Quantifying Barriers to Meditation as a Health Behavior: Exploratory and Confirmatory Factor Analysis of the Determinants of Meditation Practice Inventory

Although the benefits of mindfulness meditation practices have been widely documented, research data suggest that there are barriers to regularly engaging in meditation behavior. In order to explore research questions pertaining to meditation initiation and adherence, psychometrically valid scales to assess barriers to meditation practice are necessary. The aim of the present study was to explore the factor structure and construct validity of the Determinants of Meditation Practice Inventory (DMPI) (Williams et al., 2011), a perceived barriers to meditation scale. Exploratory and confirmatory factor analyses along with construct validity tests were performed on data obtained from two large, community samples. Results supported the DMPI as a valid scale assessing perceived barriers with four factors, Lack of Interest, Knowledge Concerns, Pragmatic Concerns and Sociocultural Beliefs. The present study offers a DMPI-revised scale that may be reliably used to assess attitudes and beliefs that might impede meditation behavior.

Un desafío pendiente para el próximo quinquenio : Los objetivos de desarrollo del milenio

En el año 2000, los gobiernos de 189 países se comprometieron a alcanzar dieciocho metas para combatir la desigualdad y mejorar el desarrollo humano en el mundo a través del cumplimiento de los denominados Objetivos de Desarrollo del Milenio (ODM) de la Organización de las Naciones Unidas (ONU), todo ello con un horizonte para el año 2015. Los ODM deben ser monitoreados por los institutos de estadística existentes en la mayoría de los países que calculan indicadores económicos. En la Argentina, el Instituto Nacional de Estadística y Censos tiene una larga experiencia en la creación y cálculo de índices, específicamente, del índice de Precios al Consumidor el cual ha sido considerado como el mejor índice de precios de toda América Latina. Sin embargo, desde el año 2007 se ha implementado una nueva metodología para su cálculo. En esta comunicación se presentan resultados de trabajos realizados desde diferentes puntos de vista que aportan los métodos exploratorios y confirmatorios tendientes a conocer la situación de pobreza e indigencia y la distribución de los ingresos de los habitantes del Aglomerado Gran Rosario. Los análisis exploratorios y confirmatorios aplicados presentan incuestionables resultados que reflejan la coherencia de las conclusiones a que se ha arribado. Los datos primarios de calidad utilizados permitieron plasmar análisis dinámicos con la información homogénea disponible. Finalmente y a la luz de estas circunstancias, ¿se podrá saber fehacientemente si se alcanzarán los Objetivos de Desarrollo del Milenio en el año 2015?

Un desafío pendiente para el próximo quinquenio : Los objetivos de desarrollo del milenio

En el año 2000, los gobiernos de 189 países se comprometieron a alcanzar dieciocho metas para combatir la desigualdad y mejorar el desarrollo humano en el mundo a través del cumplimiento de los denominados Objetivos de Desarrollo del Milenio (ODM) de la Organización de las Naciones Unidas (ONU), todo ello con un horizonte para el año 2015. Los ODM deben ser monitoreados por los institutos de estadística existentes en la mayoría de los países que calculan indicadores económicos. En la Argentina, el Instituto Nacional de Estadística y Censos tiene una larga experiencia en la creación y cálculo de índices, específicamente, del índice de Precios al Consumidor el cual ha sido considerado como el mejor índice de precios de toda América Latina. Sin embargo, desde el año 2007 se ha implementado una nueva metodología para su cálculo. En esta comunicación se presentan resultados de trabajos realizados desde diferentes puntos de vista que aportan los métodos exploratorios y confirmatorios tendientes a conocer la situación de pobreza e indigencia y la distribución de los ingresos de los habitantes del Aglomerado Gran Rosario. Los análisis exploratorios y confirmatorios aplicados presentan incuestionables resultados que reflejan la coherencia de las conclusiones a que se ha arribado. Los datos primarios de calidad utilizados permitieron plasmar análisis dinámicos con la información homogénea disponible. Finalmente y a la luz de estas circunstancias, ¿se podrá saber fehacientemente si se alcanzarán los Objetivos de Desarrollo del Milenio en el año 2015?

Un desafío pendiente para el próximo quinquenio : Los objetivos de desarrollo del milenio

En el año 2000, los gobiernos de 189 países se comprometieron a alcanzar dieciocho metas para combatir la desigualdad y mejorar el desarrollo humano en el mundo a través del cumplimiento de los denominados Objetivos de Desarrollo del Milenio (ODM) de la Organización de las Naciones Unidas (ONU), todo ello con un horizonte para el año 2015. Los ODM deben ser monitoreados por los institutos de estadística existentes en la mayoría de los países que calculan indicadores económicos. En la Argentina, el Instituto Nacional de Estadística y Censos tiene una larga experiencia en la creación y cálculo de índices, específicamente, del índice de Precios al Consumidor el cual ha sido considerado como el mejor índice de precios de toda América Latina. Sin embargo, desde el año 2007 se ha implementado una nueva metodología para su cálculo. En esta comunicación se presentan resultados de trabajos realizados desde diferentes puntos de vista que aportan los métodos exploratorios y confirmatorios tendientes a conocer la situación de pobreza e indigencia y la distribución de los ingresos de los habitantes del Aglomerado Gran Rosario. Los análisis exploratorios y confirmatorios aplicados presentan incuestionables resultados que reflejan la coherencia de las conclusiones a que se ha arribado. Los datos primarios de calidad utilizados permitieron plasmar análisis dinámicos con la información homogénea disponible. Finalmente y a la luz de estas circunstancias, ¿se podrá saber fehacientemente si se alcanzarán los Objetivos de Desarrollo del Milenio en el año 2015?

Testing the psychometric properties of the Brisbane Practice Environment Measure using Exploratory Factor Analysis and Confirmatory Factor Analysis in an Australian registered nurse population

A cross-sectional survey was conducted, and the construct validity and reliability of the Brisbane Practice Environment Measure in an Australian sample of registered nurses were examined. Nurses were randomly selected from the database of an Australian nursing organization. The original 33 items of the Brisbane Practice Environment Measure were utilized to inform the psychometric properties using confirmatory factor analysis. The Cronbach's alpha was 0.938 for the total scale and ranged 0.657–0.887 for the subscales. A five-factor structure of the measure was confirmed, χ2 = 944.622, (P < 0.01), χ2/d.f. ratio = 2.845, Tucker Lewis Index 0.929, Root Mean Square Error = 0.061 and Comparative Fit Index = 0.906. The selected 28 items of the measure proved reliable and valid in measuring effects of the practice environment upon Australian nurses. The implications are that regular measurement of the practice environment using these 28 items might assist in the development of strategies which might improve job satisfaction and retention of registered nurses in Australia.

Optimizing the balance between false positive and false negative error probabilities of confirmatory methods for the detection of veterinary drug residues

GC-MS data on veterinary drug residues in bovine urine are used for controlling the illegal practice of fattening cattle. According to current detection criteria, peak patterns of preferably four ions should agree within 10 or 20% from a corresponding standard pattern. These criteria are rigid, rather arbitrary and do not match daily practice. A new model, based on multivariate modeling of log peak abundance ratios, provides a theoretical basis for the identification of analytes and optimizes the balance between the avoidance of false positives and false negatives. The performance of the model is demonstrated on data provided by five laboratories, each supplying GC-MS measurements on the detection of clenbuterol, dienestrol and 19 beta-nortestosterone in urine. The proposed model shows a better performance than confirmation by using the current criteria and provides a statistical basis for inspection criteria in terms of error probabilities.

Mathematical symbols and computing methods in high dimensional biomimetic informatics and their applications

High dimensional biomimetic informatics (HDBI) is a novel theory of informatics developed in recent years. Its primary object of research is points in high dimensional Euclidean space, and its exploratory and resolving procedures are based on simple geometric computations. However, the mathematical descriptions and computing of geometric objects are inconvenient because of the characters of geometry. With the increase of the dimension and the multiformity of geometric objects, these descriptions are more complicated and prolix especially in high dimensional space. In this paper, we give some definitions and mathematical symbols, and discuss some symbolic computing methods in high dimensional space systematically from the viewpoint of HDBI. With these methods, some multi-variables problems in high dimensional space can be solved easily. Three detailed algorithms are presented as examples to show the efficiency of our symbolic computing methods: the algorithm for judging the center of a circle given three points on this circle, the algorithm for judging whether two points are on the same side of a hyperplane, and the algorithm for judging whether a point is in a simplex constructed by points in high dimensional space. Two experiments in blurred image restoration and uneven lighting image correction are presented for all these algorithms to show their good behaviors.

Bayesian and multivariate methods applied to favorability quantification in recôncavo Basin and Ribeira Belt, Brazil

A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

Testing the structural and cross-cultural validity of the KIDSCREEN-27 quality of life questionnaire

OBJECTIVES: The aim of this study is to assess the structural and cross-cultural validity of the KIDSCREEN-27 questionnaire. METHODS: The 27-item version of the KIDSCREEN instrument was derived from a longer 52-item version and was administered to young people aged 8-18 years in 13 European countries in a cross-sectional survey. Structural and cross-cultural validity were tested using multitrait multi-item analysis, exploratory and confirmatory factor analysis, and Rasch analyses. Zumbo's logistic regression method was applied to assess differential item functioning (DIF) across countries. Reliability was assessed using Cronbach's alpha. RESULTS: Responses were obtained from n = 22,827 respondents (response rate 68.9%). For the combined sample from all countries, exploratory factor analysis with procrustean rotations revealed a five-factor structure which explained 56.9% of the variance. Confirmatory factor analysis indicated an acceptable model fit (RMSEA = 0.068, CFI = 0.960). The unidimensionality of all dimensions was confirmed (INFIT: 0.81-1.15). Differential item functioning (DIF) results across the 13 countries showed that 5 items presented uniform DIF whereas 10 displayed non-uniform DIF. Reliability was acceptable (Cronbach's alpha = 0.78-0.84 for individual dimensions). CONCLUSIONS: There was substantial evidence for the cross-cultural equivalence of the KIDSCREEN-27 across the countries studied and the factor structure was highly replicable in individual countries. Further research is needed to correct scores based on DIF results. The KIDSCREEN-27 is a new short and promising tool for use in clinical and epidemiological studies.

The structure of psychopathological symptoms and the associations with DSM-diagnoses in treatment seeking individuals

BACKGROUND: Research on comorbidity of psychiatric disorders identifies broad superordinate dimensions as underlying structure of psychopathology. While a syndrome-level approach informs diagnostic systems, a symptom-level approach is more likely to represent the dimensional components within existing diagnostic categories. It may capture general emotional, cognitive or physiological processes as underlying liabilities of different disorders and thus further develop dimensional-spectrum models of psychopathology. METHODS: Exploratory and confirmatory factor analyses were used to examine the structure of psychopathological symptoms assessed with the Brief Symptom Inventory in two outpatient samples (n=3171), including several correlated-factors and bifactor models. The preferred models were correlated with DSM-diagnoses. RESULTS: A model containing eight correlated factors for depressed mood, phobic fear, aggression, suicidal ideation, nervous tension, somatic symptoms, information processing deficits, and interpersonal insecurity, as well a bifactor model fit the data best. Distinct patterns of correlations with DSM-diagnoses identified a) distress-related disorders, i.e., mood disorders, PTSD, and personality disorders, which were associated with all correlated factors as well as the underlying general distress factor; b) anxiety disorders with more specific patterns of correlations; and c) disorders defined by behavioural or somatic dysfunctions, which were characterised by non-significant or negative correlations with most factors. CONCLUSIONS: This study identified emotional, somatic, cognitive, and interpersonal components of psychopathology as transdiagnostic psychopathological liabilities. These components can contribute to a more accurate description and taxonomy of psychopathology, may serve as phenotypic constructs for further aetiological research, and can inform the development of tailored general and specific interventions to treat mental disorders.

Pelvic floor muscle electromyography during different running speeds: an exploratory and reliability study.

PURPOSE Stress urinary incontinence (SUI) affects women of all ages including young athletes, especially those involved in high-impact sports. To date, hardly any studies are available testing pelvic floor muscles (PFM) during sports activities. The aim of this study was the description and reliability test of six PFM electromyography (EMG) variables during three different running speeds. The secondary objective was to evaluate whether there was a speed-dependent difference between the PFM activity variables. METHODS This trial was designed as an exploratory and reliability study including ten young healthy female subjects to characterize PFM pre-activity and reflex activity during running at 7, 9 and 11 km/h. Six variables for each running speed, averaged over ten steps per subject, were presented descriptively, tested regarding their reliability (Friedman, ICC, SEM, MD) and speed difference (Friedman). RESULTS PFM EMG variables varied between 67.6 and 106.1 %EMG, showed no systematic error and were low for SEM and MD using the single value model. Applying the average model over ten steps, ICC (3,k) were >0.75 and SEM and MD about 50 % lower than for the single value model. Activity was found to be highest in 11 km/h. CONCLUSION EMG variables showed excellent ICC and very low SEM and MD. Further studies should investigate inter-session reliability and PFM reactivity patterns of SUI patients using the average over ten steps for each variable as it showed very high ICC and very low SEM and MD. Subsequently, longer running distances and other high-impact sports disciplines could be studied.

Cross-cultural confirmatory factor analysis of the CES-D in Spanish and Mexican dementia caregivers

The Center for Epidemiologic Studies-Depression Scale (CES-D) is the most frequently used scale for measuring depressive symptomatology in caregiving research. The aim of this study is to test its construct structure and measurement equivalence between caregivers from two Spanish-speaking countries. Face-to-face interviews were carried out with 595 female dementia caregivers from Madrid, Spain, and from Coahuila, Mexico. The structure of the CES-D was analyzed using exploratory and confirmatory factor analysis (EFA and CFA, respectively). Measurement invariance across samples was analyzed comparing a baseline model with a more restrictive model. Significant differences between means were found for 7 items. The results of the EFA clearly supported a four-factor solution. The CFA for the whole sample with the four factors revealed high and statistically significant loading coefficients for all items (except item number 4). When equality constraints were imposed to test for the invariance between countries, the change in chi-square was significant, indicating that complete invariance could not be assumed. Significant between-countries differences were found for three of the four latent factor mean scores. Although the results provide general support for the original four-factor structure, caution should be exercised on reporting comparisons of depression scores between Spanish-speaking countries.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.