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.

A design pattern for efficient retrieval of large data sets from remote data sources

Retrieving large amounts of information over wide area networks, including the Internet, is problematic due to issues arising from latency of response, lack of direct memory access to data serving resources, and fault tolerance. This paper describes a design pattern for solving the issues of handling results from queries that return large amounts of data. Typically these queries would be made by a client process across a wide area network (or Internet), with one or more middle-tiers, to a relational database residing on a remote server. The solution involves implementing a combination of data retrieval strategies, including the use of iterators for traversing data sets and providing an appropriate level of abstraction to the client, double-buffering of data subsets, multi-threaded data retrieval, and query slicing. This design has recently been implemented and incorporated into the framework of a commercial software product developed at Oracle Corporation.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design probes with high specificities, i.e. uniqueness, and also sensitivities, i.e., suitable melting temperature and no secondary structure. We make use of available biology tools to gain necessary sequence information of human chromosome 12, and combined with evolutionary strategy (ES) to find unique subsequences representing all predicted exons. The results are presented and discussed.