Teacher Reporting Attitudes Scale (TRAS): confirmatory and exploratory factor analyses with a Malaysian sample.

The Teacher Reporting Attitude Scale (TRAS) is a newly developed tool to assess teachers’ attitudes toward reporting child abuse and neglect. This article reports on an investigation of the factor structure and psychometric properties of the short form Malay version of the TRAS. A self-report cross-sectional survey was conducted with 667 teachers in 14 randomly selected schools in Selangor state, Malaysia. Analyses were conducted in a 3-stage process using both confirmatory (stages 1 and 3) and exploratory factor analyses (stage 2) to test, modify, and confirm the underlying factor structure of the TRAS in a non-Western teacher sample. Confirmatory factor analysis did not support a 3-factor model previously reported in the original TRAS study. Exploratory factor analysis revealed an 8-item, 4-factor structure. Further confirmatory factor analysis demonstrated appropriateness of the 4-factor structure. Reliability estimates for the four factors—commitment, value, concern, and confidence—were moderate. The modified short form TRAS (Malay version) has potential to be used as a simple tool for relatively quick assessment of teachers’ attitudes toward reporting child abuse and neglect. Cross-cultural differences in attitudes toward reporting may exist and the transferability of newly developed instruments to other populations should be evaluated.

A closer look at Carver and White's BIS/BAS scales: Factor analysis and age group differences

The Behavioural Inhibition and Behavioural Activation System (BIS/BAS) scales were developed by Carver and White (1994) and comprise four scales which measure individual differences in personality (Gray 1982, 1991). More recent modifications, namely the five-factor model derived from Gray and McNaughton's (2000) revised Reward Sensitivity Theory (RST) suggests that Anxiety and Fear are separable components of inhibition. This study employed exploratory and confirmatory factor analyses on the scales in order to test whether the four or five-factor model was the better fit in a sample of 994 participants aged 11–30 years. Consistent with RST, superior model fit was shown for the five-factor model with all variables correlated. Significant age effects were observed for BIS Fear and BIS Anxiety, with scores peaking in middle and late adolescence respectively. The BAS subscales showed differential effects of age group. Significantly increasing scores from early to mid and from mid to late adolescence were found for Drive, but the effect of age on Fun Seeking and Reward Responsiveness was not significant.

An Analysis of Work Related Stress Factor in Selected Industries in Kerala ,India

Occupational stress is becoming a major issue in both corporate and social agenda .In industrialized countries, there have been quite dramatic changes in the conditions at work, during the last decade ,caused by economic, social and technical development. As a consequence, the people today at work are exposed to high quantitative and qualitative demands as well as hard competition caused by global economy. A recent report says that ailments due to work related stress is likely to cost India’s exchequer around 72000 crores between 2009 and 2015. Though India is a fast developing country, it is yet to create facilities to mitigate the adverse effects of work stress, more over only little efforts have been made to assess the work related stress.In the absence of well defined standards to assess the work related stress in India, an attempt is made in this direction to develop the factors for the evaluation of work stress. Accordingly, with the help of existing literature and in consultation with the safety experts, seven factors for the evaluation of work stress is developed. An instrument ( Questionnaire) was developed using these seven factors for the evaluation of work stress .The validity , and unidimensionality of the questionnaire was ensured by confirmatory factor analysis. The reliability of the questionnaire was ensured before administration. While analyzing the relation ship between the variables, it is noted that no relationship exists between them, and hence the above factors are treated as independent factors/ variables for the purpose of research .Initially five profit making manufacturing industries, under public sector in the state of Kerala, were selected for the study. The influence of factors responsible for work stress is analyzed in these industries. These industries were classified in to two types, namely chemical and heavy engineering ,based on the product manufactured and work environment and the analysis is further carried out for these two categories.The variation of work stress with different age , designation and experience of the employees are analyzed by means of one-way ANOVA. Further three different type of modelling of work stress, namely factor modelling, structural equation modelling and multinomial logistic regression modelling was done to analyze the association of factors responsible for work stress. All these models are found equally good in predicting the work stress.The present study indicates that work stress exists among the employees in public sector industries in Kerala. Employees belonging to age group 40-45yrs and experience groups 15-20yrs had relatively higher work demand ,low job control, and low support at work. Low job control was noted among lower designation levels, particularly at the worker level in these industries. Hence the instrument developed using the seven factors namely demand, control, manager support, peer support, relationship, role and change can be effectively used for the evaluation of work stress in industries.

Factor analysis of the North American Spine Society outcome assessment instrument: a study based on a spine registry of patients treated with lumbar and cervical disc arthroplasty.

Background context Studies involving factor analysis (FA) of the items in the North American Spine Society (NASS) outcome assessment instrument have revealed inconsistent factor structures for the individual items. Purpose This study examined whether the factor structure of the NASS varied in relation to the severity of the back/neck problem and differed from that originally recommended by the developers of the questionnaire, by analyzing data before and after surgery in a large series of patients undergoing lumbar or cervical disc arthroplasty. Study design/setting Prospective multicenter observational case series. Patient sample Three hundred ninety-one patients with low back pain and 553 patients with neck pain completed questionnaires preoperatively and again at 3 to 6 and 12 months follow-ups (FUs), in connection with the SWISSspine disc arthroplasty registry. Outcome measures North American Spine Society outcome assessment instrument. Methods First, an exploratory FA without a priori assumptions and subsequently a confirmatory FA were performed on the 17 items of the NASS-lumbar and 19 items of the NASS-cervical collected at each assessment time point. The item-loading invariance was tested in the German version of the questionnaire for baseline and FU. Results Both NASS-lumbar and NASS-cervical factor structures differed between baseline and postoperative data sets. The confirmatory analysis and item-loading invariance showed better fit for a three-factor (3F) structure for NASS-lumbar, containing items on “disability,” “back pain,” and “radiating pain, numbness, and weakness (leg/foot)” and for a 5F structure for NASS-cervical including disability, “neck pain,” “radiating pain and numbness (arm/hand),” “weakness (arm/hand),” and “motor deficit (legs).” Conclusions The best-fitting factor structure at both baseline and FU was selected for both the lumbar- and cervical-NASS questionnaires. It differed from that proposed by the originators of the NASS instruments. Although the NASS questionnaire represents a valid outcome measure for degenerative spine diseases, it is able to distinguish among all major symptom domains (factors) in patients undergoing lumbar and cervical disc arthroplasty; overall, the item structure could be improved. Any potential revision of the NASS should consider its factorial structure; factorial invariance over time should be aimed for, to allow for more precise interpretations of treatment success.

Combination strategies for a factor analysis phone-conditioned speaker verification system

This work aims to take advantage of recent developments in joint factor analysis (JFA) in the context of a phonetically conditioned GMM speaker verification system. Previous work has shown performance advantages through phonetic conditioning, but this has not been shown to date with the JFA framework. Our focus is particularly on strategies for combining the phone-conditioned systems. We show that the classic fusion of the scores is suboptimal when using multiple GMM systems. We investigate several combination strategies in the model space, and demonstrate improvement over score-level combination as well as over a non-phonetic baseline system. This work was conducted during the 2008 CLSP Workshop at Johns Hopkins University.

Within-session variability modelling for factor analysis speaker verification

This work presents an extended Joint Factor Analysis model including explicit modelling of unwanted within-session variability. The goals of the proposed extended JFA model are to improve verification performance with short utterances by compensating for the effects of limited or imbalanced phonetic coverage, and to produce a flexible JFA model that is effective over a wide range of utterance lengths without adjusting model parameters such as retraining session subspaces. Experimental results on the 2006 NIST SRE corpus demonstrate the flexibility of the proposed model by providing competitive results over a wide range of utterance lengths without retraining and also yielding modest improvements in a number of conditions over current state-of-the-art.

Governors highway safety associations and transportation planning: Exploratory factor analysis and structural equation modeling

The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

Psychometric analysis of the Brisbane Practice Environment Measure (B-PEM)

Purpose: To undertake rigorous psychometric testing of the newly developed contemporary work environment measure (the Brisbane Practice Environment Measure [B-PEM]) using exploratory factor analysis and confirmatory factor analysis. Methods: Content validity of the 33-item measure was established by a panel of experts. Initial testing involved 195 nursing staff using principal component factor analysis with varimax rotation (orthogonal) and Cronbach's alpha coefficients. Confirmatory factor analysis was conducted using data from a further 983 nursing staff. Results: Principal component factor analysis yielded a four-factor solution with eigenvalues greater than 1 that explained 52.53% of the variance. These factors were then verified using confirmatory factor analysis. Goodness-of-fit indices showed an acceptable fit overall with the full model, explaining 21% to 73% of the variance. Deletion of items took place throughout the evolution of the instrument, resulting in a 26-item, four-factor measure called the Brisbane Practice Environment Measure-Tested. Conclusions: The B-PEM has undergone rigorous psychometric testing, providing evidence of internal consistency and goodness-of-fit indices within acceptable ranges. The measure can be utilised as a subscale or total score reflective of a contemporary nursing work environment. Clinical Relevance: An up-to-date instrument to measure practice environment may be useful for nursing leaders to monitor the workplace and to assist in identifying areas for improvement, facilitating greater job satisfaction and retention.

Applying SVMs and weight-based factor analysis to unsupervised adaptation for speaker verification

This paper presents an extended study on the implementation of support vector machine(SVM) based speaker verification in systems that employ continuous progressive model adaptation using the weight-based factor analysis model. The weight-based factor analysis model compensates for session variations in unsupervised scenarios by incorporating trial confidence measures in the general statistics used in the inter-session variability modelling process. Employing weight-based factor analysis in Gaussian mixture models (GMM) was recently found to provide significant performance gains to unsupervised classification. Further improvements in performance were found through the integration of SVM-based classification in the system by means of GMM supervectors. This study focuses particularly on the way in which a client is represented in the SVM kernel space using single and multiple target supervectors. Experimental results indicate that training client SVMs using a single target supervector maximises performance while exhibiting a certain robustness to the inclusion of impostor training data in the model. Furthermore, the inclusion of low-scoring target trials in the adaptation process is investigated where they were found to significantly aid performance.

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

Improving cyclodiode - a risk factor analysis of complications

PURPOSE: The purpose of this study is to identify risk factors for developing complications following treatment of refractory glaucoma with transscleral diode laser cyclophotocoagulation (cyclodiode), to improve the safety profile of this treatment modality. METHOD: A retrospective analysis of 72 eyes from 70 patients who were treated with cyclodiode. RESULTS: The mean pre-treatment IOP was 37.0 mmHg (SD 11.0), with a mean post-treatment reduction in intraocular pressure (IOP) of 19.8 mmHg, and a mean IOP at last follow-up of 17.1 mmHg (SD 9.7). Mean total power delivered during treatment was 156.8 Joules (SD 82.7) over a mean of 1.3 treatments (SD 0.6). Sixteen eyes (22.2% of patients) developed complications from the treatment, with the most common being hypotony, occurring in 6 patients, including 4 with neovascular glaucoma. A higher pre-treatment IOP and higher mean total power delivery also were associated with higher complications. CONCLUSIONS: Cyclodiode is an effective treatment option for glaucoma that is refractory to other treatment options. By identifying risk factors for potential complications, cyclodiode can be modified accordingly for each patient to improve safety and efficacy.