The Psychometric Properties of an Internet-Administered Version of the Depression Anxiety and Stress Scales (DASS) in a Sample of Dutch Adults

Psychometric work on the widely used Depression Anxiety and Stress Scales (DASS) has mostly used classical psychometrics and ignored common internet-administered versions. Therefore, the present study used not only classical, but also modern psychometrics based on item response theory (IRT) to evaluate an internet-administered version of the DASS (Dutch translation). Internet-administered DASS data were collected as part of a large internet-based study in the Dutch adult population (n = 7972). Initially, external correlates (i.e. demographics other measures) and some classical psychometrics (internal consistency, convergent/divergent validity) of the DASS scales were evaluated. Next, IRT was used to investigate the scales’ dimensionality, discrimination and item-functioning. Finally, the DASS depression scale was further investigated by linking it to the more clinically-oriented Quick Inventory of Depressive Symptomatology (QIDS) using item response theory (IRT). Initial classical psychometric analyses supported the scales’ internal consistency (alpha = 0.94–0.98) and convergent/divergent validity. IRT analyses showed that each of the DASS scales was only suitable to measure variations in a very narrow and rather mild severity range. Linking the DASS depression scale with the QIDS also showed that the DASS depression scale discriminated best in the mild-moderate severity range, but not at higher severity levels that were covered by the QIDS. In conclusion, the scales of the internet-administered DASS show good internal consistency and validity. However, users should be aware that the scales discriminate best at mild-moderate severity ranges in the general population.     

A comparative study of the dimensionality of the self-concealment scale using principal components analysis and Mokken scale analysis

We discuss and contrast 2 methods for investigating the dimensionality of data from tests and questionnaires: the popular principal components analysis (PCA) and the more recent Mokken scale analysis (MSA; Mokken, 1971). First, we discuss the theoretical similarities and differences between both methods. Then, we use both methods to analyze data collected by means of Larson and Chastain's (1990) Self-Concealment Scale (SCS). We present the different results and highlight the instances in which the methods complement one another so as to obtain a stronger result than would be obtained using only 1 method. Finally, we discuss the implications of the results for the dimensionality of the SCS and provide recommendations for both the further development of the SCS and the future use of PCA and MSA in personality research.     

To Recycle or Not to Recycle? An Intergenerational Approach to Nuclear Fuel Cycles

This paper approaches the choice between the open and closed nuclear fuel cycles as a matter of intergenerational justice, by revealing the value conflicts in the production of nuclear energy. The closed fuel cycle improve sustainability in terms of the supply certainty of uranium and involves less long-term radiological risks and proliferation concerns. However, it compromises short-term public health and safety and security, due to the separation of plutonium. The trade-offs in nuclear energy are reducible to a chief trade-off between the present and the future. To what extent should we take care of our produced nuclear waste and to what extent should we accept additional risks to the present generation, in order to diminish the exposure of future generation to those risks? The advocates of the open fuel cycle should explain why they are willing to transfer all the risks for a very long period of time (200,000 years) to future generations. In addition, supporters of the closed fuel cycle should underpin their acceptance of additional risks to the present generation and make the actual reduction of risk to the future plausible.     

A CONTRIBUTION TO THE DEBATE ON SCIENCE AND FAITH BY CHRISTIAN STUDENTS FROM ABIDJAN

The science and faith debate is dominated by Western voices. In order to enrich this debate, the authors study the discourses of different groups of Christian academics and master's students in francophone Africa. This article describes the process of reconstructing and analyzing the discourse of a group of master's students from Abidjan (Ivory Coast) with the help of group model building and focus groups. Three characteristic features that emerge from this discourse include the foundational position of faith, the central role of truth, and the ambiguous connotations of the term “science” in this context. The reconstructed discourse is then brought into conversation with the North Atlantic debate, with a special focus on the concept of scientism.     

Free-energy and the brain

If one formulates Helmholtz’s ideas about perception in terms of modern-day theories one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring what cause our sensory inputs and learning causal regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain’s organisation and responses. In this paper, we suggest that these perceptual processes are just one emergent property of systems that conform to a free-energy principle. The free-energy considered here represents a bound on the surprise inherent in any exchange with the environment, under expectations encoded by its state or configuration. A system can minimise free-energy by changing its configuration to change the way it samples the environment, or to change its expectations. These changes correspond to action and perception, respectively, and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment implies that the system’s state and structure encode an implicit and probabilistic model of the environment. We will look at models entailed by the brain and how minimisation of free-energy can explain its dynamics and structure.     

Review of Issues About Classical Change Scores: A Multilevel Modeling Perspective on Some Enduring Beliefs

Change scores obtained in pretest–posttest designs are important for evaluating treatment effectiveness and for assessing change of individual test scores in psychological research. However, over the years the use of change scores has raised much controversy. In this article, from a multilevel perspective, we provide a structured treatise on several persistent negative beliefs about change scores and show that these beliefs originated from the confounding of the effects of within-person change on change-score reliability and between-person change differences. We argue that psychometric properties of change scores, such as reliability and measurement precision, should be treated at suitable levels within a multilevel framework. We show that, if examined at the suitable levels with such a framework, the negative beliefs about change scores can be renounced convincingly. Finally, we summarize the conclusions about change scores to dispel the myths and to promote the potential and practical usefulness of change scores.     

A general solution to Mosier's oblique procrustes problem

Browne provided a method for finding a solution to the normal equations derived by Mosier for rotating a factor matrix to a best least squares fit with a specified structure. Cramer showed that Browne's solution is not always valid, and proposed a modified algorithm. Both Browne and Cramer assumed the factor matrix to be of full rank. In this paper a general solution is derived, which takes care of rank deficient factor matrices as well. A new algorithm is offered.     

Mokken Scale Analysis for Dichotomous Items Using Marginal Models

Scalability coefficients play an important role in Mokken scale analysis. For a set of items, scalability coefficients have been defined for each pair of items, for each individual item, and for the entire scale. Hypothesis testing with respect to these scalability coefficients has not been fully developed. This study introduces marginal modelling as a framework to derive the standard errors for the scaling coefficients and test hypotheses about these coefficients. Several examples demonstrate the possibilities of marginal modelling in Mokken scale analysis. These possibilities include testing whether Mokken’s criteria for a scale are satisfied, testing whether scalability coefficients of different items are equal, and testing whether scalability coefficients are equal across different groups.