative therapy, Horney’s personality theory, and Intersubjective theory are used to demonstrate the application of this framework. Several pastoral care implications are developed following the application of the framework.     

Abstract: Sample Size Planning for Latent Curve Models

When designing a study that uses structural equation modeling (SEM), an important task is to decide an appropriate sample size. Historically, this task is approached from the power analytic perspective, where the goal is to obtain sufficient power to reject a false null hypothesis. However, hypothesis testing only tells if a population effect is zero and fails to address the question about the population effect size. Moreover, significance tests in the SEM context often reject the null hypothesis too easily, and therefore the problem in practice is having too much power instead of not enough power.

An alternative means to infer the population effect is forming confidence intervals (CIs). A CI is more informative than hypothesis testing because a CI provides a range of plausible values for the population effect size of interest. Given the close relationship between CI and sample size, the sample size for an SEM study can be planned with the goal to obtain sufficiently narrow CIs for the population model parameters of interest.

Latent curve models (LCMs) is an application of SEM with mean structure to studying change over time. The sample size planning method for LCM from the CI perspective is based on maximum likelihood and expected information matrix. Given a sample, to form a CI for the model parameter of interest in LCM, it requires the sample covariance matrix S, sample mean vector , and sample size N. Therefore, the width (w) of the resulting CI can be considered a function of S, , and N. Inverting the CI formation process gives the sample size planning process. The inverted process requires a proxy for the population covariance matrix Σ, population mean vector μ, and the desired width ω as input, and it returns N as output. The specification of the input information for sample size planning needs to be performed based on a systematic literature review. In the context of covariance structure analysis, Lai and Kelley (2011) discussed several practical methods to facilitate specifying Σ and ω for the sample size planning procedure.     

Models of Disability: Implications for the Counseling Profession

Because of the increasing number of people with disabilities, counselors of all specialties and theoretical orientations will be called on to provide services to clients with disabilities. The authors present a brief overview of 4 major models of disability to provide an introduction to the varying definitions and causal and responsibility attributions of disability. Viewing the client with a disability as an individual with multiple identities, roles, functions, and environments facilitates the counseling process.