Therapeutic Alliance in Cognitive Behaviour Therapy for Children with Autism

This study aimed to determine child pre-treatment variables, therapist behaviours and treatment outcomes associated with early and late therapeutic alliance in cognitive behaviour therapy for children with autism. Data were collected from 48 children with autism (91.7% male) who demonstrated average verbal IQ. Therapists included 22 post-doctoral fellows or graduate trainees (90.9% female). Therapeutic alliance and therapist behaviours were measured using observational coding of early and late sessions. Pre-treatment and outcome measures included multiple informant reports of child emotional and behavioural functioning. Results indicate some relation between emotion regulation and symptom severity, and the quality of alliance. Early therapist behaviours were associated with late therapeutic bond. Pushing the child to talk early on predicted later task-collaboration. Early therapeutic alliance did not predict treatment change. Late task-collaboration predicted improvements in emotion regulation. Future research should further examine the role of task-collaboration as a mechanism of treatment change for children with autism

Exploring Slider vs. Categorical Response Formats in Web-Based Surveys

Web-based surveys have become a common mode of data collection for researchers in many fields, but there are many methodological questions that need to be answered. This article examines one such question—do the use of sliders to express numerical amounts and the use of the more traditional radio-button scales give the same, or different, measurements? First, we review the central debates surrounding the use of slider scales, including advantages and disadvantages. Second, we report findings from a controlled simple randomized design field experiment using a sample of business managers in Italy to compare the two response formats. Measures of topic sensitivity, topic interest, and likelihood of participation were obtained. No statistically significant differences were found between the response formats. The article concludes with suggestions for researchers who wish to use slider scales as a measurement device

Exploring Self-Efficacy with an Emphasis on Direct Selling

Self-efficacy, the confidence that one has in his or her capabilities to achieve a goal, is one of the most widely studied constructs in personal selling and sales management research. With few exceptions, self-efficacy has been studied as antecedent to sales performance. The present study differs from prior marketing-related studies of self-efficacy in that it explores whether a direct selling experience can enhance business/professional self-efficacy and personal life self-efficacy. In other words, in the present study self-efficacy is treated as consequent to a direct selling experience. An online survey was conducted in which a nationally representative sample of 495 current direct sellers responded to a self-efficacy scale consisting of 14 items regarding the impact of their direct selling experience on their business/professional skills and a self-efficacy scale consisting of 13 items regarding the impact of their direct selling experience on their personal life skills. More than 60 percent of the direct sellers surveyed either somewhat or strongly believed that their direct selling experience improved their business/professional and their personal life skills. There were differences in impact based on the gender and the age of the direct sellers. Both business/professional self-efficacy and personal life self-efficacy were significantly and positively related to self-perceived sales performance and performance on a non-direct selling job. The theoretical and managerial implications of the findings are discussed

Predicting Turnover of Direct Sellers

As an industry, direct selling is ubiquitous. An estimated 5.3 million people were direct sellers in the United States in 2016. Of those 5.3 million direct sellers, 4.5 million were part-time and 800,000 were full-time. Moreover, in 2016, direct selling generated an estimated US$35.54 billion in retail sales that, in turn, had a US$83.11 billion impact on the United States economy. In a broad sense, direct selling is simultaneously considered to be a distribution channel, an industry, and a business model. Traditional major modes of direct selling include person-to-person and party-plan selling at a home or in the workplace, with online sales now gaining traction in the direct selling marketplace. Individuals become direct sellers for a multitude of reasons, including a desire to earn a living as a full-time direct seller, to earn supplemental income as a part-time direct seller, or to work at a part-time job to earn extra money to make a special purchase. Consequently, there can be relatively high turnover among direct sellers, especially those whose goal was to earn extra money to make a special purchase. Turnover is an issue in direct selling for several reasons, including the time and resources direct selling companies expend to recruit, train, and support direct sellers as well as the potential loss of customers and revenues when a direct seller exits the industry. As such, being able to predict which direct sellers are likely to leave the industry before considerable company and individual resources are expended would be beneficial to all concerned marketplace constituents. This research attempted to predict direct seller turnover by analyzing responses to a set of 12 reasons why a national sample of individuals decided to join a direct selling company. This was done by first comparing the number and nature of reasons that subsamples of current and former direct sellers gave for joining a direct selling company. Significant differences were observed between the two direct seller groups for nine of the 12 reasons studied and for the total number of reasons given for joining a direct selling company. This was followed by a binary logistic regression analysis that successfully predicted the work status of 63 percent of the combined sample of current and former direct sellers. Although data for the present research were derived from a relatively large nationwide survey of current and former direct sellers, the study should be viewed as exploratory given the absence of information on the topic and the lack of theoretically based hypotheses

Ueber die freye Ein- und Ausfuhre des Getraides in Betracht Estlands : ein Beytrag zu des Hrn. Reimarus Untersuchung der wichtigen Frage von der freyen Ein- und Ausfuhre des Getraides

http://tartu.ester.ee/record=b1307918~S1*es

A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study

Albaum S, Hahne H, Otto A, et al. A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study. Proteome Science. 2011;9(1): 30.Background: Mass spectrometry-based proteomics has reached a stage where it is possible to comprehensively analyze the whole proteome of a cell in one experiment. Here, the employment of stable isotopes has become a standard technique to yield relative abundance values of proteins. In recent times, more and more experiments are conducted that depict not only a static image of the up- or down-regulated proteins at a distinct time point but instead compare developmental stages of an organism or varying experimental conditions. Results: Although the scientific questions behind these experiments are of course manifold, there are, nevertheless, two questions that commonly arise: 1) which proteins are differentially regulated regarding the selected experimental conditions, and 2) are there groups of proteins that show similar abundance ratios, indicating that they have a similar turnover? We give advice on how these two questions can be answered and comprehensively compare a variety of commonly applied computational methods and their outcomes. Conclusions: This work provides guidance through the jungle of computational methods to analyze mass spectrometry-based isotope-labeled datasets and recommends an effective and easy-to-use evaluation strategy. We demonstrate our approach with three recently published datasets on Bacillus subtilis [1,2] and Corynebacterium glutamicum [3]. Special focus is placed on the application and validation of cluster analysis methods. All applied methods were implemented within the rich internet application QuPE [4]. Results can be found at http://qupe.cebitec.uni-bielefeld.de webcite

Visualizing post genomics data-sets on customized pathway maps by ProMeTra – aeration-dependent gene expression and metabolism of Corynebacterium glutamicum as an example

Neuweger H, Persicke M, Albaum S, et al. Visualizing post genomics data-sets on customized pathway maps by ProMeTra – aeration-dependent gene expression and metabolism of Corynebacterium glutamicum as an example. BMC Systems Biology. 2009;3(1): 82.Background: The rapid progress of post-genomic analyses, such as transcriptomics, proteomics, and metabolomics has resulted in the generation of large amounts of quantitative data covering and connecting the complete cascade from genotype to phenotype for individual organisms. Various benefits can be achieved when these ''Omics'' data are integrated, such as the identification of unknown gene functions or the elucidation of regulatory networks of whole organisms. In order to be able to obtain deeper insights in the generated datasets, it is of utmost importance to present the data to the researcher in an intuitive, integrated, and knowledge-based environment. Therefore, various visualization paradigms have been established during the last years. The visualization of ''Omics'' data using metabolic pathway maps is intuitive and has been applied in various software tools. It has become obvious that the application of web-based and user driven software tools has great potential and benefits from the use of open and standardized formats for the description of pathways. Results: In order to combine datasets from heterogeneous ''Omics'' sources, we present the web-based ProMeTra system that visualizes and combines datasets from transcriptomics, proteomics, and metabolomics on user defined metabolic pathway maps. Therefore, structured exchange of data with our ''Omics'' applications Emma 2, Qupe and MeltDB is employed. Enriched SVG images or animations are generated and can be obtained via the user friendly web interface. To demonstrate the functionality of ProMeTra, we use quantitative data obtained during a fermentation experiment of the L-lysine producing strain Corynebacterium glutamicum DM1730. During fermentation, oxygen supply was switched off in order to perturb the system and observe its reaction. At six different time points, transcript abundances, intracellular metabolite pools, as well as extracellular glucose, lactate, and L-lysine levels were determined. Conclusion: The interpretation and visualization of the results of this complex experiment was facilitated by the ProMeTra software. Both transcriptome and metabolome data were visualized on a metabolic pathway map. Visual inspection of the combined data confirmed existing knowledge but also delivered novel correlations that are of potential biotechnological importance

CoryneCenter – An online resource for the integrated analysis of corynebacterial genome and transcriptome data

Neuweger H, Baumbach J, Albaum S, et al. CoryneCenter: an online resource for the integrated analysis of corynebacterial genome and transcriptome data. BMC Systems Biology. 2007;1(1): 55.Background: The introduction of high-throughput genome sequencing and post-genome analysis technologies, e.g. DNA microarray approaches, has created the potential to unravel and scrutinize complex gene-regulatory networks on a large scale. The discovery of transcriptional regulatory interactions has become a major topic in modern functional genomics. Results: To facilitate the analysis of gene-regulatory networks, we have developed CoryneCenter, a web-based resource for the systematic integration and analysis of genome, transcriptome, and gene regulatory information for prokaryotes, especially corynebacteria. For this purpose, we extended and combined the following systems into a common platform: (1) GenDB, an open source genome annotation system, (2) EMMA, a MAGE compliant application for high-throughput transcriptome data storage and analysis, and (3) CoryneRegNet, an ontology-based data warehouse designed to facilitate the reconstruction and analysis of gene regulatory interactions. We demonstrate the potential of CoryneCenter by means of an application example. Using microarray hybridization data, we compare the gene expression of Corynebacterium glutamicum under acetate and glucose feeding conditions: Known regulatory networks are confirmed, but moreover CoryneCenter points out additional regulatory interactions. Conclusion: CoryneCenter provides more than the sum of its parts. Its novel analysis and visualization features significantly simplify the process of obtaining new biological insights into complex regulatory systems. Although the platform currently focusses on corynebacteria, the integrated tools are by no means restricted to these species, and the presented approach offers a general strategy for the analysis and verification of gene regulatory networks. CoryneCenter provides freely accessible projects with the underlying genome annotation, gene expression, and gene regulation data. The system is publicly available at http://www.CoryneCenter.d