Local examination of skin diffusion using FTIR spectroscopic imaging and multivariate target factor analysis

In the context of trans-dermal drug delivery it is very important to have mechanistic insight into the barrier function of the skin's stratum corneum and the diffusion mechanisms of topically applied drugs. Currently spectroscopic imaging techniques are evolving which enable a spatial examination of various types of samples in a dynamic way. ATR-FTIR imaging opens up the possibility to monitor spatial diffusion profiles across the stratum corneum of a skin sample. Multivariate data analyses methods based on factor analysis are able to provide insight into the large amount of spectroscopically complex and highly overlapping signals generated. Multivariate target factor analysis was used for spectral resolution and local diffusion profiles with time through stratum corneum. A model drug, 4-cyanophenol in polyethylene glycol 600 and water was studied. Results indicate that the average diffusion profiles between spatially different locations show similar profiles despite the heterogeneous nature of the biological sample and the challenging experimental set-up.

The structure of the Statistics Anxiety Rating Scale: A confirmatory factor analysis using UK psychology students

This study aimed to examine the structure of the statistics anxiety rating scale. Responses from 650 undergraduate psychology students throughout the UK were collected through an on-line study. Based on previous research three different models were specified and estimated using confirmatory factor analysis. Fit indices were used to determine if the model fitted the data and a likelihood ratio difference test was used to determine the best fitting model. The original six factor model was the best explanation of the data. All six subscales were intercorrelated and internally consistent. It was concluded that the statistics anxiety rating scale was found to measure the six subscales it was designed to assess in a UK population.

Enrichment and analysis of nonenzymatically glycated peptides: Boronate affinity chromatography coupled with electron-transfer dissociation mass spectrometry

Nonenzymatic glycation of peptides and proteins by D-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low-abundance posttranslational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron-transfer dissociation (ETD) and collision induced dissociation ( CID) tandem mass spectrometry. ETD fragmentation mode permitted identification of a significantly higher number of glycated peptides (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing enrichment on first the protein and then the peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS and using ETD as the fragmentation mode is an efficient approach for analysis of glycated proteins and may have broad application in studies of diabetes mellitus.

Index of sources of stress in nursing students: a confirmatory factor analysis.

Aim. This paper is a report of a study to test the proposed factor structure of the Index of Sources of Stress in Nursing Students. Background. Research across many countries has identified a number of sources of distress in nursing students but little attempt has been made to understand and measure sources of eustress or those stressors likely to enhance performance and well-being. The Index of Sources of Stress in Nursing Students was developed to do this. Exploratory factor analysis suggested a three-factor structure, the factors being labelled: learning and teaching; placement-related and course organization. It is important, however, to subject the instrument to confirmatory factor analysis as a further test of construct validity. Method. A convenience sample of final year nursing students (n = 176) was surveyed in one university in Northern Ireland in 2007. The Index of Sources of Stress in Nursing Students, which measures sources of stress likely to contribute to distress and eustress, was completed electronically. The LISREL programme was used to carry out the confirmatory factor analysis and test the factor structure suggested in the exploratory analysis. Findings. The proposed factor structure for the items measuring ‘Uplifts’ proved to be a good fit to the data and the proposed factor structure for the items measuring ‘Hassles’ showed adequate fit. Conclusion. In nursing programmes adopting the academic model and combining university-based learning with placement experience, this instrument can be used to help identify the sources of stress or course demands that students rate as distressing and those that help them to achieve. The validity of the ISSN could be further evaluated in other education settings.

Confirmatory factor analysis of the adolescent self-report strengths and difficulties questionnaire

The Strengths and Difficulties Questionnaire (SDQ) is a widely used 25-item screening test for emotional and behavioral problems in children and adolescents. This study attempted to critically examine the factor structure of the adolescent self-report version. As part of an ongoing longitudinal cohort study, a total of 3,753 pupils completed the SDQ when aged 12. Both three- and five-factor exploratory factor analysis models were estimated. A number of deviations from the hypothesized SDQ structure were observed, including a lack of unidimensionality within particular subscales, cross-loadings, and items failing to load on any factor. Model fit of the confirmatory factor analysis model was modest, providing limited support for the hypothesized five-component structure. The analyses suggested a number of weaknesses within the component structure of the self-report SDQ, particularly in relation to the reverse-coded items.

The structure of the Beck Hopelessness Scale: A confirmatory factor analysis in UK students

The aim of this paper was to confirm the factor structure of the 20-item Beck Hopelessness Scale in a non-clinical population. Previous research has highlighted a lack of clarity in its construct validity with regards to this population.

Based on previous factor analytic findings from both clinical and non-clinical studies, 13 separate confirmatory factor models were specified and estimated using LISREL 8.72 to test the one, two and three-factor models.

Psychology and medical students at Queen's University, Belfast (n = 581) completed both the BHS and the Beck Depression Inventory (BDI).

All models showed reasonable fit, but only one, a four-item single-factor model demonstrated a nonsignificant chi-squared statistic. These four items can be used to derive a Short-Form BHS (SBHS) in which increasing scores (0-4) corresponded with increasing scores in the BDI. The four items were also drawn from all three of Beck's proposed triad, and included both positively and negatively scored items.

This study in a UK undergraduate non-clinical population suggests that the BHS best measures a one-factor model of hopelessness. It appears that a shorter four-item scale can also measure this one-factor model. (C) 2011 Elsevier Ltd. All rights reserved.

Application of factor analysis and geostatistics to identify processes controlling the distribution and bioaccessibility of trace elements in Northern Ireland soils

Geologic and environmental factors acting over varying spatial scales can control
trace element distribution and mobility in soils. In turn, the mobility of an element in soil will affect its oral bioaccessibility. Geostatistics, kriging and principal component analysis (PCA) were used to explore factors and spatial ranges of influence over a suite of 8 element oxides, soil organic carbon (SOC), pH, and the trace elements nickel (Ni), vanadium (V) and zinc (Zn). Bioaccessibility testing was carried out previously using the Unified BARGE Method on a sub-set of 91 soil samples from the Northern Ireland Tellus1 soil archive. Initial spatial mapping of total Ni, V and Zn concentrations shows their distributions are correlated spatially with local geologic formations, and prior correlation analyses showed that statistically significant controls were exerted over trace element bioaccessibility by the 8 oxides, SOC and pH. PCA applied to the geochemistry parameters of the bioaccessibility sample set yielded three principal components accounting for 77% of cumulative variance in the data
set. Geostatistical analysis of oxide, trace element, SOC and pH distributions using 6862 sample locations also identified distinct spatial ranges of influence for these variables, concluded to arise from geologic forming processes, weathering processes, and localised soil chemistry factors. Kriging was used to conduct a spatial PCA of Ni, V and Zn distributions which identified two factors comprising the majority of distribution variance. This was spatially accounted for firstly by basalt rock types, with the second component associated with sandstone and limestone in the region. The results suggest trace element bioaccessibility and distribution is controlled by chemical and geologic processes which occur over variable spatial ranges of influence.

A computational intelligent approach to multi-factor analysis of violent crime information systems

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Psychometric evaluation of the Student Authorship Questionnaire: a confirmatory factor analysis approach

This research provides new insights into the measurement of students’ authorial identity and its potential for minimising the incidence of unintentional plagiarism by providing evidence about the psychometric properties of the Student Authorship Questionnaire (SAQ). Exploratory and confirmatory factor analyses (EFA and CFA) are employed to investigate the measurement properties of the scales which comprise the SAQ using data collected from accounting students. The results provide limited psychometric support in favour of the factorial structure of the SAQ and raise a number of questions regarding the instrument’s robustness and generalisability across disciplines. An alternative model derived from the EFA outperforms the SAQ model with regard to its psychometric properties. Explanations for these findings are proffered and avenues for future research suggested.