Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

Factor analysis of the self-report Dysexecutive (DEX-S) Questionnaire

The self-rating Dysexecutive Questionnaire (DEX-S) is a recently developed standardized self-report measure of behavioral difficulties associated with executive functioning such as impulsivity, inhibition, control, monitoring, and planning. Few studies have examined its construct validity, particularly for its potential wider use across a variety of clinical and nonclinical populations. This study examines the factor structure of the DEX-S questionnaire using a sample of nonclinical (N = 293) and clinical (N = 49) participants. A series of factor analyses were evaluated to determine the best factor solution for this scale. This was found to be a 4-factor solution with factors best described as inhibition, intention, social regulation, and abstract problem solving. The first 2 factors replicate factors from the 5-factor solutions found in previous studies that examined specific subpopulations. Although further research is needed to evaluate the factor structure within a range of subpopulations, this study supports the view that the DEX has the factor structure sufficient for its use in a wider context than only with neurological or head-injured patients. Overall, a 4-factor solution is recommended as the most stable and parsimonious solution in the wider context.

Solution structure and characterization of the LGR8 receptor binding surface of insulin-like peptide 3

Insulin-like peptide 3 (INSL3), a member of the relaxin peptide family, is produced in testicular Leydig cells and ovarian thecal cells. Gene knock-out experiments have identified a key biological role in initiating testes descent during fetal development. Additionally, INSL3 has an important function in mediating male and female germ cell function. These actions are elicited via its recently identified receptor, LGR8, a member of the leucine-rich repeat-containing G-protein- coupled receptor family. To identify the structural features that are responsible for the interaction of INSL3 with its receptor, its solution structure was determined by NMR spectroscopy together with in vitro assays of a series of B-chain alanine-substituted analogs. Synthetic human INSL3 was found to adopt a characteristic relaxin/ insulin-like fold in solution but is a highly dynamic molecule. The four termini of this two-chain peptide are disordered, and additional conformational exchange is evident in the molecular core. Alanine-substituted analogs were used to identify the key residues of INSL3 that are responsible for the interaction with the ectodomain of LGR8. These include Arg(B16) and Val(B19), with His(B12) and Arg(B20) playing a secondary role, as evident from the synergistic effect on the activity in double and triple mutants involving these residues. Together, these amino acids combine with the previously identified critical residue, Trp(B27), to form the receptor binding surface. The current results provide clear direction for the design of novel specific agonists and antagonists of this receptor.

Molecular cloning and characterization of the mouse Na+ sulfate cotransporter gene (Slc13a4): structure and expression

Sulfate is an essential ion required for numerous functions in mammalian physiology. Due to its hydrophilic nature, cells require sulfate transporters on their plasma membranes to allow entry of sulfate into cells. In this study, we identified a new mouse Na+-sulfate cotransporter (mNaS2), characterized its tissue distribution and determined its cDNA and gene (Slc13a4) structures. mNaS2 mRNA was expressed in placenta, brain, lung, eye, heart, testis, thymus and liver. The mouse NaS2 cDNA spans 3384 nucleotides and its open frame encodes a protein of 624 amino acids. Slc13a4 maps to mouse chromosome 6131 and contains 16 exons, spanning over 40 kb in length. Its 5'-flanking region contains CART- and GC-box motifs and a number of putative transcription factor binding sites, including GATA-1, MTF-1, STAT6 and HNF4 consensus sequences. This is the first study to define the tissue distribution of mNaS2 and resolve its cDNA and gene structures, which will allow us to investigate mNaS2 gene expression in vivo and determine its role in mammalian physiology.

Evaluating the properties of a stage-specific self-efficacy scale for physical activity using classical test theory, confirmatory factor analysis and item response modeling

The purpose of this paper was to evaluate the psychometric properties of a stage-specific selfefficacy scale for physical activity with classical test theory (CTT), confirmatory factor analysis (CFA) and item response modeling (IRM). Women who enrolled in the Women On The Move study completed a 20-item stage-specific self-efficacy scale developed for this study [n = 226, 51.1% African-American and 48.9% Hispanic women, mean age = 49.2 (67.0) years, mean body mass index = 29.7 (66.4)]. Three analyses were conducted: (i) a CTT item analysis, (ii) a CFA to validate the factor structure and (iii) an IRM analysis. The CTT item analysis and the CFA results showed that the scale had high internal consistency (ranging from 0.76 to 0.93) and a strong factor structure. Results also showed that the scale could be improved by modifying or eliminating some of the existing items without significantly altering the content of the scale. The IRM results also showed that the scale had few items that targeted high self-efficacy and the stage-specific assumption underlying the scale was rejected. In addition, the IRM analyses found that the five-point response format functioned more like a four-point response format. Overall, employing multiple methods to assess the psychometric properties of the stage-specific self-efficacy scale demonstrated the complimentary nature of these methods and it highlighted the strengths and weaknesses of this scale.

Revising the theoretical structure of personality and applying it to the world of work

Most modern models of personality are hierarchical, perhaps as a result of their development by means of exploratory factor analysis. Based on new ideas about the structure of personality and how it divides into biologically based and sociocognitively based components (as proposed by Carver, Cloninger, EUiot and Thrash, and ReveUe), I develop a series of rules that show how scales of personality may be linked from those that are most distal to those which are most proximal. I use SEM to confirm the proposed structure in scales of the Temperament Character Inventory (TCI) and the Eysenck Personality Profiler. Good fit is achieved and all proposed paths are significant. The model is then used to predict work performance, deviance and job satisfacdon.

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.