The Four-Dimensional Symptom Questionnaire (4DSQ): a validation study of a multidimensional self-report questionnaire to assess distress, depression, anxiety and somatization

BACKGROUND: The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire that has been developed in primary care to distinguish non-specific general distress from depression, anxiety and somatization. The purpose of this paper is to evaluate its criterion and construct validity. METHODS: Data from 10 different primary care studies have been used. Criterion validity was assessed by comparing the 4DSQ scores with clinical diagnoses, the GPs' diagnosis of any psychosocial problem for Distress, standardised psychiatric diagnoses for Depression and Anxiety, and GPs' suspicion of somatization for Somatization. ROC analyses and logistic regression analyses were used to examine the associations. Construct validity was evaluated by investigating the inter-correlations between the scales, the factorial structure, the associations with other symptom questionnaires, and the associations with stress, personality and social functioning. The factorial structure of the 4DSQ was assessed through confirmatory factor analysis (CFA). The associations with other questionnaires were assessed with Pearson correlations and regression analyses. RESULTS: Regarding criterion validity, the Distress scale was associated with any psychosocial diagnosis (area under the ROC curve [AUC] 0.79), the Depression scale was associated with major depression (AUC = 0.83), the Anxiety scale was associated with anxiety disorder (AUC = 0.66), and the Somatization scale was associated with the GPs' suspicion of somatization (AUC = 0.65). Regarding the construct validity, the 4DSQ scales appeared to have considerable inter-correlations (r = 0.35-0.71). However, 30–40% of the variance of each scale was unique for that scale. CFA confirmed the 4-factor structure with a comparative fit index (CFI) of 0.92. The 4DSQ scales correlated with most other questionnaires measuring corresponding constructs. However, the 4DSQ Distress scale appeared to correlate with some other depression scales more than the 4DSQ Depression scale. Measures of stress (i.e. life events, psychosocial problems, and work stress) were mainly associated with Distress, while Distress, in turn, was mainly associated with psychosocial dysfunctioning, including sick leave. CONCLUSION: The 4DSQ seems to be a valid self-report questionnaire to measure distress, depression, anxiety and somatization in primary care patients. The 4DSQ Distress scale appears to measure the most general, most common, expression of psychological problems

Progesterone Inhibits Epithelial-to-Mesenchymal Transition in Endometrial Cancer

Background: Every year approximately 74,000 women die of endometrial cancer, mainly due to recurrent or metastatic disease. The presence of tumor infiltrating lymphocytes (TILs) as well as progesterone receptor (PR) positivity has been correlated with improved prognosis. This study describes two mechanisms by which

Where Snow is a Landmark: Route Direction Elements in Alpine Contexts

Route directions research has mostly focused on urban space so far, highlighting human concepts of street networks based on a range of recurring elements such as route segments, decision points, landmarks and actions. We explored the way route directions reflect the features of space and activity in the context of mountaineering. Alpine route directions are only rarely segmented through decision points related to reorientation; instead, segmentation is based on changing topography. Segments are described with various degrees of detail, depending on difficulty. For landmark description, direction givers refer to properties such as type of surface, dimension, colour of landscape features; terrain properties (such as snow) can also serve as landmarks. Action descriptions reflect the geometrical conceptualization of landscape features and dimensionality of space. Further, they are very rich in the semantics of manner of motion

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases

A case of mistaken identity: HSPs are no DAMPs but DAMPERs

Until recently, the immune system was seen solely as a defense system with its primary task being the elimination of unwanted microbial invaders. Currently, however, the functional significance of the immune system has obtained a much wider perspective, to include among others the maintenance and restoration of homeostasis following tissue damage. In this latter aspect, there is a growing interest in the identification of molecules involved, such as the so-called danger or damage-associated molecular patterns (DAMPs), also called alarmins. Since heat shock proteins are archetypical molecules produced under stressful conditions, such as tissue damage or inflammation, they are frequently mentioned as prime examples of DAMPs (Bianchi, J Leukoc Biol 81:1–5, 2007; Kono and Rock, Nat Rev Immunol 8:279–289, 2008; Martin-Murphy et al., Toxicol Lett 192:387–394, 2010). See for instance also a recent review (Chen and Nunez, Science 298:1395–1401, 2010). Contrary to this description, we recently presented some of the arguments against a role of heat shock protein as DAMPs (Broere et al., Nat Rev Immunol 11:565-c1, 2011). With this perspective and reflection article, we hope to elaborate on this debate and provide additional thoughts to further ignite this discussion on this critical and evolving issue

Secondary mineral formation associated with respiration of nontronite, NAu-1 by iron reducing bacteria

Experimental batch and miscible-flow cultures were studied in order to determine the mechanistic pathways of microbial Fe(III) respiration in ferruginous smectite clay, NAu-1. The primary purpose was to resolve if alteration of smectite and release of Fe precedes microbial respiration. Alteration of NAu-1, represented by the morphological and mineralogical changes, occurred regardless of the extent of microbial Fe(III) reduction in all of our experimental systems, including those that contained heat-killed bacteria and those in which O(2), rather than Fe(III), was the primary terminal electron acceptor. The solid alteration products observed under transmission electron microscopy included poorly crystalline smectite with diffuse electron diffraction signals, discrete grains of Fe-free amorphous aluminosilicate with increased Al/Si ratio, Fe-rich grains, and amorphous Si globules in the immediate vicinity of bacterial cells and extracellular polymeric substances. In reducing systems, Fe was also found as siderite. The small amount of Fe partitioned to the aqueous phase was primarily in the form of dissolved Fe(III) species even in the systems in which Fe(III) was the primary terminal electron acceptor for microbial respiration. From these observations, we conclude that microbial respiration of Fe(III) in our laboratory systems proceeded through the following: (1) alteration of NAu-1 and concurrent release of Fe(III) from the octahedral sheets of NAu-1; and (2) subsequent microbial respiration of Fe(III)

How Genomics Is Changing What We Know About the Evolution and Genome of Bordetella pertussis

The evolution of Bordetella pertussis from a common ancestor similar to Bordetella bronchiseptica has occurred through large-scale gene loss, inactivation and rearrangements, largely driven by the spread of insertion sequence element repeats throughout the genome. B. pertussis is widely considered to be monomorphic, and recent evolution of the B. pertussis genome appears to, at least in part, be driven by vaccine-based selection. Given the recent global resurgence of whooping cough despite the wide-spread use of vaccination, a more thorough understanding of B. pertussis genomics could be highly informative. In this chapter we discuss the evolution of B. pertussis, including how vaccination is changing the circulating B. pertussis population at the gene-level, and how new sequencing technologies are revealing previously unknown levels of inter- and intra-strain variation at the genome-level

Physical Fitness and Telomere Length in Patients with Coronary Heart Disease: Findings from the Heart and Soul Study

Background: Short telomere length (TL) is an independent predictor of mortality in patients with coronary heart disease (CHD). However, the relationship between physical fitness and TL has not been explored in these patients. Methods: In a cross sectional study of 944 outpatients with stable CHD, we performed exercise treadmill testing, assessed self-reported physical activity, and measured leukocyte TL using a quantitative PCR assay. We used generalized linear models to calculate mean TL (T/S ratio), and logistic regression models to compare the proportion of patients with short TL (defined as the lowest quartile), among participants with low, medium and high physical fitness, based on metabolic equivalent tasks achieved (METs). Results: 229 participants had low physical fitness (,5 METS), 334 had moderate physical fitness (5–7 METS), and 381 had high physical fitness (.7 METS). Mean6 T/S ratio ranged from 0.8660.21 (534963781 base pairs) in those with low physical fitness to 0.9560.23 (556663829 base pairs) in those with high physical fitness (p,.001). This association remained strong after adjustment for numerous patient characteristics, including measures of cardiac disease severity and physical inactivity (p = 0.005). Compared with participants with high physical fitness, those with low physical fitness had 2-fold greater odds o